230 citations as recorded by crossref.

1. Accuracy of Interpolated Bathymetry in Digital Elevation Models C. Amante & B. Eakins https://doi.org/10.2112/SI76-011
2. Quantifying local flow direction uncertainty G. O'Neil & A. Shortridge https://doi.org/10.1080/13658816.2012.719627
3. Assessment of Remotely Sensed Digital Elevation Models (DEMs) Compared with DGPS Elevation Data and Its Influence on Topographic Attributes M. Moawad & A. El Aziz https://doi.org/10.4236/ars.2018.72010
4. Effects of sample and grid size on the accuracy and stability of regression‐based snow interpolation methods J. Moreno et al. https://doi.org/10.1002/hyp.7564
5. Deep learning-based downscaling of global digital elevation models for enhanced urban flood modeling Z. Zandsalimi et al. https://doi.org/10.1016/j.jhydrol.2025.132687
6. Void Filling of Digital Elevation Models with a Terrain Texture Learning Model Based on Generative Adversarial Networks Z. Qiu et al. https://doi.org/10.3390/rs11232829
7. Hydrogeomorphic Controls on Flood Susceptibility Revealed Through Machine Learning and Explainable AI in a Multi-hazard-prone Fragile Biodiversity Hotspot of India S. Karmakar & S. Sk https://doi.org/10.1007/s41403-026-00582-6
8. Uncertain seas: probabilistic modeling of future coastal flood zones C. Amante https://doi.org/10.1080/13658816.2019.1635253
9. High-quality seamless DEM generation blending SRTM-1, ASTER GDEM v2 and ICESat/GLAS observations L. Yue et al. https://doi.org/10.1016/j.isprsjprs.2016.11.002
10. Recommendations for the quantitative analysis of landslide risk J. Corominas et al. https://doi.org/10.1007/s10064-013-0538-8
11. Impacts of elevation bias and topographic uncertainty on flood modeling: model robustness and floodplain sensitivity mapping in a lowland River Basin X. Le et al. https://doi.org/10.1016/j.jhydrol.2025.134832
12. Determining the optimum cell size of digital elevation model for hydrologic application A. SHARMA et al. https://doi.org/10.1007/s12040-011-0092-3
13. Vertical accuracy evaluation of SRTM-GL1, GDEM-V2, AW3D30 and CartoDEM-V3.1 of 30-m resolution with dual frequency GNSS for lower Tapi Basin India A. Jain et al. https://doi.org/10.1080/10106049.2017.1343392
14. Local Knowledge and Professional Background Have a Minimal Impact on Volunteer Citizen Science Performance in a Land-Cover Classification Task C. Salk et al. https://doi.org/10.3390/rs8090774
15. DEM Resolution Effects on Coastal Flood Vulnerability Assessment: Deterministic and Probabilistic Approach M. Fereshtehpour & M. Karamouz https://doi.org/10.1029/2017WR022318
16. Impact of Uncertainty of Floodplain Digital Terrain Model on 1D Hydrodynamic Flow Calculation A. Kiczko & D. Mirosław-Świątek https://doi.org/10.3390/w10101308
17. Demystifying the Differences between Structure-from-MotionSoftware Packages for Pre-Processing Drone Data T. Pell et al. https://doi.org/10.3390/drones6010024
18. The rise of brownfield mining is reshaping global mineral supply and intensifying social and environmental risk D. Kemp et al. https://doi.org/10.1016/j.oneear.2025.101563
19. Comparing alpine watershed attributes from LiDAR, Photogrammetric, and Contour‐based Digital Elevation Models C. Hopkinson et al. https://doi.org/10.1002/hyp.7155
20. Catchments of German surface water bodies A. Gericke et al. https://doi.org/10.1002/hyp.14272
21. Comparing the accuracy of estimated terrain elevations across spatial resolution M. Ghandehari et al. https://doi.org/10.1080/01431161.2019.1577581
22. Testing a low-complexity spatially distributed model to simulate the intra-annual dynamics of soil erosion and sediment delivery F. Matthews et al. https://doi.org/10.1016/j.catena.2025.109054
23. The Importance of Digital Elevation Model Selection in Flood Simulation and a Proposed Method to Reduce DEM Errors: A Case Study in Shanghai K. Xu et al. https://doi.org/10.1007/s13753-021-00377-z
24. Remote detection of upland surface water storage capacity in deglaciated terrain B. Van Dam & S. Smith https://doi.org/10.1002/esp.5708
25. Uncertainty due to DEM error in landslide susceptibility mapping C. Qin et al. https://doi.org/10.1080/13658816.2013.770515
26. Uncertainty Assessment in Soil Erosion Modelling Using RUSLE, Multisource and Multiresolution DEMs A. Pandey et al. https://doi.org/10.1007/s12524-021-01351-4
27. How does the choice of DEMs affect catchment hydrological modeling? D. Moges et al. https://doi.org/10.1016/j.scitotenv.2023.164627
28. Heuristic approach to urban sewershed delineation for pluvial flood modeling S. Park et al. https://doi.org/10.1016/j.jwpe.2024.106129
29. Effect of Elevation Resolution on Evapotranspiration Simulations using MODFLOW B. Kambhammettu et al. https://doi.org/10.1111/j.1745-6584.2011.00852.x
30. Embedding rivers in triangulated irregular networks with linear programming M. Kreveld & R. Silveira https://doi.org/10.1080/13658816.2010.488240
