Land use and land cover change detection using Landsat 8 imagery and GIS techniques: a case study of Belkheir municipality, Guelma province, Algeria
DOI:
https://doi.org/10.14311/AP.2026.66.0317Keywords:
change detection, land use, land cover, remote sensing, Landsat 8, geographic information system, support vector machine, post-classification comparisonAbstract
The Belkheir municipality, located in Guelma province, Algeria, has recently undergone significant Land Use and Land Cover (LULC) changes. This study aims to detect and analyse these changes between 2016 and 2021 using Landsat 8 satellite imagery, GIS techniques, and a postclassification method. Four supervised classifiers (SVM, ANN, MLC, and MDC) were compared to produce LULC maps with seven classes. The SVM achieved high overall accuracies of 96.24 % in 2016 and 96.31 % in 2021. It was, therefore, selected for the change detection analysis. Significant changes in LULC classes were identified based on the results of the analysis. The dense forest cover has increased by 82.70 %, urban area by 34.62 %, barren land by 9.94 %, and agricultural land by 0.43 %. Grassland, sparse forest, and water bodies, conversely, have decreased by 18.85 %, 13.71 %, and 5.29 %, respectively. Such results have a high relevance for the planning and sustainable resource management of the Belkheir municipality.
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Copyright (c) 2026 Brahmia Souhaira, Doghmane Hakim, Bencheriet Chemss Ennahar, Bourouba Hocine, Messaoudi Kamel
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