Uncertainty Analysis of Digital Elevation Models by Spatial Inference From Stable Terrain-Reference-Cited by-同舟云学术

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Uncertainty Analysis of Digital Elevation Models by Spatial Inference From Stable Terrain

Published:2022 Issue: Volume:15 Page:6456-6472
ISSN:1939-1404
Container-title:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
language:
Short-container-title:IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Author:

Hugonnet Romain¹^ORCID,Brun Fanny²^ORCID,Berthier Etienne¹^ORCID,Dehecq Amaury³^ORCID,Mannerfelt Erik Schytt⁴^ORCID,Eckert Nicolas⁵^ORCID,Farinotti Daniel⁴^ORCID

Affiliation:

1. LEGOS, Université de Toulouse, CNES, CNRS, IRD, UPS, Toulouse, France

2. IGE, Université Grenoble Alpes, CNRS, IRD, Grenoble INP, Grenoble, France

3. Laboratory of Hydraulics, Hydrology and Glaciology (VAW), ETH Zürich, Zürich, Switzerland

4. Laboratory of Hydraulics, Hydrology and Glaciology (VAW), ETH Zürich, Switzerland

5. Université Grenoble Alpes, INRAE, UR ETNA, Grenoble, France

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Atmospheric Science,Computers in Earth Sciences

Link

http://xplorestaging.ieee.org/ielx7/4609443/9656571/09815885.pdf?arnumber=9815885

Reference157 articles.

1. Snow depth mapping from stereo satellite imagery in mountainous terrain: evaluation using airborne laser-scanning data

2. Mapping snow depth in open alpine terrain from stereo satellite imagery

3. Active Machine Learning Approach for Crater Detection From Planetary Imagery and Digital Elevation Models

4. A new lunar digital elevation model from the Lunar Orbiter Laser Altimeter and SELENE Terrain Camera

5. Global LiDAR land elevation data reveal greatest sea-level rise vulnerability in the tropics

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