NASADEM GLOBAL ELEVATION MODEL: METHODS AND PROGRESS

129 citations as recorded by crossref.

1. Identifying tree species in mining landscapes of the middle Yellow River: 5-year phenological trajectory divergence time-series from Sentinel-2 data Y. Su et al. https://doi.org/10.1080/10095020.2026.2667718
2. Assessing the Performance of Different Time of Concentration Equations in Urban Ungauged Watersheds: Case Study of Cartagena de Indias, Colombia Á. González-Álvarez et al. https://doi.org/10.3390/hydrology7030047
3. A 30 m global map of elevation with forests and buildings removed L. Hawker et al. https://doi.org/10.1088/1748-9326/ac4d4f
4. Reconstructing Lake Storage for the Major Water Bodies in the Aral Sea Basin Using Multi-DEM Hypsometry S. Huang et al. https://doi.org/10.3390/rs18050763
5. A note on the temporary misregistration of Landsat-8 Operational Land Imager (OLI) and Sentinel-2 Multi Spectral Instrument (MSI) imagery J. Storey et al. https://doi.org/10.1016/j.rse.2016.08.025
6. Soil bulk density assessment in Europe P. Panagos et al. https://doi.org/10.1016/j.agee.2024.108907
7. Extracting a Connected River Network from DEM by Incorporating Surface River Occurrence Data and Sentinel-2 Imagery in the Danjiangkou Reservoir Area L. Lu et al. https://doi.org/10.3390/rs15041014
8. Nationwide Subsidence in Bahrain Island: Drivers and Implications for Relative Sea-Level Rise J. Normand et al. https://doi.org/10.1109/JSTARS.2023.3286471
9. E-Agriculture Planning Tool for Supporting Smallholder Cocoa Intensification Using Remotely Sensed Data K. Singh et al. https://doi.org/10.3390/rs15143492
10. Shoreline Response to Hurricane Otis and Flooding Impact from Hurricane John in Acapulco, Mexico L. Valderrama-Landeros et al. https://doi.org/10.3390/coasts5030028
11. Segment Anything Model Combined with Multi-Scale Segmentation for Extracting Complex Cultivated Land Parcels in High-Resolution Remote Sensing Images Z. Huang et al. https://doi.org/10.3390/rs16183489
12. Crop flood damage assessment integrating Sentinel-2 imagery and in situ data: the 2023 Emilia-Romagna case F. Bocchino et al. https://doi.org/10.1016/j.rsase.2025.101852
13. Towards ice-thickness inversion: an evaluation of global digital elevation models (DEMs) in the glacierized Tibetan Plateau W. Chen et al. https://doi.org/10.5194/tc-16-197-2022
14. Multi-Type Change Detection and Distinction of Cultivated Land Parcels in High-Resolution Remote Sensing Images Based on Segment Anything Model Z. Huang et al. https://doi.org/10.3390/rs17050787
15. Multi-modal DEM super-resolution using relative depth: A new benchmark and beyond W. Huang et al. https://doi.org/10.1016/j.jag.2025.104865
16. Mapping annual 10-meter evergreen and non-evergreen forests in China from 2017 to 2023 with multi-source remote sensing data W. Zhao et al. https://doi.org/10.1080/15481603.2026.2702254
17. Global Digital Elevation Model Comparison Criteria: An Evident Need to Consider Their Application C. López-Vázquez & F. Ariza-López https://doi.org/10.3390/ijgi12080337
18. Frontiers in Hydrology and Water Resources Research T. TANAKA et al. https://doi.org/10.3178/jjshwr.31.509
19. Mapping biological activity of soils using the ‘Life in Undies’ citizen science programme T. Takáts et al. https://doi.org/10.1080/17445647.2026.2614168
20. Evaluating the Vertical Accuracy of Global DEMs Using ICESat-2 and Its Cascading Impact on HAND-Based Flood Modeling in a Low-Gradient Coastal Plain Y. Sun et al. https://doi.org/10.3390/rs18101511
21. Divergent changes of surface water and its climatic drivers in the headwater region of the Three Rivers on the Qinghai-Tibet Plateau Z. Xiao et al. https://doi.org/10.1016/j.ecolind.2024.111615
