UPDATES OF ‘AW3D30’ ALOS GLOBAL DIGITAL SURFACE MODEL WITH OTHER OPEN ACCESS DATASETS

83 citations as recorded by crossref.

1. A regional map of mangrove extent for Myanmar, Thailand, and Cambodia shows losses of 44% by 1996 P. Baltezar et al. https://doi.org/10.3389/fmars.2023.1127720
2. Globally Increasing Atmospheric Aridity Over the 21st Century Z. Fang et al. https://doi.org/10.1029/2022EF003019
3. The Significance of Digital Elevation Models in the Calculation of LS Factor and Soil Erosion M. Michalopoulou et al. https://doi.org/10.3390/land11091592
4. Ground Surface Displacement After a Forest Fire Near Mayya, Eastern Siberia, Using InSAR: Observation and Implication for Geophysical Modeling T. Abe et al. https://doi.org/10.1029/2022EA002476
5. Predicting suitable breeding areas for different locust species – A multi-scale approach accounting for environmental conditions and current land cover situation I. Klein et al. https://doi.org/10.1016/j.jag.2021.102672
6. Luminescence Sensitivity of Quartz From Rocks Under in situ Chemical Weathering Conditions Z. Cao et al. https://doi.org/10.3389/feart.2022.940212
7. Enabling multi-decadal braided river monitoring through FloodMamba-Net and task-equivalent Landsat-to-Sentinel-2 data synthesis X. Song et al. https://doi.org/10.1016/j.jhydrol.2025.134737
8. An Elevation Ambiguity Resolution Method Based on Segmentation and Reorganization of TomoSAR Point Cloud in 3D Mountain Reconstruction X. Li et al. https://doi.org/10.3390/rs13245118
9. A semantic notation for comparing global high-resolution coastal flooding studies F. Baart et al. https://doi.org/10.3389/feart.2024.1465040
10. Accuracy assessment of open DTM and DSM products in urban environments J. Liu et al. https://doi.org/10.1080/10095020.2026.2694226
11. A Fully Unsupervised Machine Learning Framework for Algal Bloom Forecasting in Inland Waters Using MODIS Time Series and Climatic Products P. Ananias et al. https://doi.org/10.3390/rs14174283
12. Process-explicit ecological sensitivity assessment in Hohhot, China: asynchronous dynamics and spatial clustering T. Chulhuud et al. https://doi.org/10.1016/j.ecolind.2026.115556
13. SBAS-InSAR Monitoring and Analysis of Surface Deformation in Xingtai City from 2019 to 2021 月. 杨 https://doi.org/10.12677/GST.2022.104024
14. Relationship between land surface temperature and air quality in urban and suburban areas: Dynamic changes and interaction effects P. Zhang et al. https://doi.org/10.1016/j.scs.2024.106043
15. Improving the Accuracy of Global DEM of Differences (DoD) in Google Earth Engine for 3-D Change Detection Analysis A. Capolupo https://doi.org/10.1109/JSTARS.2021.3130063
16. Filling and drainage of a subglacial lake beneath the Flade Isblink ice cap, northeast Greenland Q. Liang et al. https://doi.org/10.5194/tc-16-2671-2022
17. Multi-hazard risk to global port infrastructure and resulting trade and logistics losses J. Verschuur et al. https://doi.org/10.1038/s43247-022-00656-7
18. Comparative Analysis of Global DEMs for Dam-Break Flood Modeling and Inundation Mapping S. Toledo Salgado et al. https://doi.org/10.1007/s11269-025-04427-9
19. Morphometric analysis and LULC change dynamics of Nayar watershed for the sustainable watershed management A. Mani et al. https://doi.org/10.1007/s44288-024-00064-8
20. NBDNet: A Self-Supervised CNN-Based Method for InSAR Phase and Coherence Estimation H. Li et al. https://doi.org/10.3390/rs17071181
21. Deformation Characteristics and Activation Dynamics of the Xiaomojiu Landslide in the Upper Jinsha River Basin Revealed by Multi-Track InSAR Analysis X. Ma et al. https://doi.org/10.3390/rs16111940
22. Spatiotemporal trends of rubber defoliation and refoliation and their responses to abiotic factors in the northern edge of the Asian tropics Y. Chen et al. https://doi.org/10.1016/j.indcrop.2025.120753
23. Seismic Source Complexities Revealed by InSAR and Analytical Modeling: The 2025 Mw 7.1 Dingri Earthquake S. Puliero et al. https://doi.org/10.3390/rs18111751
24. Helicopter-borne RGB orthomosaics and photogrammetric digital elevation models from the MOSAiC Expedition N. Neckel et al. https://doi.org/10.1038/s41597-023-02318-5
25. Determination of long-term volume change in lakes by integration of UAV and satellite data: the case of Lake Burdur in Türkiye Y. Kaya et al. https://doi.org/10.1007/s11356-023-30369-z
26. Evaluation of Selected Digital Elevation Models over a Tropical Rainforest: A Case Study at Brunei Darussalam’s Tropical Rainforest E. Zadbagher et al. https://doi.org/10.1007/s12524-024-02070-2
