726 citations as recorded by crossref.

1. 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
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. Modeling intensification decisions in the Kilombero Valley floodplain: A Bayesian belief network approach B. Gebrekidan et al. https://doi.org/10.1111/agec.12740
4. 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
5. 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
6. 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
7. 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
8. Local fresh- and sea-water effects on fog occurrence I. Hůnová et al. https://doi.org/10.1016/j.scitotenv.2021.150799
9. 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
10. 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
11. 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
12. 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
13. 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
14. 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
15. 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
16. Mapping an Indicator Species of Sea-Level Rise along the Forest–Marsh Ecotone B. Norlin et al. https://doi.org/10.3390/land13101551
17. 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
18. 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
19. Using movement ecology to investigate meningeal worm risk in moose, Alces alces M. Ditmer et al. https://doi.org/10.1093/jmammal/gyaa019
20. Hybrid Gravimetry to Map Water Storage Dynamics in a Mountain Catchment Q. Chaffaut et al. https://doi.org/10.3389/frwa.2021.715298
21. 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
22. 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
23. 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
24. Modelling hydrological factors from DEM using GIS M. Chowdhury https://doi.org/10.1016/j.mex.2023.102062
25. 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
26. 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
27. 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
28. 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
29. 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
30. 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
31. 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
32. 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
33. 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
34. 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
35. 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
36. 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
37. Identification of Columbian Sharp-Tailed Grouse Lek Sites in South Central Wyoming K. Smith et al. https://doi.org/10.3398/064.076.0115
38. 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
39. 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
40. 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
41. Climate and topography control variation in the tropical dry forest–rainforest ecotone J. Walter et al. https://doi.org/10.1002/ecy.4442
42. 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
43. 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
44. 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
45. 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
46. 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
47. 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
48. 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
49. 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
50. 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
51. 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
52. 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
53. 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
54. 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
55. Global patterns and environmental correlates of high‐priority conservation areas for vertebrates F. Albuquerque & P. Beier https://doi.org/10.1111/jbi.12498
56. 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
57. 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
58. 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
59. 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
60. 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
61. 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
62. 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
63. 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
64. Habitat diversity predicts orchid diversity in the tropical south‐west Pacific G. Keppel et al. https://doi.org/10.1111/jbi.12805
65. Innovative Risk Assessment Framework for Hydraulic Control of Irrigation Reservoirs´ Breaching F. Espejo et al. https://doi.org/10.1007/s11269-022-03128-x
66. 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
67. 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
68. 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
69. Machine learning for predicting landslide risk of Rohingya refugee camp infrastructure N. Ahmed et al. https://doi.org/10.1080/24751839.2019.1704114
70. 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
71. 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
72. An innovative, fast method for landslide susceptibility mapping using GIS-based LSAT toolbox A. Polat https://doi.org/10.1007/s12665-021-09511-y
73. 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
74. 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
75. 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
76. 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
77. 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
78. 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
79. 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
80. 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
81. 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
82. 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
83. 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
84. 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
85. 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
86. 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
87. 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
88. 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
89. 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
90. 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
91. 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
92. 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
93. 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
94. 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
95. 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
96. 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
97. Spatiotemporal predictions of soil properties and states in variably saturated landscapes T. Franz et al. https://doi.org/10.1002/2017JG003837
98. 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
99. Tracking a blue wave of ephemeral water across arid southern Africa D. Schaffer-Smith et al. https://doi.org/10.1088/1748-9326/ac98d9
100. 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
101. 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
102. 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
103. 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
104. 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
105. 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
106. 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
107. 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
108. Regional dynamic early warning model for rainfall-induced landslide in Fujian, China H. Dou et al. https://doi.org/10.1080/19475705.2024.2435510
109. Walk the Talk: Private Sustainability Standards in the Ugandan Coffee Sector K. Akoyi & M. Maertens https://doi.org/10.1080/00220388.2017.1327663