22. Development of a variable instantaneous unit hydrograph based on quantified rainfall spatial distribution W. Dong et al. https://doi.org/10.1016/j.jhydrol.2025.134497
23. A Fully Automatic Algorithm for Editing the TanDEM-X Global DEM C. González et al. https://doi.org/10.3390/rs12233961
24. The Evolution of Cropland Slope Structure and Its Implications for Fragmentation and Soil Erosion in China G. Liu et al. https://doi.org/10.3390/land14051093
25. Brief communication: Inferring Glacier Equilibrium Line Altitudes in the Europe Alps with FROST O. Herrmann et al. https://doi.org/10.5194/tc-20-3817-2026
26. Upscaling Forest Canopy Height Estimation Using Waveform-Calibrated GEDI Spaceborne LiDAR and Sentinel-2 Data J. Wang et al. https://doi.org/10.3390/rs16122138
27. Africa-wide diversification of livelihood strategies: Isotopic insights into Holocene human adaptations to climate change L. Phelps et al. https://doi.org/10.1016/j.oneear.2025.101304
28. Accuracy Assessment of High-Resolution Globally Available Open-Source DEMs Using ICESat/GLAS over Mountainous Areas, A Case Study in Yunnan Province, China M. Li et al. https://doi.org/10.3390/rs15071952
29. A Feature-Reinforced Ensemble Learning Framework for Space-Based DEM Correction Z. Ouyang et al. https://doi.org/10.3390/rs17081337
30. Digital Elevation Models: An Important Source of Data for Geoscientists [Education] B. Daya Sagar https://doi.org/10.1109/MGRS.2020.3031910
31. Advancing Earth Observation-based methods for rapid mapping and estimation of flood and drought impacts on rice production in the Philippines A. Araza & E. Alosnos https://doi.org/10.1016/j.ijdrr.2025.105979
32. Validation of Global 30 m DEMs Over Czechia Identifies FathomDEM as the Most Accurate Model P. Bašta et al. https://doi.org/10.1007/s41064-026-00399-6
33. SPT-UNet: A Superpixel-Level Feature Fusion Network for Water Extraction from SAR Imagery T. Zhao et al. https://doi.org/10.3390/rs16142636
34. Discussion: ‘Exploratory modelling of the impacts of sea-level rise on the Sundarbans mangrove forest, West Bengal, India’ by Samanta et al. (2023), Science of the Total Environment, 903, 166624 A. Das & S. Bandyopadhyay https://doi.org/10.1016/j.scitotenv.2025.178937
35. Mapping vegetation canopy height across the contiguous United States using ICESat-2 and ancillary datasets L. Malambo & S. Popescu https://doi.org/10.1016/j.rse.2024.114226
36. A Fast Algorithm for High Accuracy Airborne SAR Geolocation Based on Local Linear Approximation X. Liu et al. https://doi.org/10.1109/TIM.2022.3165255
37. Dynamic difference between surging and normal glaciers in the context of climate change: Insights from multi-source remote sensing Y. Gao et al. https://doi.org/10.1016/j.ejrh.2025.102990
38. Slope Structure Evolution and Spatial Competition Mechanisms Among Urban, Agricultural, and Ecological Spaces in China G. Liu et al. https://doi.org/10.3390/agriculture16101094
39. Spectral Complexity of Hyperspectral Images: A New Approach for Mangrove Classification P. Osei Darko et al. https://doi.org/10.3390/rs13132604
40. Bayesian estimation of glacier surface elevation changes from DEMs G. Guillet & T. Bolch https://doi.org/10.3389/feart.2023.1076732
41. Spatiotemporal Changes of Glaciers in the Yigong Zangbo River Basin over the Period of the 1970s to 2023 and Their Driving Factors S. Yuan et al. https://doi.org/10.3390/rs16173272
42. Assessing the discrepancies and uncertainties of regional shared and pixel-specific trapezoidal feature spaces using a Priestley-Taylor-based evapotranspiration model L. Yang et al. https://doi.org/10.1080/15481603.2025.2590783