27. Global cities under multiple climate hazards R. Nogherotto et al. https://doi.org/10.1016/j.uclim.2026.103132
28. Assessing LISFLOOD-FP with the next-generation digital elevation model FABDEM using household survey and remote sensing data in the Central Highlands of Vietnam L. Hawker et al. https://doi.org/10.5194/nhess-24-539-2024
29. Fusing Enhanced Flux Measurements and Multi-Source Satellite Observations to Improve GPP Estimation for the Qinghai–Tibet Plateau Based on AutoML Techniques M. Zhao et al. https://doi.org/10.3390/rs18010130
30. 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
31. A pan‐European citizen science study shows population size, climate and land use are related to biased morph ratios in the heterostylous plant Primula veris T. Aavik et al. https://doi.org/10.1111/1365-2745.14477
32. Detrital zircon evidence for provenance and paleodrainage in Miocene south Tauride basins, southern Turkey G. Chen et al. https://doi.org/10.1130/B38287.1
33. Isostatic Characteristics and Uplift Mechanisms of the Eastern Qilian Mountains: Constraints from High-Resolution Gravity and GNSS Data G. Zhang et al. https://doi.org/10.1007/s00024-026-03946-9
34. Performance analysis of open-source DEMs in tsunami inundation modelling D. Tufekci-Enginar et al. https://doi.org/10.1007/s12145-022-00852-1
35. Less extreme and earlier outbursts of ice-dammed lakes since 1900 G. Veh et al. https://doi.org/10.1038/s41586-022-05642-9
36. Farm dam enhancement significantly improves water quality M. Evans et al. https://doi.org/10.1016/j.agee.2024.109134
37. Environmental and Anthropogenic Drivers of Mammalian Functional Diversity in Bénoué National Park, Cameroon M. Majiteu et al. https://doi.org/10.1002/ece3.72363
38. Quantitative evaluation of flood extent detection using attention U-Net case studies from Eastern South Wales Australia in March 2021 and July 2022 F. Fakhri & I. Gkanatsios https://doi.org/10.1038/s41598-025-92734-x
39. Multi-Baseline InSAR DEM Reconstruction and Multi-Source Performance Evaluation Based on the PIESAT-1 “Wheel” Constellation S. Qiao et al. https://doi.org/10.3390/rs18071101
40. Influence of Digital Terrain Data Accuracy on Diffraction Prediction in NLOS Wireless Backhauls M. Al-Zubi & M. Alouini https://doi.org/10.1109/TVT.2024.3415358
41. Validation of Recent DSM/DEM/DBMs in Test Areas in Greece Using Spirit Leveling, GNSS, Gravity and Echo Sounding Measurements V. Grigoriadis et al. https://doi.org/10.3390/ijgi12030099
42. Simulating Runoff Formation in Mountain Crimea Rivers under Current and Projected Climate Conditions A. Kalugin et al. https://doi.org/10.1134/S0097807824701173
43. GIS-Based Automated Waterlogging Depth Calculation and Building Loss Assessment in Urban Communities C. Tseng et al. https://doi.org/10.3390/w17182725
44. An interactive toolkit based on Google Earth Engine for visual interpretation and analysis of land cover and land cover changes T. Zhao et al. https://doi.org/10.1080/20964471.2025.2608464
45. Apatite (U-Th)/He Thermochronology from Marsh Creek Anticline Reconciles Cenozoic and Holocene Strain Patterns and Elucidates the Cenozoic Canning Displacement Zone of Arctic Alaska W. Craddock et al. https://doi.org/10.2113/lithosphere_2025_134
46. Machine learning-based tsunami inundation prediction derived from offshore observations I. Mulia et al. https://doi.org/10.1038/s41467-022-33253-5
47. 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
48. A Globally Applicable Method for NDVI Estimation from Sentinel-1 SAR Backscatter Using a Deep Neural Network and the SEN12TP Dataset T. Roßberg & M. Schmitt https://doi.org/10.1007/s41064-023-00238-y
49. 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
50. Malaria risk assessment in Indonesia: a machine and deep learning framework A. Sakti et al. https://doi.org/10.1016/j.jag.2025.104793
51. 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
52. Climate change impacts on flood dynamics and seasonal flow variability in central Nepal: the Kaligandaki River Basin case K. Maharjan et al. https://doi.org/10.1007/s00704-025-05378-2
53. Multi-technique SAR coseismic deformation retrieval and fault modeling of the 2025 Mw 7.7 Myanmar earthquake V. Ruocco et al. https://doi.org/10.1186/s40645-026-00804-z
54. Generation and Assessment of Digital Elevation Models by Combining Sentinel-1A and Sentinel-1B Data in Mountain Glacier Area L. Yan et al. https://doi.org/10.1109/JSTARS.2024.3489576
55. Towards more consistent volcano morphometry datasets: Assessing boundary delineation and DEM impact on geometric and drainage parameters R. van Wees et al. https://doi.org/10.1016/j.geomorph.2024.109381
