Spatial analysis of LST in relation to surface moisture and NDBI using landsat imagery in Cheongju city

Abstract

The survey of Landsat satellite image is effective in the continuous monitoring of a vast area during long periods of time. It is increasingly being used to derive and analyze spatial distribution data of both the normalized difference built-up index (NDBI) and land surface temperature (LST) that are major indicators for an analysis of urban environment. Especially, LST is one of the key parameters in physics and meteorology of land surface processes on regional and global scales. Satellite remote sensing has been expected to be effective for obtaining thermal information of the earth's surface with a high resolution. Meanwhile as more than 50% of the populations are situated in cities, urbanization has become an important contributor to global warming due to remarkable urban heat island (UHI) effect. UHI effect is meteorological phenomenon that the air temperature increases in urban area than the suburbs because grows with the progress of urbanization. UHI effect has been affected to the regional climate and environment. This study aims to examine relationships of LST with NDBI, and with surface moisture using Landsat TM and ETM+ imagery obtained for the city of Chungbuk in Korea; and to quantitatively compare the patterns and intensity of UHI with land-use/land-cover (LULC) types. Landsat TM (thematic mapper) and ETM+ (enhanced thematic mapper plus) imagery, respectively acquired in 1991, 1994, 2000 and 2006, were utilized to assess urban area thermal characteristics in Cheongju, the city of Chungbuk province in Korea. In order to accurately estimate urban surface moisture, tasseled cap model (TCM) was utilized to generate the proportion of surface moisture. The results indicate urbanization is an accurate indicator of UHI effects with strong linear relationships between LST and NDBI. This implies that surface moisture can be used to analyze temperature quantitatively for UHI studies validated by NDBI. And this suggests that surface moisture, combined with LST, and NDBI, can quantitatively describe the spatial distribution and temporal variation of urban thermal patterns and associated LULC types.