43. Implication of Nari Caldera structure of Ulleung Island from a 3-D resistivity model using magnetotellurics K. Kim et al. https://doi.org/10.1007/s12303-024-0023-3
44. Enhancing the Spatial Applicability of SMAP Soil Moisture Using Multi-Stage Machine Learning Downscaling J. Park & J. Chang https://doi.org/10.3390/rs18172913
45. A semantic notation for comparing global high-resolution coastal flooding studies F. Baart et al. https://doi.org/10.3389/feart.2024.1465040
46. Glacier mass variations in the China-Pakistan highway regions from multi-source altimetric remote sensing data Y. Zheng et al. https://doi.org/10.1080/10106049.2025.2491649
47. Historical and projected evolutions of glaciers in response to climate change in the Muzart River basin, Central Asia X. Jin et al. https://doi.org/10.1080/17538947.2025.2528611
48. Winter tree and terrain shadow correction reveals land cover mapping errors in Sentinel-2 satellite imagery K. Lasko et al. https://doi.org/10.1016/j.ecoinf.2026.103809
49. Regionalizing Meteorological-to-Agricultural Drought Propagation for Agricultural Risk Management Using Event Metrics and Explainable Machine Learning H. Yan et al. https://doi.org/10.3390/agriculture16151660
50. Heterogeneous spatial and temporal pattern of surface elevation change and mass balance of the Patagonian ice fields between 2000 and 2016 W. Abdel Jaber et al. https://doi.org/10.5194/tc-13-2511-2019
51. Multi-Source DEM Vertical Accuracy Evaluation of Taklimakan Desert Hinterland Based on ICESat-2 ATL08 and UAV Data M. Wang et al. https://doi.org/10.3390/rs17111807
52. Resolving blind mid-crustal earthquake deformation with InSAR time-series: the 2021 Mw 6.4 San Juan earthquake and implications for a non-optimal fault reactivation in the Andean Fold and Thrust Belt, Argentina P. León-Ibáñez & F. Delgado https://doi.org/10.1093/gji/ggaf394
53. Uncertainty interval estimates for computing slope and aspect from a gridded digital elevation model C. López-Vázquez https://doi.org/10.1080/13658816.2022.2063294
54. Development and evaluation of hydraulic geometry relationships for large Brazilian river basins C. Coelho et al. https://doi.org/10.1080/02626667.2024.2396062
55. A new inventory of High Mountain Asia surging glaciers derived from multiple elevation datasets since the 1970s L. Guo et al. https://doi.org/10.5194/essd-15-2841-2023
56. The importance of digital elevation model accuracy in XCO2 retrievals: improving the Orbiting Carbon Observatory 2 Atmospheric Carbon Observations from Space version 11 retrieval product N. Jacobs et al. https://doi.org/10.5194/amt-17-1375-2024
57. Emerging global reservoirs in the new millennium: Abundance, hotspots, and total water storage C. Fan et al. https://doi.org/10.1016/j.scib.2024.04.043
58. Spatiotemporal light exposure modeling for environmental circadian misalignment and solar jetlag T. VoPham et al. https://doi.org/10.1097/EE9.0000000000000301
59. A national-scale assessment of land subsidence in China’s major cities Z. Ao et al. https://doi.org/10.1126/science.adl4366
60. Integrating topographic continuity and lake recession dynamics for improved bathymetry mapping from DEMs F. Tao et al. https://doi.org/10.5194/hess-30-2741-2026
61. Novel Approach for Ranking DEMs: Copernicus DEM Improves One Arc Second Open Global Topography C. Bielski et al. https://doi.org/10.1109/TGRS.2024.3368015
62. Modeling three-dimensional built-up volume dynamics and projections using long-term satellite observations G. Yu et al. https://doi.org/10.1016/j.scs.2026.107735
63. Global digital elevation model (GDEM) product generation by correcting ASTER GDEM elevation with ICESat-2 altimeter data B. Li et al. https://doi.org/10.5194/essd-17-205-2025
