Analyzing the urban heat island using time series land surface temperature (LST) data
2017 IEEE International Geoscience and Remote Sensing Symposium …, 2017•ieeexplore.ieee.org
This study aims to carefully analyze the urban heat island (UHI). Using the LST images from
the MODIS and LANDSAT 8, high spatial-temporal resolution LST from May to November in
2013 were generated with the Spatial and Temporal Adaptive Reflectance Fusion Model
(STARFM). Furthermore, the relationships between urban LST and four Landscape Metrics
were analyzed based on two GaoFen imageries. UHI effects were found accentuated in
Beijing from May to October. Moreover, the UHI intensities were more obvious in the July …
the MODIS and LANDSAT 8, high spatial-temporal resolution LST from May to November in
2013 were generated with the Spatial and Temporal Adaptive Reflectance Fusion Model
(STARFM). Furthermore, the relationships between urban LST and four Landscape Metrics
were analyzed based on two GaoFen imageries. UHI effects were found accentuated in
Beijing from May to October. Moreover, the UHI intensities were more obvious in the July …
This study aims to carefully analyze the urban heat island (UHI). Using the LST images from the MODIS and LANDSAT 8, high spatial-temporal resolution LST from May to November in 2013 were generated with the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM). Furthermore, the relationships between urban LST and four Landscape Metrics were analyzed based on two GaoFen imageries. UHI effects were found accentuated in Beijing from May to October. Moreover, the UHI intensities were more obvious in the July and August. Study demonstrated that relatively weak linear relationships existed between urban impervious surface landscape metrics and remotely sensing LSTs. Contrarily, urban green landscape metrics exhibited well correlations with the LSTs.
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