Detection of Land Use/Land Cover Change and Land Surface Temperature in the Eastern Part of Batna City (North East Algeria) Using Remote Sensing Data and GIS.

The present paper aims to evaluate the accuracy of classifying Land Use /Land Cover (LULC) types and assesses the trends of their changes in the Eastern Part of Batna City (Northernf Algeria) using remote sensing and GIS. The accuracy of image Land Satellite (Land Sat ) was evaluated using the supervised classification technique, it's applied in multi spectral and multi temporal satellite data acquired in 2000,2010,2022 and assessed with GOOGLE EARTH PRO and IMAGERY Land Use and topographical map. The second part focused on extraction of LST in three phases and explored the relationship between two land cover indices (NDVI, NDBI) and LST.LU/LC detected, quantified, and statically analyzed, the result indicate that from 2000-2022 the built-up areas increased by 0.34% (6.638km(2)), the forest area increased by 1.8% (35.144km(2)), agricultural land cover increased by 1.12% (21.867km(2)), while bare land decreased by 2.17% (42.368km(2)). The conversions of areas from bare land to urban land represent the most significant Land Cover changes. The accuracy assessment and correlation coefficient R-2 analysis in this study affirms the previous research findings. Even a single land use unit like built-up area, bare land and vegetation also create differences in LST (R-2 of NDBI vs. LST ranges from 0.64 to 0.79; NDVI vs. LST ranges from-0.73 to-0.82). With the change of the LU/LC style, its imprint is reflected on the LST. Therefore, immediate reflection on new urbanism must be adopted, initiated and implemented to stop the warming that contributes to climate change in the study area.