64. Evaluation of vertical accuracy of five open-source DEM datasets in a mountainous city: A case study of Chongqing central urban area, China Z. Chen et al. https://doi.org/10.1007/s11629-026-0487-2
65. ML-CASCADE: A machine learning and cloud computing-based tool for rapid and automated mapping of landslides using earth observation data N. Sharma & M. Saharia https://doi.org/10.1007/s10346-024-02360-3
66. Integrating optimal terrain representations from public DEMs using spaceborne LiDAR X. Zhang et al. https://doi.org/10.1080/17538947.2025.2505631
67. Assessing the Utility of Sentinel-1 Coherence Time Series for Temperate and Tropical Forest Mapping I. Borlaf-Mena et al. https://doi.org/10.3390/rs13234814
68. WaveUNet: An efficient deep network based on discrete wavelet transform and attention mechanism for InSAR phase unwrapping W. Mao et al. https://doi.org/10.1016/j.isprsjprs.2026.06.025
69. High Spatial Resolution Simulation of Sunshine Duration over the Complex Terrain of Ghana M. Adamu et al. https://doi.org/10.3390/s19071743
70. Investigation of glacier mass balance based on multi-source observation in the Karakoram over the past 25 years A. Yu et al. https://doi.org/10.1371/journal.pone.0358980
71. Evaluation of Copernicus DEM and Comparison to the DEM Used for Landsat Collection-2 Processing S. Franks & R. Rengarajan https://doi.org/10.3390/rs15102509
72. Identifying the Dimensions of Degraded Impact Structures Using Digital Elevation Models: A Proof of Concept for Silicate Planets C. Anderson et al. https://doi.org/10.3847/PSJ/adb969
73. Spatial Heterogeneity and Drivers of Vertical Error in Global DEMs: An Explainable Machine Learning Approach in Complex Subtropical Coastal Zones J. Chen et al. https://doi.org/10.3390/rs18081125
74. Relationship between Crustal Deformation and Thermal Anomalies in the 2022 Ninglang Ms 5.5 Earthquake in China: Clues from InSAR and RST Z. Lai et al. https://doi.org/10.3390/rs15051271
75. Ranking of 10 Global One-Arc-Second DEMs Reveals Limitations in Terrain Morphology Representation P. Guth et al. https://doi.org/10.3390/rs16173273
76. Topographical dynamics based on global and UAV-SfM derived DEM products: a case study of transboundary Teesta River, Bangladesh B. Faisal & Y. Hayakawa https://doi.org/10.1080/04353676.2024.2323347
77. Global Distribution and Local Variation of Pre-Rain Green-Up in Tropical Dryland S. Huang et al. https://doi.org/10.3390/rs17081377
78. Uncovering dominant drivers of Erigeron annuus distribution in Dajiuhu‐Shennongjia wetland using multiscale remote sensing data B. Xu et al. https://doi.org/10.1002/ps.70033
79. Impacts of Digital Elevation Model Elevation Error on Terrain Gravity Field Calculations: A Case Study in the Wudalianchi Airborne Gravity Gradiometer Test Site, China L. Wang et al. https://doi.org/10.3390/rs16213948
80. Delineation of Intermittent Rivers and Ephemeral Streams Using a Hybrid Method N. Wang et al. https://doi.org/10.3390/rs16132489
81. Vertical Accuracy Assessment and Improvement of Five High-Resolution Open-Source Digital Elevation Models Using ICESat-2 Data and Random Forest: Case Study on Chongqing, China W. Xu et al. https://doi.org/10.3390/rs16111903
82. Hillslope memory of sequential earthquakes X. Wang et al. https://doi.org/10.1126/sciadv.aeh3921
83. Urban Expansion and the Evolution of Morphological Polycentricity in Shandong Province, China, 2000–2020: Evidence from Long-Term Nighttime Light Data H. Xu et al. https://doi.org/10.3390/su18168567
84. High-resolution species distribution modelling reveals spatio-temporal variability of habitat suitability in a declining grassland bird T. Crispim-Mendes et al. https://doi.org/10.1007/s10980-024-01848-6
