Urban land surface temperature prediction using parallel STL-Bi-LSTM neural network-Reference-Cited by-同舟云学术

Urban land surface temperature prediction using parallel STL-Bi-LSTM neural network

Published:2022-09-09 Issue:03 Volume:16 Page:
ISSN:1931-3195
Container-title:Journal of Applied Remote Sensing
language:
Short-container-title:J. Appl. Rem. Sens.

Author:

Huo Xing¹,Cui Guangpeng¹,Ma Lingling²,Tang Bohui³,Tang Ronglin⁴,Shao Kun¹,Wang Xinhong²

Affiliation:

1. Hefei University of Technology, Hefei, China

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

3. Kunming University of Science and Technology, Kunming, China

4. Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences, State Key Laboratory of Resources and Environment Information System, Beijing, China

Publisher

SPIE-Intl Soc Optical Eng

Subject

General Earth and Planetary Sciences

Reference31 articles.

1. Temperature increase reduces global yields of major crops in four independent estimates

2. Simulating the impact of extreme heat and frost events on wheat crop production: A review

3. Causal analysis of the temperature impact on deep-sea biodiversity

4. Increased human and economic losses from river flooding with anthropogenic warming

5. Urban heat island impacts on building energy consumption: A review of approaches and findings

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