Investigating the Impact of Land Use/Land Cover Change on Present and Future Land Surface Temperature (LST) of Chittagong, Bangladesh

Urbanization has a significant impact on microclimate, which eventually contributes to local and regional climate change. Unplanned urbanization is widespread in developing countries like Bangladesh. Chittagong, the second largest city, is experiencing rapid urban expansion. Since urban growth introduces a number of environmental issues, including changes in land surface temperature (LST), it is important to investigate the association between urbanization pattern and LST in Chittagong. In this work, we have analyzed the influence of land use and land cover (LULC) of Chittagong Metropolitan Area (CMA) on LST using multi-date Landsat data of 1990, 2005 and 2020. We have used an artificial neural network (ANN) algorithm for LULC classification and an image-based method to compute LST from Landsat data. The results revealed that built-up areas, waterbodies and agricultural lands have increased by 4.57%, 1.04% and 0.94%, respectively, whereas vegetation has decreased by 0.34% and bare lands by 0.87% between 1990 and 2020. As expected, built-up area experienced maximum temperatures followed by bare lands. Waterbodies, on the other hand, exhibited minimum temperature in all years considered, followed by vegetation. Correlations between biophysical variables, Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-up Index (NDBI), Modified Normalized Difference Water Index (MNDWI) and Bare Soil Index (BSI), and LST indicated that NDVI and MNDWI were in a strong negative relationship, whereas NDBI and BSI have showed positive correlation with LST. Lastly, LST is predicted based on the relationship between LST and biophysical variables with an ANN algorithm, which demonstrated that the temperature may reach to a critical state by 2050, if the present trend of urban growth continues.

Automated summary

Urbanization has a significant impact on microclimate and investigating the relationship between urbanization pattern and land surface temperature (LST) is crucial. The study in Chittagong reveals that built-up areas have the highest temperature while waterbodies have the lowest. Normalized Difference Vegetation Index (NDVI) and Modified Normalized Difference Water Index (MNDWI) are negatively correlated with temperature, whereas Normalized Difference Built-up Index (NDBI) and Bare Soil Index (BSI) show positive correlation. The predicted LST indicates that temperature may reach a critical state by 2050 if the current trend of urban growth continues.