Spatio-Temporal Residential Land-Use Change in District Abbottabad by Using Machine Learning Model from 1992-2022 Pakistan
DOI:
https://doi.org/10.54938/ijemdss.2026.05.1.716Keywords:
Land Use Land Cover change (LULC), Geographic Information System (GIS), Remote Sensing (RS)Abstract
A city not only grows in population but also changes in spatial dimension. Land transformation is a natural phenomenon that can not be stopped but may be regulated. Land is one of the most important sources for human survival and other activities, including its ecosystem. All humans benefit from the available resources on land, which is called land use. The purpose of the study is to monitor land use and land cover in District Abbottabad, focusing on the major transformation in different types of land use changes from 1992 to 2022 by using Geographic Information Systems (GIS), Remote Sensing (RS) technologies, and data visualization performed by Phython Libraries in Machine learning. Supervised digital classification using a maximum likelihood classifier was applied to prepare a land use/land cover map. The land was classified into five categories: settlement, forest, water bodies, barren land, and vegetation cover. Resultant land cover land use overlay maps were generated in ArcMap to indicate the significant shift from Vegetation to Settlement. Analysis revealed that vegetation and forest areas have improved in the study area at a greater pace due to the billion Tsunami project, but settlement is increasing drastically and barren land is also reducing due to urbanization. Water bodies are also being adversely affected due to increasing settlement. The city is facing water stress and a shortage of drinking water. One of the main causes of Population growth is migration from rural and other catering area.
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