775 citations as recorded by crossref.

1. Scaling the mountains: multiscale proxies derived from very high-resolution digital elevation models to characterize heterogeneous alpine landscapes and their local effects on plant adaptation S. Joost et al. https://doi.org/10.1007/s00035-026-00368-0
2. Conservation study of Myrsine seguinii in Japan: current distribution explained by past land use and prediction of distribution by land use‐planning simulation L. Vega et al. https://doi.org/10.1007/s11284-010-0734-y
3. Assessment of flora diversity in a minor river valley using ecological indicator values, Geographical Information Systems and Digital Elevation Models B. Czarnecka & Ł. Chabudziński https://doi.org/10.2478/s11535-013-0263-0
4. Evaluating the impact of using digital soil mapping products as input for spatializing a crop model: The case of drainage and maize yield simulated by STICS in the Berambadi catchment (India) P. Lagacherie et al. https://doi.org/10.1016/j.geoderma.2021.115503
5. Climate change and human activity impacts on future flood risk in the Pearl River Delta based on the MaxEnt model D. Zuo et al. https://doi.org/10.3389/feart.2022.1053829
6. National-Scale Flood Susceptibility Mapping of Nigeria Using Statistical and Machine Learning Models with Satellite-Driven Validation for Data-Sparse Environments D. Idowu et al. https://doi.org/10.3390/rs18193264
7. Landscape patterns of catchment and land-use regulate legacy phosphorus releases in subtropical mixed agricultural and woodland catchments C. Meng et al. https://doi.org/10.1016/j.scitotenv.2021.150055
8. Landslide susceptibility assessment in medium-scale: case studies from the major drainage basins of Turkey K. Okalp & H. Akgün https://doi.org/10.1007/s12665-022-10355-3
9. Decoding drivers of corn yield stability zones in New York using topography and soil fertility M. Marcaida et al. https://doi.org/10.1016/j.jafr.2026.103000
10. Factors affecting forest dynamics in the Iberian Peninsula from 1987 to 2012. The role of topography and drought J. José Vidal-Macua et al. https://doi.org/10.1016/j.foreco.2017.10.011
11. Using movement ecology to investigate meningeal worm risk in moose, Alces alces M. Ditmer et al. https://doi.org/10.1093/jmammal/gyaa019
12. Landscape features and forest maturity promote the occurrence of macroinvertebrates specialized for seepage springs in urban forests in Washington, DC E. Burch et al. https://doi.org/10.1002/aqc.3803
13. A novel evapotranspiration based irrigation quantification method using the hydrological similar pixels algorithm J. Brombacher et al. https://doi.org/10.1016/j.agwat.2022.107602
14. Topographic Wetness Index as a Proxy for Soil Moisture: The Importance of Flow‐Routing Algorithm and Grid Resolution H. Riihimäki et al. https://doi.org/10.1029/2021WR029871
15. Identification of Columbian Sharp-Tailed Grouse Lek Sites in South Central Wyoming K. Smith et al. https://doi.org/10.3398/064.076.0115
16. Towards optimizing riparian buffer zones: Ecological and biogeochemical implications for forest management L. Kuglerová et al. https://doi.org/10.1016/j.foreco.2014.08.033
17. Regional debris flow susceptibility analysis based on principal component analysis and self-organizing map: a case study in Southwest China Q. Wang et al. https://doi.org/10.1007/s12517-016-2752-8
18. Identifying Spatial Variation of Carbon Stock in a Warm Temperate Forest in Central Japan Using Sentinel-2 and Digital Elevation Model Data H. Pei et al. https://doi.org/10.3390/rs15081997
19. Earth observation based landslide susceptibility mapping along the Kailash-Mansarovar route in Uttarakhand Himalaya using AHP-TOPSIS integrated approach D. Das et al. https://doi.org/10.1007/s12040-026-02807-2
20. Selection of training samples for updating conventional soil map based on spatial neighborhood analysis of environmental covariates H. Gao et al. https://doi.org/10.1016/j.geoderma.2020.114244
21. Understanding drivers of eucalypt spatial patterns in temperate forests using point process modelling S. Fernando et al. https://doi.org/10.1016/j.fecs.2026.100493
22. Abundance and spatial attributes of forest remnants differently influence colonization patterns of contrasting oak species O. Lorente-Casalini et al. https://doi.org/10.1007/s10980-025-02177-y
23. Mapping groundwater potential zones using remote sensing and geographical information systems in a fractured rock setting, Southern Flinders Ranges, South Australia S. Fildes et al. https://doi.org/10.1007/s12040-020-01420-1
24. A spatial machine-learning model for predicting crop water stress index for precision irrigation of vineyards A. Peeters et al. https://doi.org/10.1016/j.compag.2024.109578
25. Conceptual planning approach of low impact developments for combined water quality‐quantity control at an urban scale: A case study in Southern China Q. Zhou et al. https://doi.org/10.1111/jfr3.12760
26. Modeling the Spatial Impact of Topography on Land Cover Map Accuracy: A Spatial Statistical Analysis of the ESA WorldCover 2020 Product F. Chaaban & H. Darwishe https://doi.org/10.1007/s41976-026-00288-x
27. Prediction of some soil properties in volcanic soils using random forest modeling: A case study at chinyero special nature reserve (Tenerife, canary islands) V. Romeo Jiménez et al. https://doi.org/10.1016/j.ecoinf.2025.103054
28. Improving regional flood risk assessment using flood frequency and dendrogeomorphic analyses in mountain catchments impacted by tropical cyclones A. Quesada-Román et al. https://doi.org/10.1016/j.geomorph.2021.108000
29. Flood hazard assessment using AHP–FR–Fuzzy ensemble of a sub-Himalayan catchment in a transboundary piedmont landscape of the Eastern Himalayas D. Chandra et al. https://doi.org/10.1007/s11069-025-07766-3
30. Habitat diversity predicts orchid diversity in the tropical south‐west Pacific G. Keppel et al. https://doi.org/10.1111/jbi.12805
31. Innovative Risk Assessment Framework for Hydraulic Control of Irrigation Reservoirs´ Breaching F. Espejo et al. https://doi.org/10.1007/s11269-022-03128-x
32. Integration of geospatial techniques and analytical hierarchy process (AHP) ind demarcating groundwater potential zones in Lakhimpur district, Assam, India A. Handique et al. https://doi.org/10.24057/2071-9388-2024-3208
33. Comparative Study of Convolutional Neural Network and Conventional Machine Learning Methods for Landslide Susceptibility Mapping R. Liu et al. https://doi.org/10.3390/rs14020321
34. Patterns of plant abundances in natural systems: is there value in modelling both species abundance and distribution? T. Duff et al. https://doi.org/10.1071/BT11017
35. Disentangling management factors influencing nitrogen balance in producer fields in the western Corn Belt F. Tenorio et al. https://doi.org/10.1016/j.agsy.2021.103245
36. Landslide susceptibility prediction and mapping using the LD-BiLSTM model in seismically active mountainous regions J. Wang et al. https://doi.org/10.1007/s10346-023-02141-4
37. ESTIMATING SLOPE FROM RASTER DATA – A TEST OF EIGHT ALGORITHMS AT DIFFERENT RESOLUTIONS IN FLAT AND STEEP TERRAIN J. Tang et al. https://doi.org/10.3846/20296991.2013.806702
38. Evaluating topography-based approaches for fast floodplain mapping in data-scarce complex-terrain regions: Findings from a Himalayan basin P. Dhote et al. https://doi.org/10.1016/j.jhydrol.2023.129309
39. Rapid case-based mapping of seasonal malaria transmission risk for strategic elimination planning in Swaziland J. Cohen et al. https://doi.org/10.1186/1475-2875-12-61
40. Controlling factors of organic carbon stocks in agricultural topsoils and subsoils of Bavaria S. Mayer et al. https://doi.org/10.1016/j.still.2019.04.021
41. Landslide Susceptibility Assessment Model Construction Using Typical Machine Learning for the Three Gorges Reservoir Area in China J. Cheng et al. https://doi.org/10.3390/rs14092257
42. A runoff risk model based on topographic wetness indices and probability distributions of rainfall and soil moisture for central New York agricultural fields K. Hofmeister et al. https://doi.org/10.2489/jswc.71.4.289
43. Modeling the Spatial Distribution of Soil Organic Carbon and Carbon Stocks in the Casanare Flooded Savannas of the Colombian Llanos J. Martín-López et al. https://doi.org/10.1007/s13157-023-01705-3
44. Linking weed incidence to natural grassland vegetation patterns and environmental drivers in a smallholder crop-livestock system T. Mncube et al. https://doi.org/10.1007/s12600-026-01383-x
45. Estimating Forest Carbon Stocks in Danyang Using Kriging Methods for Aboveground Biomass H. Park et al. https://doi.org/10.11108/kagis.2012.15.1.016
46. Evaluating flood and landslide hazards to cultural heritage sites in Historic Cairo A. Allam et al. https://doi.org/10.1007/s11069-025-07401-1
47. Quantitative characterization of geomorphological and topographical features of debris-flow channels at the Alpe di Succiso mountain, Northern Apennines (Italy) M. Rashid et al. https://doi.org/10.1080/17445647.2024.2422549
48. Modeling the Effect of Environmental and Topographic Variables Affecting the Height Increment of Norway Spruce Stands in Mountainous Conditions with the Use of LiDAR Data R. Bałazy et al. https://doi.org/10.3390/rs11202407
49. Combination of statistical and physically based methods to assess shallow slide susceptibility at the basin scale S. Oliveira et al. https://doi.org/10.5194/nhess-17-1091-2017
50. Ecosystem Health Assessment Using a Fuzzy Spatial Decision Support System in Taleghan Watershed Before and After Dam Construction P. Jafary et al. https://doi.org/10.1007/s40710-018-0341-4
51. Integrating CMIP6 climate change projections into machine learning–based flood susceptibility mapping: a comparative analysis for Pontian district, Johor M. Salleh et al. https://doi.org/10.1007/s40808-026-02892-8
52. Tracking a blue wave of ephemeral water across arid southern Africa D. Schaffer-Smith et al. https://doi.org/10.1088/1748-9326/ac98d9
53. Characterization of soil moisture responses on a hillslope to sequential rainfall events during late autumn and spring S. Kim https://doi.org/10.1029/2008WR007239
54. Evaluation of Soil Water Index of distributed tank model in a small basin with field data S. Vasconcellos et al. https://doi.org/10.1016/j.jsames.2025.105416
55. Identification of flood vulnerability using the topographic wetness index method in Pantai Labu Baru village, Deli Serdang, North Sumatera J. Fitra et al. https://doi.org/10.1051/e3sconf/202448301014
56. Predicting Current and Future Habitat Suitability of an Endemic Species Using Data-Fusion Approach: Responses to Climate Change A. Amindin et al. https://doi.org/10.1016/j.rama.2024.03.002
57. Application of a spatial risk model of the crystalline spider mite (Oligonychus sp.) to avocado crop damage using remote sensing H. Báñez Aldave et al. https://doi.org/10.15446/rfnam.v76n2.102479
58. Assessment of flash flood vulnerability zonation through Geospatial technique in high altitude Himalayan watershed, Himachal Pradesh India S. Bisht et al. https://doi.org/10.1016/j.rsase.2018.09.001
59. Doline susceptibility mapping using multisource data in the karst aquifers of Saldaran mountain, High Zagros Belt P. Mohammadi-Ahmadmahmoudi et al. https://doi.org/10.1007/s11629-024-8834-2
60. Regional spatial and vertical patterns of SOC stocks in a low mountain landscape in Germany B. Haas et al. https://doi.org/10.1016/j.geodrs.2026.e01102
61. Plants and environment: results of archaeobotanical research of the Bronze Age settlements in the Carpathian Foothills in Poland M. Moskal-del Hoyo et al. https://doi.org/10.1016/j.jas.2014.10.024
62. Integrated effects of neighbourhood composition and resource levels on growth of a dominant tree species in a tropical forest X. Shao et al. https://doi.org/10.1098/rspb.2024.2373
63. Aşağı Pınar (Kırklareli - Türkiye) Tarih Öncesi Yerleşiminin Coğrafi Veriler ve CBS Teknolojileriyle Yaşam Çevresi Analizi Ö. YURTSEVEN UYAR & H. TUROGLU https://doi.org/10.46453/jader.1207499
64. Multitemporal landslide inventory and susceptibility map for the Arun River Basin, Nepal P. Amatya et al. https://doi.org/10.1002/gdj3.240
65. GIS-Based Identification of Critical Points and Contributing Areas for Concentrated Runoff Hazard Screening K. Drbal et al. https://doi.org/10.3390/w18172164
66. Assessments of gully erosion susceptibility in typical thick-layer Mollisol region of Northeast China B. Wu et al. https://doi.org/10.1016/j.still.2026.107277
67. Control of Short‐Stature Vegetation Type on Shallow Ground Temperatures in Permafrost Across the Eastern Canadian Arctic S. Evans et al. https://doi.org/10.1029/2022JG006941
68. Detection of Flood-Prone Areas Using Digital Elevation Models S. Manfreda et al. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000367
69. Ongoing invasions by American bullfrogs and red-eared sliders in the Republic of Korea D. Andersen et al. https://doi.org/10.1080/19768354.2025.2455080
70. Evaluating the effects of topography and land use change on hydrological signatures: a comparative study of two adjacent watersheds H. Liu et al. https://doi.org/10.5194/hess-29-2109-2025
71. Review: Advances in groundwater potential mapping S. Díaz-Alcaide & P. Martínez-Santos https://doi.org/10.1007/s10040-019-02001-3
72. GIS-based landform and LULC classifications in the Sub-Himalayan Kaljani Basin: Special reference to 2016 Flood L. Roy & S. Das https://doi.org/10.1016/j.ejrs.2021.06.005
73. The role of mineral soil topography on the spatial distribution of organic layer thickness in a paludified boreal landscape A. Laamrani et al. https://doi.org/10.1016/j.geoderma.2014.01.003
74. Spatial Planning of Green Infrastructure for Mitigation and Adaptation to Climate Change at a Regional Scale A. García et al. https://doi.org/10.3390/su122410525
75. An Optimized Object-Based Random Forest Algorithm for Marsh Vegetation Mapping Using High-Spatial-Resolution GF-1 and ZY-3 Data P. Lou et al. https://doi.org/10.3390/rs12081270
76. Understanding the role of lineament-controlled factors in landslide susceptibility: a machine learning approach in the Uhl Basin, Himachal Pradesh N. Dhiman et al. https://doi.org/10.3389/feart.2026.1896285
77. Topographically driven differences in energy and water constrain climatic control on forest carbon sequestration T. Swetnam et al. https://doi.org/10.1002/ecs2.1797
78. Modelling and mapping topographic variations in forest soils at high resolution: A case study P. Murphy et al. https://doi.org/10.1016/j.ecolmodel.2011.01.003
79. Fantastic Wetlands and Where to Find Them: Modeling Rich Fen Distribution in New York State with Maxent P. Raney & D. Leopold https://doi.org/10.1007/s13157-017-0958-5
80. Effects of DEM resolution on the calculation of topographical indices: TWI and its components R. Sørensen & J. Seibert https://doi.org/10.1016/j.jhydrol.2007.09.001
81. The role of soil pH in linking groundwater flow and plant species density in boreal forest landscapes U. Zinko et al. https://doi.org/10.1111/j.0906-7590.2006.04581.x
82. A Self-Powered, Real-Time, LoRaWAN IoT-Based Soil Health Monitoring System S. Ramson et al. https://doi.org/10.1109/JIOT.2021.3056586
83. Linking Soil Moisture Variation and Abundance of Plants to Geomorphic Processes: A Generalized Model for Erosion‐Uplifting Landscapes J. Ding et al. https://doi.org/10.1002/2017JG004244
84. Unraveling flood dynamics at sub-daily time scales in semi-arid to arid basins in south Morocco M. Rachdane et al. https://doi.org/10.1007/s11069-024-07022-0
85. Guiding riparian vegetation planting with machine learning R. Diaz-Gomez et al. https://doi.org/10.1080/24705357.2025.2481033
86. Spatial modeling of sediment transfer and identification of sediment sources during snowmelt in an agricultural watershed in boreal climate C. Gonzales-Inca et al. https://doi.org/10.1016/j.scitotenv.2017.08.142
87. Topographically controlled soil moisture is the primary driver of local vegetation patterns across a lowland region J. Moeslund et al. https://doi.org/10.1890/ES13-00134.1
88. Restored saltmarshes lack the topographic diversity found in natural habitat P. Lawrence et al. https://doi.org/10.1016/j.ecoleng.2018.02.007
89. Applying species distribution modelling to improving conservation based decisions: a gap analysis of Trinidad and Tobago’s endemic vascular plants J. Spiers et al. https://doi.org/10.1007/s10531-018-1578-y
90. Tree mortality during long-term droughts is lower in structurally complex forest stands Q. Ma et al. https://doi.org/10.1038/s41467-023-43083-8
91. Mapping groundwater and agriculture potential zones in central Southwest Bangladesh using AHP remote sensing and GIS M. Jayed et al. https://doi.org/10.1016/j.ecofro.2026.02.005
92. Spatial relationships between soil moisture patterns and topographic variables at multiple scales in a humid temperate forested catchment G. Ali et al. https://doi.org/10.1029/2009WR008804
93. A continental-scale XGBoost framework for multi-hazard susceptibility and socioeconomic exposure in South America M. Gomes & M. Castro https://doi.org/10.1016/j.scs.2026.107858
94. GIS-based risk assessment of typhoon disasters in coastal provinces of China Y. Wang et al. https://doi.org/10.3389/fmars.2025.1548763
95. Use of Landsat images for yield evaluation within a small plot J. Kumhálová et al. https://doi.org/10.17221/515/2014-PSE
96. The Shift from Energy to Water Limitation in Local Canopy Height from Temperate to Tropical Forests in China B. Wang et al. https://doi.org/10.3390/f13050639
97. Landsat to monitor an endangered beetle population and its habitat: addressing annual life history and imperfect detection D. Leasure et al. https://doi.org/10.1111/icad.12233
