114 citations as recorded by crossref.

1. Airborne LiDAR-derived elevation data in terrain trafficability mapping M. Niemi et al. 10.1080/02827581.2017.1296181
2. A topographic moisture index explains understory vegetation response to retention harvesting L. Echiverri & S. Ellen Macdonald 10.1016/j.foreco.2020.118358
3. Spatio-temporal controls of dissolved organic carbon stream water concentrations A. Musolff et al. 10.1016/j.jhydrol.2018.09.011
4. A national-scale high-resolution runoff risk and channel network mapping workflow for diffuse pollution management T. Service et al. 10.1016/j.jenvman.2024.122110
5. Evaluation of different approaches for identifying optimal sites to predict mean hillslope soil moisture content K. Liao et al. 10.1016/j.jhydrol.2017.01.043
6. Groundwater flow paths drive longitudinal patterns of stream dissolved organic carbon (DOC) concentrations in boreal landscapes A. Lupon et al. 10.5194/hess-27-613-2023
7. Mapping Earth Hummocks in Daisetsuzan National Park in Japan Using UAV-SfM Framework Y. Meng et al. 10.3390/rs16193610
8. Wetland mapping with multi-temporal sentinel-1 & -2 imagery (2017 – 2020) and LiDAR data in the grassland natural region of alberta A. Onojeghuo et al. 10.1080/15481603.2021.1952541
9. Whether the Rock Fragment Content Should Be Considered When Investigating Nitrogen Cycle in Stony Soils? K. Liao et al. 10.1029/2018JG004780
10. Towards dynamic forest trafficability prediction using open spatial data, hydrological modelling and sensor technology A. Salmivaara et al. 10.1093/forestry/cpaa010
11. An approach to select optimum inputs for hydrological modeling to improve simulation accuracy in data-scarce regions J. Zhou et al. 10.1016/j.ejrh.2023.101447
12. A Comparative Assessment of Machine Learning Models for Landslide Susceptibility Mapping in the Rugged Terrain of Northern Pakistan N. Shahzad et al. 10.3390/app12052280
13. Spatio-temporal prediction of soil moisture and soil strength by depth-to-water maps M. Schönauer et al. 10.1016/j.jag.2021.102614
14. Prediction of soil drainage classes in Denmark by means of decision tree classification A. Møller et al. 10.1016/j.geoderma.2017.10.015
15. Effects of LiDAR DEM Smoothing and Conditioning Techniques on a Topography‐Based Wetland Identification Model G. O'Neil et al. 10.1029/2019WR024784
16. Predicting soil moisture conditions across a heterogeneous boreal catchment using terrain indices J. Larson et al. 10.5194/hess-26-4837-2022
17. Object-based random forest modelling of aboveground forest biomass outperforms a pixel-based approach in a heterogeneous and mountain tropical environment E. Silveira et al. 10.1016/j.jag.2019.02.004
18. A Citizen-Contributed GIS Approach for Evaluating the Impacts of Land Use on Hurricane-Harvey-Induced Flooding in Houston Area D. Yang et al. 10.3390/land8020025
19. Soils of Cuttings and Secondary Forests A. Dymov 10.1134/S1064229323700205
20. Identifying and assessing the potential hydrological function of past artificial forest drainage E. Hasselquist et al. 10.1007/s13280-017-0984-9
21. Spatio-temporal prediction of soil moisture using soil maps, topographic indices and SMAP retrievals M. Schönauer et al. 10.1016/j.jag.2022.102730
22. The role of biogeochemical hotspots, landscape heterogeneity, and hydrological connectivity for minimizing forestry effects on water quality H. Laudon et al. 10.1007/s13280-015-0751-8
23. Evaluating the potential for site-specific modification of LiDAR DEM derivatives to improve environmental planning-scale wetland identification using Random Forest classification G. O'Neil et al. 10.1016/j.jhydrol.2018.02.009
24. GIS-based multi criteria decision making method to identify potential runoff storage zones within watershed V. Rana & T. Suryanarayana 10.1080/19475683.2020.1733083
25. High-resolution harvester data for estimating rolling resistance and forest trafficability A. Salmivaara et al. 10.1007/s10342-024-01717-6
26. Predicting Habitat Properties Using Remote Sensing Data: Soil pH and Moisture, and Ground Vegetation Cover H. Haugen et al. 10.3390/rs14205207
27. Effect of bound water on the quality of dried Lentinus edodes during storage W. Yang et al. 10.1002/jsfa.10210
28. Landslides on dry badlands: UAV images to identify the drivers controlling their unexpected occurrence on vegetated hillslopes E. Rodriguez-Caballero et al. 10.1016/j.jaridenv.2020.104434
