Seamless Reconstruction of AMSR-E Land Surface Temperature Swath Gaps for China’s Landmass-Reference-Cited by-同舟云学术

Seamless Reconstruction of AMSR-E Land Surface Temperature Swath Gaps for China’s Landmass

Published:2023 Issue: Volume:61 Page:1-15
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Huang Xiaohan¹,Li Chan¹,Yang Tian¹,Cao Biao²^ORCID,Cheng Jie³^ORCID,Xie Guochen⁴,Wu Penghai¹^ORCID

Affiliation:

1. Anhui Province Key Laboratory of Wetland Ecosystem Protection and Restoration, Anhui University, Hefei, China

2. State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China

3. State Key Laboratory of Remote Sensing Science, Beijing Normal University, Beijing, China

4. Anhui Province Key Laboratory of Wetland Ecosystem Protection and Restoration and the Information Materials and Intelligent Sensing Laboratory of Anhui Province, Anhui University, Hefei, China

Funder

National Natural Science Foundation of China

Open Fund of State Key Laboratory of Remote Sensing Science

Anhui Provincial Natural Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/10006360/10330069.pdf?arnumber=10330069

Reference47 articles.

1. Balancing prediction accuracy and generalization ability: A hybrid framework for modelling the annual dynamics of satellite-derived land surface temperatures

2. Deep learning in environmental remote sensing: Achievements and challenges

3. A Review of Reconstructing Remotely Sensed Land Surface Temperature under Cloudy Conditions

4. Reconstructing Geostationary Satellite Land Surface Temperature Imagery Based on a Multiscale Feature Connected Convolutional Neural Network

5. Spatio‐temporal interpolation of daily temperatures for global land areas at 1 km resolution

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