98. Currents Status, Challenges, and Future Directions in Identifying Critical Source Areas for Non-Point Source Pollution in Canadian Conditions R. Rudra et al. https://doi.org/10.3390/agriculture10100468
99. Evaluating topographic wetness indices across central New York agricultural landscapes B. Buchanan et al. https://doi.org/10.5194/hess-18-3279-2014
100. Leveraging synergies between UAV and Landsat 8 sensors to evaluate the impact of pale lichen biomass on land surface temperature in heath tundra ecosystems M. Villoslada et al. https://doi.org/10.1016/j.scitotenv.2025.178982
101. Geodiversity as a Driver of Soil Microbial Community Diversity and Adaptation in a Mediterranean Landscape S. Pelacani et al. https://doi.org/10.3390/land14030583
102. A fine spatial resolution estimation scheme for large-scale gross primary productivity (GPP) in mountain ecosystems by integrating an eco-hydrological model with the combination of linear and non-linear downscaling processes X. Xie et al. https://doi.org/10.1016/j.jhydrol.2022.128833
103. Updating Conventional Soil Maps through Digital Soil Mapping L. Yang et al. https://doi.org/10.2136/sssaj2010.0002
104. Proposal of a facet-to-facet multiple flow direction algorithm based on geometrical and mathematical analysis of physical dispersion over triangle facet Z. Li et al. https://doi.org/10.1016/j.geomorph.2024.109440
105. Potential distribution of wild edible fruit trees under climate change scenarios: promoting food security in a Neotropical region G. Benítez et al. https://doi.org/10.1007/s10113-024-02231-6
106. Decision tree-based machine learning models for above-ground biomass estimation using multi-source remote sensing data and object-based image analysis H. Tamiminia et al. https://doi.org/10.1080/10106049.2022.2071475
107. A novel framework for feature simplification and selection in flood susceptibility assessment based on machine learning K. Zhu et al. https://doi.org/10.1016/j.ejrh.2024.101739
108. Landslide susceptibility modelling using the quantitative random forest method along the northern portion of the Yukon Alaska Highway Corridor, Canada P. Behnia & A. Blais-Stevens https://doi.org/10.1007/s11069-017-3104-z
109. Causes and Controlling Factors of Valley Bottom Gullies S. Amare et al. https://doi.org/10.3390/land8090141
110. Snow avalanche susceptibility assessment using machine-learning and hybrid ensemble models in the NW Himalaya, India A. Mohanty et al. https://doi.org/10.1016/j.coldregions.2026.105101
111. Pathways of geomorphic evolution of sandstone escarpments in the Góry Stołowe tableland (SW Poland) — Insights from LiDAR-based high-resolution DEM P. Migoń & M. Kasprzak https://doi.org/10.1016/j.geomorph.2015.08.022
112. Geomorphic Analysis, Morphometric-based Prioritization and Tectonic Implications in Chite Lui River, Northeast India B. Barman et al. https://doi.org/10.1007/s12594-021-1696-0
113. Satellite-based modelling of potential tsetse (Glossina pallidipes) breeding and foraging sites using teneral and non-teneral fly occurrence data S. Gachoki et al. https://doi.org/10.1186/s13071-021-05017-5
114. Optimizing landslide susceptibility mapping using machine learning and geospatial techniques G. Agboola et al. https://doi.org/10.1016/j.ecoinf.2024.102583
115. Flood risk zoning using a rule mining based on ant colony algorithm C. Lai et al. https://doi.org/10.1016/j.jhydrol.2016.09.003
116. Assessing fire hazard potential and its main drivers in Mazandaran province, Iran: a data-driven approach H. Adab et al. https://doi.org/10.1007/s10661-018-7052-1
117. Evaluation of a wetland classification system devised for management in a region with a high cover of peatlands: an example from the Cook Inlet Basin, Alaska M. Gracz & P. Glaser https://doi.org/10.1007/s11273-016-9504-0
118. Wetland landscapes in the Southern Maya Lowlands (Naachtun, Guatemala) from the ancient agroecosystems to the tropical biosphere reserve: Ecology, exploitation and management of water and soil resources, and heritage legacy C. Castanet et al. https://doi.org/10.1002/gea.22003
119. Burn Severity Drivers in Italian Large Wildfires F. Malandra et al. https://doi.org/10.3390/fire5060180
120. Landslide Susceptibility Using Climatic–Environmental Factors Using the Weight-of-Evidence Method—A Study Area in Central Italy M. Gentilucci et al. https://doi.org/10.3390/app13158617
121. On the nexus between landslide susceptibility and transport infrastructure – an agent-based approach M. Schlögl et al. https://doi.org/10.5194/nhess-19-201-2019
122. Environmental variables and dispersal barriers explain broad‐scale variation in tree species composition across Neotropical non‐flooded evergreen forests M. Cupertino‐Eisenlohr et al. https://doi.org/10.1111/jvs.13026
123. Automated Flood Prediction along Railway Tracks Using Remotely Sensed Data and Traditional Flood Models A. Zakaria et al. https://doi.org/10.3390/rs16132332
124. Large-scale mapping of existing and lost wetlands: Earth Observation data and tools to support restoration in the Sebou and Medjerda river basins A. Guelmami https://doi.org/10.1007/s41207-023-00443-6
125. Geochemical Pathways Defined by Predictive Regolith-Landform Models Using TanDEM-X Data in the Tanami Region, Australia R. Langford https://doi.org/10.3389/esss.2024.10111
126. Predicting Potential Fire Severity Using Vegetation, Topography and Surface Moisture Availability in a Eurasian Boreal Forest Landscape L. Fang et al. https://doi.org/10.3390/f9030130
127. Assessing groundwater potential zones and artificial recharge sites in the monsoon-fed Murredu river basin, India: An integrated approach using GIS, AHP, and Fuzzy-AHP P. Raja Shekar & A. Mathew https://doi.org/10.1016/j.gsd.2023.100994
128. A partitioned conditioned Latin hypercube sampling method considering spatial heterogeneity in digital soil mapping B. Huang et al. https://doi.org/10.1038/s41598-025-95631-5
129. Spatio-Temporal Analysis of Water Dynamics of a Large-Scale Plain Region Using Remote Sensing and Proxy Variables E. Gómez et al. https://doi.org/10.1007/s41748-025-00673-4
130. Modelling the extent of northern peat soil and its uncertainty with Sentinel: Scotland as example of highly cloudy region L. Poggio et al. https://doi.org/10.1016/j.geoderma.2019.03.017
131. Risk analysis of forest roads using landslide susceptibility maps and generation of the optimum forest road route: a case study in Macka, Turkey F. Kadi et al. https://doi.org/10.1080/10106049.2019.1659424
132. Identification of Groundwater Potential Zones Using GIS and Multi-Criteria Decision-Making Techniques: A Case Study Upper Coruh River Basin (NE Turkey) Ü. Yıldırım https://doi.org/10.3390/ijgi10060396
133. Digital mapping of soil organic matter stocks using Random Forest modeling in a semi-arid steppe ecosystem M. Wiesmeier et al. https://doi.org/10.1007/s11104-010-0425-z
134. Landslide susceptibility maps using different probabilistic and bivariate statistical models and comparison of their performance at Wadi Itwad Basin, Asir Region, Saudi Arabia A. Youssef et al. https://doi.org/10.1007/s10064-015-0734-9
135. The first occupation of the mountains: Neolithic human-environmental interactions in the Kohgiluyeh region (southern Zagros, Iran) A. Azadi et al. https://doi.org/10.1016/j.quaint.2023.04.007
136. Assessing the Spatiotemporal Variability of SMAP Soil Moisture Accuracy in a Deciduous Forest Region M. Abdelkader et al. https://doi.org/10.3390/rs14143329
137. Land use/land cover change detection using remote sensing and gis based techniques for solani river basin, uttarakhand A. Ashish et al. https://doi.org/10.26634/jce.12.4.19070
138. Does conserving roadless wildland increase wildfire activity in western US national forests? J. Johnston et al. https://doi.org/10.1088/1748-9326/ac13ee
139. Rapid shrub expansion in a subarctic mountain basin revealed by repeat airborne LiDAR S. Leipe & S. Carey https://doi.org/10.1088/2515-7620/ac0e0c
140. Distribution and Characteristics of Springs in Two Neighboring Areas of Different Morphogenic Relief Type—Example of SW Medvednica Mountain (Central Croatia) I. Martinić & I. Čanjevac https://doi.org/10.3390/w16070994
141. Establishing uncertainty ranges of hydrologic indices across climate and physiographic regions of the Congo River Basin P. Kabuya et al. https://doi.org/10.1016/j.ejrh.2020.100710
142. Mapping of earthquake hotspot and coldspot zones for identifying potential landslide hotspot areas in the Himalayan region I. Chowdhuri et al. https://doi.org/10.1007/s10064-022-02761-5
143. Predicting the risk of arsenic contaminated groundwater in Shanxi Province, Northern China Q. Zhang et al. https://doi.org/10.1016/j.envpol.2012.02.020
144. Within-field variation of mycotoxin contamination of winter wheat is related to indicators of soil moisture M. Müller et al. https://doi.org/10.1007/s11104-010-0695-5
145. Evaluation of Gully Erosion Susceptibility Using a Maximum Entropy Model in the Upper Mkhomazi River Basin in South Africa A. Bernini et al. https://doi.org/10.3390/ijgi10110729
146. Determining the extent and runout path of large earthflow through multi-temporal InSAR and topographic analysis W. Liu et al. https://doi.org/10.1080/01431161.2026.2639131
147. Topographic water redistribution, rather thanclimate, dictates eco-hydrological recovery: Flux- and runoff-based validation in the Upper Minjiang River, eastern Qinghai-Tibet Plateau Y. Liu et al. https://doi.org/10.1016/j.ejrh.2026.103831
148. Estimation of total organic carbon storage and its driving factors in soils of Bavaria (southeast Germany) M. Wiesmeier et al. https://doi.org/10.1016/j.geodrs.2014.09.001
149. Quantified ecology and co-occurrence of Mediterranean woody species in a landscape context F. Goedecke et al. https://doi.org/10.1007/s11258-018-0810-x
150. Convolutional Neural Network for High-Resolution Wetland Mapping with Open Data: Model Transferability and Predictor's Role K. Mainali et al. https://doi.org/10.2139/ssrn.4165348
151. Tailoring a non-path-dependent model for environmental risk management and polycentric urban land-use planning Y. Sakieh et al. https://doi.org/10.1007/s10661-017-5796-7
152. Indicator-based evaluation of spatiotemporal characteristics of rice flood in Southwest China J. Yang et al. https://doi.org/10.1016/j.agee.2016.06.008
153. Delineation of groundwater vulnerable zone for sustainable development in the southwestern part of Bihar, India A. Chouhan et al. https://doi.org/10.1016/j.gsd.2024.101240
154. Urban pluvial flood susceptibility mapping based on a novel explainable machine learning model with synchronous enhancement of fitting capability and explainability Z. Wang et al. https://doi.org/10.1016/j.jhydrol.2024.131903
155. Connectivity patterns in contrasting types of tableland sandstone relief revealed by Topographic Wetness Index K. Jancewicz et al. https://doi.org/10.1016/j.scitotenv.2018.11.467
156. Relationships between landform properties and vegetation patterns in the Cerro Zonda Mt., Central Precordillera of San Juan. Argentina D. Flores et al. https://doi.org/10.1016/j.jsames.2019.102359
157. Landslide Susceptibility Modeling Using a Hybrid Bivariate Statistical and Expert Consultation Approach in Canada Hill, Sarawak, Malaysia M. Daniel et al. https://doi.org/10.3389/feart.2021.616225
158. Mapping Wetlands with High-Resolution Planet SuperDove Satellite Imagery: An Assessment of Machine Learning Models Across the Diverse Waterscapes of New Zealand M. Khan et al. https://doi.org/10.3390/rs17152626
159. Susceptibility Modeling and Potential Risk Analysis of Thermokarst Hazard in Qinghai–Tibet Plateau Permafrost Landscapes Using a New Interpretable Ensemble Learning Method Y. Yang et al. https://doi.org/10.3390/atmos15070788
160. National scale 3D modelling of soil organic carbon stocks with uncertainty propagation — An example from Scotland L. Poggio & A. Gimona https://doi.org/10.1016/j.geoderma.2014.05.004
161. Assessment of terrain stability zones for human habitation in Himalayan Upper Pindar River Basin, Uttarakhand using AHP and GIS S. Nandy https://doi.org/10.1007/s12665-021-09634-2
162. ON GENERATING DIGITAL ELEVATION MODELS FROM LIDAR DATA – RESOLUTION VERSUS ACCURACY AND TOPOGRAPHIC WETNESS INDEX INDICES IN NORTHERN PEATLANDS A. Hasan et al. https://doi.org/10.3846/20296991.2012.702983
163. Ecological niche modelling using MaxEnt for riparian species in a Mediterranean context J. Stephan & M. Korban https://doi.org/10.1016/j.ecolind.2025.113167
164. Rescue and renewal of legacy soil resource inventories in Iran as an input to digital soil mapping Z. Rasaei et al. https://doi.org/10.1016/j.geodrs.2020.e00262
165. Temporal changes in soil carbon and nitrogen in response to grazing management and vegetation cover in south-eastern Australia D. Lindenmayer et al. https://doi.org/10.1371/journal.pone.0342006
166. <b>Geographic Information Systems and Analytic Hierarchy Process Based Integrated Framework for Flood Susceptibility Mapping in Panzara River Basin of Maharashtra, India</b> A. Pawar & A. Sharma https://doi.org/10.52151/jae2026633.2026
167. Regional flood frequency analysis in North Africa Y. Tramblay et al. https://doi.org/10.1016/j.jhydrol.2024.130678
168. Integrating FR, MFR and IV Models for Landslide Susceptibility Zonation Mapping in Joshimath Watershed, Uttarakhand, India I. Khan et al. https://doi.org/10.1007/s40996-024-01708-y
169. How climate, fire types and topography drive forest biomass vulnerability to fires assessed from high resolution space-for-time analysis L. Vallet & F. Mouillot https://doi.org/10.1016/j.ecolind.2026.114850
170. Regression‐Kriged Soil Organic Carbon Stock Changes in Manured Corn Silage–Alfalfa Production Systems J. Gamble et al. https://doi.org/10.2136/sssaj2017.04.0138
171. A geospatial analysis of multi-hazard risk in Dharan, Nepal S. Aksha et al. https://doi.org/10.1080/19475705.2019.1710580
172. A Citizen-Science Study Documents Environmental Exposures and Asthma Prevalence in Two Communities S. Eiffert et al. https://doi.org/10.1155/2016/1962901
173. Mapping small inland wetlands in the South-Kivu province by integrating optical and SAR data with statistical models for accurate distribution assessment C. Géant et al. https://doi.org/10.1038/s41598-023-43292-7
174. Integrating an empirical erosion model and machine learning for assessing soil loss and sediment delivery dynamics in a sub-humid catchment K. Phinzi https://doi.org/10.1007/s40808-026-02780-1
175. GIS-based comparative study of Bayes network, Hoeffding tree and logistic model tree for landslide susceptibility modeling W. Chen & S. Zhang https://doi.org/10.1016/j.catena.2021.105344
176. Distributed, high-resolution modelling of critical source areas for erosion and phosphorus losses F. Djodjic & A. Villa https://doi.org/10.1007/s13280-014-0618-4
177. Linking LiDAR with streamwater biogeochemistry in coastal temperate rainforest watersheds J. Fellman et al. https://doi.org/10.1139/cjfas-2016-0130
178. Wetland extent tools for SDG 6.6.1 reporting from the Satellite-based Wetland Observation Service (SWOS) K. Weise et al. https://doi.org/10.1016/j.rse.2020.111892
179. Efficiency of local minima and GLM techniques in sinkhole extraction from a LiDAR-based terrain model P. Enyedi et al. https://doi.org/10.1080/17538947.2018.1501107
180. Modern Farming Practices in Paddy Fields Negatively Affect an Endemic Frog, Glandirana susurra, in Japan T. Miyu et al. https://doi.org/10.1007/s13157-020-01289-2
181. Quantifying the space – time variability of water balance components in an agricultural basin using a process-based hydrologic model and the Budyko framework H. Qiu et al. https://doi.org/10.1016/j.scitotenv.2019.04.147
182. Topographic indices and two-dimensional hydrodynamic modelling for flood hazard mapping in a data-scarce plain area: a case study of Oued Laou catchment (Northern of Morocco) O. Amellah et al. https://doi.org/10.1080/10106049.2022.2082548
183. Application of analytical hierarchical process, multi-influencing factor, and geospatial techniques for groundwater potential zonation in a semi-arid region of western India B. Yadav et al. https://doi.org/10.1016/j.jconhyd.2022.104122
184. Identifying environmental phosphorus risk classes at the scale of Prince Edward Island, Canada R. Benjannet et al. https://doi.org/10.1139/cjss-2017-0076
185. Integrated assessment of groundwater potential zones and artificial recharge sites using GIS and Fuzzy-AHP: a case study in Peddavagu watershed, India P. Shekar & A. Mathew https://doi.org/10.1007/s10661-023-11474-5
186. Flash flood susceptibility assessment using the parameters of drainage basin morphometry in SE Bangladesh A. Alam et al. https://doi.org/10.1016/j.quaint.2020.04.047
187. Quantifying Dieback in a Vulnerable Population of Eucalyptus macrorhyncha Using Remote Sensing D. Fitzgerald et al. https://doi.org/10.3390/land12071271
188. Topographic Metrics for Improved Mapping of Forested Wetlands M. Lang et al. https://doi.org/10.1007/s13157-012-0359-8
189. Shifting from traditional landslide occurrence modeling to scenario estimation with a “glass-box” machine learning F. Caleca et al. https://doi.org/10.1016/j.scitotenv.2024.175277
190. Wind protection rather than soil water availability contributes to the restriction of high-mountain forest to ravines J. Sparacino et al. https://doi.org/10.1007/s11056-019-09722-z
191. The Machine Learning-Based Mapping of Urban Pluvial Flood Susceptibility in Seoul Integrating Flood Conditioning Factors and Drainage-Related Data J. Bersabe & B. Jun https://doi.org/10.3390/ijgi14020057
