Modeling on microclimatic variation of land surface temperature and vegetation cover at Rangpur City in Bangladesh

Land surface temperature (LST) and vegetation cover are essential in all environmental aspects. Understanding the spatiotemporal variation of LST and vegetation abundance is beneficial to investigate the microclimate studies of an urban area. In urban areas, vegetation is an essential element in flourishing microclimate and outdoor thermal consolation. Due to unplanned rapid urbanization and lack of proper management, the vegetation cover in Rangpur City Corporation (RpCC) are decline day by day. The vegetation covers are declined in fast-growing city like RpCC and it is leading to more sensible heat than the normal heat flux. This study focused on the relationship between LST and vegetation cover of the RpCC area of different periods and how they affect the regional microclimate. Through this research has also been evaluate the impacts of reducing the vegetation cover on the microclimate conditions in the study area. To fulfil the aim of the study, satellite imageries of the year 2021 (Operational Landsat), 2017 (Operational Landsat), 2009 and (Thematic mapper), 2000 (Thematic mapper) were processed using ArcGIS 10.5 software. From the satellite imageries, normalized difference vegetation index (NDVI) and LST have been estimated to show the relation between LST and vegetation in RpCC and ANN (Artificial neural network) model was developed to predict the value of LST and NDVI after 7 years, particularly to the year 2028 based on datasets from 2000 to 2021. The linear regression analysis provides the inverse relationship between LST and vegetation in the study area that explains that due to urban growth materials, the amount of vegetation has been decreased, leading to increased surface temperature during 2000-2021. The developed ANN model using obtained data sets of LST and NDVI of RpCC predicts that the value of LST and NDVI till the year 2028 will not be changed so much compared to the previous 21 years (2000-2021). The highest LST may occur 32.71 degrees c in the year 2028 whereas the predicted highest NDVI value has been observed 0.57 which is not so sufficient in controlling LST in the city. However, more amount forestation is needed to minimize the effects of LST to make the city comfortable for the inhabitants including flora and fauna and others process as well like as cultivation, fishing, farming, etc.

Automated summary

Land surface temperature (LST) and vegetation cover are crucial for studying urban microclimates. Due to rapid urbanization and poor management, vegetation cover in Rangpur City Corporation (RpCC) is decreasing, resulting in higher sensible heat. Using satellite imagery and modeling, this study reveals an inverse relationship between LST and vegetation cover in RpCC, and predicts minimal changes in LST and vegetation cover till 2028. However, more forestation is needed to improve urban comfort and protect ecosystems.