31. Generating Nested Wetland Catchments with Readily-Available Digital Elevation Data May Improve Evaluations of Land-Use Change on Wetlands L. McCauley & M. Anteau https://doi.org/10.1007/s13157-014-0571-9
32. Quantifying human risk from rainfall‐induced landslides across different return periods: A case study of Ba To, Quang Ngai, Vietnam B. Nguyen & T. Nguyen https://doi.org/10.1002/esp.70210
33. Assessing Flood Vulnerability of Landfills in Southern New Jersey: Incorporating Climate Change and Extreme Weather Impacts R. Chowdhury et al. https://doi.org/10.3390/w18091085
34. Error Characteristics of Pan-Arctic Digital Elevation Models and Elevation Derivatives in Northern Sweden M. Karlson et al. https://doi.org/10.3390/rs13224653
35. Characterizing errors in digital elevation models and estimating the financial costs of accuracy S. Januchowski et al. https://doi.org/10.1080/13658811003591680
36. A probabilistic approach to river network detection in digital elevation models L. Poggio & P. Soille https://doi.org/10.1016/j.catena.2011.07.001
37. Habitat suitability and flood risk modeling for Gazella conservation actions in Mond protected area E. Abbasi et al. https://doi.org/10.1016/j.ijdrr.2024.104816
38. Comparison of differences in resolution and sources of controlling factors for gully erosion susceptibility mapping Y. Garosi et al. https://doi.org/10.1016/j.geoderma.2018.05.027
39. On the topology of topography: a review K. Clarke & B. Romero https://doi.org/10.1080/15230406.2016.1164625
40. High-resolution automated detection of headwater streambeds for large watersheds F. Lessard et al. https://doi.org/10.5194/hess-28-1027-2024
41. Spatial Global Sensitivity Analysis of High Resolution classified topographic data use in 2D urban flood modelling M. Abily et al. https://doi.org/10.1016/j.envsoft.2015.12.002
42. Evaluating Digital Elevation Model generation from Sentinel-1 SAR data in challenging tropical environments Z. Zylshal et al. https://doi.org/10.1007/s40808-024-02171-4
43. Perspectives on Digital Elevation Model (DEM) Simulation for Flood Modeling in the Absence of a High-Accuracy Open Access Global DEM L. Hawker et al. https://doi.org/10.3389/feart.2018.00233
44. Accounting for uncertainties in compound flood hazard assessment: The value of data assimilation D. Muñoz et al. https://doi.org/10.1016/j.coastaleng.2021.104057
45. Pre-storm hydrology buffers saltwater intrusion in coastal forests A. Noori & S. Fagherazzi https://doi.org/10.1016/j.jhydrol.2026.135315
46. Possibilities of Using Low Quality Digital Elevation Models of Floodplains in Hydraulic Numerical Models I. Laks et al. https://doi.org/10.3390/w9040283
47. JSPSR: Joint Spatial Propagation Super-Resolution Networks for Enhancement of Bare-Earth Digital Elevation Models from Global Data X. Cai & M. Wilson https://doi.org/10.3390/rs17213591
48. Study on the Prediction of Debris Flow Risk Using LS-RAPID N. Kim et al. https://doi.org/10.9798/KOSHAM.2023.23.1.73
49. Terrain-Aided Navigation With Coarse Maps—Toward an Arctic Crossing With an AUV G. Salavasidis et al. https://doi.org/10.1109/JOE.2021.3085941
50. Hydrological data uncertainty and its implications H. McMillan et al. https://doi.org/10.1002/wat2.1319
51. Open-Channel Hydrodynamic Numerical Simulation of Topographically Uncharted River Based on Observational Data-Driven Method G. Li et al. https://doi.org/10.1061/JWRMD5.WRENG-6156
52. Sediment Balance Estimation of the ‘Cuvette Centrale’ of the Congo River Basin Using the SWAT Hydrological Model P. Datok et al. https://doi.org/10.3390/w13101388
53. Assessing the potential of harvested rainwater for forest fire suppression using InSAR and the Analytic Hierarchy Process (AHP) A. Genc et al. https://doi.org/10.1080/1573062X.2025.2560542
54. Bank erosion in agricultural drainage networks: new challenges from structure‐from‐motion photogrammetry for post‐event analysis M. Prosdocimi et al. https://doi.org/10.1002/esp.3767
55. CABra: a novel large-sample dataset for Brazilian catchments A. Almagro et al. https://doi.org/10.5194/hess-25-3105-2021
56. Modeling transport and fate of heavy metals at the watershed scale: State-of-the-art and future directions L. Zhou et al. https://doi.org/10.1016/j.scitotenv.2023.163087
57. Landslide dynamics from high-resolution aerial photographs: A case study from the Western Carpathians, Slovakia R. Prokešová et al. https://doi.org/10.1016/j.geomorph.2009.09.033
58. Hydrological and water resources investigations of the Mereb-Gash river basin in Eritrea A. Ghebrehiwot & D. Kozlov https://doi.org/10.22227/1997-0935.2022.12.1687-1706
59. Sensitivity of DEM, slope, aspect and watershed attributes to LiDAR measurement uncertainty T. Goulden et al. https://doi.org/10.1016/j.rse.2016.03.005
60. Rainfall simulation and Structure-from-Motion photogrammetry for the analysis of soil water erosion in Mediterranean vineyards M. Prosdocimi et al. https://doi.org/10.1016/j.scitotenv.2016.09.036