192. Assessing climate change risks using multi-criteria decision-making (MCDM) techniques in Raichur Taluk, Karnataka, India D. Zewdu et al. https://doi.org/10.1007/s00477-024-02816-x
193. Detection and analysis of landslide geomorphology based on UAV vertical photogrammetry R. Bi et al. https://doi.org/10.1007/s11629-022-7766-y
194. Ranking Importance of Topographical Surface and Subsurface Parameters on Paludification in Northern Boreal Forests Using Very High Resolution Remotely Sensed Datasets A. Laamrani & O. Valeria https://doi.org/10.3390/su12020577
195. Assessing hydrogeological vulnerability and its socio-economic consequences in a Himalayan river watershed S. Sati et al. https://doi.org/10.1007/s44475-026-00054-z
196. A new distributed rainfall-runoff (DR2) model based on soil saturation and runoff cumulative processes M. López-Vicente & A. Navas https://doi.org/10.1016/j.agwat.2011.12.007
197. Geomorphometric characterization and sediment connectivity of the middle Brahmaputra River basin B. Faisal & Y. Hayakawa https://doi.org/10.1016/j.geomorph.2023.108665
198. Assessing the utility of topographic variables in predicting structural complexity of tree stands in a reforested urban landscape K. Sithole et al. https://doi.org/10.1016/j.ufug.2018.02.012
199. Runoff Generation Processes and Thresholds in Agricultural Catchments of Central Chile C. Arancibia et al. https://doi.org/10.3390/w18172134
200. Shallow groundwater potential mapping and evaluation for climate resilient smallholder irrigation in the Zeway-Shalla Sub-basin, Ethiopia T. Hulluka et al. https://doi.org/10.1016/j.gsd.2024.101367
201. Climate limitation at the cold edge: contrasting perspectives from species distribution modelling and a transplant experiment C. Greiser et al. https://doi.org/10.1111/ecog.04490
202. Unravelling the role of digital soil mapping to assess the soil subgroup development in northwestern Iran B. Mohammadhosseini Sagayesh et al. https://doi.org/10.1007/s40808-025-02564-z
203. Predicting urban cold-air paths using boosted regression trees L. Grunwald et al. https://doi.org/10.1016/j.landurbplan.2020.103843
204. GIS-based comparative assessment of flood susceptibility mapping using hybrid multi-criteria decision-making approach, naïve Bayes tree, bivariate statistics and logistic regression: A case of Topľa basin, Slovakia S. Ali et al. https://doi.org/10.1016/j.ecolind.2020.106620
205. Flood Susceptibility Assessment with Random Sampling Strategy in Ensemble Learning (RF and XGBoost) H. Ren et al. https://doi.org/10.3390/rs16020320
206. Integrated geospatial, rainfall threshold and physical based modelling for landslides in parts of upper bhagirathi basin, Uttarakhand P. Mohan et al. https://doi.org/10.1016/j.qsa.2024.100172
207. Identifying individual drivers of damage to oak during severe UK storms in winter 2021 K. Halstead et al. https://doi.org/10.1016/j.agrformet.2025.110797
208. TMDL for phosphorus and contributing factors in subtropical watersheds of southern China C. Meng et al. https://doi.org/10.1007/s10661-015-4737-6
209. A watershed-scale multi-approach assessment of design flood discharge estimates used in hydrologic risk analyses for forest road stream crossings and culverts S. Mukherjee et al. https://doi.org/10.1016/j.jhydrol.2024.130698
210. Effect of morphological terraces on earthquake-induced landslides: Insights from the January 23, 2024, Ms 7.1 Wushi earthquake in the South Tianshan Mountains, China J. Huang et al. https://doi.org/10.1016/j.enggeo.2025.108210
211. Sampling design optimization of a wireless sensor network for monitoring ecohydrological processes in the Babao River basin, China Y. Ge et al. https://doi.org/10.1080/13658816.2014.948446
212. Determining local wetness conditions within the mined lands using GIS O. Skrypnyk et al. https://doi.org/10.33271/mining14.04.058
213. Predicting spatial variations of tree species richness in tropical forests from high‐resolution remote sensing G. Fricker et al. https://doi.org/10.1890/14-1593.1
214. Unveiling the role of forests in landslide occurrence, recurrence and recovery Y. Law et al. https://doi.org/10.1111/1365-2664.14741
215. Delineation of Potential Groundwater Zones and Assessment of Their Vulnerability to Pollution from Cemeteries Using GIS and AHP Approaches Based on the DRASTIC Index and Specific DRASTIC V. Gonçalves et al. https://doi.org/10.3390/w16040585
216. Space–time landslide hazard modeling via Ensemble Neural Networks A. Dahal et al. https://doi.org/10.5194/nhess-24-823-2024
217. Storage and drivers of organic carbon in forest soils of southeast Germany (Bavaria) – Implications for carbon sequestration M. Wiesmeier et al. https://doi.org/10.1016/j.foreco.2013.01.025
218. Conservation of salamanders in managed forests: Methods and costs of monitoring abundance and habitat selection A. Romano et al. https://doi.org/10.1016/j.foreco.2017.05.048
219. Spatial structure and multiscale environmental associations of arsenic in karst agricultural soils of Zhijin County, southwestern China Z. Liu et al. https://doi.org/10.1007/s10661-026-15960-4
220. Evaluation of Birecik Basin Flood Detection with GIS Assisted AHP Methods V. Aslan https://doi.org/10.1007/s12205-023-1271-x
221. Effect of high-resolution spatial soil moisture variability on simulated runoff response using a distributed hydrologic model J. Minet et al. https://doi.org/10.5194/hess-15-1323-2011
222. Crop biomass and humidity related factors reflect the spatial distribution of phytopathogenic Fusarium fungi and their mycotoxins in heterogeneous fields and landscapes M. Müller et al. https://doi.org/10.1007/s11119-016-9444-y
223. Modelling of flood hazard using topographic wetness index in Yeh Ho Watershed, Bali, Indonesia I. Adnyana et al. https://doi.org/10.1051/bioconf/202515904002
224. An integrated regionalization framework for incorporating flood seasonality into agricultural flood risk assessments A. Scorzini et al. https://doi.org/10.1007/s00477-025-03137-3
225. A comparison of wetness indices for the prediction of observed connected saturated areas under contrasting conditions G. Ali et al. https://doi.org/10.1002/esp.3506
226. Convolutional neural network and long short-term memory algorithms for groundwater potential mapping in Anseong, South Korea W. Hakim et al. https://doi.org/10.1016/j.ejrh.2022.100990
227. Anatolian Sageretia as an indicator species for prediction of putative refuges in Taurus Mountains E. Berberoğlu et al. https://doi.org/10.30516/bilgesci.1926502
228. Detecting Woody Plant Cover in the Foothills Parkland and Montane Ecoregions of Southern Alberta E. Denning et al. https://doi.org/10.3390/rs18081229
229. Proxy Data of Surface Water Floods in Rural Areas: Application to the Evaluation of the IRIP Intense Runoff Mapping Method Based on Satellite Remote Sensing and Rainfall Radar A. Cerbelaud et al. https://doi.org/10.3390/w14030393
230. Associations between local-scale soil and tree context factors and Acute Oak Decline (AOD): plant-soil feedbacks and the cause-effect conundrum L. Shaw et al. https://doi.org/10.1007/s11104-025-07649-3
231. Stand age related differences in forest microclimate D. Lindenmayer et al. https://doi.org/10.1016/j.foreco.2022.120101
232. Evaluating digital terrain indices for soil wetness mapping – a Swedish case study A. Ågren et al. https://doi.org/10.5194/hess-18-3623-2014
233. A Topographic Wetness Index for Forest Road Quality Assessment: An Application in the Lakeland Region of Finland K. Waga et al. https://doi.org/10.3390/f11111165
234. Testing a model for the prediction of isolated waters in the Sonoran Desert J. Drake et al. https://doi.org/10.1016/j.jaridenv.2015.02.018
235. Assessment of streamflow components and hydrologic transit times using stable isotopes of oxygen and hydrogen in waters of a subtropical watershed in eastern China M. Hu et al. https://doi.org/10.1016/j.jhydrol.2020.125363
236. Understanding the role of stakeholder preferences in extraction system selection: insights from a decision support system applied across Mediterranean forests F. Latterini et al. https://doi.org/10.1093/forestry/cpag058
237. Hydrologic responses to restored wildfire regimes revealed by soil moisture-vegetation relationships G. Boisramé et al. https://doi.org/10.1016/j.advwatres.2017.12.009
238. Landslide hydrology: from hydrology to pore pressure T. Bogaard & R. Greco https://doi.org/10.1002/wat2.1126
239. Review of sediment connectivity: Conceptual connotations, characterization indicators, and their relationships with soil erosion and sediment yield C. Shi et al. https://doi.org/10.1016/j.earscirev.2025.105091
240. GIS-based multi-criteria decision analysis for groundwater dam site selection in an arid and semi-arid region of Algeria A. Hamlat et al. https://doi.org/10.1016/j.gsd.2024.101231
241. Terrain-mediated slope-unit sensitivity and mapped rainfall-induced landslide occurrence under matched gridded rainfall exposure X. Zhang et al. https://doi.org/10.1007/s10346-026-02855-1
242. How the landscape influences soil respiration: Explaining spatio-temporal patterns with interpretable machine learning M. Baumberger et al. https://doi.org/10.1016/j.geoderma.2026.117904
243. Integration of hydrogeophysical datasets and empirical orthogonal functions for improved irrigation water management C. Finkenbiner et al. https://doi.org/10.1007/s11119-018-9582-5
244. Flood susceptibility mapping with ensemble machine learning: a case of Eastern Mediterranean basin, Türkiye H. Özdemir et al. https://doi.org/10.1007/s00477-023-02507-z
245. Negative Impacts of an Invasive Pasture Grass on a Native Wetland Herb Increase with Hydroperiod G. Hart-Fredeluces et al. https://doi.org/10.1007/s13157-026-02126-8
246. GIS-based forest fire susceptibility modeling in Pauri Garhwal, India: a comparative assessment of frequency ratio, analytic hierarchy process and fuzzy modeling techniques A. Tiwari et al. https://doi.org/10.1007/s11069-020-04351-8
247. TWI Computations and Topographic Analysis of Depression-Dominated Surfaces K. Grimm et al. https://doi.org/10.3390/w10050663
248. Quantifying the drivers of tree mortality: A case study from urban recreational boreal forest J. Jääskeläinen et al. https://doi.org/10.1016/j.ufug.2025.128672
249. CMIP6-based projections of climate-driven contraction and topographic refugia in German peatland habitat suitability: implications for restoration prioritization and 2045 carbon neutrality E. İlter & C. Türe https://doi.org/10.1007/s11273-026-10195-z
250. Investigation of the effects of hybrid modeling approaches, factor standardization, and categorical mapping on the performance of landslide susceptibility mapping in Van, Turkey D. Ozturk & N. Uzel-Gunini https://doi.org/10.1007/s11069-022-05480-y
251. Flood Susceptibility and Risk Mapping of Kathmandu Valley Watershed, Nepal U. Chaudhary et al. https://doi.org/10.3390/su16167101
252. Terrain-based Predictive Modeling of Riparian Vegetation in a Northern Rocky Mountain Watershed L. Shoutis et al. https://doi.org/10.1007/s13157-010-0047-5
253. Land tenure and landscape change: a comparison of public-private lands in the southern High Plains T. Fagin et al. https://doi.org/10.1186/s13717-016-0056-2
254. Integrating geospatial and hydrodynamic modelling to unravel cultural heritage vulnerability to dam breaches and flash flood in arid environments Y. Youssef et al. https://doi.org/10.1016/j.ijdrr.2025.105605
255. Tracing the culprits over the destruction of three coastal communities during a rouge rainstorm on August 2021 in north central Türkiye A. Oguz Altunel & F. Kara https://doi.org/10.1016/j.ocecoaman.2023.106630
256. External environmental factors shaping spatiotemporal patterns of bark beetle outbreaks in Central Mexico M. Salinas-Melgoza et al. https://doi.org/10.1088/2515-7620/ae14be
257. Integrating physics-guided Persistent Scatterer Interferometry (PS-InSAR) derived indices and machine learning for landslide susceptibility mapping D. Khadka et al. https://doi.org/10.1016/j.asr.2026.08.058
258. Importance of geological information for assessing drain flow in a Danish till landscape A. Hansen et al. https://doi.org/10.1002/hyp.13338
259. Digital terrain analysis of a landslide on the loess tableland using high-resolution topography data S. Hu et al. https://doi.org/10.1007/s10346-018-1103-0
260. Natural landscapes preferred for the location of past watermills and their predisposition to preserve cultural landscape enclaves D. Szatten et al. https://doi.org/10.1016/j.ancene.2023.100376
261. Recovery of ecosystem functions after experimental disturbance in 73 grasslands differing in land‐use intensity, plant species richness and community composition D. Schäfer et al. https://doi.org/10.1111/1365-2745.13211
262. Space-time dynamics of soil moisture and groundwater in an agriculture-dominated critical zone observatory (CZO) in the Ganga basin, India S. Dash & R. Sinha https://doi.org/10.1016/j.scitotenv.2022.158231
263. SLEM (Shallow Landslide Express Model): A Simplified Geo-Hydrological Model for Powerlines Geo-Hazard Assessment A. Abbate & L. Mancusi https://doi.org/10.3390/w16111507
264. Development of Pedo-Transfer Functions for the Saturated Hydraulic Conductivity of Forest Soil in South Korea Considering Forest Stand and Site Characteristics H. Lim et al. https://doi.org/10.3390/w12082217
265. Does Wyoming’s Core Area Policy Protect Winter Habitats for Greater Sage-Grouse? K. Smith et al. https://doi.org/10.1007/s00267-016-0745-8
266. More Data or a Better Model? Figuring Out What Matters Most for the Spatial Prediction of Soil Carbon P. Somarathna et al. https://doi.org/10.2136/sssaj2016.11.0376
267. A comparison of hillslope drainage area estimation methods using high‐resolution DEMs with implications for topographic studies of gullies S. Walker et al. https://doi.org/10.1002/esp.5171
268. Flood vulnerability assessment in Mopani District Municipality, South Africa. Part 1: Physical factors and adaptation framework R. Munyai et al. https://doi.org/10.1007/s11069-026-08299-z
269. Multisensor earth observations to characterize wetlands and malaria epidemiology in Ethiopia A. Midekisa et al. https://doi.org/10.1002/2014WR015634
270. Increased flood susceptibility in the Tibetan Plateau with climate and land use changes R. Ya et al. https://doi.org/10.1016/j.ecolind.2023.111086
271. Enhancing snow avalanche susceptibility assessment with meta-heuristic optimization and deep learning algorithms A. Ghayur Sadigh et al. https://doi.org/10.1007/s13762-025-06387-4
272. Environmental and socioeconomic factors of abandonment of rainfed and irrigated crops in northeast Spain J. Vidal-Macua et al. https://doi.org/10.1016/j.apgeog.2017.12.005
273. Monthly microclimate models in a managed boreal forest landscape C. Greiser et al. https://doi.org/10.1016/j.agrformet.2017.12.252
274. Comparison of Flow Direction Algorithms in the Application of the CTI for Mapping Wetlands in Minnesota L. Rampi et al. https://doi.org/10.1007/s13157-014-0517-2
275. Multiple factors associated with forest decline in the context of control measures for the pinewood nematode C. Pimentel et al. https://doi.org/10.1007/s10658-025-03122-0
276. GIS-based modeling of landslide susceptibility zonation by integrating the frequency ratio and objective–subjective weighting approach: a case study in a tropical monsoon climate region P. Hoa et al. https://doi.org/10.3389/fenvs.2023.1175567
277. Mapping Earth Hummocks in Daisetsuzan National Park in Japan Using UAV-SfM Framework Y. Meng et al. https://doi.org/10.3390/rs16193610
278. Application of Support Vector Regression and Metaheuristic Optimization Algorithms for Groundwater Potential Mapping in Gangneung-si, South Korea M. Fadhillah et al. https://doi.org/10.3390/rs13061196
279. Coastal shallow groundwater in Togo: vulnerability assessment using the DRASTIC method with EC validation K. Djongon et al. https://doi.org/10.1007/s40808-025-02346-7
280. Comparison of different statistical approaches to assess spring potential mapping in a multi-aquifer system: a case study of Kurdistan Region, Iraq D. Hamamin et al. https://doi.org/10.1007/s12665-023-11250-1
281. Efficacy of using radar-derived factors in landslide susceptibility analysis: case study of Koslanda, Sri Lanka A. Ranasinghe et al. https://doi.org/10.5194/nhess-19-1881-2019
282. Where and When Soil Amendment is Most Effective as a Low Impact Development Practice in Residential Areas C. Voter & S. Loheide https://doi.org/10.1111/1752-1688.12870
283. Delineating wetland areas from the cut-and-fill method using a Digital Elevation Model (DEM) Z. Lidzhegu et al. https://doi.org/10.1080/03736245.2019.1638825
284. Spatial Identification and Distribution Pattern of the Complexity of Rural Poverty in China Using Multisource Spatial Data Z. Qi et al. https://doi.org/10.1155/2024/7012402
285. Delineation of groundwater potential zones using GIS and AHP techniques in Coimbatore district, South India K. Kom et al. https://doi.org/10.1007/s42108-022-00188-y
286. Physical land suitability map for Tuber magnatum Pico in Piana Crixia municipality territory (Liguria-Italy) I. Rellini et al. https://doi.org/10.4113/jom.2011.1180
287. A Citizen-Contributed GIS Approach for Evaluating the Impacts of Land Use on Hurricane-Harvey-Induced Flooding in Houston Area D. Yang et al. https://doi.org/10.3390/land8020025
288. Modeling habitat suitability and spread dynamics of two invasive rose species in protected areas of Mendoza, Argentina A. Mazzolari et al. https://doi.org/10.1016/j.ecocom.2020.100868
