DeepLCZChange: A REMOTE SENSING DEEP LEARNING MODEL ARCHITECTURE FOR URBAN CLIMATE RESILIENCECRediT
IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium(2023)
摘要
Urban land use structures impact local climate conditions of metropolitan areas. To shed light on the mechanism of local climate wrt. urban land use, we present a novel, data-driven deep learning architecture and pipeline, DeepLCZChange, to correlate airborne LiDAR data statistics with the Landsat 8 satellite's surface temperature product. A proof-of-concept numerical experiment utilizes corresponding remote sensing data for the city of New York to verify the cooling effect of urban forests.
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关键词
urban planning,local climate zones,climate resilience,LiDAR,Landsat 8,deep neural network architecture,explainable artificial intelligence
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