Paper ID: 2306.06269

DeepLCZChange: A Remote Sensing Deep Learning Model Architecture for Urban Climate Resilience

Wenlu Sun, Yao Sun, Chenying Liu, Conrad M Albrecht

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.

Submitted: Jun 9, 2023