289. Habitat associations of woody plant species in evergreen–deciduous broadleaf karst forests in southwest China L. Su et al. https://doi.org/10.3389/fevo.2023.1148910
290. Assessment of Neotectonic Landscape Deformation in Evia Island, Greece, Using GIS-Based Multi-Criteria Analysis K. Valkanou et al. https://doi.org/10.3390/ijgi10030118
291. Design principles for social-ecological research at the landscape scale applied to western Rwanda M. Baumann et al. https://doi.org/10.1371/journal.pone.0330704
292. Discriminating disturbance from natural variation with LiDAR in semi‐arid forests in the southwestern USA T. Swetnam et al. https://doi.org/10.1890/ES14-00384.1
293. A New Hybrid Firefly–PSO Optimized Random Subspace Tree Intelligence for Torrential Rainfall-Induced Flash Flood Susceptible Mapping V. Nhu et al. https://doi.org/10.3390/rs12172688
294. Disentangling the functional trait correlates of spatial aggregation in tropical forest trees I. McFadden et al. https://doi.org/10.1002/ecy.2591
295. Enhancing groundwater potential zone mapping with a hybrid analytical method: The case of semiarid basin B. Zerouali et al. https://doi.org/10.1016/j.gsd.2024.101261
296. Application of NRCS-CN method for estimation of watershed runoff and disaster risk W. Zhang https://doi.org/10.1080/19475705.2019.1686431
297. The Anatomy of Uncertain Terrains: Soil Topography Characterization and Discharge Analysis of the Baroro River Basin, Northern Philippines J. Trio et al. https://doi.org/10.69569/jip.2025.818
298. Mixed-Severity Fire Fosters Heterogeneous Spatial Patterns of Conifer Regeneration in a Dry Conifer Forest S. Malone et al. https://doi.org/10.3390/f9010045
299. A GIS-Based Hydrological Modeling Approach for Rapid Urban Flood Hazard Assessment Q. Zhou et al. https://doi.org/10.3390/w13111483
300. Landslide Susceptibility Mapping with Deep Learning Algorithms J. Habumugisha et al. https://doi.org/10.3390/su14031734
301. Relationship between human population density and urban land use as an indicator of urbanization in landscape ecological approach and its regional differences in Japan M. SAITO et al. https://doi.org/10.3825/ece.20.205
302. Functional traits help identify remote sensing blind spots in polar vegetation mapping I. de Jonge et al. https://doi.org/10.1016/j.ecolind.2026.115107
303. Landslide Mapping and Susceptibility Assessment in the Middle and Lower Reaches of the Nujiang River (2017–2025) Using Satellite Embedding and Multidimensional Environmental Factors W. Liu et al. https://doi.org/10.3390/rs18111854
304. Locally rare species influence grassland ecosystem multifunctionality S. Soliveres et al. https://doi.org/10.1098/rstb.2015.0269
305. Integrating Landslide Typology with Weighted Frequency Ratio Model for Landslide Susceptibility Mapping: A Case Study from Lanzhou City of Northwestern China H. Shu et al. https://doi.org/10.3390/rs13183623
306. Tillage Management Impacts on Soil Phosphorus Variability under Maize–Soybean Rotation in Eastern Canada J. Nze Memiaghe et al. https://doi.org/10.3390/soilsystems6020045
307. Representativeness of FLUXNET Sites Across Latin America S. Villarreal & R. Vargas https://doi.org/10.1029/2020JG006090
308. Geospatial Landslide Risk Mapping Using AHP and GIS: A Case Study of the Utcubamba River Basin, Peru C. Rivera et al. https://doi.org/10.3390/app15179423
309. Flood Susceptibility Assessment for Improving the Resilience Capacity of Railway Infrastructure Networks G. Varra et al. https://doi.org/10.3390/w16182592
310. Spatial variability of forest floor and topsoil thicknesses and their relation to topography and forest stand characteristics in managed forests of Norway spruce and European beech K. Zajícová & T. Chuman https://doi.org/10.1007/s10342-020-01316-1
311. Contrasting responses of above- and belowground diversity to multiple components of land-use intensity G. Le Provost et al. https://doi.org/10.1038/s41467-021-23931-1
312. Drought tolerance as a driver of tropical forest assembly: resolving spatial signatures for multiple processes M. Bartlett et al. https://doi.org/10.1890/15-0468.1
313. Assessing explanatory factors for variation in on-farm irrigation in US maize-soybean systems K. Gibson et al. https://doi.org/10.1016/j.agwat.2017.11.008
314. A Spatial Database of Ecosystems of the Lake Baikal Basin S. Bazha et al. https://doi.org/10.1134/S2079096122030039
315. A hybrid approach: remote sensing, analytic hierarchy process and geographic information system for groundwater potential mapping in Dediapada, India G. Kiran et al. https://doi.org/10.1007/s11356-024-35666-9
316. Geoinformatics and hydrogeophysical-based delineation of groundwater potential zone through surface and subsurface indicators U. Basharat et al. https://doi.org/10.1007/s13201-025-02580-5
317. Spatial Prediction of the Groundwater Potential Using Remote Sensing Data and Bivariate Statistical-Based Artificial Intelligence Models Y. Ye et al. https://doi.org/10.1007/s11269-022-03307-w
318. The Driving Forces and Spatial Predictions of Soil Total Nitrogen and Soil Total Phosphorus Using Machine Learning and Explainable AI: A Case Study of Grasslands in Qinghai Province, China X. Guo et al. https://doi.org/10.3390/land15050843
319. Synergistic Use of Geospatial Data for Water Body Extraction from Sentinel-1 Images for Operational Flood Monitoring across Southeast Asia Using Deep Neural Networks J. Kim et al. https://doi.org/10.3390/rs13234759
320. Identification of spatial potential flood-prone area using topographic wetness index under the digital elevation model of Kr. Keureuto watershed, North Aceh. M. Rizalihadi et al. https://doi.org/10.1088/1742-6596/2916/1/012009
321. Integrating remote sensing and GBIF to map the biodiversity-threatening invasive Acacia species K. Matsokane & S. Tesfamichael https://doi.org/10.1016/j.ecofro.2026.04.013
322. Insights from the topographic characteristics of a large global catalog of rainfall-induced landslide event inventories R. Emberson et al. https://doi.org/10.5194/nhess-22-1129-2022
323. Review of remotely sensed data products for disease mapping and epidemiology S. Dlamini et al. https://doi.org/10.1016/j.rsase.2019.02.005
324. Integrated remote sensing and geographic information system overlay analysis for groundwater potential evaluation using AHP and fuzzy AHP: Southern sections of the western Afar rift margin and associated rift floor D. Gidafie et al. https://doi.org/10.1016/j.gsd.2024.101310
325. Hydrological assessment of groundwater potential zones of Cauvery River Basin, India: a geospatial approach P. Arulbalaji et al. https://doi.org/10.1007/s12665-019-8673-6
326. Seismic site characterization using satellite-derived terrain morphometry and geological data: A machine learning approach for predominant frequency prediction H. Thakur & P. Anbazhagan https://doi.org/10.1016/j.enggeo.2025.108541
327. Entropy-Based Modelling for Flash Flood Hazard Mapping in Uttarakhand Himalaya H. Prince et al. https://doi.org/10.1007/s12524-023-01797-8
328. Application of a hybrid neural-fuzzy inference system for mapping crop suitability areas and predicting rice yields K. Dang et al. https://doi.org/10.1016/j.envsoft.2019.01.015
329. A Semi-empirical Approach Based on Genetic Programming for the Study of Biophysical Controls on Diameter-Growth of Fagus orientalis in Northern Iran M. Bayat et al. https://doi.org/10.3390/rs11141680
330. Multi-hazard Vulnerability Assessment Through RS-GIS and AHP: A Geo-Spatial Study of Keleghai River Basin in India A. Roy & S. Dhar https://doi.org/10.1007/s41742-025-00867-8
331. High-Resolution Bioclimatic Surfaces for Southern Peru: An Approach to Climate Reality for Biological Conservation G. Pauca-Tanco et al. https://doi.org/10.3390/cli11050096
332. Environmental factors influencing DDT–DDE spatial distribution in an agricultural drainage system determined by using machine learning techniques I. Melendez-Pastor et al. https://doi.org/10.1007/s10653-023-01486-y
333. Eco-Cultural Niche Breadth and Overlap Within the Cucuteni–Trypillia Culture Groups During the Eneolithic A. Mihu-Pintilie & I. Gherghel https://doi.org/10.3389/feart.2022.910836
334. Brown Bear Food-Probability Models in West-European Russia: On the Way to the Real Resource Selection Function S. Ogurtsov et al. https://doi.org/10.3390/f13081247
335. A hydrologic and land cover‐based habitat model for use in bog turtle (Glyptemys muhlenbergii) conservation J. Feaga et al. https://doi.org/10.1002/aqc.4215
336. Amount, distribution and driving factors of soil organic carbon and nitrogen in cropland and grassland soils of southeast Germany (Bavaria) M. Wiesmeier et al. https://doi.org/10.1016/j.agee.2013.05.012
337. Landslide Susceptibility Mapping Using Rotation Forest Ensemble Technique with Different Decision Trees in the Three Gorges Reservoir Area, China Z. Fang et al. https://doi.org/10.3390/rs13020238
338. Spatial patterns of tree cover change at a dry forest margin are driven by initial conditions, water balance and wildfire L. Harris & A. Taylor https://doi.org/10.1007/s10980-020-01178-3
339. Incorporating probabilistic approach into local multi-criteria decision analysis for flood susceptibility assessment Z. Tang et al. https://doi.org/10.1007/s00477-017-1431-y
340. Landscape structure control on soil CO2 efflux variability in complex terrain: Scaling from point observations to watershed scale fluxes D. Riveros‐Iregui & B. McGlynn https://doi.org/10.1029/2008JG000885
341. Topoclimatic factors create favourable conditions for carbon-dense forests in the Central Himalayas S. Khanal et al. https://doi.org/10.1038/s41598-025-19127-y
342. Estimating aboveground biomass of broadleaf, needleleaf, and mixed forests in Northeastern China through analysis of 25-m ALOS/PALSAR mosaic data J. Ma et al. https://doi.org/10.1016/j.foreco.2016.12.020
343. Parameter's Controls of Distributed Catchment Models—How Much Information is in Conventional Catchment Descriptors? R. Merz et al. https://doi.org/10.1029/2019WR026008
344. Geomorphic edge effects in response to abiotic and anthropogenic disturbances in forest ecosystems of the Gorce Mountains, Western Carpathians Ł. Pawlik et al. https://doi.org/10.1016/j.catena.2019.02.013
345. Poor transferability of richness models: Predicting plot-scale plant diversity in the Waterberg, South Africa T. Venter et al. https://doi.org/10.1016/j.sajb.2024.05.052
346. Soil organic carbon storage as a key function of soils - A review of drivers and indicators at various scales M. Wiesmeier et al. https://doi.org/10.1016/j.geoderma.2018.07.026
347. Development of an Integrated DBH Estimation Model Based on Stand and Climatic Conditions D. Piao et al. https://doi.org/10.3390/f9030155
348. Organic carbon accumulation in the glacier forelands with regard to variability of environmental conditions in different ecogenesis stages of High Arctic ecosystems P. Wietrzyk-Pełka et al. https://doi.org/10.1016/j.scitotenv.2019.135151
349. Combining geomorphometry, feature extraction techniques and Earth-surface processes research: The way forward G. Sofia https://doi.org/10.1016/j.geomorph.2020.107055
350. Engineered slope failure susceptibility modelling using high spatial resolution geospatial data S. Obrike et al. https://doi.org/10.1007/s10064-021-02413-0
351. Estimating habitat extent and carbon loss from an eroded northern blanket bog using UAV derived imagery and topography P. Scholefield et al. https://doi.org/10.1177/0309133319841300
352. Intercomparison of regional flood frequency estimation procedures in West Africa S. Diop et al. https://doi.org/10.1007/s00477-026-03258-3
353. The hydrologic nature of swales uncovers remarkable influence of non-topographic factors on catchment-scale soil moisture variation Y. Zhang et al. https://doi.org/10.1016/j.jhydrol.2024.131196
354. Guiding oil palm intensification through a spatial extrapolation domain framework F. Agus et al. https://doi.org/10.1016/j.agsy.2023.103778
355. Transforming MGNREGA assets to ecosystem benefits in Andhra Pradesh Region, India: A geospatial approach A. Rahaman et al. https://doi.org/10.1016/j.nxsust.2026.100522
356. The Effects of Clear-Cutting on Ground Thermal Regimes After a Wildfire Using Hand-Held Thermal Imaging Camera in a Semi-arid Forest Ecosystems T. Dindaroglu et al. https://doi.org/10.1007/s41742-022-00504-8
357. Predicted areas of potential distributions of alpine wetlands under different scenarios in the Qinghai-Tibetan Plateau, China Z. Xue et al. https://doi.org/10.1016/j.gloplacha.2014.10.012
358. Wetland and groundwater chemistry shows evidence of aluminosilicate weathering in hyperarid Antarctic cold desert soils J. Levy et al. https://doi.org/10.1130/B38634.1
359. Regional rainfall and local topography jointly drive tree community assembly in lowland tropical forests of New Caledonia G. Blanchard et al. https://doi.org/10.1111/jvs.12781
360. High species diversity and turnover in granite inselberg floras highlight the need for a conservation strategy protecting many outcrops C. Yates et al. https://doi.org/10.1002/ece3.5318
361. Ecological manifestation of slope instability, its application in identification of areas of potential hill slope movement in Indian Himalaya P. Negi https://doi.org/10.1016/j.ecolind.2012.09.009
362. Within-field spatial variability of greenhouse gas fluxes from an extensive and intensive sheep-grazed pasture A. Charteris et al. https://doi.org/10.1016/j.agee.2021.107355
363. Interspecific interaction, habitat, or neighborhood occupancy? Long-term dataset reveals factors influencing the barred owl invasion through time K. McGee et al. https://doi.org/10.1016/j.biocon.2026.111835
364. Mapping crop yield spatial variability using Sentinel-2 vegetation indices in Ethiopia G. Tiruneh et al. https://doi.org/10.1007/s12517-023-11754-x
365. Effects of artificial land drainage on hydrology, nutrient and pesticide fluxes from agricultural fields – A review A. Gramlich et al. https://doi.org/10.1016/j.agee.2018.04.005
366. Landslide susceptibility assessment using the frequency ratio model in the Mae Chan River watershed, northern Thailand P. Manopkawee & N. Mankhemthong https://doi.org/10.1016/j.qsa.2024.100263
367. GIS-based spatial prediction of poor-drainage areas using frequency ratio: a case study of Tekirdag Province, Turkey E. Ozsahin et al. https://doi.org/10.1007/s12518-022-00439-x
368. Predicting soil moisture conditions across a heterogeneous boreal catchment using terrain indices J. Larson et al. https://doi.org/10.5194/hess-26-4837-2022
369. Legacy effects of sika deer overpopulation on ground vegetation and soil physical properties K. Harada et al. https://doi.org/10.1016/j.foreco.2020.118346
370. Estimating Invasion Success by Non-Native Trees in a National Park Combining WorldView-2 Very High Resolution Satellite Data and Species Distribution Models A. Monteiro et al. https://doi.org/10.3390/d9010006
371. Vegetation recovery and management proposal for spoil heaps in Sorachi, Hokkaido H. Kawai et al. https://doi.org/10.5738/jale.27.3
372. Trajectories, drivers, and probabilities of land cover change in a disturbed forested watershed in eastern Taiwan C. Yeh & S. Liaw https://doi.org/10.1007/s11069-016-2235-y
373. Evolution of particulate organic matter (POM) along a headwater drainage: role of sources, particle size class, and storm magnitude R. Rowland et al. https://doi.org/10.1007/s10533-017-0325-x
374. Using Remote Sensing and Machine Learning to Locate Groundwater Discharge to Salmon-Bearing Streams M. Gerlach et al. https://doi.org/10.3390/rs14010063
375. Generalized Mathematical Morphological Method for 3D Shape Analysis of Geological Boundaries: Application in Identifying Mineralization-Associated Shape Features H. Deng et al. https://doi.org/10.1007/s11053-021-09975-6
376. Variability in soil carbon-to-nitrogen ratios explained by environmental conditions in a boreal catchment J. Larson et al. https://doi.org/10.1016/j.foreco.2024.122108
377. Spatial Prediction of Organic Matter Quality in German Agricultural Topsoils A. Sakhaee et al. https://doi.org/10.3390/agriculture14081298
378. Positive effects of projected climate change on post-disturbance forest regrowth rates in northeastern North American boreal forests V. Danneyrolles et al. https://doi.org/10.1088/1748-9326/acb72a
379. Urban Flood Dynamic Risk Assessment Based on Typhoon Rainfall Process: A Case Study of Typhoon “Lupit” (2109) in Fuzhou, China X. Qin et al. https://doi.org/10.3390/rs15123116
380. Using topographic wetness index in vegetation ecology: does the algorithm matter? M. Kopecký & Š. Čížková https://doi.org/10.1111/j.1654-109X.2010.01083.x
381. Modeling intensification decisions in the Kilombero Valley floodplain: A Bayesian belief network approach B. Gebrekidan et al. https://doi.org/10.1111/agec.12740
382. Principled XAI analysis of the deep learning-based landslide susceptibility prediction model J. Oh et al. https://doi.org/10.1038/s41598-026-52786-z
383. Method for classifying sites to Atlantic Rainforest restoration aiming to increase basin’s streamflows R. Cecílio et al. https://doi.org/10.3832/ifor3658-013
384. Local fresh- and sea-water effects on fog occurrence I. Hůnová et al. https://doi.org/10.1016/j.scitotenv.2021.150799
385. Management zone delineation strategies for phosphorus fertilizer recommendations under a no-till field in Eastern Canada J. Nze Memiaghe et al. https://doi.org/10.1139/cjss-2023-0088