85. Spatial patterns and drivers of permafrost peatlands on the Qinghai-Tibet Plateau Y. Dong et al. https://doi.org/10.1016/j.geoderma.2026.118076
86. Integrated analysis of land use and land cover changes and landslide susceptibility: a machine learning approach in Rangamati Sadar, Bangladesh S. Hossen et al. https://doi.org/10.1007/s11069-025-07580-x
87. Coupled hydrological–hydrodynamic modelling of GLOFs triggered by extreme precipitation in the Western Himalayas D. Gaikwad et al. https://doi.org/10.1016/j.ejrh.2026.103738
88. GIS-Integrated Groundwater Flow Modeling for Heterogeneous Media: Application to the Calera Aquifer R. Silva-Avalos et al. https://doi.org/10.3390/w18010059
89. SWMManywhere: Synthesise Urban Drainage Network Models Anywhere in the World B. Dobson et al. https://doi.org/10.21105/joss.07729
90. Conformity of the NASADEM_HGT and ALOS AW3D30 DEM with the Altitude from the Brazilian Geodetic Reference Stations: A Case Study from Brazilian Cerrado G. Bettiol et al. https://doi.org/10.3390/s21092935
91. Tracking the historical urban development by classifying Landsat MSS data with training samples migrated across time and space Z. Feng et al. https://doi.org/10.1080/17538947.2023.2230951
92. Future glacio-hydrological changes in the Andes: a focus on near-future projections up to 2050 A. Caro et al. https://doi.org/10.1038/s41598-025-88069-2
93. Exploring implications of input parameter uncertainties in glacial lake outburst flood (GLOF) modelling results using the modelling code r.avaflow S. Rinzin et al. https://doi.org/10.5194/nhess-25-1841-2025
94. Integrating Neighboring Structure Knowledge Into a CNN-Transformer Hybrid Model for Global Open-Access DEM Correction Using ICESat-2 Altimetry J. Chen et al. https://doi.org/10.1109/TGRS.2026.3651262
95. Enhanced Co-Registration Method for Long-Baseline SAR Images D. Zeng et al. https://doi.org/10.3390/rs17244034
96. Best Practices for Elevation-Based Assessments of Sea-Level Rise and Coastal Flooding Exposure D. Gesch https://doi.org/10.3389/feart.2018.00230
97. Remote sensing and the new global river science D. Feng et al. https://doi.org/10.1038/s44221-026-00665-2
98. Measuring decadal vertical land-level changes from SRTM-C (2000) and TanDEM-X ( ∼ 2015) in the south-central Andes B. Purinton & B. Bookhagen https://doi.org/10.5194/esurf-6-971-2018
99. A Geodetic-Data-Calibrated Ice Flow Model to Simulate Historical and Future Response of Glaciers in Southeastern Tibetan Plateau L. Xiao et al. https://doi.org/10.3390/rs16030522
100. 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
101. Geomorphometric characterization and sediment connectivity of the middle Brahmaputra River basin B. Faisal & Y. Hayakawa https://doi.org/10.1016/j.geomorph.2023.108665
102. GeoidLab: An automated open-source Python toolbox for gravity-field analysis and vertical datum unification C. Kelly et al. https://doi.org/10.1007/s12145-026-02118-6
103. Assessing the accuracy of different open-source Digital Elevation Models (DEMs) in morphometric analysis of Kanchi River basin A. Mondal et al. https://doi.org/10.1016/j.ejrh.2026.103429
104. Urban correction of global DEMs using building density for Nairobi, Kenya V. Olajubu et al. https://doi.org/10.1007/s12145-021-00647-w
105. DeltaDTM: A global coastal digital terrain model M. Pronk et al. https://doi.org/10.1038/s41597-024-03091-9
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. Global Digital Terrain Models: Evaluation of vertical accuracy against different morphological contexts M. Helmy et al. https://doi.org/10.1177/03091333251406853
108. Hydrological response of Andean catchments to recent glacier mass loss A. Caro et al. https://doi.org/10.5194/tc-18-2487-2024