110. 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
111. Sustainable Geoinformatic Approaches to Insurance for Small-Scale Farmers in Colombia A. Abd Rabuh et al. https://doi.org/10.3390/su16125104
112. 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
113. 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
114. 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
115. Determining local wetness conditions within the mined lands using GIS O. Skrypnyk et al. https://doi.org/10.33271/mining14.04.053
116. 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
117. 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
118. 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
119. 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
120. 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
121. Urban flood susceptibility assessment based on convolutional neural networks G. Zhao et al. https://doi.org/10.1016/j.jhydrol.2020.125235
122. 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
123. Evaluating Machine Learning-Based Approaches in Land Subsidence Susceptibility Mapping E. Hosseinzadeh et al. https://doi.org/10.3390/land13030322
124. 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
125. 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
126. A framework to bridge scales in distribution modeling of soil microbiota J. Lembrechts et al. https://doi.org/10.1093/femsec/fiaa051
127. Multitemporal landslide inventory and susceptibility map for the Arun River Basin, Nepal P. Amatya et al. https://doi.org/10.1002/gdj3.240
128. 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
129. Flood Risk Assessment and Regionalization from Past and Future Perspectives at Basin Scale C. Lai et al. https://doi.org/10.1111/risa.13493
130. Training Machine Learning Algorithms Using Remote Sensing and Topographic Indices for Corn Yield Prediction M. Oliveira et al. https://doi.org/10.3390/rs14236171
131. 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
132. 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
133. What makes segmentation good? A case study in boreal forest habitat mapping A. Räsänen et al. https://doi.org/10.1080/01431161.2013.845318
134. 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
135. 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
136. 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
137. A Remote Sensing Approach for Landslide Hazard Assessment on Engineered Slopes P. Miller et al. https://doi.org/10.1109/TGRS.2011.2165547
138. 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
139. Detection of Flood-Prone Areas Using Digital Elevation Models S. Manfreda et al. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000367
140. Estimation of the Budyko model parameter for small basins in China P. Bai et al. https://doi.org/10.1002/hyp.13577
141. Active layer modelling at Stelvio Pass, Italian Alps V. Chaturvedi et al. https://doi.org/10.1016/j.coldregions.2025.104762
142. 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
143. 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
144. 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
145. 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
146. Review: Advances in groundwater potential mapping S. Díaz-Alcaide & P. Martínez-Santos https://doi.org/10.1007/s10040-019-02001-3
147. 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
148. 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
149. 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
150. 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
151. 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
152. 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
153. 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
154. Chamaecyparis montane cloud forest in Taiwan: ecology and vegetation classification C. Li et al. https://doi.org/10.1007/s11284-015-1284-0
155. 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
156. 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
157. 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
158. 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
159. 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
160. 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
161. 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
162. 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
163. 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
164. A Self-Powered, Real-Time, LoRaWAN IoT-Based Soil Health Monitoring System S. Ramson et al. https://doi.org/10.1109/JIOT.2021.3056586
165. 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
166. 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
167. 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
168. 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
169. 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
170. Guiding riparian vegetation planting with machine learning R. Diaz-Gomez et al. https://doi.org/10.1080/24705357.2025.2481033
171. 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
172. 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
173. 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
174. 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
175. How much surface water can gilgai microtopography capture? A. Kishné et al. https://doi.org/10.1016/j.jhydrol.2014.03.053
176. Restored saltmarshes lack the topographic diversity found in natural habitat P. Lawrence et al. https://doi.org/10.1016/j.ecoleng.2018.02.007
177. 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
178. 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
179. 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
180. 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
181. 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
182. 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
183. 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
184. 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
185. 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
186. 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
187. GIS-based risk assessment of typhoon disasters in coastal provinces of China Y. Wang et al. https://doi.org/10.3389/fmars.2025.1548763
188. Use of Landsat images for yield evaluation within a small plot J. Kumhálová et al. https://doi.org/10.17221/515/2014-PSE
189. 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
190. Mapping the Serological Prevalence Rate of West Nile fever in Equids, Tunisia R. Bargaoui et al. https://doi.org/10.1111/tbed.12077
191. 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
192. Restoration of urban forests to reduce flood susceptibility: A starting point J. Viezzer et al. https://doi.org/10.1016/j.ijdrr.2022.102944
193. 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
194. 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
195. 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
196. Evaluating topographic wetness indices across central New York agricultural landscapes B. Buchanan et al. https://doi.org/10.5194/hess-18-3279-2014
197. 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
198. 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
199. Spatiotemporal railway use by grizzly bears in Canada's Rocky Mountains S. Pollock et al. https://doi.org/10.1002/jwmg.21750
200. 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
201. 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
202. 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
203. Updating Conventional Soil Maps through Digital Soil Mapping L. Yang et al. https://doi.org/10.2136/sssaj2010.0002
204. 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