386. Flood Risk and Community Resilience in Northeast Thailand: A Multi-Temporal Analysis of Population Dynamics and Environmental Indicators for Sustainable Development P. Littidej et al. https://doi.org/10.3390/su18178912
387. Hydrological convergence and surface–groundwater connectivity are associated with fluorescent groundwater DOM in the Victoria and Kyoga Basins, Uganda D. Muloogi et al. https://doi.org/10.1016/j.apgeochem.2026.106955
388. Development of the critical zone environment in the highly dynamic landscape of the Forni Glacier forefield: Winds, tree vegetation, pedogenesis and surface waters after glacier retreat G. Leonelli et al. https://doi.org/10.1002/esp.5983
389. Digital mapping of DTPA extractable micronutrients using combined AVIRIS-NG hyperspectral and multispectral data of Sentinel-2 and SRTM-DEM B. Mondal et al. https://doi.org/10.1016/j.compag.2025.110905
390. Potential storages and drivers of soil organic carbon and total nitrogen across river basin landscape: The case of Mo river basin (Togo) in West Africa B. Diwediga et al. https://doi.org/10.1016/j.ecoleng.2016.11.055
391. Revisiting the tension water storage capacity distribution in conceptual rainfall-runoff modeling: A large-sample approach Y. Zhou et al. https://doi.org/10.1016/j.jhydrol.2024.131834
392. Mapping an Indicator Species of Sea-Level Rise along the Forest–Marsh Ecotone B. Norlin et al. https://doi.org/10.3390/land13101551
393. Hybrid Gravimetry to Map Water Storage Dynamics in a Mountain Catchment Q. Chaffaut et al. https://doi.org/10.3389/frwa.2021.715298
394. Radon emissions as indicators of changes in tropical Andean ecosystems emerging after glacial retreat under climate forcing C. Yarleque et al. https://doi.org/10.1007/s11629-025-0214-z
395. Predictive mapping of aquatic ecosystems by means of support vector machines and random forests P. Martínez-Santos et al. https://doi.org/10.1016/j.jhydrol.2021.126026
396. A multi-source framework for shallow landslide detection and warning in Da-river basin, Vietnam H. Nguyen et al. https://doi.org/10.1080/01431161.2026.2618102
397. Modelling hydrological factors from DEM using GIS M. Chowdhury https://doi.org/10.1016/j.mex.2023.102062
398. Drivers of the Fine- and Broad-Scale Distribution of a Woody Encroacher in a Montane Grassland G. Akomolafe et al. https://doi.org/10.1016/j.rama.2025.10.008
399. The Nonpoint Sources and Transport of Baseflow Nitrogen Loading Across a Developed Rural‐Urban Gradient J. Delesantro et al. https://doi.org/10.1029/2021WR031533
400. A new dynamic wetness index (DWI) predicts soil moisture persistence and correlates with key indicators of surface soil geochemistry M. Li et al. https://doi.org/10.1016/j.geoderma.2020.114239
401. Geology, geomorphology and Vs30 based site classification of the Himalayan region using a stacked model H. Thakur & P. Anbazhagan https://doi.org/10.1016/j.enggeo.2025.108229
402. Spatially distributed tracer‐aided modelling to explore water and isotope transport, storage and mixing in a pristine, humid tropical catchment J. Dehaspe et al. https://doi.org/10.1002/hyp.13258
403. The potential of combining satellite and airborne remote sensing data for habitat classification and monitoring in forest landscapes A. Iglseder et al. https://doi.org/10.1016/j.jag.2022.103131
404. Carbon sequestration potential of soils in southeast Germany derived from stable soil organic carbon saturation M. Wiesmeier et al. https://doi.org/10.1111/gcb.12384
405. New sediment continuum measurements in the Brda River (Poland): the results of the functioning of the 50-year Koronowo dam D. Szatten et al. https://doi.org/10.1007/s11368-023-03582-z
406. Modelling farmland abandonment: A study combining GIS and data mining techniques B. Zaragozí et al. https://doi.org/10.1016/j.agee.2012.03.019
407. Challenges in Tropical Dendrochronology: Perspectives from a 10-Year Effort in Eastern Amazonia D. Granato et al. https://doi.org/10.3959/TRR2026-1
408. Assessing the Potential of EMIT Hyperspectral Data Combined with DEM-Derived Terrain Variables for Predicting Soil As, Cu and Zn Concentrations in a Mountainous Region of Southwest China G. Qie et al. https://doi.org/10.3390/rs18132211
409. Assessment of Antarctic moss health from multi-sensor UAS imagery with Random Forest Modelling D. Turner et al. https://doi.org/10.1016/j.jag.2018.01.004
410. Climate and topography control variation in the tropical dry forest–rainforest ecotone J. Walter et al. https://doi.org/10.1002/ecy.4442
411. Controls on Temperature in Salmonid‐Bearing Headwater Streams in Two Common Hydrogeologic Settings, Kenai Peninsula, Alaska M. Callahan et al. https://doi.org/10.1111/jawr.12235
412. Distinguishing and mapping permanent and reversible paludified landscapes in Canadian black spruce forests A. Laamrani et al. https://doi.org/10.1016/j.geoderma.2014.08.011
413. Uncovering patterns of near-surface saturated hydraulic conductivity in an overland flow-controlled landscape A. Zimmermann et al. https://doi.org/10.1016/j.geoderma.2012.11.002
414. Remote Soil Moisture Measurement from Drone-Borne Reflectance Spectroscopy: Applications to Hydroperiod Measurement in Desert Playas J. Levy & J. Johnson https://doi.org/10.3390/rs13051035
415. Unmanned Aircraft System (UAS) Structure-From-Motion (SfM) for Monitoring the Changed Flow Paths and Wetness in Minerotrophic Peatland Restoration L. Ikkala et al. https://doi.org/10.3390/rs14133169
416. Algorithms and Predictors for Land Cover Classification of Polar Deserts: A Case Study Highlighting Challenges and Recommendations for Future Applications É. Desjardins et al. https://doi.org/10.3390/rs15123090
417. Predicting Redox Conditions in Groundwater at a National Scale Using Random Forest Classification A. Tesoriero et al. https://doi.org/10.1021/acs.est.3c07576
418. Global patterns and environmental correlates of high‐priority conservation areas for vertebrates F. Albuquerque & P. Beier https://doi.org/10.1111/jbi.12498
419. Using a hybrid demand-allocation algorithm to enable distributional analysis of land use change patterns E. Brooks et al. https://doi.org/10.1371/journal.pone.0240097
420. Catchment topography and wetland geomorphology drive macroinvertebrate community structure and juvenile salmonid distributions in south-central Alaska headwater streams R. King et al. https://doi.org/10.1899/11-109.1
421. Evaluation of geomorphometric characteristics and soil properties after a wildfire using Sentinel-2 MSI imagery for future fire-safe forest T. Dindaroglu et al. https://doi.org/10.1016/j.firesaf.2021.103318
422. Identifying potential for rice expansion in Burkina Faso: integrating EO and climate data for suitability mapping J. Meier et al. https://doi.org/10.3389/fclim.2025.1548416
423. Assimilation of optical and radar remote sensing data in 3D mapping of soil properties over large areas L. Poggio & A. Gimona https://doi.org/10.1016/j.scitotenv.2016.11.078
424. Machine learning for predicting landslide risk of Rohingya refugee camp infrastructure N. Ahmed et al. https://doi.org/10.1080/24751839.2019.1704114
425. Enhancing Machine Learning-Based GPP Upscaling Error Correction: An Equidistant Sampling Method with Optimized Step Size and Intervals Z. Wang et al. https://doi.org/10.3390/rs18010023
426. An innovative, fast method for landslide susceptibility mapping using GIS-based LSAT toolbox A. Polat https://doi.org/10.1007/s12665-021-09511-y
427. Predictive modeling of Cedrus atlantica natural regeneration: grazing intensity and bioclimatic extremes as the primary drivers in the Ain Leuh Forest, Middle Atlas of Morocco Y. Boussalim & Y. Dallahi https://doi.org/10.1007/s40808-024-02191-0
428. Simulation and validation of concentrated subsurface lateral flow paths in an agricultural landscape Q. Zhu & H. Lin https://doi.org/10.5194/hess-13-1503-2009
429. Using drone-based multispectral imaging for investigating gravelly debris flows and geomorphic characteristics H. Chen et al. https://doi.org/10.1007/s12665-024-11544-y
430. Vegetation, soil, and weathered bedrock control hillslope rainfall-runoff processes on the Qinghai-Tibetan plateau P. Lin et al. https://doi.org/10.1016/j.catena.2026.110488
431. Fine-Scale Environmental Heterogeneity Shapes Post-Fire Macrofungal Richness in a Mediterranean Relict Forest C. Santos-Silva et al. https://doi.org/10.3390/fire8110438
432. Deciphering complexity of block-faulted topography – Insights from morphometric variables, drainage patterns and river profiles (Orlickie-Bystrzyckie Mountains Block, Central Europe) M. Różycka & P. Migoń https://doi.org/10.1016/j.geomorph.2023.108621
433. Evaluation of TWI index and TOPMODEL hydrological model in erosion and runoff (case study: Maroon basin in southwest Iran) A. Ghalesardi Gonjanak et al. https://doi.org/10.61186/jeer.14.3.66
434. Landslide susceptibility modeling based on remote sensing data and data mining techniques X. Wang et al. https://doi.org/10.1007/s12665-022-10195-1
435. Spatiotemporal predictions of soil properties and states in variably saturated landscapes T. Franz et al. https://doi.org/10.1002/2017JG003837
436. Assessment of coastal flood risks in a selected urban area in Bangladesh M. Rahman & A. Akter https://doi.org/10.1007/s11069-024-06752-5
437. Weathering dynamics and micro-scale biogeomorphology in the proglacial environment of Midtre Lovénbreen, Spitsbergen I. Badura et al. https://doi.org/10.1016/j.catena.2025.109665
438. Modeling soil salinity using direct and indirect measurement techniques: A comparative analysis A. Abdullah et al. https://doi.org/10.1016/j.envdev.2018.12.007
439. Regional dynamic early warning model for rainfall-induced landslide in Fujian, China H. Dou et al. https://doi.org/10.1080/19475705.2024.2435510
440. Walk the Talk: Private Sustainability Standards in the Ugandan Coffee Sector K. Akoyi & M. Maertens https://doi.org/10.1080/00220388.2017.1327663
441. Modelling the ecosystem indicators of British Columbia using Earth observation data and terrain indices J. Fitterer et al. https://doi.org/10.1016/j.ecolind.2012.02.024
442. Sustainable Geoinformatic Approaches to Insurance for Small-Scale Farmers in Colombia A. Abd Rabuh et al. https://doi.org/10.3390/su16125104
443. LiDAR-based TWI and terrain attributes in improving parametric predictor for tree growth in southeast Finland C. Mohamedou et al. https://doi.org/10.1016/j.jag.2017.06.004
444. Remotely-sensed assessment of the impact of century-old biochar on chicory crop growth using high-resolution UAV-based imagery R. Heidarian Dehkordi et al. https://doi.org/10.1016/j.jag.2020.102147
445. Determining local wetness conditions within the mined lands using GIS O. Skrypnyk et al. https://doi.org/10.33271/mining14.04.053
446. An effective alternative for predicting coastal floodplain inundation by considering rainfall, storm surge, and downstream topographic characteristics P. Huang https://doi.org/10.1016/j.jhydrol.2022.127544
447. A Random Forest-Based Multi-Index Classification (RaFMIC) Approach to Mapping Three-Decadal Inundation Dynamics in Dryland Wetlands Using Google Earth Engine I. Senanayake et al. https://doi.org/10.3390/rs15051263
448. A GIS-based integrated assessment of geomorphometry with land use dynamics for topographically harsh ungauged watershed D. Roy et al. https://doi.org/10.1007/s12040-025-02557-7
449. Urban flood susceptibility assessment based on convolutional neural networks G. Zhao et al. https://doi.org/10.1016/j.jhydrol.2020.125235
450. Evaluating Machine Learning-Based Approaches in Land Subsidence Susceptibility Mapping E. Hosseinzadeh et al. https://doi.org/10.3390/land13030322
451. Using the Agricultural Policy/Environmental eXtender to develop and validate physically based indices for the delineation of critical management areas A. Mudgal et al. https://doi.org/10.2489/jswc.67.4.284
452. A data-driven approach to assess large fire size generation in Greece I. Mitsopoulos & G. Mallinis https://doi.org/10.1007/s11069-017-2934-z
453. A framework to bridge scales in distribution modeling of soil microbiota J. Lembrechts et al. https://doi.org/10.1093/femsec/fiaa051
454. Analysis of the Role of Topography in the Spatial Differentiation of Landscapes Using Geoinformation and Statistical Methods N. Pomazkova & V. Abakumova https://doi.org/10.1134/S1995425518020099
455. Flood Risk Assessment and Regionalization from Past and Future Perspectives at Basin Scale C. Lai et al. https://doi.org/10.1111/risa.13493
456. Training Machine Learning Algorithms Using Remote Sensing and Topographic Indices for Corn Yield Prediction M. Oliveira et al. https://doi.org/10.3390/rs14236171
457. Disentangling the effects of environmental factors on the distribution of vascular plants in Japan: the importance of land use for common species on a macroscale M. Saito et al. https://doi.org/10.1080/17550874.2015.1051153
458. Carbon isotope discrimination by Picea glauca and Populus tremuloides is related to the topographic depth to water index and rainfall G. Oltean et al. https://doi.org/10.1139/cjfr-2015-0491
459. What makes segmentation good? A case study in boreal forest habitat mapping A. Räsänen et al. https://doi.org/10.1080/01431161.2013.845318
460. Identifying groundwater potential zones in a typical irrigation district using the geospatial technique and analytic hierarchy process Q. Song et al. https://doi.org/10.1080/10106049.2025.2453025
461. A Remote Sensing Approach for Landslide Hazard Assessment on Engineered Slopes P. Miller et al. https://doi.org/10.1109/TGRS.2011.2165547
462. Geological Exploration, Landslide Characterization and Susceptibility Mapping at the Boundary between Two Crystalline Bodies in Jajarkot, Nepal Y. Shahi et al. https://doi.org/10.3390/geotechnics2040050
463. Estimation of the Budyko model parameter for small basins in China P. Bai et al. https://doi.org/10.1002/hyp.13577
464. Active layer modelling at Stelvio Pass, Italian Alps V. Chaturvedi et al. https://doi.org/10.1016/j.coldregions.2025.104762
465. Spatial filtering and Bayesian data fusion for mapping soil properties: A case study combining legacy and remotely sensed data in Iran Z. Rasaei & P. Bogaert https://doi.org/10.1016/j.geoderma.2019.02.031
466. Multicriterial techniques for wetland identification using geospatial analyses: the case of the Mefou Basin, Centre Region, Cameroon W. Kongnso et al. https://doi.org/10.1007/s42108-024-00294-z
467. Exploring the application of topographic indices in urban areas as indicators of pluvial flooding locations C. Kelleher & L. McPhillips https://doi.org/10.1002/hyp.13628
468. Advanced geospatial and machine learning models identify groundwater potential and reveal storage dynamics in Ethiopia’s abbay river basin K. Yasin et al. https://doi.org/10.1016/j.ejrh.2025.102762
469. Assessment of flood susceptible areas using spatially explicit, probabilistic multi-criteria decision analysis Z. Tang et al. https://doi.org/10.1016/j.jhydrol.2018.01.033
470. Chamaecyparis montane cloud forest in Taiwan: ecology and vegetation classification C. Li et al. https://doi.org/10.1007/s11284-015-1284-0
471. Distribution and habitat of endangered American burying beetle in northern and southern regions D. Leasure & W. Hoback https://doi.org/10.1007/s10841-017-9955-5
472. Ensemble Multi-Criteria Flood Susceptibility Modelling with Spatial Uncertainty Quantification: A Provincial-Scale Application in KwaZulu-Natal, South Africa P. Nxumalo et al. https://doi.org/10.3390/w18151912
473. Integration of multi-geostatistical approaches for deciphering groundwater potential zones in complex water-bearing mediums D. Hamamin https://doi.org/10.1016/j.gsd.2024.101208
474. The influence of climatic and topographic parameters on the distribution of forest communities of the Ufa plateau S. Zhigunova et al. https://doi.org/10.1088/1755-1315/876/1/012085
475. A new approach to flood susceptibility assessment in data-scarce and ungauged regions based on GIS-based hybrid multi criteria decision-making method Y. Kanani-Sadat et al. https://doi.org/10.1016/j.jhydrol.2019.02.034
476. Comparative Analysis of Future Landslide Susceptible Areas Based on Climate Change Scenario Applications J. Kim et al. https://doi.org/10.11628/ksppe.2023.26.5.565
477. Susceptibility modelling of hummocky terrain distribution using the information value method (Deception Island, Antarctic Peninsula) R. Melo et al. https://doi.org/10.1016/j.geomorph.2011.12.027
478. Fine- and broad-scale distribution of a cushion plant species: Patterns and predictors for Euphorbia clavarioides M. Momberg et al. https://doi.org/10.1080/15230430.2018.1505136
479. Simulating Hydrologic Effects of Raised Roads within a Low-Relief Watershed X. Wang et al. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000351
480. Tree height and leaf drought tolerance traits shape growth responses across droughts in a temperate broadleaf forest I. McGregor et al. https://doi.org/10.1111/nph.16996
481. How much surface water can gilgai microtopography capture? A. Kishné et al. https://doi.org/10.1016/j.jhydrol.2014.03.053
482. The 30 m land cover dataset for capturing land cover changes induced by ecological restoration from 1990 to 2022 on the Chinese Loess Plateau Z. Wang et al. https://doi.org/10.1038/s41597-025-04575-y
483. GIS and Remote Sensing-Based Multi-Criteria Analysis for Delineation of Groundwater Potential Zones: A Case Study for Industrial Zones in Bangladesh M. Rahman et al. https://doi.org/10.3390/su14116667
484. Distributed dynamic modelling of suspended sediment mobilization and transport from small agricultural catchments S. Sandström et al. https://doi.org/10.3389/fenvs.2023.1196048