61. Inca water channel flow analysis based on 3D models from terrestrial and UAV laser scanning at the Chachabamba archaeological site (Machu Picchu National Archaeological Park, Peru) S. Dominika et al. https://doi.org/10.1016/j.jas.2021.105515
62. Assessment of open-source and proprietary generated digital elevation models and building footprints for urban flood modelling in Cartagena De Indias, Colombia A. Masud et al. https://doi.org/10.1080/10106049.2026.2681279
63. InSAR Digital Elevation Model Void-Filling Method Based on Incorporating Elevation Outlier Detection Z. Hu et al. https://doi.org/10.3390/rs16081452
64. ANADEM: A Digital Terrain Model for South America L. Laipelt et al. https://doi.org/10.3390/rs16132321
65. Assessing land elevation in the Ayeyarwady Delta (Myanmar) and its relevance for studying sea level rise and delta flooding K. Seeger et al. https://doi.org/10.5194/hess-27-2257-2023
66. Effect of DEM resolution on assessing hydrological connectivity in tropical and semi-arid basins of central Mexico A. Ortíz-Rodríguez et al. https://doi.org/10.1016/j.jhydrol.2022.128104
67. Uncertainty of SWAT model at different DEM resolutions in a large mountainous watershed P. Zhang et al. https://doi.org/10.1016/j.watres.2014.01.018
68. An improved method to represent DEM uncertainty in glacial lake outburst flood propagation using stochastic simulations C. Watson et al. https://doi.org/10.1016/j.jhydrol.2015.08.046
69. New elevation data triple estimates of global vulnerability to sea-level rise and coastal flooding S. Kulp & B. Strauss https://doi.org/10.1038/s41467-019-12808-z
70. Comparative Assessment of SWAT Model Performance in two Distinct Catchments under Various DEM Scenarios of Varying Resolution, Sources and Resampling Methods M. Goyal et al. https://doi.org/10.1007/s11269-017-1840-1
71. Uncertainty Analysis of Digital Elevation Models by Spatial Inference From Stable Terrain R. Hugonnet et al. https://doi.org/10.1109/JSTARS.2022.3188922
72. Flood Analysis Supported by Low‐cost Geometric Modelling S. Zazo et al. https://doi.org/10.1002/rra.3113
73. Implications of Simulating Global Digital Elevation Models for Flood Inundation Studies L. Hawker et al. https://doi.org/10.1029/2018WR023279
74. The effects of topographic depressions on multiscale overland flow connectivity: A high‐resolution spatiotemporal pattern analysis approach based on connectivity statistics F. Yu & J. Harbor https://doi.org/10.1002/hyp.13409
75. Ranking sources of uncertainty in flood damage modelling: a case study on the cost‐benefit analysis of a flood mitigation project in the Orb Delta, France N. Saint‐Geours et al. https://doi.org/10.1111/jfr3.12068
76. Determining the optimal grid resolution for topographic analysis on an airborne lidar dataset T. Smith et al. https://doi.org/10.5194/esurf-7-475-2019
77. VERTICAL ACCURACY ASSESSMENT OF OPEN ACCESS DIGITAL ELEVATION MODELS: BUCARAMANGA-COLOMBIA CASE STUDY J. Aponte Saravia https://doi.org/10.3846/gac.2022.14266
78. Integrating DEM and field data to unravel the impact of bedrock topography on Late Quaternary ice flows: A case study of the Lake Mistassini area, Canada M. El Amrani et al. https://doi.org/10.1007/s12040-023-02251-6
79. The potential of small unmanned aircraft systems and structure-from-motion for topographic surveys: A test of emerging integrated approaches at Cwm Idwal, North Wales T. Tonkin et al. https://doi.org/10.1016/j.geomorph.2014.07.021
80. Evaluating the capacity of single photon lidar for terrain characterization under a range of forest conditions J. White et al. https://doi.org/10.1016/j.rse.2020.112169
81. TanDEM-X IDEM precision and accuracy assessment based on a large assembly of differential GNSS measurements in Kruger National Park, South Africa J. Baade & C. Schmullius https://doi.org/10.1016/j.isprsjprs.2016.05.005
82. Impacts of DEM uncertainties on critical source areas identification for non-point source pollution control based on SWAT model F. Xu et al. https://doi.org/10.1016/j.jhydrol.2016.06.019
83. Evaluation of the Vertical Accuracy of Open Global DEMs over Steep Terrain Regions Using ICESat Data: A Case Study over Hunan Province, China Z. Liu et al. https://doi.org/10.3390/s20174865
84. Application of Filtering Techniques to Smooth a Surface of Hybrid Digital Bathymetric Model J. Lubczonek & G. Zaniewicz https://doi.org/10.3390/rs15194737
85. ‘Benefit Maximizing Routes’: Development and Evaluation Using the Historical Roads of Korea’s Joseon Dynasty (1392–1910) W. Shim et al. https://doi.org/10.5334/jcaa.97
86. Inverse unsaturated-zone flow modeling for groundwater recharge estimation: a regional spatial nonstationary approach M. Karamouz et al. https://doi.org/10.1007/s10040-022-02502-8
87. Analysis of flood modeling through innovative geomatic methods S. Zazo et al. https://doi.org/10.1016/j.jhydrol.2015.03.011