205. 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
206. 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
207. 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
208. 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
209. 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
210. 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
211. 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
212. 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
213. Causes and Controlling Factors of Valley Bottom Gullies S. Amare et al. https://doi.org/10.3390/land8090141
214. 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
215. 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
216. Modelling and Mapping Likely Soil Rutting Occurrences across Forested Areas D. Snow et al. https://doi.org/10.4236/jgis.2024.166023
217. 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
218. 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
219. Mapping and assessment of lake ecosystem services in Lithuania M. Inácio et al. https://doi.org/10.1016/j.ecoser.2023.101589
220. Optimizing landslide susceptibility mapping using machine learning and geospatial techniques G. Agboola et al. https://doi.org/10.1016/j.ecoinf.2024.102583
221. 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
222. 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
223. 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
224. 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
225. 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
226. 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
227. 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
228. Burn Severity Drivers in Italian Large Wildfires F. Malandra et al. https://doi.org/10.3390/fire5060180
229. 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
230. 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
231. 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
232. 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
233. 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
234. 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
235. 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
236. Automated Flood Prediction along Railway Tracks Using Remotely Sensed Data and Traditional Flood Models A. Zakaria et al. https://doi.org/10.3390/rs16132332
237. A comparative study of heterogeneous ensemble-learning techniques for landslide susceptibility mapping Z. Fang et al. https://doi.org/10.1080/13658816.2020.1808897
238. 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
239. 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
240. 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
241. 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
242. 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
243. A Modified Distributed CN-VSA Method for Mapping of the Seasonally Variable Source Areas K. Panjabi et al. https://doi.org/10.3390/w13091270
244. 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
245. 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
246. 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
247. 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
248. 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
249. Analyzing and Projecting Soil Moisture and Cone Penetrability Variations in Forest Soils M. Jones & P. Arp https://doi.org/10.4236/ojf.2019.92005
250. 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
251. Spatio‐temporal interpolation of daily temperatures for global land areas at 1 km resolution M. Kilibarda et al. https://doi.org/10.1002/2013JD020803
252. 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
253. 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
254. 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
255. 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
256. 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
257. 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
258. Assessing the Spatiotemporal Variability of SMAP Soil Moisture Accuracy in a Deciduous Forest Region M. Abdelkader et al. https://doi.org/10.3390/rs14143329
259. 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
260. Does conserving roadless wildland increase wildfire activity in western US national forests? J. Johnston et al. https://doi.org/10.1088/1748-9326/ac13ee
261. 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
262. 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
263. 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
264. 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
265. 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
266. 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
267. 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
268. A Depression-Based Index to Represent Topographic Control in Urban Pluvial Flooding H. Huang et al. https://doi.org/10.3390/w11102115
269. 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
270. 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
271. 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
272. 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
273. 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
274. 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
275. Topography Wetness Index Application in Flood-Risk-Based Land Use Planning S. Pourali et al. https://doi.org/10.1007/s12061-014-9130-2
276. 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
277. 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
278. 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
279. 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
280. Mapping Groundwater Potential Through an Ensemble of Big Data Methods P. Martínez‐Santos & P. Renard https://doi.org/10.1111/gwat.12939
281. 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
282. 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
283. 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
284. 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
285. 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
286. 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
287. 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
288. 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
289. The Least Square Adjustment for Estimating the Tropical Peat Depth Using LiDAR Data B. Cahyono et al. https://doi.org/10.3390/rs12050875
290. 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
291. 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
292. Predicting Streamflow Duration From Crowd‐Sourced Flow Observations D. Peterson et al. https://doi.org/10.1029/2023WR035093
293. 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
294. 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
295. 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
296. 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
297. 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
298. 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
299. 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
300. 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
301. 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
302. 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
303. 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
304. 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
305. 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
306. 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
307. 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
308. 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
309. 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
310. 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
311. 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