485. Improving yield and profit in smallholder oil palm fields through better agronomy H. Sugianto et al. https://doi.org/10.1016/j.agsy.2025.104269
486. Multi-sensor airborne and satellite data for upscaling tree number information in a structurally complex eucalypt forest I. Shendryk et al. https://doi.org/10.1016/j.jag.2018.07.011
487. Landslide Hazard and Exposure Modelling in Data‐Poor Regions: The Example of the Rohingya Refugee Camps in Bangladesh R. Emberson et al. https://doi.org/10.1029/2020EF001666
488. Delineation of Groundwater Potential Zones (GWPZs) in a Semi-Arid Basin through Remote Sensing, GIS, and AHP Approaches J. Uc Castillo et al. https://doi.org/10.3390/w14132138
489. Mapping the Serological Prevalence Rate of West Nile fever in Equids, Tunisia R. Bargaoui et al. https://doi.org/10.1111/tbed.12077
490. Sequence-based mapping approach to spatio-temporal snow patterns from MODIS time-series applied to Scotland L. Poggio & A. Gimona https://doi.org/10.1016/j.jag.2014.08.005
491. Restoration of urban forests to reduce flood susceptibility: A starting point J. Viezzer et al. https://doi.org/10.1016/j.ijdrr.2022.102944
492. Cattle Grazing Distribution Patterns Related to Topography Across Diverse Rangeland Ecosystems of North America E. Raynor et al. https://doi.org/10.1016/j.rama.2020.12.002
493. Spatiotemporal railway use by grizzly bears in Canada's Rocky Mountains S. Pollock et al. https://doi.org/10.1002/jwmg.21750
494. Site suitability of emerging maize cultivation in a changing agroclimatic setting of eastern India: a fuzzy-MCE integrated analysis T. Goswami et al. https://doi.org/10.1007/s10668-022-02756-y
495. Unraveling the Relative Contributions of Deterministic and Stochastic Processes in Shaping Species Community Assembly in a Floodplain and Shallow Hillslope System G. Mendoza-Arroyo et al. https://doi.org/10.3390/f15020250
496. Using Remote Sensing and Climate Data to Map the Extent and Severity of Balsam Woolly Adelgid Infestation in Northern Utah, USA M. Campbell et al. https://doi.org/10.3390/f14071357
497. Understanding flood susceptibility in a monsoon-influenced catchment through interpretable deep learning and hydro-climatic controls D. Ghose & B. Mishra https://doi.org/10.1007/s11600-026-02001-4
498. Late quaternary thrust faulting in the western front of the Eastern Precordillera: the Villicum–Zonda–Pedernal fault system in the Sierra Chica de Zonda section, Central Andes of Argentina P. Blanc et al. https://doi.org/10.1007/s00531-026-02578-7
499. Convolutional neural network for high-resolution wetland mapping with open data: Variable selection and the challenges of a generalizable model K. Mainali et al. https://doi.org/10.1016/j.scitotenv.2022.160622
500. Modelling and Mapping Likely Soil Rutting Occurrences across Forested Areas D. Snow et al. https://doi.org/10.4236/jgis.2024.166023
501. Impact of topography on in situ soil wetness measurements for regional landslide early warning – a case study from the Swiss Alpine Foreland A. Wicki et al. https://doi.org/10.5194/nhess-23-1059-2023
502. Mapping and assessment of lake ecosystem services in Lithuania M. Inácio et al. https://doi.org/10.1016/j.ecoser.2023.101589
503. Statistical-based models for the production of landslide susceptibility maps and general risk analyses: a case study in Maçka, Turkey F. Kadi https://doi.org/10.1007/s11600-024-01380-w
504. UAV RGB, thermal infrared and multispectral imagery used to investigate the control of terrain on the spatial distribution of dryland biocrust J. Blanco‐Sacristán et al. https://doi.org/10.1002/esp.5189
505. Advancement of a diagnostic prediction model for spatiotemporal calibration of earth observation data: a case study on projecting forest net primary production in the mid-latitude region E. Park et al. https://doi.org/10.1080/15481603.2024.2401247
506. Towards better flood risk management: Assessing flood risk and investigating the potential mechanism based on machine learning models J. Chen et al. https://doi.org/10.1016/j.jenvman.2021.112810
507. A Novel Relevance Vector Machine Classifier with Cuckoo Search Optimization for Spatial Prediction of Landslides N. Hoang & D. Tien Bui https://doi.org/10.1061/(ASCE)CP.1943-5487.0000557
508. Quantification of continuous flood hazard using random forest classification and flood insurance claims at large spatial scales: a pilot study in southeast Texas W. Mobley et al. https://doi.org/10.5194/nhess-21-807-2021
509. Comparison of general kernel, multiple kernel, infinite ensemble and semi-supervised support vector machines for landslide susceptibility prediction Z. Fang et al. https://doi.org/10.1007/s00477-022-02208-z
510. A comparative study of heterogeneous ensemble-learning techniques for landslide susceptibility mapping Z. Fang et al. https://doi.org/10.1080/13658816.2020.1808897
511. GIS-based AHP approach to flood susceptibility assessment in Tangail district, Bangladesh R. Sharker et al. https://doi.org/10.1007/s12040-024-02480-3
512. GIS-based landslide susceptibility mapping of Western Rwanda: an integrated artificial neural network, frequency ratio, and Shannon entropy approach V. Nwazelibe et al. https://doi.org/10.1007/s12665-023-11134-4
513. A Modified Distributed CN-VSA Method for Mapping of the Seasonally Variable Source Areas K. Panjabi et al. https://doi.org/10.3390/w13091270
514. Analysing hydrological impacts of controlled drainage, peat thickness and groundwater fluxes in cultivated peat soils M. Tähtikarhu et al. https://doi.org/10.1080/09064710.2025.2454388
515. Analyzing and Projecting Soil Moisture and Cone Penetrability Variations in Forest Soils M. Jones & P. Arp https://doi.org/10.4236/ojf.2019.92005
516. Multivariate Assessment of Groundwater Depletion and Recharge Prospect in a Sub-tropical Basin of Eastern India S. Ghosh & S. Kundu https://doi.org/10.17491/jgsi/2024/172984
517. Spatio‐temporal interpolation of daily temperatures for global land areas at 1 km resolution M. Kilibarda et al. https://doi.org/10.1002/2013JD020803
518. Mapping soil moisture as an indicator of transport corridor slope instability using remotely sensed data A. Hardy https://doi.org/10.1080/jom.2010.9711033
519. Assessing the impacts of topographic and climatic factors on radial growth of major forest forming tree species of South Korea M. Kim et al. https://doi.org/10.1016/j.foreco.2017.08.048
520. Multi-View Analysis of High-Resolution Geomorphic Features in Complex Mountains Based on UAV–LiDAR and SfM–MVS: A Case Study of the Northern Pit Rim Structure of the Mountains of Lufeng, China R. Bi et al. https://doi.org/10.3390/app13020738
521. Effects of China’s payment for ecosystem services programs on cropland abandonment: A case study in Tiantangzhai Township, Anhui, China Q. Zhang et al. https://doi.org/10.1016/j.landusepol.2018.01.001
522. Evaluating spatial patterns of drought-induced tree mortality in a coastal California pine forest S. Baguskas et al. https://doi.org/10.1016/j.foreco.2013.12.020
523. A Depression-Based Index to Represent Topographic Control in Urban Pluvial Flooding H. Huang et al. https://doi.org/10.3390/w11102115
524. From single fields to river basins: Identification of critical source areas for erosion and phosphorus losses at high resolution F. Djodjic & H. Markensten https://doi.org/10.1007/s13280-018-1134-8
525. Up-Scaling Fuel Hazard Metrics Derived from Terrestrial Laser Scanning Using a Machine Learning Model R. Taneja et al. https://doi.org/10.3390/rs15051273
526. Machine learning-based landslide risk assessment in Doti district, western Nepal C. Bhandari et al. https://doi.org/10.1007/s10064-026-05040-9
527. Hydrological and hydraulic models for determination of flood-prone and flood inundation areas H. Aksoy et al. https://doi.org/10.5194/piahs-373-137-2016
528. Topography Wetness Index Application in Flood-Risk-Based Land Use Planning S. Pourali et al. https://doi.org/10.1007/s12061-014-9130-2
529. Characterizing the kinematics of active rock glaciers in Daxue Shan, southeastern Tibetan plateau, using SAR interferometry and generalized boosted modeling J. Cai et al. https://doi.org/10.1016/j.rse.2024.114352
530. Mapping Groundwater Potential Through an Ensemble of Big Data Methods P. Martínez‐Santos & P. Renard https://doi.org/10.1111/gwat.12939
531. Assessment and monitoring of land degradation in the northwest coast region, Egypt using Earth observations data F. Abdel-Kader https://doi.org/10.1016/j.ejrs.2018.02.001
532. Spatial prioritization of groundwater resources in mountain region of Nepal: a GIS and AHP integrated framework A. Poudel et al. https://doi.org/10.2166/ws.2024.181
533. Evaluation of different machine learning models for predicting and mapping the susceptibility of gully erosion O. Rahmati et al. https://doi.org/10.1016/j.geomorph.2017.09.006
534. Spatial analysis approaches for the evaluation and protection of groundwater resources in large watersheds of the Canadian Shield S. Nadeau et al. https://doi.org/10.1007/s10040-021-02367-3
535. The Least Square Adjustment for Estimating the Tropical Peat Depth Using LiDAR Data B. Cahyono et al. https://doi.org/10.3390/rs12050875
536. Topographic wetness index explains soil moisture better than bioindication with Ellenberg’s indicator values M. Raduła et al. https://doi.org/10.1016/j.ecolind.2017.10.011
537. Predicting Streamflow Duration From Crowd‐Sourced Flow Observations D. Peterson et al. https://doi.org/10.1029/2023WR035093
538. Multifactorial spatial analysis of mycotoxin contamination of winter wheat at the field and landscape scale M. Müller et al. https://doi.org/10.1016/j.agee.2010.08.010
539. Assessing Climate Change Impact on Cropland Suitability in Kyrgyzstan: Where Are Potential High-Quality Cropland and the Way to the Future S. Park et al. https://doi.org/10.3390/agronomy11081490
540. Mapping and modelling land degradation vulnerability in a semi-arid region: a case study from Battalgazi District, Turkiye M. Kılıç https://doi.org/10.7717/peerj.20606
541. Evaluating the area and position accuracy of surface water paths obtained by flow direction algorithms Z. Li et al. https://doi.org/10.1016/j.jhydrol.2020.124619
542. Tropical tree species assemblages in topographical habitats change in time and with life stage R. Kanagaraj et al. https://doi.org/10.1111/j.1365-2745.2011.01878.x
543. Multi-scale analysis identifies habitat suitability and conservation priorities for snow leopards (Panthera uncia) in the Qilian Mountains Y. Wang et al. https://doi.org/10.1007/s10980-026-02328-9
544. Delineating dambo catenary soil-landscape units using aerial gamma-ray and terrain data: a comparison of classification approaches J. Lugumira et al. https://doi.org/10.1080/01431161.2014.979302
545. Groundwater potential zones mapping by applying GIS, remote sensing and multi-criteria decision analysis in the Ghiss basin, northern Morocco A. Bourjila et al. https://doi.org/10.1016/j.gsd.2021.100693
546. Restoration Plan for Degraded Forest in The Democratic People’s Republic of Korea Considering Suitable Tree Species and Spatial Distribution S. Lee et al. https://doi.org/10.3390/su10030856
547. Using satellite-derived land surface temperatures to clarify the spatiotemporal warming trends of the Alborz Mountains in northern Iran G. Roshan et al. https://doi.org/10.1007/s11629-023-8384-z
548. Effects of topography on structuring local species assemblages in a Sri Lankan mixed dipterocarp forest R. Punchi‐Manage et al. https://doi.org/10.1111/1365-2745.12017
549. Modelling soil moisture in a high‐latitude landscape using LiDAR and soil data J. Kemppinen et al. https://doi.org/10.1002/esp.4301
550. Probability of Streamflow Permanence Model (PROSPER): A spatially continuous model of annual streamflow permanence throughout the Pacific Northwest K. Jaeger et al. https://doi.org/10.1016/j.hydroa.2018.100005
551. Augmenting agroecosystem models with remote sensing data and machine learning increases overall estimates of nitrate-nitrogen leaching M. Nowatzke et al. https://doi.org/10.1088/1748-9326/ac998b
552. Morphometric Parameters and Geospatial Analysis for Flash Flood Susceptibility Assessment: A Case Study of Jeddah City along the Red Sea Coast, Saudi Arabia B. Bashir https://doi.org/10.3390/w15050870
553. Multi-scale path-level analysis of jaguar habitat use in the Pantanal ecosystem G. Alvarenga et al. https://doi.org/10.1016/j.biocon.2020.108900
554. Analysis of factors associated with fruiting and vigor of <i>Melastoma tetramerum</i> using three-dimensional data. S. KATSUTA et al. https://doi.org/10.7211/jjsrt.52.25
555. Landslide susceptibility mapping using maximum entropy and support vector machine models along the highway corridor, Garhwal Himalaya V. Pandey et al. https://doi.org/10.1080/10106049.2018.1510038
556. Thermokarst Lake Susceptibility Assessment Induced by Permafrost Degradation in the Qinghai–Tibet Plateau Using Machine Learning Methods R. Wang et al. https://doi.org/10.3390/rs15133331
557. Geomorphometric Appraisal for Seismic Hazard Assessment in the Chenab River Basin of the NW Himalayas, India A. Padder et al. https://doi.org/10.1134/S0016852122040069
558. Landscape and Wetland Influences on Headwater Stream Chemistry in the Kenai Lowlands, Alaska C. Walker et al. https://doi.org/10.1007/s13157-011-0260-x
559. Advances in soil moisture retrieval from multispectral remote sensing using unoccupied aircraft systems and machine learning techniques S. Araya et al. https://doi.org/10.5194/hess-25-2739-2021
560. Quantitative studies of the morphology of the south Poland using Relief Index (RI) B. Szypuła https://doi.org/10.1515/geo-2017-0039
561. Vegetative Community Response to Landscape-Scale Post-fire Herbicide (Imazapic) Application C. Applestein et al. https://doi.org/10.1017/inp.2018.18
562. Planning Framework for Mesolevel Optimization of Urban Runoff Control Schemes Q. Zhou et al. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000748
563. Yozgat ili topoğrafik ıslaklık indeksinin (TWI) Coğrafi Bilgi Sistemleri ile belirlenmesi Ö. Karaca https://doi.org/10.70700/bjea.1576651
564. Multiscale Landscape Pattern Affecting on Stream Water Quality in Agricultural Watershed, SW Finland C. Gonzales-Inca et al. https://doi.org/10.1007/s11269-014-0903-9
565. Flood and drought susceptibility zonation in the mountain environment: a case study of Upper Siang district, Eastern Himalayas, India D. Sharma et al. https://doi.org/10.1007/s12665-023-11084-x
566. Spatial assessment of groundwater potential using geospatial techniques and analytical hierarchy process (AHP) in a drought-affected river basin of eastern India K. Shiwani et al. https://doi.org/10.1016/j.eve.2026.100140
567. Digital assessments of soil organic carbon storage using digital maps provided by static and dynamic environmental covariates F. Rahbar Alam Shirazi et al. https://doi.org/10.1111/sum.12900
568. Development characteristics and hazard mode of loess sinkhole-landslide-mudflow hazard chain: A typical case study of loess tableland K. Liu et al. https://doi.org/10.1016/j.enggeo.2026.108974
569. Soil erosion risk for farming futures: Novel model application and validation to an agricultural landscape in southern England C. Hudson & P. Soar https://doi.org/10.1016/j.envres.2022.115050
570. Delineation of groundwater potential zones using analytical hierarchy process (AHP) and GIS in Weserbi sub-catchment, Oromia, Ethiopia A. Yacob et al. https://doi.org/10.2166/wpt.2025.050
571. Identifying watershed predictors of surface water quality through iterative input selection L. Mejía & M. Barrios https://doi.org/10.1007/s13762-022-04406-2
572. Photogrammetry for environmental monitoring: The use of drones and hydrological models for detection of soil contaminated by copper A. Capolupo et al. https://doi.org/10.1016/j.scitotenv.2015.01.109
573. Modeling the geographic spread and proliferation of invasive alien plants (IAPs) into new ecosystems using multi-source data and multiple predictive models in the Heuningnes catchment, South Africa B. Mtengwana et al. https://doi.org/10.1080/15481603.2021.1903281
574. Integrated flood hazard assessment based on spatial ordered weighted averaging method considering spatial heterogeneity of risk preference Y. Xiao et al. https://doi.org/10.1016/j.scitotenv.2017.04.218
575. Enhanced forest fire susceptibility mapping by integrating feature selection genetic algorithm and bagging-based support vector machine with artificial neural networks A. Mabdeh et al. https://doi.org/10.1007/s00477-024-02851-8
576. Understanding the effect of spatial patterns on the vulnerability of urban areas to flooding Y. Sakieh https://doi.org/10.1016/j.ijdrr.2017.09.004
577. Integrated hydrologic and hydrodynamic modeling to assess water exchange in a data-scarce reservoir B. Wu et al. https://doi.org/10.1016/j.jhydrol.2017.09.057
578. Site conditions for regeneration of climax species, the key for restoring moist deciduous tropical forest in Southern Vietnam H. Do et al. https://doi.org/10.1371/journal.pone.0233524
579. Evaluation of a surface hydrological connectivity index in agricultural catchments M. Shore et al. https://doi.org/10.1016/j.envsoft.2013.04.003
580. Drivers of drought-induced canopy mortality in conifer and broadleaf forests across Luxembourg S. Schwarz et al. https://doi.org/10.5194/bg-23-2985-2026
581. Digital soil mapping for soil types using machine learning approaches at the landscape scale in the arid regions of Iran S. Manteghi et al. https://doi.org/10.1016/j.asr.2024.04.042
582. Invasive Shrub Mapping in an Urban Environment from Hyperspectral and LiDAR-Derived Attributes C. Chance et al. https://doi.org/10.3389/fpls.2016.01528
