Version 1
: Received: 18 April 2024 / Approved: 19 April 2024 / Online: 19 April 2024 (04:59:10 CEST)
How to cite:
Laipelt, L.; Comini de Andrade, B.; Collischonn, W.; Amorim, A.; Paiva, R.C.D.D.; Ruhoff, A. Anadem: A Digital Terrain Model for South America. Preprints2024, 2024041305. https://doi.org/10.20944/preprints202404.1305.v1
Laipelt, L.; Comini de Andrade, B.; Collischonn, W.; Amorim, A.; Paiva, R.C.D.D.; Ruhoff, A. Anadem: A Digital Terrain Model for South America. Preprints 2024, 2024041305. https://doi.org/10.20944/preprints202404.1305.v1
Laipelt, L.; Comini de Andrade, B.; Collischonn, W.; Amorim, A.; Paiva, R.C.D.D.; Ruhoff, A. Anadem: A Digital Terrain Model for South America. Preprints2024, 2024041305. https://doi.org/10.20944/preprints202404.1305.v1
APA Style
Laipelt, L., Comini de Andrade, B., Collischonn, W., Amorim, A., Paiva, R.C.D.D., & Ruhoff, A. (2024). Anadem: A Digital Terrain Model for South America. Preprints. https://doi.org/10.20944/preprints202404.1305.v1
Chicago/Turabian Style
Laipelt, L., Rodrigo Cauduro Dias de Paiva and Anderson Ruhoff. 2024 "Anadem: A Digital Terrain Model for South America" Preprints. https://doi.org/10.20944/preprints202404.1305.v1
Abstract
Digital elevation models (DEMs) have a wide range of applications and play a crucial role in many studies. Numerous public DEMs, frequently acquired using radar and optical satellite imagery, are currently available; however, DEM datasets tend to exhibit elevation values influenced by vegetation height and coverage, which can compromise the accuracy of models in representing terrain elevation. In this study, we developed a digital terrain model for South America using a novel methodology to remove vegetation bias in the Copernicus DEM GLO-30 (COPDEM) model using machine learning, Global Ecosystem Dynamics Investigation (GEDI) elevation data, and multispectral remote sensing products. Our results indicate considerable improvements compared to COPDEM in representing terrain elevation, reducing average errors (BIAS) from 9.6 m to 1.5 m. Furthermore, we evaluated our product (ANADEM) by comparison with other global DEMs, obtaining more accurate results for different conditions of vegetation fraction cover and land use. As a publicly available and open-source dataset, ANADEM will play a crucial role in advancing studies that demand accurate terrain elevation representations at large scales.
Keywords
LIDAR; Digital Elevation Model; Remote Sensing
Subject
Environmental and Earth Sciences, Remote Sensing
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