29. Soil Moisture Variations From Boreal Forests to the Tundra J. Kemppinen et al. 10.1029/2022WR032719
30. Groundwater inflows control patterns and sources of greenhouse gas emissions from streams A. Lupon et al. 10.1002/lno.11134
31. Dwarf Shrubs Impact Tundra Soils: Drier, Colder, and Less Organic Carbon J. Kemppinen et al. 10.1007/s10021-020-00589-2
32. Spatially Explicit Model for Statistical Downscaling of Satellite Passive Microwave Soil Moisture Y. Xu et al. 10.1109/TGRS.2019.2944421
33. Spatial optimization of ground-based primary extraction routes using the BestWay decision support system P. Flisberg et al. 10.1139/cjfr-2020-0238
34. Unmanned Aircraft System (UAS) Structure-From-Motion (SfM) for Monitoring the Changed Flow Paths and Wetness in Minerotrophic Peatland Restoration L. Ikkala et al. 10.3390/rs14133169
35. 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 10.1007/s41207-023-00443-6
36. Delineating northern peatlands using Sentinel-1 time series and terrain indices from local and regional digital elevation models M. Karlson et al. 10.1016/j.rse.2019.111252
37. Comparing buffer zone alternatives in forest planning using a decision support system J. Lundström et al. 10.1080/02827581.2018.1441900
38. Topography-based statistical modelling reveals high spatial variability and seasonal emission patches in forest floor methane flux E. Vainio et al. 10.5194/bg-18-2003-2021
39. Modelling soil moisture in a high‐latitude landscape using LiDAR and soil data J. Kemppinen et al. 10.1002/esp.4301
40. A holistic optimization framework for forest machine trail network design accounting for multiple objectives and machines A. Hosseini et al. 10.1139/cjfr-2018-0258
41. An inverse shortest path approach to find forwarder productivity functions N. Søvde et al. 10.1016/j.compag.2018.05.023
42. The effects of an auxiliary axle on forwarder rut development – a Norwegian field study D. Fjeld & Ø. Østby-Berntsen 10.1080/14942119.2020.1765645
43. A tree-based intelligence ensemble approach for spatial prediction of potential groundwater M. Avand et al. 10.1080/17538947.2020.1718785
44. Are dissolved organic carbon concentrations in riparian groundwater linked to hydrological pathways in the boreal forest? S. Ploum et al. 10.5194/hess-24-1709-2020
45. Digital mapping for soil texture class prediction in northwestern Türkiye by different machine learning algorithms F. Kaya et al. 10.1016/j.geodrs.2022.e00584
46. A web application for hydrogeomorphic flood hazard mapping R. Tavares da Costa et al. 10.1016/j.envsoft.2019.04.010
47. Forest harvest contribution to Boreal freshwater methyl mercury load R. Kronberg et al. 10.1002/2015GB005316
48. Évaluation du risque d’inondation par intégration du SAGA Wetness Index (SAGAWI) et de l’Analyse Hiérarchique des Procédés (AHP) : cas du District Autonome d’Abidjan K. Traoré 10.4000/belgeo.60310
49. Using a digital elevation model to place overland flow fields and uncleaned ditch sections for water protection in peatland forest management M. Niemi et al. 10.1016/j.ecoleng.2023.106945
50. Remote sensing and forest inventories in Nordic countries – roadmap for the future A. Kangas et al. 10.1080/02827581.2017.1416666
51. TWI computation: a comparison of different open source GISs P. Mattivi et al. 10.1186/s40965-019-0066-y
52. GIS-based MCDA for Gully Vulnerability Mapping Using AHP Techniques I. Bashir et al. 10.21523/gcj5.20040201
53. Relating Bryophyte Assemblages to a Remotely Sensed Depth-to-Water Index in Boreal Forests S. Bartels et al. 10.3389/fpls.2018.00858
54. Topographic conditions of soil drainage of Vladimir Opolie P. Shilov 10.19047/0136-1694-2020-105-28-56
55. Trafficability Prediction Using Depth-to-Water Maps: the Status of Application in Northern and Central European Forestry S. Hoffmann et al. 10.1007/s40725-021-00153-8
56. Using Random Forest Classification and Nationally Available Geospatial Data to Screen for Wetlands over Large Geographic Regions B. Felton et al. 10.3390/w11061158
57. Soils of Post-Pyrogenic Forests A. Dymov 10.1134/S1064229323700217
58. Cost of riparian buffer zones: A comparison of hydrologically adapted site‐specific riparian buffers with traditional fixed widths T. Tiwari et al. 10.1002/2015WR018014
59. A decision support model for individual tree stump harvesting options based on criteria for economic return and environmental protection B. Olsson et al. 10.1080/02827581.2016.1236983