88. Topographic uncertainty quantification for flow-like landslide models via stochastic simulations H. Zhao & J. Kowalski https://doi.org/10.5194/nhess-20-1441-2020
89. Assessment of Landslide Susceptibility Using Statistical- and Artificial Intelligence-Based FR–RF Integrated Model and Multiresolution DEMs A. Arabameri et al. https://doi.org/10.3390/rs11090999
90. A Fuzzy Logic Based Method for Modeling the Spatial Distribution of Indicators of Decomposition in a High Mountain Environment N. Hellwig et al. https://doi.org/10.1657/AAAR0015-073
91. Modelling of piping collapses and gully headcut landforms: Evaluating topographic variables from different types of DEM A. Arabameri et al. https://doi.org/10.1016/j.gsf.2021.101230
92. Toward Reliable UAV-Enabled Positioning in Mountainous Environments: System Design and Preliminary Results Z. Wang et al. https://doi.org/10.1109/TR.2021.3088132
93. Understanding the scale effects of topographical variables on landslide susceptibility mapping in Sikkim Himalaya using deep learning approaches A. Saha et al. https://doi.org/10.1080/10106049.2022.2136255
94. Evaluation of TanDEM-X DEMs on selected Brazilian sites: Comparison with SRTM, ASTER GDEM and ALOS AW3D30 C. Grohmann https://doi.org/10.1016/j.rse.2018.04.043
95. A Methodological Framework for Identification of Baseline Scenario and Assessing the Impact of DEM Scenarios on SWAT Model Outputs H. Sukumaran & S. Sahoo https://doi.org/10.1007/s11269-020-02691-5
96. City-scale high-resolution flood models and the role of topographic data: a case study of Kathmandu, Nepal C. Watson et al. https://doi.org/10.1080/10106049.2024.2387073
97. Improving the usability of global SRTM DEM for reach-scale floodplain inundation mapping in data-scarce regions through bias correction I. Jesna et al. https://doi.org/10.1007/s12145-025-01812-1
98. Forest Road Detection Using LiDAR Data Z. Azizi et al. https://doi.org/10.1007/s11676-014-0544-0
99. Land Cover and Water Quality Patterns in an Urban River: A Case Study of River Medlock, Greater Manchester, UK C. Medupin et al. https://doi.org/10.3390/w12030848
100. Effect of User Decision and Environmental Factors on Computationally Derived River Networks N. Olsen et al. https://doi.org/10.1029/2022JF006873
101. Terrain‐aided navigation for long‐range AUVs in dynamic under‐mapped environments G. Salavasidis et al. https://doi.org/10.1002/rob.21994
102. Mensuration of FABDEM’s vertical accuracy using ICESat-2 photon profiles over sloped terrains S. Roy et al. https://doi.org/10.1007/s41324-025-00612-5
103. Modeling the extent of surface water floods in rural areas: Lessons learned from the application of various uncalibrated models D. Bernet et al. https://doi.org/10.1016/j.envsoft.2018.08.005
104. LiDAR-derived slopes for headwater channel network analysis A. Vianello et al. https://doi.org/10.1016/j.catena.2008.09.012
105. Comparison of soil moisture fields estimated by catchment modelling and remote sensing: a case study in South Africa T. Vischel et al. https://doi.org/10.5194/hess-12-751-2008
106. New Method to Correct Vegetation Bias in a Copernicus Digital Elevation Model to Improve Flow Path Delineation G. Brochado & C. Rennó https://doi.org/10.3390/rs16224332
107. Terrain‐derived measures for basin conservation and restoration planning J. Matt et al. https://doi.org/10.1002/rra.4181
108. DEM Generation Incorporating River Channels in Data-Scarce Contexts: The “Fluvial Domain Method” J. Villanueva et al. https://doi.org/10.3390/hydrology12020033
109. Evaluating the Impact of Digital Elevation Models on Urban Flood Modeling: A Comprehensive Analysis of Flood Inundation, Hazard Mapping, and Damage Estimation Z. Zandsalimi et al. https://doi.org/10.1007/s11269-024-03862-4
110. Accuracy assessment of the TanDEM-X 90 Digital Elevation Model for selected floodplain sites L. Hawker et al. https://doi.org/10.1016/j.rse.2019.111319
111. Digital Elevation Model Quality Assessment Methods: A Critical Review L. Polidori & M. El Hage https://doi.org/10.3390/rs12213522
112. Statistical relationship between land surface altitude and soil salinity in the enclosed desert depressions of arid regions N. Bakr & R. Ali https://doi.org/10.1007/s12517-019-4969-9
113. DEM resolution influences on peak flow prediction: a comparison of two different based DEMs through various rescaling techniques A. Suliman et al. https://doi.org/10.1080/10106049.2019.1622599
114. Piezometry mapping accuracy based on elevation extracted from various spatial data sources I. Hentati et al. https://doi.org/10.1007/s12665-016-5589-2
115. Long-term effects of mining activities in the karst area: A geomorphological and landscape approach (Kaczawskie Mountains, SW Poland) M. Sadkiewicz & M. Kasprzak https://doi.org/10.1016/j.ancene.2026.100557
116. Benchmarking observational uncertainties for hydrology: rainfall, river discharge and water quality H. McMillan et al. https://doi.org/10.1002/hyp.9384