312. 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
313. 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
314. Regional flood frequency analysis in North Africa Y. Tramblay et al. https://doi.org/10.1016/j.jhydrol.2024.130678
315. 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
316. 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
317. 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
318. Modelling soil moisture in a high‐latitude landscape using LiDAR and soil data J. Kemppinen et al. https://doi.org/10.1002/esp.4301
319. 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
320. 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
321. 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
322. A geospatial analysis of multi-hazard risk in Dharan, Nepal S. Aksha et al. https://doi.org/10.1080/19475705.2019.1710580
323. 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
324. 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
325. A Citizen-Science Study Documents Environmental Exposures and Asthma Prevalence in Two Communities S. Eiffert et al. https://doi.org/10.1155/2016/1962901
326. 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
327. 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
328. 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
329. 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
330. 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
331. 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
332. 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
333. 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
334. 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
335. Quantitative studies of the morphology of the south Poland using Relief Index (RI) B. Szypuła https://doi.org/10.1515/geo-2017-0039
336. Vegetative Community Response to Landscape-Scale Post-fire Herbicide (Imazapic) Application C. Applestein et al. https://doi.org/10.1017/inp.2018.18
337. Planning Framework for Mesolevel Optimization of Urban Runoff Control Schemes Q. Zhou et al. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000748
338. 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
339. Yozgat ili topoğrafik ıslaklık indeksinin (TWI) Coğrafi Bilgi Sistemleri ile belirlenmesi Ö. Karaca https://doi.org/10.70700/bjea.1576651
340. Linking LiDAR with streamwater biogeochemistry in coastal temperate rainforest watersheds J. Fellman et al. https://doi.org/10.1139/cjfas-2016-0130
341. 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
342. 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
343. 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
344. 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
345. 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
346. 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
347. 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
348. 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
349. 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
350. 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
351. 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
352. 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
353. 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
354. Identifying watershed predictors of surface water quality through iterative input selection L. Mejía & M. Barrios https://doi.org/10.1007/s13762-022-04406-2
355. 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
356. 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
357. 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
358. Quantifying Dieback in a Vulnerable Population of Eucalyptus macrorhyncha Using Remote Sensing D. Fitzgerald et al. https://doi.org/10.3390/land12071271
359. Topographic Metrics for Improved Mapping of Forested Wetlands M. Lang et al. https://doi.org/10.1007/s13157-012-0359-8
360. 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
361. 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
362. 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
363. 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
364. 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
365. 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
366. Detection and analysis of landslide geomorphology based on UAV vertical photogrammetry R. Bi et al. https://doi.org/10.1007/s11629-022-7766-y
367. 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
368. 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
369. 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
370. 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
371. 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
372. 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
373. Evaluation of a surface hydrological connectivity index in agricultural catchments M. Shore et al. https://doi.org/10.1016/j.envsoft.2013.04.003
374. 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
375. Geomorphometric characterization and sediment connectivity of the middle Brahmaputra River basin B. Faisal & Y. Hayakawa https://doi.org/10.1016/j.geomorph.2023.108665
376. 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
377. 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
378. 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
379. 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
380. 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
381. 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
382. 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
383. Morphology, timing, and drivers of post‐glacial landslides in the northern Yellowstone region J. Dixon et al. https://doi.org/10.1002/esp.5943
384. 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
385. 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
386. 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
387. 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
388. 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
389. Predicting urban cold-air paths using boosted regression trees L. Grunwald et al. https://doi.org/10.1016/j.landurbplan.2020.103843
390. 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
391. Flood Susceptibility Assessment with Random Sampling Strategy in Ensemble Learning (RF and XGBoost) H. Ren et al. https://doi.org/10.3390/rs16020320
392. 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
393. 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
394. 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
395. 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
396. 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
397. 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
398. 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
399. 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
400. 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
401. 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
402. 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
403. 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
404. 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
405. Determining local wetness conditions within the mined lands using GIS O. Skrypnyk et al. https://doi.org/10.33271/mining14.04.058
406. 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
407. 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
408. 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
409. 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
410. 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
411. 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
412. Unveiling the role of forests in landslide occurrence, recurrence and recovery Y. Law et al. https://doi.org/10.1111/1365-2664.14741
