QUANTITATIVE REMOTE SENSING ANALYSIS OF THERMAL ENVIRONMENT CHANGES IN THE MAIN URBAN AREA OF Guilin BASED ON GEE

Abstract

The dynamic change of urban thermal environment caused by the change of land use type has become one of the important problems of urban ecological environment protection. In Guilin city as research area, based on the Google Earth Engine (GEE), the random forest algorithm was used to classify the land use classification of Landsat remote sensing images in 2010, 2014 and 2018, and the mono-window algorithm was used to calculate the surface temperature. The surface vegetation was solved according to the NDVI pixel binary model. Coverage, and finally dynamic statistics and comparative analysis of land use, vegetation cover and surface temperature. The main results as follows. (1) From 2010 to 2018, the average temperature in the main urban area of Guilin is on the rise (increased by 1.29 °C), and the temperature zones in each class are converted from low temperature zone, lower temperature zone and medium temperature zone to higher temperature zone and high temperature zone. (2) Lower temperature zone and the low temperature zone is mainly distributed in vegetation and water body coverage areas, while the medium temperature zone, higher temperature zone and the high temperature zone are mainly distributed in construction land and unused land cover area. (3) High vegetation cover area in 2014–2018 (reduced by 31.34%) The main reason for the sharp decline is the substantial increase in the area of construction land (expansion 30.19%). (4) GEE-based random forest algorithm Land use classification had higher classification accuracy (more than 80% in all three periods). The results can provide scientific basis for improving urban thermal environment and scientific reference for the development strategy of Guilin city.