Evaluation of urban heat environment using multi-algorithm and multi-scale images

Abstract

Remote sensing of Urban Heat Islands (UHIs) usually used Land Use and Land Cover (LULC), Normalized Difference Vegetation Index (NDVI), normalized difference built-up index (NDBI) and Vegetation-Impervious Surface Area (ISA)-Soil (V-I-S) model separately in the past. The purpose of this paper is to examine the relationship between surface thermal patterns with land cover types, NDVI and VIS model as a whole. LST was derived using three different algorithms from remotely sensed images at two different scales and LUCC map was obtained by SVM classification method. The results demonstrate that LST retrieval from Landsat ETM+ image by improved MWA algorithm is more suitable for analyzing relationship between urban structures with urban heat islands in Xuzhou. By analyzing the relationship between LST and land cover type, it also indicated that SVM classified result and VIS have a good uniformity. The analytical correlation between UHIs and different indices indicated that correlation between indices with UHIs change slightly among the different fraction in different city structures. The special distribution of heat island shows that building area, bare land, semi-bare land and land under development are warmer than other surface type, and higher temperature in the UHIs was related to certain land cover types and distributed with a scattered pattern. By making an integration analysis of NDVI, NDBI and LST, it was confirmed that strong positive correlations between LST and NDBI existed, as with negative correlations between LST and NDVI.