413. Characterising soil moisture in transport corridor environments using airborne LIDAR and CASI data A. Hardy et al. https://doi.org/10.1002/hyp.8217
414. Landslide Susceptibility Analysis: A Logistic Regression Model Case Study in Coonoor, India E. Sujatha & V. Sridhar https://doi.org/10.3390/hydrology8010041
415. 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
416. 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
417. 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
418. Space–time landslide hazard modeling via Ensemble Neural Networks A. Dahal et al. https://doi.org/10.5194/nhess-24-823-2024
419. 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
420. 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
421. 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
422. 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
423. 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
424. Evaluation of Birecik Basin Flood Detection with GIS Assisted AHP Methods V. Aslan https://doi.org/10.1007/s12205-023-1271-x
425. Correlation and causation in tree‐ring‐based reconstruction of paleohydrology in cold semiarid regions A. Elshorbagy et al. https://doi.org/10.1002/2016WR018985
426. 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
427. 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
428. 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
429. 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
430. 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
431. Kinematic Reconstruction of a Deep-Seated Gravitational Slope Deformation by Geomorphic Analyses S. Morelli et al. https://doi.org/10.3390/geosciences8010026
432. 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
433. 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
434. 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
435. 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
436. 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
437. 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
438. Detecting Woody Plant Cover in the Foothills Parkland and Montane Ecoregions of Southern Alberta E. Denning et al. https://doi.org/10.3390/rs18081229
439. 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
440. 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
441. 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
442. 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
443. 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
444. Stand age related differences in forest microclimate D. Lindenmayer et al. https://doi.org/10.1016/j.foreco.2022.120101
445. 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
446. 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
447. 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
448. 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
449. 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
450. 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
451. 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
452. 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
453. 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
454. 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
455. 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
456. 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
457. Landslide hydrology: from hydrology to pore pressure T. Bogaard & R. Greco https://doi.org/10.1002/wat2.1126
458. 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
459. 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
460. 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
461. 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
462. 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
463. 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
464. 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
465. 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
466. 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
467. 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
468. 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
469. 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
470. 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
471. TWI Computations and Topographic Analysis of Depression-Dominated Surfaces K. Grimm et al. https://doi.org/10.3390/w10050663
472. 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
473. Mapping Forest Canopy Fuels in the Western United States with LiDAR–Landsat Covariance C. Moran et al. https://doi.org/10.3390/rs12061000
474. The status and future of essential geodiversity variables F. Schrodt et al. https://doi.org/10.1098/rsta.2023.0052
475. 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
476. Flood Hazard Evaluation Using a Flood Potential Index N. Popescu & A. Bărbulescu https://doi.org/10.3390/w15203533
477. 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
478. 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
479. Flood Susceptibility and Risk Mapping of Kathmandu Valley Watershed, Nepal U. Chaudhary et al. https://doi.org/10.3390/su16167101
480. 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
481. Effect of Urban Green Spaces and Flooded Area Type on Flooding Probability H. Kim et al. https://doi.org/10.3390/su8020134
482. 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
483. 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
484. 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
485. 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
486. 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
487. 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
488. 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
489. Importance of geological information for assessing drain flow in a Danish till landscape A. Hansen et al. https://doi.org/10.1002/hyp.13338
490. 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
491. 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
492. 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
493. 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
494. Factors affecting variations of soil pH in different horizons in hilly regions Y. Zhang et al. https://doi.org/10.1371/journal.pone.0218563
495. 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
496. 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
497. 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
498. 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
499. Topography not tenure controls extent of wildfire within Mountain Ash forests M. Adams et al. https://doi.org/10.1088/1748-9326/abe57e
500. 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
501. 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
502. 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
503. 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
504. 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
505. Multisensor earth observations to characterize wetlands and malaria epidemiology in Ethiopia A. Midekisa et al. https://doi.org/10.1002/2014WR015634
506. 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
507. 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
508. 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
509. 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
510. 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
511. Relationships between Arctic shrub dynamics and topographically derived hydrologic characteristics A. Naito & D. Cairns https://doi.org/10.1088/1748-9326/6/4/045506
512. 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
513. 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
514. 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
515. Monthly microclimate models in a managed boreal forest landscape C. Greiser et al. https://doi.org/10.1016/j.agrformet.2017.12.252
