A Terrain Feature Guided-Diffusion Model for Void Filling of Digital Elevation Models-Reference-Cited by-同舟云学术

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A Terrain Feature Guided-Diffusion Model for Void Filling of Digital Elevation Models

Published:2024-07-07 Issue: Volume:33 Page:7007-7010
ISSN:
Container-title:IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium
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Author:

Yuan Yingying¹,Zhao Ji¹,Shao Changliang²,Dong Yuting³

Affiliation:

1. China University of Geosciences,School of Computer Science,Wuhan,China

2. China Meteorological Administration Meteorological Observation Center,Beijing,China

3. China University of Geosciences,School of Geography and Information Engineering,Wuhan,China

Funder

Ministry of Education

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10640349/10640352/10642792.pdf?arnumber=10642792

Reference15 articles.

1. A practical method for reducing terrain effect on land surface temperature using random forest regression

2. Automatic calving front extraction from digital elevation model-derived data

3. EarthEnv-DEM90: A nearly-global, void-free, multi-scale smoothed, 90m digital elevation model from fused ASTER and SRTM data

4. A shadow constrained conditional generative adversarial net for SRTM data restoration

5. Gapless-REMA100: A gapless 100-m reference elevation model of Antarctica with voids filled by multi-source DEMs

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