60. Determining diagnostic indicators for fine-scale short vegetation aboveground biomass inversion using a HVRU-based analysis approach J. Wang et al. 10.1016/j.ecolind.2019.106033
61. Effects of stump harvest and site preparation on N2O and CH4 emissions from boreal forest soils after clear-cutting M. Strömgren et al. 10.1016/j.foreco.2016.03.019
62. GIS-fuzzy logic technique in modeling soil depth classes: Using parts of the Clay Belt and Hornepayne region in Ontario, Canada as a case study C. Akumu et al. 10.1016/j.geoderma.2016.07.028
63. Mapping of peatlands in the forested landscape of Sweden using lidar-based terrain indices L. Rimondini et al. 10.5194/essd-15-3473-2023
64. Remote sensing proxies of productivity and moisture predict forest stand type and recovery rate following experimental harvest W. Nijland et al. 10.1016/j.foreco.2015.08.027
65. GIS-based planning of buffer zones for protection of boreal streams and their riparian forests H. Mykrä et al. 10.1016/j.foreco.2022.120639
66. Wheel rut measurements by forest machine-mounted LiDAR sensors – accuracy and potential for operational applications? A. Salmivaara et al. 10.1080/14942119.2018.1419677
67. Scale‐dependent effects of environmental factors on soil organic carbon, soil nutrients and stoichiometry under two contrasting land‐use types Q. Zhu et al. 10.1111/sum.12695
68. Delineating wetland areas from the cut-and-fill method using a Digital Elevation Model (DEM) Z. Lidzhegu et al. 10.1080/03736245.2019.1638825
69. Depth‐to‐water mediates bryophyte response to harvesting in boreal forests S. Bartels et al. 10.1111/1365-2664.13359
70. Utilization of Image, LiDAR and Gamma-Ray Information to Improve Environmental Sustainability of Cut-to-Length Wood Harvesting Operations in Peatlands: A Management Systems Perspective T. Palander & K. Kärhä 10.3390/ijgi10050273
71. Growth and Yield Characterization of Soybean (Glycine max L.) and Adzuki Bean (Vigna angularis L.) Cultivated from Paddy Fields with Different Topographic Features H. Chun et al. 10.7745/KJSSF.2018.51.4.536
72. Modelling forest road trafficability with satellite-based soil moisture variables D. Fjeld et al. 10.1080/14942119.2023.2276628
73. Landscape-scale factors driving plant species composition in mountain streamside and spring riparian forests R. Pielech et al. 10.1016/j.foreco.2015.03.038
74. A comprehensive strategy for modeling watershed restoration priority areas under epistemic uncertainty: A case study in the Atlantic Forest, Brazil I. Possantti et al. 10.1016/j.jhydrol.2022.129003
75. Use of multiple LIDAR-derived digital terrain indices and machine learning for high-resolution national-scale soil moisture mapping of the Swedish forest landscape A. Ågren et al. 10.1016/j.geoderma.2021.115280
76. Modelling aboveground biomass in forest remnants of the Brazilian Atlantic Forest using remote sensing, environmental and terrain-related data E. Silveira et al. 10.1080/10106049.2019.1594394
77. Evaluating the effect of DEM resolution on performance of cartographic depth-to-water maps, for planning logging operations S. Mohtashami et al. 10.1016/j.jag.2022.102728
78. Applying continuous-cover forestry on drained boreal peatlands; water regulation, biodiversity, climate benefits and remaining uncertainties H. Laudon & E. Maher Hasselquist 10.1016/j.tfp.2022.100363
79. Terrain wetness indices derived from LiDAR to inform soil moisture and corrosion potential for underground infrastructure D. Bretreger et al. 10.1016/j.scitotenv.2020.144138
80. Forurenset grunn på avveier og nasjonalt datasett over dreneringslinjer J. Rød & T. Opach 10.18261/kp.116.1-2.2
81. Evaluating topography‐based predictions of shallow lateral groundwater discharge zones for a boreal lake‐stream system J. Leach et al. 10.1002/2016WR019804
82. Utilizing a topographic moisture index to characterize understory vegetation patterns in the boreal forest L. Echiverri & S. Macdonald 10.1016/j.foreco.2019.05.054
83. Application of the Conservation Planning Tool Zonation to Inform Retention Planning in the Boreal Forest of Western Canada F. Robinne et al. 10.3389/fevo.2020.584291
84. Google Earth Engine, Open-Access Satellite Data, and Machine Learning in Support of Large-Area Probabilistic Wetland Mapping J. Hird et al. 10.3390/rs9121315
85. Regional rainfall and local topography jointly drive tree community assembly in lowland tropical forests of New Caledonia G. Blanchard et al. 10.1111/jvs.12781