583. A First Approach to Determine If It Is Possible to Delineate In-Season N Fertilization Maps for Wheat Using NDVI Derived from Sentinel-2 A. Uribeetxebarria et al. https://doi.org/10.3390/rs14122872
584. Land use effects on organic carbon storage in soils of Bavaria: The importance of soil types M. Wiesmeier et al. https://doi.org/10.1016/j.still.2014.10.003
585. WITHDRAWN: Coupling of analytical hierarchy process and frequency ratio based spatial prediction of soil erosion susceptibility in Keleghai river basin, India N. Sar et al. https://doi.org/10.1016/j.iswcr.2016.09.004
586. Morphology, timing, and drivers of post‐glacial landslides in the northern Yellowstone region J. Dixon et al. https://doi.org/10.1002/esp.5943
587. Testing the performances of different fuzzy overlay methods in GIS-based landslide susceptibility mapping of Udi Province, SE Nigeria V. Nwazelibe et al. https://doi.org/10.1016/j.catena.2022.106654
588. Village-Scale Winter Wheat Yield Prediction in Coastal Saline–Alkali Farmland Using a Three-Stage Fusion XGBoost Framework and SHAP W. Jia et al. https://doi.org/10.3390/rs18132233
589. Establishing a shallow-landslide prediction method by using machine-learning techniques based on the physics-based calculation of soil slope stability P. Huang https://doi.org/10.1007/s10346-023-02139-y
590. Flood susceptibility modeling based on new hybrid intelligence model: Optimization of XGboost model using GA metaheuristic algorithm N. Thi Thuy Linh et al. https://doi.org/10.1016/j.asr.2022.02.027
591. Flood susceptibility mapping through geoinformatics and ensemble learning methods, with an emphasis on the AdaBoost-Decision Tree algorithm, in Mazandaran, Iran M. Jahanbani et al. https://doi.org/10.1007/s12145-023-01213-2
592. Deciphering groundwater potential zones of Sarenga block, West Bengal, India using Geographic Information System and Multi-Criteria Decision-Analysis methods S. Dule & A. Sharma https://doi.org/10.26833/ijeg.1654595
593. Statistical characterization of environmental hot spots and hot moments and applications in groundwater hydrology J. Chen et al. https://doi.org/10.5194/hess-25-4127-2021
594. Terrain characterization of small island using publicly available data and open- source software: a case study of Marinduque, Philippines A. Salvacion https://doi.org/10.1007/s40808-016-0085-y
595. The spatial variability of temporal changes in soil pH affected by topography and fertilization X. Zhang et al. https://doi.org/10.1016/j.catena.2022.106586
596. The relative importance of antecedent soil moisture and precipitation in flood generation in the middle and lower Yangtze River basin Q. Ran et al. https://doi.org/10.5194/hess-26-4919-2022
597. Topographic species–habitat associations of tree species in a heterogeneous tropical karst seasonal rain forest, China Y. Guo et al. https://doi.org/10.1093/jpe/rtw057
598. Flood susceptibility mapping of Cheongju, South Korea based on the integration of environmental factors using various machine learning approaches L. Widya et al. https://doi.org/10.1016/j.jenvman.2024.121291
599. Hydraulic shortcuts increase the connectivity of arable land areas to surface waters U. Schönenberger & C. Stamm https://doi.org/10.5194/hess-25-1727-2021
600. Flood vulnerability assessment at the local scale using remote sensing and GIS techniques: a case study in Da Nang City, Vietnam T. Thi An et al. https://doi.org/10.2166/wcc.2022.029
601. Understanding fire patterns and fire drivers for setting a sustainable management policy of the New-Caledonian biodiversity hotspot T. Curt et al. https://doi.org/10.1016/j.foreco.2014.10.032
602. Toward the development of deep learning analyses for snow avalanche releases in mountain regions Y. Chen et al. https://doi.org/10.1080/10106049.2021.1986578
603. Soils and broad-scale topography predict historical stand structure across Front Range dry conifer forests K. Willson et al. https://doi.org/10.1016/j.foreco.2026.124144
604. Characterising soil moisture in transport corridor environments using airborne LIDAR and CASI data A. Hardy et al. https://doi.org/10.1002/hyp.8217
605. Landslide Susceptibility Analysis: A Logistic Regression Model Case Study in Coonoor, India E. Sujatha & V. Sridhar https://doi.org/10.3390/hydrology8010041
606. Comparing the prediction performance of logistic model tree with different ensemble techniques in susceptibility assessments of different landslide types J. Huang et al. https://doi.org/10.1080/10106049.2022.2087751
607. Integration Sentinel-1 SAR data and machine learning for land subsidence in-depth analysis in the North Coast of Central Java, Indonesia A. Yananto et al. https://doi.org/10.1007/s12145-024-01413-4
608. Spatial Scaling of Gross Primary Productivity Over Sixteen Mountainous Watersheds Using Vegetation Heterogeneity and Surface Topography X. Xie et al. https://doi.org/10.1029/2020JG005848
609. Morphology, Sedimentology and OSL Chronology of the Lower Prosna River System Evolution – A Case Study in Rokutów, West-Central Poland A. Wojtalak et al. https://doi.org/10.2478/geochr-2023-0017
610. Predictive machine learning for gully susceptibility modeling with geo-environmental covariates: main drivers, model performance, and computational efficiency K. Phinzi & S. Szabó https://doi.org/10.1007/s11069-024-06481-9
611. Correlation and causation in tree‐ring‐based reconstruction of paleohydrology in cold semiarid regions A. Elshorbagy et al. https://doi.org/10.1002/2016WR018985
612. The measurement, prediction, and development of soil management zones in low-relief sodic soils Y. He et al. https://doi.org/10.1007/s11119-018-9561-x
613. Late Holocene niche construction and carrying capacity in Tairona chiefdoms of the Río Frío Basin, Sierra Nevada de Santa Marta, Colombia L. Soto Rodríguez https://doi.org/10.1016/j.ancene.2026.100559
614. Kinematic Reconstruction of a Deep-Seated Gravitational Slope Deformation by Geomorphic Analyses S. Morelli et al. https://doi.org/10.3390/geosciences8010026
615. Development of a Precipitation-Induced Moisture-Driven Landslide Threshold Atlas for the Northwestern and Northeastern Himalayas D. Monga & P. Ganguli https://doi.org/10.1061/JHYEFF.HEENG-6745
616. Land-use changes and geo-hydrological phenomena in the Abruzzo Periadriatic Area (central Italy): The case of the Pescara River basin G. Paglia et al. https://doi.org/10.1080/27658511.2024.2391135
617. Regional-Scale Mapping of Gully Network in Mediterranean Olive Landscapes Using Machine Learning Algorithms: The Guadalquivir Basin P. González-Garrido et al. https://doi.org/10.3390/agronomy16060622
618. Interpolation of Instantaneous Air Temperature Using Geographical and MODIS Derived Variables with Machine Learning Techniques M. Ruiz-Álvarez et al. https://doi.org/10.3390/ijgi8090382
619. Prioritization of Landslide Effective Factors using Logistic Regression (Case Study: A part of KopeDagh-HezarMasjedZone) S. Abdi Bastami et al. https://doi.org/10.29252/jwmr.10.19.154
620. Development of a novel Slope-Integrated Drought Index (SIDI) for comprehensive drought assessment M. Anuruddhika et al. https://doi.org/10.1007/s00704-025-05563-3
621. No deceleration signs in the permafrost ground subsidence four years after the 2019 fire in Northwest Territories, Canada Z. Cao & M. Furuya https://doi.org/10.1088/1748-9326/ad7871
622. Landscape patterns of shrubification in the Siberian Low Arctic: A machine learning perspective A. Derkacheva et al. https://doi.org/10.1111/1365-2745.70129
623. Ecological drivers of spatial community dissimilarity, species replacement and species nestedness across temperate forests X. Wang et al. https://doi.org/10.1111/geb.12719
624. Interaction between sediment transport rate and tectonic activity: the case of Kızılırmak Basin on the tectonically active NAFZ, Turkey G. Sarp https://doi.org/10.1007/s12517-020-5240-0
625. Maximum entropy modeling to identify physical drivers of shallow snowpack heterogeneity using unpiloted aerial system (UAS) lidar E. Cho et al. https://doi.org/10.1016/j.jhydrol.2021.126722
626. Soil Moisture Analysis by Means of Multispectral Images According to Land Use and Spatial Resolution on Andosols in the Colombian Andes M. Casamitjana et al. https://doi.org/10.3390/app10165540
627. The supply of multiple ecosystem services requires biodiversity across spatial scales G. Le Provost et al. https://doi.org/10.1038/s41559-022-01918-5
628. The potential for modelling peatland habitat condition in Scotland using long-term MODIS data R. Artz et al. https://doi.org/10.1016/j.scitotenv.2018.12.327
629. Enhancing digital mapping of soil organic carbon through spatial modeling and validation A. Jafari et al. https://doi.org/10.1038/s41598-026-39496-2
630. New metrics for characterizing and comparing soil moisture dynamics across depths and locations M. Meles et al. https://doi.org/10.3389/frwa.2026.1840091
631. Modeling the distribution of headwater streams using topoclimatic indices, remote sensing and machine learning. J. Erickson et al. https://doi.org/10.1016/j.hydroa.2023.100165
632. Variation in habitat selection by white‐bearded wildebeest across different degrees of human disturbance J. Stabach et al. https://doi.org/10.1002/ecs2.1428
633. Geospatial technology-based MCDA and machine learning algorithms: an ensemble and inter-evaluating frameworks for conceptualizing groundwater potential K. Ozegin et al. https://doi.org/10.1016/j.ecofro.2026.02.003
634. Spatiotemporal Mapping of Urban Flood Susceptibility: A Multi-Criteria GIS-Based Assessment in Nangarhar, Afghanistan I. Ahmad et al. https://doi.org/10.3390/land14122376
635. Multi-source global wetland maps combining surface water imagery and groundwater constraints A. Tootchi et al. https://doi.org/10.5194/essd-11-189-2019
636. Assessing above-ground biomass in reforested urban landscapes using machine learning and remotely sensed data C. Matiza et al. https://doi.org/10.1080/14498596.2024.2343764
637. Mapping Forest Canopy Fuels in the Western United States with LiDAR–Landsat Covariance C. Moran et al. https://doi.org/10.3390/rs12061000
638. The status and future of essential geodiversity variables F. Schrodt et al. https://doi.org/10.1098/rsta.2023.0052
639. Groundwater Potential Mapping Using SWAT and GIS-Based Multi-Criteria Decision Analysis B. Yifru et al. https://doi.org/10.1007/s12205-020-0168-1
640. Flood Hazard Evaluation Using a Flood Potential Index N. Popescu & A. Bărbulescu https://doi.org/10.3390/w15203533
641. GIS-based modeling of rainfall-induced landslides using data mining-based functional trees classifier with AdaBoost, Bagging, and MultiBoost ensemble frameworks D. Tien Bui et al. https://doi.org/10.1007/s12665-016-5919-4
642. Challenges of Reducing Phosphorus Based Water Eutrophication in the Agricultural Landscapes of Northwest Europe R. Bol et al. https://doi.org/10.3389/fmars.2018.00276
643. Effect of Urban Green Spaces and Flooded Area Type on Flooding Probability H. Kim et al. https://doi.org/10.3390/su8020134
644. Large-scale slope remodelling by landslides – Geomorphic diversity and geological controls, Kamienne Mts., Central Europe P. Migoń et al. https://doi.org/10.1016/j.geomorph.2016.09.037
645. A comparative analysis of statistical landslide susceptibility mapping in the southeast region of Minas Gerais state, Brazil C. Barella et al. https://doi.org/10.1007/s10064-018-1341-3
646. Landslide susceptibility mapping using morphological and hydrological parameters in Sikkim Himalaya: frequency ratio model and geospatial technologies I. Sonker et al. https://doi.org/10.1007/s11069-024-06491-7
647. Factors affecting variations of soil pH in different horizons in hilly regions Y. Zhang et al. https://doi.org/10.1371/journal.pone.0218563
648. The influence of loess cave development upon landslides and geomorphologic evolution: A case study from the northwest Loess Plateau, China S. Hu et al. https://doi.org/10.1016/j.geomorph.2020.107167
649. Runoff Potential Index (RPI): 3D modelling of surface-driven hydrological dynamics for drought resilience E. Correa https://doi.org/10.1038/s41598-025-34699-5
650. Topography not tenure controls extent of wildfire within Mountain Ash forests M. Adams et al. https://doi.org/10.1088/1748-9326/abe57e
651. Characteristics and susceptibility assessment of landslides triggered by historical mega earthquakes in the northeastern margin of the qinghai-tibet plateau: a case study of the 1927 gulang M8 earthquake S. Liu et al. https://doi.org/10.1080/19475705.2026.2700846
652. Mobile species’ responses to surrounding land use generate trade-offs and synergies among nature’s contributions to people S. O’Brien et al. https://doi.org/10.1073/pnas.2505401122
653. Open digital mapping as a cost-effective method for mapping peat thickness and assessing the carbon stock of tropical peatlands . Rudiyanto et al. https://doi.org/10.1016/j.geoderma.2017.10.018
654. The Influence of Climate and Relief on the Distribution of Forest Communities in Different Botanical and Geographical Districts of the Southern Urals N. Fedorov et al. https://doi.org/10.1134/S1067413622060042
655. Exploring the Critical Zone Heterogeneity and the Hydrological Diversity Using an Integrated Ecohydrological Model in Three Contrasted Long‐Term Observatories J. Ackerer et al. https://doi.org/10.1029/2023WR035672
656. Relationships between Arctic shrub dynamics and topographically derived hydrologic characteristics A. Naito & D. Cairns https://doi.org/10.1088/1748-9326/6/4/045506
657. Using the farmers’ knowledge on soils improves local digital soil mapping products: A case study in South India P. Lagacherie et al. https://doi.org/10.1016/j.geoderma.2025.117609
658. Exploration of Potential Groundwater Zones in Nambiyar Watershed, South India using Frequency Ratio and Multi-Influencing Models R. Libina et al. https://doi.org/10.14796/JWMM.C568
659. Flood Susceptibility Mapping Using GIS-Based Frequency Ratio and Shannon’s Entropy Index Bivariate Statistical Models: A Case Study of Chandrapur District, India A. Sharma et al. https://doi.org/10.3390/ijgi13080297
660. An ensemble model of knowledge- and data-driven geospatial methods for mapping groundwater potential in a data-scarce, semi-arid fractured rock region S. Fildes et al. https://doi.org/10.1007/s13201-025-02407-3
661. Reducing scale dependence in TOPMODEL using a dimensionless topographic index A. Ducharne https://doi.org/10.5194/hess-13-2399-2009
662. Spatial Asymmetry in Topographic Controls on Flood Intensity: A Machine Learning Investigation of the Chi River Floodplain, Thailand N. Buasri et al. https://doi.org/10.3390/sym18071231
663. Agronomy explains large yield gaps in smallholder oil palm fields J. Monzon et al. https://doi.org/10.1016/j.agsy.2023.103689
664. Integration of fuzzy logic and geographic weighted regression modeling for enhanced groundwater potential mapping using remote sensing and GIS J. Gao et al. https://doi.org/10.1186/s12302-025-01182-x
665. Terrestrial CDOM in Lakes of Yamal Peninsula: Connection to Lake and Lake Catchment Properties Y. Dvornikov et al. https://doi.org/10.3390/rs10020167
666. Time‐scale dependency of host plant biomass‐ and trait‐mediated indirect effects of deer herbivory on a swallowtail butterfly S. Takagi et al. https://doi.org/10.1111/1365-2656.12415
667. Wetness index based on landscape position and topography (WILT): Modifying TWI to reflect landscape position M. Meles et al. https://doi.org/10.1016/j.jenvman.2019.109863
668. Disentangling the potential effects of land‐use and climate change on stream conditions K. Maloney et al. https://doi.org/10.1111/gcb.14961
669. Spatio-temporal prediction of soil moisture using soil maps, topographic indices and SMAP retrievals M. Schönauer et al. https://doi.org/10.1016/j.jag.2022.102730
670. Application of bivariate frequency ratio and information value models for landslide susceptibility in Thuligad watershed of far-western Nepal T. Saud et al. https://doi.org/10.1007/s44288-025-00308-1
671. Urban growth or urban risk? Unraveling the flood paradox in Kumasi (Ghana) through the lens of natural factors and spatial decision modeling S. Liwur et al. https://doi.org/10.1016/j.jafrearsci.2025.105814
672. Insights from Optimized Non-Landslide Sampling and SHAP Explainability for Landslide Susceptibility Prediction M. Li & H. Tian https://doi.org/10.3390/app15031163
673. In-Season Interactions between Vine Vigor, Water Status and Wine Quality in Terrain-Based Management-Zones in a ‘Cabernet Sauvignon’ Vineyard I. Bahat et al. https://doi.org/10.3390/rs13091636
674. Estimation of the groundwater balance of a mountainous basin based on long-term streamflow data: a case study of the Tao’er River Basin, China W. Yang et al. https://doi.org/10.1007/s12665-021-09974-z
675. Morphometric Indicators of High Tatra Mts. Lakes and Their Catchments to Analyse Debris Flow Dynamics (Slovakia) S. Čajková et al. https://doi.org/10.2478/eko-2024-0014
676. Reconstruction of a Flash Flood in a Semi‐Arid Ungauged Catchment Using Integrated Surface–Subsurface Modelling and Non‐Stationary Extreme Value Analysis K. Norouzi‐Moghanjoghi et al. https://doi.org/10.1002/hyp.70700
677. Comparison of Selected Terramechanical Test Procedures and Cartographic Indices to Predict Rutting Caused by Machine Traffic during a Cut-to-Length Thinning Operation M. Schönauer et al. https://doi.org/10.3390/f12020113
678. Topographic indices and ERA5-Land data to describe soil moisture variability in a Central European beech forest M. Schönauer et al. https://doi.org/10.1016/j.ejrh.2025.102456
