A global regression method for thermal sharpening of urban land surface temperatures from MODIS and Landsat

• المؤلفون الرئيسيون: WANG, James. W., CHOW, Winston T. L., WANG, Yi-Chen
• التنسيق: text
• اللغة: English
• منشور في: Institutional Knowledge at Singapore Management University 2020
• الموضوعات: Impervious surface; Normalized differences; Regression method; Spatial resolution; Statistical scheme; Thermal infrared sensors; Urban applications; Urban land surface temperature; Environmental Sciences; Political Science; Urban Studies and Planning
• الوصول للمادة أونلاين: https://ink.library.smu.edu.sg/soss_research/3048; https://ink.library.smu.edu.sg/context/soss_research/article/4305/viewcontent/urban1.pdf

Land surface temperatures (LST) in urban landscapes are typically more heterogeneous than can be monitored by the spatial resolution of satellite-based thermal infrared sensors. Thermal sharpening (TS) methods permit the disaggregation of LST based on finer-grained multispectral information, but the...