86. Wetland extent tools for SDG 6.6.1 reporting from the Satellite-based Wetland Observation Service (SWOS) K. Weise et al. 10.1016/j.rse.2020.111892
87. Contrasting responses of above- and belowground diversity to multiple components of land-use intensity G. Le Provost et al. 10.1038/s41467-021-23931-1
88. Depth-to-water maps as predictors of rut severity in fully mechanized harvesting operations J. Heppelmann et al. 10.1080/14942119.2022.2044724
89. Groundwater-surface water interactions across scales in a boreal landscape investigated using a numerical modelling approach E. Jutebring Sterte et al. 10.1016/j.jhydrol.2018.03.011
90. 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. 10.1007/s13280-019-01196-9
91. Moisture Stress Indicators in Giant Sequoia Groves in the Southern Sierra Nevada of California, USA R. Ray 10.2136/vzj2016.03.0018
92. Exploring the reliability of CAN-bus data in assessing forwarder rolling resistance under real working conditions F. Guerra et al. 10.3832/ifor4687-017
93. Towards an Improved Conceptualization of Riparian Zones in Boreal Forest Headwaters J. Ledesma et al. 10.1007/s10021-017-0149-5
94. Multiple stressors in small streams in the forestry context of Fennoscandia: The effects in time and space L. Kuglerová et al. 10.1016/j.scitotenv.2020.143521
95. Age-independent site index mapping with repeated single-tree airborne laser scanning S. Solberg et al. 10.1080/02827581.2019.1616814
96. An operational UAV-based approach for stand-level assessment of soil disturbance after forest harvesting B. Talbot et al. 10.1080/02827581.2017.1418421
97. Land cover classification of treeline ecotones along a 1100 km latitudinal transect using spectral‐ and three‐dimensional information from UAV‐based aerial imagery I. Mienna et al. 10.1002/rse2.260
98. Management perspectives onAqua incognita: Connectivity and cumulative effects of small natural and artificial streams in boreal forests L. Kuglerová et al. 10.1002/hyp.11281
99. Scale-dependent groundwater contributions influence patterns of winter baseflow stream chemistry in boreal catchments A. Peralta-Tapia et al. 10.1002/2014JG002878
100. Predicting forwarder rut formation on fine-grained mineral soils M. Sirén et al. 10.1080/02827581.2018.1562567
101. A Stepwise GIS Approach for the Delineation of River Valley Bottom within Drainage Basins Using a Cost Distance Accumulation Analysis G. Sechu et al. 10.3390/w13060827
102. Soil moisture modeling with ERA5-Land retrievals, topographic indices, and in situ measurements and its use for predicting ruts M. Schönauer et al. 10.5194/hess-28-2617-2024
103. Deep learning Using Physically-Informed Input Data for Wetland Identification G. O'Neil et al. 10.1016/j.envsoft.2020.104665
104. Groundwater, Soil, and Vegetation Interactions at Discrete Riparian Inflow Points (DRIPs) and Implications for Boreal Streams S. Ploum et al. 10.3389/frwa.2021.669007
105. Evaluating preprocessing methods of digital elevation models for hydrological modelling W. Lidberg et al. 10.1002/hyp.11385
106. 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. 10.3390/f12020113
107. Carbon isotope discrimination by Picea glauca and Populus tremuloides is related to the topographic depth to water index and rainfall G. Oltean et al. 10.1139/cjfr-2015-0491
108. Depth-to-Water Maps to Identify Soil Areas That Are Potentially Sensitive to Logging Disturbance: Initial Evaluations in the Mediterranean Forest Context F. Latterini et al. 10.3390/land11050709
109. Multi‐Source Mapping of Peatland Types Using Sentinel‐1, Sentinel‐2, and Terrain Derivatives—A Comparison Between Five High‐Latitude Landscapes M. Karlson & D. Bastviken 10.1029/2022JG007195
110. Relationship between structural features and water chemistry in boreal headwater streams—evaluation based on results from two water management survey tools suggested for Swedish forestry R. Lestander et al. 10.1007/s10661-015-4385-x
111. GIS‐based prediction of stream chemistry using landscape composition, wet areas, and hydrological flow pathways T. Tiwari et al. 10.1002/2016JG003399
112. Statistical-spatial modeling of the potential of landslide occurrence in Yamchi catchment F. Pourfarrashzadeh et al. 10.61186/jsaeh.11.1.4
113. Hydrological and thermal controls of ice formation in 25 boreal stream reaches L. Lind et al. 10.1016/j.jhydrol.2016.06.053
114. Towards optimizing riparian buffer zones: Ecological and biogeochemical implications for forest management L. Kuglerová et al. 10.1016/j.foreco.2014.08.033