679. Clustering Urban Tree Climate Responses: A Multi-Metric Ensemble SDM Approach Across SSP Scenarios J. Yun et al. https://doi.org/10.3390/land15040616
680. Nitrogen fixing shrubs advance the pace of tall-shrub expansion in low-Arctic tundra A. Schore et al. https://doi.org/10.1038/s43247-023-01098-5
681. Legacy data for 3D modelling of peat properties with uncertainty estimation in Dava bog - Scotland L. Poggio et al. https://doi.org/10.1016/j.geodrs.2020.e00288
682. Assessment of Convolution Neural Networks for Wetland Mapping with Landsat in the Central Canadian Boreal Forest Region D. Pouliot et al. https://doi.org/10.3390/rs11070772
683. Erzincan Havzası’nın Frekans Oranı Yöntemine Göre Heyelan Duyarlılık Analizi A. Uysal et al. https://doi.org/10.35341/afet.1823965
684. A Deterministic Topographic Wetland Index Based on LiDAR-Derived DEM for Delineating Open-Water Wetlands L. Bian et al. https://doi.org/10.3390/w13182487
685. Landslide Risk Mapping Using the Weight-of-Evidence Method in the Datong Mining Area, Qinghai Province H. Yang et al. https://doi.org/10.3390/su151411330
686. Environmental diversity as a surrogate for species representation P. Beier & F. de Albuquerque https://doi.org/10.1111/cobi.12495
687. Prioritizing commercial thinning: quantification of growth and competition with high-density drone laser scanning L. Irwin et al. https://doi.org/10.1093/forestry/cpae030
688. Spatiotemporal Analysis of the Distribution of Waterborne Diseases in Children Under 5 Years of Age From 2018 to 2022 in the Lemba Health Zone in Kinshasa, DR Congo: A Retrospective and Observational Analysis J. Mazama Sukami et al. https://doi.org/10.1002/hsr2.70605
689. Groundwater potential zone assessment using integrated analytical hierarchy process-geospatial driven in a GIS environment in Gobele watershed, Wabe Shebele river basin, Ethiopia J. Guduru & N. Jilo https://doi.org/10.1016/j.ejrh.2022.101218
690. Topographic attributes and ecological indicator values in assessing the ground-floor vegetation patterns B. Czarnecka et al. https://doi.org/10.1515/biorc-2017-0010
691. A global-scale dataset of direct natural groundwater recharge rates: A review of variables, processes and relationships C. Moeck et al. https://doi.org/10.1016/j.scitotenv.2020.137042
692. Direct climate effects are more influential than functional composition in determining future gross primary productivity J. McCarthy et al. https://doi.org/10.1007/s10980-020-00994-x
693. Integrating GIS and remote sensing for spatial distribution assessment of Drought Vulnerability Index H. Hameed et al. https://doi.org/10.1007/s10661-025-14323-9
694. Vegetation recovery drivers at short-term after fire are plant community-dependent in mediterranean burned landscapes J. Fernández-Guisuraga et al. https://doi.org/10.1016/j.foreco.2023.121034
695. Improving the Predictive Analytics of Machine-Learning Pipelines for Bridge Infrastructure Asset Management Applications: An Upstream Data Workflow to Address Data Quality Issues in the National Bridge Inventory Database X. Hu & R. Assaad https://doi.org/10.1061/JBENF2.BEENG-6012
696. A Remote Sensing-Based Approach for Debris-Flow Susceptibility Assessment Using Artificial Neural Networks and Logistic Regression Modeling R. Elkadiri et al. https://doi.org/10.1109/JSTARS.2014.2337273
697. Drivers of tall shrub proliferation adjacent to the Dempster Highway, Northwest Territories, Canada E. Cameron & T. Lantz https://doi.org/10.1088/1748-9326/11/4/045006
698. Influence path identification of topography, soil, hydrology and landscape on phosphorus buffering capacity in typical agricultural catchments in central subtropical China C. Meng et al. https://doi.org/10.1016/j.jenvman.2022.115164
699. Integrating the landscape scale supports SAR-based detection and assessment of the phenological development at the field level J. Löw et al. https://doi.org/10.3389/frsen.2025.1610005
700. Impacts of Landuse/Landcover change on groundwater recharge potential of the Lusaka Aquifer system using Fuzzy-AHP M. Lweendo et al. https://doi.org/10.1016/j.pce.2025.104073
701. Enhancing the WorldClim data set for national and regional applications L. Poggio et al. https://doi.org/10.1016/j.scitotenv.2017.12.258
702. Non-perennial stream networks as directed acyclic graphs: The R-package streamDAG K. Aho et al. https://doi.org/10.1016/j.envsoft.2023.105775
703. Multi-property digital soil mapping at 30-m spatial resolution down to 1 m using extreme gradient boosting tree model and environmental covariates F. Rahbar Alam Shirazi et al. https://doi.org/10.1016/j.rsase.2023.101123
704. Vegetation change as related to terrain factors at two glacier forefronts, Glacier National Park, Montana, U.S.A. C. Lambert et al. https://doi.org/10.1007/s11629-019-5603-8
705. Deep Learning-Based Flood Area Extraction for Fully Automated and Persistent Flood Monitoring Using Cloud Computing J. Kim et al. https://doi.org/10.3390/rs14246373
706. Distribution of agricultural land regulates stream water isotopes over multiple spatial scale in a subtropical forested watershed L. Sun et al. https://doi.org/10.1016/j.jhydrol.2019.124206
707. Flood susceptibility mapping leveraging open-source remote-sensing data and machine learning approaches in Nam Ngum River Basin (NNRB), Lao PDR S. Mangkhaseum et al. https://doi.org/10.1080/19475705.2024.2357650
708. A comparative study of the bivariate, multivariate and machine-learning-based statistical models for landslide susceptibility mapping in a seismic-prone region in China S. Zhou et al. https://doi.org/10.1007/s12517-021-06630-5
709. Seasonal Surface Subsidence and Frost Heave Detected by C-Band DInSAR in a High Arctic Environment, Cape Bounty, Melville Island, Nunavut, Canada G. Robson et al. https://doi.org/10.3390/rs13132505
710. Elevated Genetic Structure in the Coastal Tailed Frog (Ascaphus truei) in Managed Redwood Forests A. Aguilar et al. https://doi.org/10.1093/jhered/ess138
711. Spatial Variation in Soil Available Potassium and Temporal Changes due to Intrinsic and Extrinsic Factors: a 10-Year Study Y. Jing et al. https://doi.org/10.1007/s42729-021-00732-5
712. Determination of Potential Aquifer Recharge Zones Using Geospatial Techniques for Proxy Data of Gilgel Gibe Catchment, Ethiopia T. Mengistu et al. https://doi.org/10.3390/w14091362
713. Species Traits Mediate Environmental Responses but Not Conspecific Density Dependence in Tropical Tree Saplings X. Ma et al. https://doi.org/10.1086/739608
714. Enhancing groundwater potential mapping in arid regions through integrated microwave remote sensing, statistical analysis, and geophysical-based modeling Y. Youssef et al. https://doi.org/10.1038/s41598-026-64619-0
715. Comparison of regression techniques for mapping fog frequency: application to the Aragón region (northeast Spain) S. Vicente‐Serrano et al. https://doi.org/10.1002/joc.1935
716. Insights from Long-Term Ungrazed and Grazed Watersheds in a Salt Desert Colorado Plateau Ecosystem M. Duniway et al. https://doi.org/10.1016/j.rama.2018.02.007
717. Influence of groundwater and topography on stream drying in semi‐arid headwater streams S. Warix et al. https://doi.org/10.1002/hyp.14185
718. Post-Flood Ecosystem Recovery and Policy Zoning in the Chi River Basin, Thailand N. Prasertsri et al. https://doi.org/10.3390/su18199999
719. Uncertainty Modelling of Groundwater-Dependent Vegetation T. Robinson et al. https://doi.org/10.3390/land13122208
720. Integrating satellite radar vegetation indices and environmental descriptors with visible-infrared soil spectroscopy improved organic carbon prediction in soils of semi-arid Brazil E. dos Santos et al. https://doi.org/10.1016/j.geoderma.2025.117288
721. Socioecological Evaluation of the Complexity of Wildlife Management Systems: A Case Study of Mexican Socioecosystems C. Álvarez-Peredo et al. https://doi.org/10.3390/su18199852
722. A national-scale high-resolution runoff risk and channel network mapping workflow for diffuse pollution management T. Service et al. https://doi.org/10.1016/j.jenvman.2024.122110
723. Flood hazard risk assessment model based on random forest Z. Wang et al. https://doi.org/10.1016/j.jhydrol.2015.06.008
724. Modeling the Spatial Distribution of Soil Nitrogen Content at Smallholder Maize Farms Using Machine Learning Regression and Sentinel-2 Data Z. Mashaba-Munghemezulu et al. https://doi.org/10.3390/su132111591
725. Hurricane risk assessment in a multi-hazard context for Dominica in the Caribbean P. Sammonds et al. https://doi.org/10.1038/s41598-023-47527-5
726. Integration of Logistic Regression and Evidential Belief Function for Flood Risk Assessment in the West Bengal Plain, India D. Mandal et al. https://doi.org/10.1007/s42108-024-00311-1
727. Controlling factors in the interferometric coherence derived from Sentinel-1 images: an example from the Río Chubut Lower Valley, Argentina N. Scivetti et al. https://doi.org/10.1080/10106049.2022.2136258
728. Groundwater Mapping Through Integration of Resistivity Survey, Remote Sensing, Geographic Information Systems and AHP Techniques in Bwari Area Council, FCT Abuja, Nigeria A. Farouq et al. https://doi.org/10.38124/ijisrt/25nov1069
729. Topoedaphic constraints on woody plant cover in a semi-arid grassland S. Jones et al. https://doi.org/10.1016/j.ecolind.2023.110226
730. Topographic Wetness Index calculation guidelines based on measured soil moisture and plant species composition M. Kopecký et al. https://doi.org/10.1016/j.scitotenv.2020.143785
731. Competition and Burn Severity Determine Post-Fire Sapling Recovery in a Nationally Protected Boreal Forest of China: An Analysis from Very High-Resolution Satellite Imagery L. Fang et al. https://doi.org/10.3390/rs11060603
732. Flash Flood Susceptibility Modeling Using New Approaches of Hybrid and Ensemble Tree-Based Machine Learning Algorithms S. Band et al. https://doi.org/10.3390/rs12213568
733. A Land Systems Science Framework for Bridging Land System Architecture and Landscape Ecology: A Case Study from the Southern High Plains J. Vadjunec et al. https://doi.org/10.3390/land7010027
734. The effects of geomorphology, soil and climate on the trajectory of aboveground biomass accumulation of beech (Fagus sylvatica L.) at the southern range margin F. Latterini et al. https://doi.org/10.1016/j.catena.2023.107787
735. Identifying Extreme Heat and Moisture Zones for Vulnerable Populations in Athens: A Geospatial Analysis G. Papakonstantinou https://doi.org/10.3390/land14071375
736. Identification of forest fire-prone region in Lamington National Park using GIS-based multicriteria technique: validation using field and Sentinel-2-based observations H. Singh & S. Srivastava https://doi.org/10.1080/10106049.2025.2462484
737. Factors Influencing Point Measurement of Near‐surface Saturated Soil Hydraulic Conductivity in a Small Sicilian Basin G. Baiamonte et al. https://doi.org/10.1002/ldr.2674
738. Landslide susceptibility mapping of Rangamati District of Bangladesh using statistical and machine intelligence model B. Hafsa et al. https://doi.org/10.1007/s12517-022-10607-3
739. A multi-sensor, multi-scale approach to mapping tree mortality in woodland ecosystems M. Campbell et al. https://doi.org/10.1016/j.rse.2020.111853
740. Comparative assessment of ensemble machine learning models for landslide susceptibility mapping in Kohima–Mokokchung, Nagaland, India D. Maisnam et al. https://doi.org/10.1007/s11069-026-08261-z
741. Coseismic landslides triggered by the 2018 Hokkaido, Japan (Mw 6.6), earthquake: spatial distribution, controlling factors, and possible failure mechanism F. Wang et al. https://doi.org/10.1007/s10346-019-01187-7
742. Interpretation and use of geomorphometry in remote sensing: a guide and review of integrated applications S. Franklin https://doi.org/10.1080/01431161.2020.1792577
743. A GIS Automated Tool for Morphometric Flood Analysis Based on the Horton–Strahler River Classification System A. Enea et al. https://doi.org/10.3390/w16040536
744. Integrating conventional classifiers with a GIS expert system to increase the accuracy of invasive species mapping M. Masocha & A. Skidmore https://doi.org/10.1016/j.jag.2010.10.004
745. GIS-based multi-criteria decision analysis for mapping flood-prone areas in Dehradun city, India N. Bansal et al. https://doi.org/10.1007/s12517-023-11605-9
746. The impact of integrating WorldView-2 sensor and environmental variables in estimating plantation forest species aboveground biomass and carbon stocks in uMgeni Catchment, South Africa T. Dube & O. Mutanga https://doi.org/10.1016/j.isprsjprs.2016.06.017
747. Cartographie numérique de la capacité maximale de sorption du phosphore des sols à l’échelle de la parcelle agricole à l'aide de variables auxiliaires M. Quenum et al. https://doi.org/10.4141/cjss2011-087
748. Trade‐offs in seedling growth and survival within and across tropical forest microhabitats F. Inman‐Narahari et al. https://doi.org/10.1002/ece3.1196
749. PyLandslide: A Python tool for landslide susceptibility mapping and uncertainty analysis M. Basheer & T. Oommen https://doi.org/10.1016/j.envsoft.2024.106055
750. Using machine learning to generate high-resolution wet area maps for planning forest management: A study in a boreal forest landscape W. Lidberg et al. https://doi.org/10.1007/s13280-019-01196-9
751. Enhancing smallholder agricultural production through sustainable use of shallow groundwater in the Borkena catchment, Awash River Basin, Ethiopia G. Ebrahim et al. https://doi.org/10.2166/nh.2024.050
752. Smart Geospatial Analytics for Maladaptation Hotspot Detection: Integrating Trajectory Classification, Random Forest, and SHAP N. Buasri et al. https://doi.org/10.3390/s26154853
753. Using a soil topographic index to distribute denitrification fluxes across a northeastern headwater catchment T. Anderson et al. https://doi.org/10.1016/j.jhydrol.2014.12.043
754. Niches for Species, a multi-species model to guide woodland management: An example based on Scotland’s native woodlands A. Broome et al. https://doi.org/10.1016/j.ecolind.2019.04.021
755. Review of the use of the analytical hierarchy process for flood risk assessment in Bangladesh P. Debnath et al. https://doi.org/10.1007/s11069-025-07523-6
756. Frekans Oranı ve Shannon Entropisi Yöntemi Kullanarak Ezine Çayı Havzası Taşkın Duyarlılık Analizi (Kastamonu-Bozkurt) M. UTLU https://doi.org/10.46453/jader.1358845
757. Identification of wetland areas in the context of agricultural development using Remote Sensing and GIS J. Anaya et al. https://doi.org/10.15446/dyna.v84n201.58600
758. Current awareness https://doi.org/10.1002/hyp.6366
759. Range-wide assessment of habitat suitability for jaguars using multiscale species distribution modelling G. Alvarenga et al. https://doi.org/10.1038/s41598-025-30512-5
760. Application of logistic regression (LR) and frequency ratio (FR) models for landslide susceptibility mapping in Relli Khola river basin of Darjeeling Himalaya, India G. Das & K. Lepcha https://doi.org/10.1007/s42452-019-1499-8
761. The burning question: does fire affect habitat selection and forage preference of the black rhinoceros Diceros bicornis in East African savannahs? T. Anderson et al. https://doi.org/10.1017/S0030605318000388
762. Effect of agronomic treatments on the accuracy of soil moisture mapping by electromagnetic induction D. Altdorff et al. https://doi.org/10.1016/j.catena.2017.12.036
763. Retrospective Assessment of Urban Flooding Susceptibility on the Qinghai–Tibet Plateau Under Data Scarcity Y. Liu et al. https://doi.org/10.3390/ijgi15070309
764. Grazing management or physiography? Factors controlling vegetation recovery in Mediterranean grasslands C. Carmona et al. https://doi.org/10.1016/j.ecolmodel.2012.12.005
765. Effects of LiDAR DEM Smoothing and Conditioning Techniques on a Topography‐Based Wetland Identification Model G. O'Neil et al. https://doi.org/10.1029/2019WR024784
766. Ecological behavior of Quercus suber and Quercus ilex inferred by topographic wetness index (TWI) A. Petroselli et al. https://doi.org/10.1007/s00468-013-0869-x
767. Quantification of functional soil organic carbon pools for major soil units and land uses in southeast Germany (Bavaria) M. Wiesmeier et al. https://doi.org/10.1016/j.agee.2013.12.028
768. Using topographic attributes to predict the density of vegetation layers in a wet eucalypt forest B. Yadav et al. https://doi.org/10.1080/00049158.2021.2004687
769. Delineating floodplain and upland areas for hydrologic models: a comparison of methods H. Rathjens et al. https://doi.org/10.1002/hyp.10918
770. Block-level spatial integration of population density, social vulnerability, and heavy precipitation reveals intensified urban flooding risk J. Zhu et al. https://doi.org/10.1016/j.scs.2024.105984
771. Effect of Terrain Characteristics on Soil Organic Carbon and Total Nitrogen Stocks in Soils of Herschel Island, Western Canadian Arctic J. Obu et al. https://doi.org/10.1002/ppp.1881
772. Hydro-morphometry of a trans-Himalayan River basin: Spatial variance, inference and significance B. Anya & C. Bhuiyan https://doi.org/10.1016/j.envc.2024.100890
773. Benchmarking impact of nitrogen inputs on grain yield and environmental performance of producer fields in the western US Corn Belt F. Tenorio et al. https://doi.org/10.1016/j.agee.2020.106865
774. Airborne LiDAR-derived elevation data in terrain trafficability mapping M. Niemi et al. https://doi.org/10.1080/02827581.2017.1296181
775. Prioritizing winter habitat quality for greater sage‐grouse in a landscape influenced by energy development K. Smith et al. https://doi.org/10.1890/ES13-00238.1