117. 3‐D uncertainty‐based topographic change detection with structure‐from‐motion photogrammetry: precision maps for ground control and directly georeferenced surveys M. James et al. https://doi.org/10.1002/esp.4125
118. Geostatistical approach for identifying scale-specific correlations between soil thickness and topographic attributes H. Bourennane et al. https://doi.org/10.1016/j.geomorph.2014.05.026
119. Disaster Risk Reduction Based on a GIS Case Study of the Čađavica River Watershed R. Ristić et al. https://doi.org/10.15177/seefor.17-12
120. The agricultural impact of the 2015–2016 floods in Ireland as mapped through Sentinel 1 satellite imagery R. O’Hara et al. https://doi.org/10.2478/ijafr-2019-0006
121. Impacts of DEM resolution, source, and resampling technique on SWAT-simulated streamflow M. Tan et al. https://doi.org/10.1016/j.apgeog.2015.07.014
122. Determination of sensitivity of drainage morphometry towards hydrological response interactions for various datasets A. Jain et al. https://doi.org/10.1007/s10668-020-00652-x
123. Drainage Structure Datasets and Effects on LiDAR-Derived Surface Flow Modeling R. Li et al. https://doi.org/10.3390/ijgi2041136
124. Exploring the sensitivity of coastal inundation modelling to DEM vertical error H. West et al. https://doi.org/10.1080/13658816.2018.1444165
125. A GIS based approach for the mitigation of surface runoff to a shallow lowland reservoir J. Dąbrowska et al. https://doi.org/10.1016/j.ecohyd.2018.07.002
126. Assessing potential coastal flood exposure along the Port-Bouët Bay in Côte d’Ivoire using the enhanced bathtub model M. Kouakou et al. https://doi.org/10.1088/2515-7620/acfdfa
127. Enhancing debris flow simulation accuracy through high-resolution terrain information: a case study utilizing LS-RAPID and UAV-derived models N. Kim & B. Jun https://doi.org/10.1007/s10346-024-02290-0
128. Use of bathymetry and clay mineralogy of reservoir sediment to reconstruct the recent changes in sediment yields from a mountain catchment in the Western High Atlas region, Morocco A. Gourfi et al. https://doi.org/10.1016/j.catena.2020.104560
129. Real-Time DTM Generation with Sequential Estimation and OptD Method W. Błaszczak-Bąk et al. https://doi.org/10.3390/app15074068
130. TanDEM-X Water Indication Mask: Generation and First Evaluation Results A. Wendleder et al. https://doi.org/10.1109/JSTARS.2012.2210999
131. A similarity index for storm runoff due to saturation excess overland flow B. Bates & S. Aryal https://doi.org/10.1016/j.jhydrol.2014.03.021
132. Identifying Surface Runoff Pathways for Cost-Effective Mitigation of Pollutant Inputs to Drinking Water Reservoir J. Dąbrowska et al. https://doi.org/10.3390/w10101300
133. Effects of DEM Depression Filling on River Drainage Patterns and Surface Runoff Generated by 2D Rain-on-Grid Scenarios P. Costabile et al. https://doi.org/10.3390/w14070997
134. Impacts of Dem Uncertainty on Estimated Surface Solar Radiation and Extracted River Network L. Wang & K. Wang https://doi.org/10.1175/BAMS-D-13-00285.1
135. Identification of karst sinkholes in a forested karst landscape using airborne laser scanning data and water flow analysis J. Hofierka et al. https://doi.org/10.1016/j.geomorph.2018.02.004
136. Quality Assessment of TanDEM-X DEMs, SRTM and ASTER GDEM on Selected Chinese Sites H. Han et al. https://doi.org/10.3390/rs13071304
137. An algorithm to extract more accurate stream longitudinal profiles from unfilled DEMs J. Byun & Y. Seong https://doi.org/10.1016/j.geomorph.2015.03.015
138. A Novel Airborne Dual-Antenna InSAR Calibration Method for Backprojection Imaging Model X. Hu et al. https://doi.org/10.1109/ACCESS.2021.3066098
139. Evaluating the performance of various interpolation techniques on digital elevation models in highly dense forest vegetation environment S. Adedapo & H. Zurqani https://doi.org/10.1016/j.ecoinf.2024.102646
140. Multi-Task Learning of Relative Height Estimation and Semantic Segmentation from Single Airborne RGB Images M. Lu et al. https://doi.org/10.3390/rs14143450
141. Multiple thematic spatial integration technique to identify the groundwater recharge potential zones—a case study along the Courtallam region, Tamil Nadu, India B. Panda et al. https://doi.org/10.1007/s12517-020-06223-8
142. Utilization of Satellite-based Digital Elevation Model (DEM) for Hydrologic Applications: A Review S. Zaidi et al. https://doi.org/10.1007/s12594-018-1016-5
143. Evaluation of ASTER GDEM2, SRTMv3.0, ALOS AW3D30 and TanDEM-X DEMs for the Peruvian Andes against highly accurate GNSS ground control points and geomorphological-hydrological metrics M. González-Moradas & W. Viveen https://doi.org/10.1016/j.rse.2019.111509
144. Topographic uncertainty and catchment-based models A. Gericke https://doi.org/10.5004/dwt.2010.1908
145. How large is the Upper Indus Basin? The pitfalls of auto-delineation using DEMs A. Khan et al. https://doi.org/10.1016/j.jhydrol.2013.11.028
