DeepLCZChange: A REMOTE SENSING DEEP LEARNING MODEL ARCHITECTURE FOR URBAN CLIMATE RESILIENCECRediT
Author:
Affiliation:
1. Technical University of Munich,Data Science in Earth Observation
2. German Aerospace Center,Remote Sensing Technology Institute
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10281394/10281399/10281573.pdf?arnumber=10281573
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1. Urban forests for carbon sequestration and heat island mitigation;klein;AI4Good Fragile Earth workshop at ACM Knowledge Discovery and Data Mining (KDD) conference,2022
2. PyTorch-VAE;subramanian,2020
3. An Operational Land Surface Temperature Product for Landsat Thermal Data: Methodology and Validation
4. City of New York: Metadata LiDAR Summary,2017
5. Land use and land cover change impacts on the regional climate of non-Amazonian South America: A review
Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. AutoLCZ: Towards Automatized Local Climate Zone Mapping from Rule-Based Remote Sensing;IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium;2024-07-07
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