109. Verification of the accuracy of Sentinel-1 for DEM extraction error analysis under complex terrain conditions S. Zhang et al. https://doi.org/10.1016/j.jag.2024.104157
110. TPRoGI: a comprehensive rock glacier inventory for the Tibetan Plateau using deep learning Z. Sun et al. https://doi.org/10.5194/essd-16-5703-2024
111. Use of Very High-Resolution Optical Data for Landslide Mapping and Susceptibility Analysis along the Karnali Highway, Nepal P. Amatya et al. https://doi.org/10.3390/rs11192284
112. Landslide mapping using object-based image analysis and open source tools P. Amatya et al. https://doi.org/10.1016/j.enggeo.2021.106000
113. Analysing long-term spatiotemporal land surface phenology patterns over the Iberian Peninsula using 250 m MODIS EVI2 data J. Caparros-Santiago & V. Rodriguez-Galiano https://doi.org/10.1016/j.scitotenv.2024.176453
114. The Role of Earth Observation, with a Focus on SAR Interferometry, for Sinkhole Hazard Assessment A. Theron & J. Engelbrecht https://doi.org/10.3390/rs10101506
115. Regional “Bare-Earth” Digital Terrain Model for Costa Rica Based on NASADEM Corrected for Vegetation Bias O. Pimenova et al. https://doi.org/10.3390/rs14102421
116. Digital Elevation Models: Terminology and Definitions P. Guth et al. https://doi.org/10.3390/rs13183581
117. Spatially non-stationary and threshold-dependent drivers of cropland productivity in humid subtropical China revealed by explainable machine learning Y. Liao et al. https://doi.org/10.1016/j.ecolind.2026.115170
118. Effect of DEM and Gravity Field Representation Strategy On Regional Gravity and Height Anomaly Recovery By the Spectral Enhancement Method M. Lin et al. https://doi.org/10.1007/s11200-026-00019-4
119. Large-scale landslide susceptibility mapping via deep learning: A case study of Pakistan B. Liu et al. https://doi.org/10.1016/j.rse.2026.115710
120. Adaptive high-quality sampling for winter wheat early mapping: A novel cascade index and machine learning approach Z. Zhang et al. https://doi.org/10.1016/j.atech.2024.100725
121. Local Scale Current and Projected Future Total Flood Hazard Mapping for Canada—Literature Review S. Simonovic & B. Perry https://doi.org/10.1111/jfr3.70091
122. Landscape fragmentation and climate impacts in the western ghats: insights from entropy and LULC dynamics in Idukki district S. Jose et al. https://doi.org/10.1007/s00704-026-06515-1
123. Physically informed TabPFN mapping of glacier collapse susceptibility in the southeastern Qinghai–Xizang Plateau Y. Duan et al. https://doi.org/10.1016/j.accre.2026.09.010
124. Identification and mapping of yellow-flowering rapeseed fields by combining social media data, Sentinel-2 imagery, deep learning algorithm, and Google Earth Engine Z. Liu et al. https://doi.org/10.1016/j.jag.2024.104047
125. Sensitivity of peak flow response to imperviousness increase in a tropical Caribbean ungauged urban catchment Á. González-Álvarez et al. https://doi.org/10.1080/1573062X.2022.2044864
126. New LiDAR‐Based Elevation Model Shows Greatest Increase in Global Coastal Exposure to Flooding to Be Caused by Early‐Stage Sea‐Level Rise R. Vernimmen & A. Hooijer https://doi.org/10.1029/2022EF002880
127. A Methodology for Identifying Coastal Cultural Heritage Assets Exposed to Future Sea Level Rise Scenarios S. Chalkidou et al. https://doi.org/10.3390/app14167210
128. National-Scale Flood Susceptibility Mapping of Nigeria Using Statistical and Machine Learning Models with Satellite-Driven Validation for Data-Sparse Environments D. Idowu et al. https://doi.org/10.3390/rs18193264
129. LiDAR point cloud and ICESat‐2 evaluation of 1 second global digital elevation models: Copernicus wins P. Guth & T. Geoffroy https://doi.org/10.1111/tgis.12825