146. Evaluating Vertical Accuracies of Open-Source Digital Elevation Models over Multiple Sites in China Using GPS Control Points X. Liu et al. https://doi.org/10.3390/rs14092000
147. Integrating multi-source remote sensing and numerical simulation approaches for enhanced flood hazard assessment E. Hamidi et al. https://doi.org/10.1016/j.jhydrol.2026.135933
148. Position paper: Sensitivity analysis of spatially distributed environmental models- a pragmatic framework for the exploration of uncertainty sources H. Koo et al. https://doi.org/10.1016/j.envsoft.2020.104857
149. Assessing modern ground survey methods and airborne laser scanning for digital terrain modelling: A case study from the Lake District, England M. Gallay et al. https://doi.org/10.1016/j.cageo.2012.08.015
150. Validation of digital elevation models (DEMs) and comparison of geomorphic metrics on the southern Central Andean Plateau B. Purinton & B. Bookhagen https://doi.org/10.5194/esurf-5-211-2017
151. Evaluation of the U.S. Geological Survey standard elevation products in a two-dimensional hydraulic modeling application for a low relief coastal floodplain E. Witt https://doi.org/10.1016/j.jhydrol.2015.10.051
152. Assessment of Open Access Global Elevation Model Errors Impact on Flood Extents in Southern Niger R. Muench et al. https://doi.org/10.3389/fenvs.2022.880840
153. Multi-Aspect Critical Assessment of Applying Digital Elevation Models in Environmental Hazard Mapping M. Habib et al. https://doi.org/10.32604/rig.2024.053857
154. Best Practices for Elevation-Based Assessments of Sea-Level Rise and Coastal Flooding Exposure D. Gesch https://doi.org/10.3389/feart.2018.00230
155. An application-driven approach to terrain model construction A. Darnell et al. https://doi.org/10.1080/13658810903318889
156. The Impact of DEM Resolution on Runoff and Sediment Modelling Results G. Ghaffari https://doi.org/10.3923/rjes.2011.691.702
157. Bathymetric mapping and estimation of water storage in a shallow lake using a remote sensing inversion method based on machine learning H. Yang et al. https://doi.org/10.1080/17538947.2022.2069873
158. Influence of resolution on slope in areas with different topographic characteristics C. Wang et al. https://doi.org/10.1016/j.cageo.2011.10.028
159. DEM Fusion using a modifiedk-means clustering algorithm C. Fuss et al. https://doi.org/10.1080/17538947.2016.1208685
160. Comparison of remotely sensed water stages from LiDAR, topographic contours and SRTM G. Schumann et al. https://doi.org/10.1016/j.isprsjprs.2007.09.004
161. Dune migration and volume change from airborne LiDAR, terrestrial LiDAR and Structure from Motion-Multi View Stereo C. Grohmann et al. https://doi.org/10.1016/j.cageo.2020.104569
162. Assessing ecological risk through automated drainage extraction and watershed delineation L. Mantelli et al. https://doi.org/10.1016/j.ecoinf.2011.04.003
163. Sandy beach evolution in the low-energy microtidal Baltic Sea: Attribution of changes to hydrometeorological forcing M. Eelsalu et al. https://doi.org/10.1016/j.geomorph.2022.108383
164. Effects of best management practices on nitrogen load reduction in tea fields with different slope gradients using the SWAT model W. Wang et al. https://doi.org/10.1016/j.apgeog.2017.08.020
165. Comparison of ASTER GDEM3, SRTM3, NASADEM, TanDEM-X90, AW3D30, and ALOS PALSAR data with TanDEM-X12: a case study of Tagragra of Akka inlier, Moroccan Anti-Atlas Z. Adiri et al. https://doi.org/10.1007/s12517-022-10885-x
166. Development of topo-bathymetric continuum profiles for coastal barriers with global open-access data V. Fanti et al. https://doi.org/10.1016/j.rsase.2025.101528
167. Breakdown of hydrologic patterns upon model coarsening at hillslope scales and implications for experimental design T. Mahmood & E. Vivoni https://doi.org/10.1016/j.jhydrol.2011.10.011
168. Variations in multiscale curvature distribution and signatures of LiDAR DTM errors G. Sofia et al. https://doi.org/10.1002/esp.3363
169. Application of LiDAR Data for Hydrologic Assessments of Low-Gradient Coastal Watershed Drainage Characteristics D. Amatya et al. https://doi.org/10.4236/jgis.2013.52017
170. Improving the Accuracy of Open Source Digital Elevation Models with Multi-Scale Fusion and a Slope Position-Based Linear Regression Method Y. Tian et al. https://doi.org/10.3390/rs10121861
171. Finite Mixture Models in the Evaluation of Positional Accuracy of Geospatial Data J. Rodríguez-Avi & F. Ariza-López https://doi.org/10.3390/rs14092062
172. Mapping Potential Groundwater Discharge Indicators in Urban Rivers: A Thermal Remote Sensing and Machine-Learning Approach for Tangshan City A. Ullah et al. https://doi.org/10.3390/rs18142376
173. Measuring ground surface elevation changes in a slow-moving colluvial landslide using combinations of regional airborne lidar, UAV lidar and UAV photogrammetric surveys S. Johnson et al. https://doi.org/10.1144/qjegh2022-078