516. 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
517. 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
518. 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
519. 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
520. Mapping Earth Hummocks in Daisetsuzan National Park in Japan Using UAV-SfM Framework Y. Meng et al. https://doi.org/10.3390/rs16193610
521. 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
522. 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
523. 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
524. 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
525. Reducing scale dependence in TOPMODEL using a dimensionless topographic index A. Ducharne https://doi.org/10.5194/hess-13-2399-2009
526. 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
527. 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
528. 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
529. 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
530. 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
531. Agronomy explains large yield gaps in smallholder oil palm fields J. Monzon et al. https://doi.org/10.1016/j.agsy.2023.103689
532. 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
533. Terrestrial CDOM in Lakes of Yamal Peninsula: Connection to Lake and Lake Catchment Properties Y. Dvornikov et al. https://doi.org/10.3390/rs10020167
534. 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
535. 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
536. 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
537. 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
538. 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
539. 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
540. Disentangling the potential effects of land‐use and climate change on stream conditions K. Maloney et al. https://doi.org/10.1111/gcb.14961
541. 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
542. 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
543. 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
544. 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
545. 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
546. 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
547. 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
548. Disentangling the functional trait correlates of spatial aggregation in tropical forest trees I. McFadden et al. https://doi.org/10.1002/ecy.2591
549. 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
550. Application of NRCS-CN method for estimation of watershed runoff and disaster risk W. Zhang https://doi.org/10.1080/19475705.2019.1686431
551. 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
552. Insights from Optimized Non-Landslide Sampling and SHAP Explainability for Landslide Susceptibility Prediction M. Li & H. Tian https://doi.org/10.3390/app15031163
553. 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
554. 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
555. A GIS-Based Hydrological Modeling Approach for Rapid Urban Flood Hazard Assessment Q. Zhou et al. https://doi.org/10.3390/w13111483
556. 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
557. Landslide Susceptibility Mapping with Deep Learning Algorithms J. Habumugisha et al. https://doi.org/10.3390/su14031734
558. 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
559. 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
560. 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
561. Locally rare species influence grassland ecosystem multifunctionality S. Soliveres et al. https://doi.org/10.1098/rstb.2015.0269
562. 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
563. 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
564. 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
565. 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
566. Clustering Urban Tree Climate Responses: A Multi-Metric Ensemble SDM Approach Across SSP Scenarios J. Yun et al. https://doi.org/10.3390/land15040616
567. Representativeness of FLUXNET Sites Across Latin America S. Villarreal & R. Vargas https://doi.org/10.1029/2020JG006090
568. 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
569. 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
570. Flood Susceptibility Assessment for Improving the Resilience Capacity of Railway Infrastructure Networks G. Varra et al. https://doi.org/10.3390/w16182592
571. 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
572. 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
573. 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
574. 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
575. 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
576. 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
577. 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
578. 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
579. A Spatial Database of Ecosystems of the Lake Baikal Basin S. Bazha et al. https://doi.org/10.1134/S2079096122030039
580. Environmental diversity as a surrogate for species representation P. Beier & F. de Albuquerque https://doi.org/10.1111/cobi.12495
581. 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
582. 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
583. 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
584. 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
585. 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
586. 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
587. 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
588. 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
589. 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
590. 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
591. 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
592. 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
593. 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
594. 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
595. 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
596. 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
597. 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
598. 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
599. 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
600. 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
601. 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
602. 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
603. Enhancing the WorldClim data set for national and regional applications L. Poggio et al. https://doi.org/10.1016/j.scitotenv.2017.12.258
604. 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
605. 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
606. 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
607. 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
608. 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
609. 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
610. 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
611. 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
612. Entropy-Based Modelling for Flash Flood Hazard Mapping in Uttarakhand Himalaya H. Prince et al. https://doi.org/10.1007/s12524-023-01797-8
613. 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
614. 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
615. 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
616. 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
617. 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
618. 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
619. 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
620. 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
621. 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
622. 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
