This paper evaluates the impact of land-use and land-cover (LULC) changes on land surface temperature (LST) in the Kuala Lumpur metropolitan city using multi-spectral and multi-temporal satellite data. The spectral radiance model was used to extract the LST from Landsat 8 OLI and Landsat 5 TM. The analysis on LULC changes revealed a phenomenal increase in the urban (high built-up area) areas and a decrease in the forest land area. The distribution of average changes in LST shows that urban (high built-up area) areas recorded the highest increase in temperature followed by urban (low built-up area) areas, grass land area, forest land area and waterbodies. The LST and normalised difference vegetation index (NDVI) were computed based on changes in LULC which indicates that a strong correlation value was observed between LST and NDVI for urban (high and low built-up areas) areas, grass land area and forest land area. This study demonstrated that an increase in non-evaporating surfaces and a decrease in the vegetation area have increased the surface temperature and modified the temperature of the study area. Remote-sensing techniques were found to be efficient, especially in reducing the time for analysis of urban expansion, and are useful tools to evaluate the impact of urbanisation on LST.

Malacca River water quality is affected due to rapid urbanization development. The present study applied LULC changes towards water quality detection in Malacca River. The method uses LULC, PCA, CCA, HCA, NHCA, and ANOVA. PCA confirmed DS, EC, salinity, turbidity, TSS, DO, BOD, COD, As, Hg, Zn, Fe,E. coli, and total coliform. CCA confirmed 14 variables into two variates; first variate involves residential and industrial activities; and second variate involves agriculture, sewage treatment plant, and animal husbandry. HCA and NHCA emphasize that cluster 1 occurs in urban area with Hg, Fe, total coliform, and DO pollution; cluster 3 occurs in suburban area with salinity, EC, and DS; and cluster 2 occurs in rural area with salinity and EC. ANOVA between LULC and water quality data indicates that built-up area significantly polluted the water quality throughE. coli, total coliform, EC, BOD, COD, TSS, Hg, Zn, and Fe, while agriculture activities cause EC, TSS, salinity,E. coli, total coliform, arsenic, and iron pollution; and open space causes contamination of turbidity, salinity, EC, and TSS. Research finding provided useful information in identifying pollution sources and understanding LULC with river water quality as references to policy maker for proper management of Land Use area.