174. An Improved Flow Direction Algorithm That Considers Mass Conservation for Sediment Transport Simulations H. Wei et al. https://doi.org/10.3390/w15234111
175. Utilizing Geospatial Tools to Assign Unique Identifiers to Water Bodies in a Low-Income Country A. Mansaray et al. https://doi.org/10.4236/jwarp.2021.133014
176. A comparison of statistical methods and multi-criteria decision making to map flood hazard susceptibility in Northern Iran A. Arabameri et al. https://doi.org/10.1016/j.scitotenv.2019.01.021
177. Hillslope-to-valley transition morphology: New opportunities from high resolution DTMs P. Tarolli & G. Dalla Fontana https://doi.org/10.1016/j.geomorph.2009.02.006
178. Evaluating Applicability of SRTM DEM (Shuttle Radar Topography Mission Digital Elevation Model) in Hydrologic Analysis: A Case Study of Geum River and Daedong River Areas Y. Her & S. Yoo https://doi.org/10.5389/KSAE.2013.55.6.101
179. Bathymetric Inversion and Mapping of Two Shallow Lakes Using Sentinel-2 Imagery and Bathymetry Data in the Central Tibetan Plateau H. Yang et al. https://doi.org/10.1109/JSTARS.2022.3177227
180. Assessing Tidal Hydrodynamics in a Tropical Seascape Using Structure‐from‐Motion Photogrammetry and 2D Flow Modelling C. Vulliet et al. https://doi.org/10.1007/s12237-023-01288-6
181. On the uncertainty of stream networks derived from elevation data: the error propagation approach T. Hengl et al. https://doi.org/10.5194/hess-14-1153-2010
182. Impacts of Agro-Ecological Practices on Soil Losses and Cash Crop Yield D. De Benedetto et al. https://doi.org/10.3390/agriculture7120103
183. Development of a Simulation Model for Estimation of Potential Recharge in a Semi-arid Foothill Region S. Banimahd et al. https://doi.org/10.1007/s11269-017-1593-x
184. Uncertainty in primary and secondary topographic attributes caused by digital elevation model spatial resolution S. Salekin et al. https://doi.org/10.1016/j.catena.2023.107320
185. GIS-driven evaluation of energy infrastructure vulnerability to coastal inundation in Qatar A. Hzami et al. https://doi.org/10.1038/s41598-025-05968-0
186. Short‐term Forecasting Tools for Agricultural Nutrient Management Z. Easton et al. https://doi.org/10.2134/jeq2016.09.0377
187. The Influence of the DSM Spatial Resolution in Rockfall Simulation and Validation with In Situ Data M. Kakavas et al. https://doi.org/10.3390/geosciences13020057
188. Flood Forecasting in Large River Basins Using FOSS Tool and HPC U. Dutta et al. https://doi.org/10.3390/w13243484
189. Shaping the Global High-Resolution TanDEM-X Digital Elevation Model M. Huber et al. https://doi.org/10.1109/JSTARS.2021.3095178
190. Lidar DEM error analyses and topographic depression identification in a hummocky landscape in the prairie region of Canada S. Li et al. https://doi.org/10.1016/j.geomorph.2011.02.020
191. A wrapper feature selection approach for efficient modelling of gully erosion susceptibility mapping H. Rouhani et al. https://doi.org/10.1177/0309133320979897
192. FLIAT, An Object-Relational GIS Tool for Flood Impact Assessment in Flanders, Belgium S. Van Ackere et al. https://doi.org/10.3390/w11040711
193. Evaluation of Selected Sub-Elements of Spatial Data Quality on 3D Flood Event Modeling: Case Study of Prešov City, Slovakia M. Bindzárová Gergeľová et al. https://doi.org/10.3390/app10030820
194. Generating high-resolution DEMs in mountainous regions using ICESat-2/ATLAS photons Y. Zhao et al. https://doi.org/10.1016/j.jag.2025.104461
195. Accuracy assessment of ALOS World 3D-30m DEMs using field data from Lagos and Federal Capital Territory, Nigeria C. Okolie & I. Arungwa https://doi.org/10.1080/10106049.2022.2060320
196. Accuracy assessment of global DEMs for the mapping of coastal flooding on a low-lying sandy environment: Cassino Beach, Brazil I. Emmendorfer et al. https://doi.org/10.1016/j.rsma.2024.103535
197. Fusion of multi-scale DEMs using a regularized super-resolution method L. Yue et al. https://doi.org/10.1080/13658816.2015.1063639
198. Assessing Coastal Squeeze of Tidal Wetlands D. Torio & G. Chmura https://doi.org/10.2112/JCOASTRES-D-12-00162.1
199. Scale-dependency of LiDAR derived terrain attributes in quantitative soil-landscape modeling: Effects of grid resolution vs. neighborhood extent J. Maynard & M. Johnson https://doi.org/10.1016/j.geoderma.2014.03.021
200. A novel error inversion method for landslide susceptibility assessment based on topography-derived and spatially projected factors Z. Gao et al. https://doi.org/10.1007/s10346-026-02782-1
201. Quality assessment from a hydrological perspective of a digital elevation model derived from WorldView-2 remote sensing data J. Novoa et al. https://doi.org/10.1080/02626667.2013.875179
202. An optimized use of limited ground based topographic data for river applications M. Jaballah et al. https://doi.org/10.1016/j.ijsrc.2018.11.002
