Spatiotemporal Analysis of Land Use and Land Cover Types and Their Impacts on Land Surface Temperature of Abia State, Nigeria

Rapid urbanization results to an increase in impervious layers which therefore increases the land surface temperature massively. This study is aimed at performed a spatiotemporal analysis of land surface temperature and its impact on land use/land cover types in Abia State of Nigeria. Lansat 8 OLI imageries of 2013, 2018 and 2023 were used for data analysis to retrieve the land surface temperature (LST) and the land use/ land cover (LULC) types. The methodology adopted by study for LST retrieval was the Single Channel Algorithm (SCA) and for classifying the LULC, the Supervised Classification using Maximum Likelihood Classifier (MLC) algorithm was used. The ArcGIS 10.8 was used to classify LULC types and estimate the LST. The findings indicate that LULC significantly affects LST values due to the biophysical characteristics of the land surfaces. Vegetation and water bodies lower surface temperatures, suggesting that integrating vegetation within urban areas at regular intervals can help maintain a cooler urban thermal environment. Moderate LST differences were observed between bare lands and vegetation, as well as between barren land and built-up areas, while the smallest LST differences were noted between water bodies and vegetation. The study also found that the highest LSTs are typically observed in cities such as Aba and Umuahia within the state. The study will have a positive health impact in the study area and help policies makers and relevant agencies in making an information decision and policies based on the findings from the study.