56. Digital Elevation Model Development Of The Volga And Don River’s Delta And Application In Hydrological Modeling N. Yaitskaya & I. Sheverdyaev https://doi.org/10.24057/2071-9388-2022-035
57. Habitat quality on the edge of anthropogenic pressures: Predicting the impact of land use changes in the Brazilian Upper Paraguay river Basin M. Broquet et al. https://doi.org/10.1016/j.jclepro.2024.142546
58. Shaping the Global High-Resolution TanDEM-X Digital Elevation Model M. Huber et al. https://doi.org/10.1109/JSTARS.2021.3095178
59. Asymmetric Interseismic Strain across the Western Altyn Tagh Fault from InSAR Y. Liu et al. https://doi.org/10.3390/rs14092112
60. Local prediction of temperate forest structure in Eastern North America using LiDAR, radar, and optical data C. Wei et al. https://doi.org/10.1088/2515-7620/ae718d
61. Spatial integration framework of solar, wind, and hydropower energy potential in Southeast Asia A. Sakti et al. https://doi.org/10.1038/s41598-022-25570-y
62. VERIFICATION THE ACCURACY OF DISPLACEMENT AT CORNER REFLECTOR AND SLOPE DISPLACEMENT MONITORING BY PSInSAR ANALYSIS USING Sentinel-1 SAR DATA H. ABO et al. https://doi.org/10.2208/jscejj.24-00183
63. A 2025 High-Resolution Glacier Inventory of the Greater Caucasus Reveals Accelerated Area Loss L. Tielidze et al. https://doi.org/10.3390/rs18091441
64. Evaluation of Open Geotechnical Knowledge in Urban Environments for 3D Modelling of the City of Seville (Spain) C. Soriano-Cuesta et al. https://doi.org/10.3390/rs16010141
65. Reconstruction of the volcanic history of Grande Comore and volcano-tectonic implications for the Comoros Archipelago S. Rougeau et al. https://doi.org/10.5802/crgeos.292
66. A deep learning method for building height estimation using high-resolution multi-view imagery over urban areas: A case study of 42 Chinese cities Y. Cao & X. Huang https://doi.org/10.1016/j.rse.2021.112590
67. Delineation of Intermittent Rivers and Ephemeral Streams Using a Hybrid Method N. Wang et al. https://doi.org/10.3390/rs16132489
68. Surface displacement induced by seasonal ground thaw, measured by synthetic aperture radar in the Daisetsu Mountains, Japan T. ABE et al. https://doi.org/10.5331/seppyo.84.1_13
69. 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
70. Inland Water Body Mapping Using Multitemporal Sentinel-1 SAR Data D. Marzi & P. Gamba https://doi.org/10.1109/JSTARS.2021.3127748
71. Grazing control and revegetation increases bird biodiversity at farm dams D. Smith et al. https://doi.org/10.1016/j.biocon.2025.111310
72. Low-Cost Monitoring of Spatiotemporal Changes in Forest Cover: Implications for Conservation in a Case in Quindío (Colombia) M. Quintero-Gallego et al. https://doi.org/10.1007/s00267-026-02491-4
73. Spatio-Temporal Analysis of Valley Wind Systems in the Complex Mountain Topography of the Rolwaling Himal, Nepal H. Jentsch & J. Weidinger https://doi.org/10.3390/atmos13071138
74. Precipitation-induced landslide risk escalation in China’s urbanization with high-resolution soil moisture and multi-source precipitation product K. He et al. https://doi.org/10.1016/j.jhydrol.2024.131536
75. Open-pit mining activity and stability area mapping in the Pyhäsalmi Mine using a time series of Sentinel-1 images O. Kavats et al. https://doi.org/10.1144/gslspecpub2023-216
76. 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
77. Estimating urban spatial structure based on remote sensing data M. Kii et al. https://doi.org/10.1038/s41598-023-36082-8
78. High-Precision River Network Mapping Using River Probability Learning and Adaptive Stream Burning Y. Zang et al. https://doi.org/10.3390/rs18020362
79. Comparison of digital elevation models through the analysis of geomorphic surface remnants in the Desatoya Mountains, Nevada B. Dobre et al. https://doi.org/10.1111/tgis.12819
80. The response of glaciers and glacial lakes to climate change in the Southeastern Tibetan Plateau over the past three decades X. Dou et al. https://doi.org/10.1002/ldr.4870
81. Windthrow characteristics and their regional association with rainfall, soil, and surface elevation in the Amazon R. Negron-Juarez et al. https://doi.org/10.1088/1748-9326/acaf10
82. Ground subsidence and polygon development due to thermokarst in the Lena-Aldan interfluve, eastern Siberia, revealed by satellite remote sensing data T. Abe & Y. Iijima https://doi.org/10.1186/s40645-024-00610-5
83. Comparison of 1D, coupled 1D–2D, and 2D shallow water numerical modeling for dam-break flow analysis of Way-Ela dam, Indonesia M. Lim et al. https://doi.org/10.15292/acta.hydro.2024.02