203. A comparative analysis of the vertical accuracy of multiple open-source digital elevation models for the mountainous terrain of the north-western Himalaya P. Ganie et al. https://doi.org/10.1007/s40808-022-01641-x
204. Effect of Target Moisture on Laser Scanner Intensity S. Kaasalainen et al. https://doi.org/10.1109/TGRS.2009.2036841
205. Improving the identification of hydrologically sensitive areas using LiDAR DEMs for the delineation and mitigation of critical source areas of diffuse pollution I. Thomas et al. https://doi.org/10.1016/j.scitotenv.2016.02.183
206. A systematic review and meta-analysis of Digital elevation model (DEM) fusion: pre-processing, methods and applications C. Okolie & J. Smit https://doi.org/10.1016/j.isprsjprs.2022.03.016
207. Modelling topo-bathymetric surface using a triangulation irregular network (TIN) of Tunga Dam in Nigeria P. Ibrahim et al. https://doi.org/10.1007/s12518-022-00438-y
208. A Novel Framework for Validation of DSM Data Quality Based on Hyperspectral Topographic Correction S. Liu et al. https://doi.org/10.3390/rs18111752
209. The influence of DEM resolution on simulated solar radiation‐induced glacier melt C. Hopkinson et al. https://doi.org/10.1002/hyp.7531
210. Evaluation of TanDEM-X elevation data for geomorphological mapping and interpretation in high mountain environments — A case study from SE Tibet, China I. Pipaud et al. https://doi.org/10.1016/j.geomorph.2015.06.025
211. Impact of data sources to DEM construction and application to runoff and sediment yield modelling using LISEM model C. de Barros et al. https://doi.org/10.1007/s12040-020-01547-1
212. Determination of subcatchment and watershed boundaries in a complex and highly urbanized landscape A. Kayembe & C. Mitchell https://doi.org/10.1002/hyp.13229
213. Yükselen ve Alçalan Yörüngeye Ait TerraSAR-X Görüntülerinden Üretilen Sayısal Yükseklik Modellerinin Doğruluk Karşılaştırması A. TORUN https://doi.org/10.21605/cukurovaumfd.1146081
214. Visualization of Features in 3D Terrain S. Dübel & H. Schumann https://doi.org/10.3390/ijgi6110357
215. The influence of resolution and topographic uncertainty on melt modelling using hypsometric sub‐grid parameterization F. Hebeler & R. Purves https://doi.org/10.1002/hyp.7034
216. Reconstruction and inversion of lake water depth based on ICESat-2 photon and Sentinel-2 — A case study of Caiduochaka Lake on the Tibetan Plateau T. Du et al. https://doi.org/10.1016/j.ejrh.2025.102776
217. Evaluating the impact of DEM interpolation algorithms on relief index for soil resource management M. Habib et al. https://doi.org/10.1515/geo-2022-0667
218. The evaluation of unmanned aerial system-based photogrammetry and terrestrial laser scanning to generate DEMs of agricultural watersheds M. Ouédraogo et al. https://doi.org/10.1016/j.geomorph.2014.02.016
219. Assessment of Digital Elevation Model (DEM) aggregation methods for hydrological modeling: Lake Chad basin, Africa M. Le Coz et al. https://doi.org/10.1016/j.cageo.2008.07.009
220. Comparison of one-dimensional and two-dimensional GRASS-GIS models for flood mapping R. Marzocchi et al. https://doi.org/10.1007/s12518-014-0140-1
221. Water depth inversion based on ICESat-2 and Sentinel-2—A case study of Qiagui Co and Ayakekumu Lake on the Tibetan Plateau B. Qiao et al. https://doi.org/10.1016/j.ejrh.2025.102354
222. Drainage basin morphometry: a global snapshot from the shuttle radar topography mission P. Guth https://doi.org/10.5194/hess-15-2091-2011
223. A sequential iterative dual-filter for Lidar terrain modeling optimized for complex forested environments C. Véga et al. https://doi.org/10.1016/j.cageo.2012.03.021
224. Use of environmental predictors for vegetation mapping in semi-arid mountain rangelands and the determination of conservation hotspots K. Brinkmann et al. https://doi.org/10.1111/j.1654-109X.2010.01097.x
225. Quantification of global Digital Elevation Model (DEM) – A case study of the newly released NASADEM for a river basin in Central Vietnam T. Tran et al. https://doi.org/10.1016/j.ejrh.2022.101282
226. Scale-dependent predictability of DEM-based landform attributes for soil spatial variability in a coastal dune system D. Kim & Y. Zheng https://doi.org/10.1016/j.geoderma.2011.06.002
227. A Network‐Based Flow Accumulation Algorithm for Point Clouds: Facet‐Flow Networks (FFNs) A. Rheinwalt et al. https://doi.org/10.1029/2018JF004827
228. A review of statistically-based landslide susceptibility models P. Reichenbach et al. https://doi.org/10.1016/j.earscirev.2018.03.001
229. Impacts of spatial data resolution on simulated discharge, a case study of Xitiaoxi catchment in South China G. Zhao et al. https://doi.org/10.5194/adgeo-21-131-2009
230. Sampling‐Based Methods for Uncertainty Propagation in Flood Modeling Under Multiple Uncertain Inputs: Finding Out the Most Efficient Choice M. Hajihassanpour et al. https://doi.org/10.1029/2022WR034011