623. 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
624. Species Traits Mediate Environmental Responses but Not Conspecific Density Dependence in Tropical Tree Saplings X. Ma et al. https://doi.org/10.1086/739608
625. 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
626. 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
627. Influence of groundwater and topography on stream drying in semi‐arid headwater streams S. Warix et al. https://doi.org/10.1002/hyp.14185
628. 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
629. 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
630. Uncertainty Modelling of Groundwater-Dependent Vegetation T. Robinson et al. https://doi.org/10.3390/land13122208
631. 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
632. 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
633. 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
634. Flood hazard risk assessment model based on random forest Z. Wang et al. https://doi.org/10.1016/j.jhydrol.2015.06.008
635. 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
636. 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
637. 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
638. 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
639. 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
640. 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
641. 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
642. 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
643. Topoedaphic constraints on woody plant cover in a semi-arid grassland S. Jones et al. https://doi.org/10.1016/j.ecolind.2023.110226
644. 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
645. 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
646. 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
647. 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
648. 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
649. 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
650. 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
651. 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
652. 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
653. 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
654. Identifying Extreme Heat and Moisture Zones for Vulnerable Populations in Athens: A Geospatial Analysis G. Papakonstantinou https://doi.org/10.3390/land14071375
655. 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
656. 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
657. 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
658. 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
659. 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
660. 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
661. 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
662. 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
663. 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
664. Development of an Integrated DBH Estimation Model Based on Stand and Climatic Conditions D. Piao et al. https://doi.org/10.3390/f9030155
665. 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
666. 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
667. 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
668. 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
669. 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
670. Combining geomorphometry, feature extraction techniques and Earth-surface processes research: The way forward G. Sofia https://doi.org/10.1016/j.geomorph.2020.107055
671. 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
672. 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
673. 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
674. Engineered slope failure susceptibility modelling using high spatial resolution geospatial data S. Obrike et al. https://doi.org/10.1007/s10064-021-02413-0
675. PyLandslide: A Python tool for landslide susceptibility mapping and uncertainty analysis M. Basheer & T. Oommen https://doi.org/10.1016/j.envsoft.2024.106055
676. 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
677. 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
678. Intercomparison of regional flood frequency estimation procedures in West Africa S. Diop et al. https://doi.org/10.1007/s00477-026-03258-3
679. 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
680. 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
681. Guiding oil palm intensification through a spatial extrapolation domain framework F. Agus et al. https://doi.org/10.1016/j.agsy.2023.103778
682. 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
683. 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
684. 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
685. Frekans Oranı ve Shannon Entropisi Yöntemi Kullanarak Ezine Çayı Havzası Taşkın Duyarlılık Analizi (Kastamonu-Bozkurt) M. UTLU https://doi.org/10.46453/jader.1358845
686. 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
687. 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
688. Current awareness https://doi.org/10.1002/hyp.6366
689. 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
690. 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
691. 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
692. 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
693. 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
694. 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
695. 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
696. 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
697. 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
698. 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
699. 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
700. 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
701. 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
702. 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
703. 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
704. 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
705. 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
706. 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
707. 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
708. 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
709. Delineating floodplain and upland areas for hydrologic models: a comparison of methods H. Rathjens et al. https://doi.org/10.1002/hyp.10918
710. 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
711. 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
712. 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
713. 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
714. 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
715. Vegetation recovery and management proposal for spoil heaps in Sorachi, Hokkaido H. Kawai et al. https://doi.org/10.5738/jale.27.3
716. 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
717. 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
718. 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
719. Using Remote Sensing and Machine Learning to Locate Groundwater Discharge to Salmon-Bearing Streams M. Gerlach et al. https://doi.org/10.3390/rs14010063
720. 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
721. Airborne LiDAR-derived elevation data in terrain trafficability mapping M. Niemi et al. https://doi.org/10.1080/02827581.2017.1296181
722. 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
723. Spatial Prediction of Organic Matter Quality in German Agricultural Topsoils A. Sakhaee et al. https://doi.org/10.3390/agriculture14081298
724. 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
725. 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
726. 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