Detecting land use/land cover changes and forest degradation: A case study of the lower Soummam valley, northern Algeria

Megdouda Smail, Zoubir Boubaker, Mohamed Sbabdji, Habib Mouaissa and Bimare Kombate
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Megdouda Smail: Conservation, Management and Improvement of Forest Ecosystems Laboratory, National Higher Agronomic School, El Harrach, Algeria
Zoubir Boubaker: Conservation, Management and Improvement of Forest Ecosystems Laboratory, National Higher Agronomic School, El Harrach, Algeria
Mohamed Sbabdji: National Institute of Forest Research (INRF), El Hammamet, Algeria
Habib Mouaissa: Agricultural Sciences Department, Faculty of Natural Sciences and Life, Ziane Achour University of Djelfa, Djelfa, Algeria
Bimare Kombate: Botany and Plant Ecology Laboratory, Department of Botany, Faculty of Sciences, University of Lomé, Lomé, Togo

Journal of Forest Science, 2024, vol. 70, issue 3, 122-134

Abstract: The environment is characterised by subtle and major mutations that cause changes in land use/land cover. Analysis of its dynamics and identification of vulnerable areas are critical to maintaining ecosystem services. The aim of this research is to quantify and qualify land cover dynamics over a 30-year period. It will also highlight forest degradation from a supervised classification of Landsat satellite imagery (L5 TM1987, L7 ETM+ 2000, and L8 OLI/TIRS 2019). The dynamics of land use/land cover were investigated by a maximum likelihood approach using geographic information system (GIS) and remote sensing (RS). Six major land use and land cover (LULC) types were mapped (build-up, agriculture, forest, clearing, matorral and olive cultivation). The classification reports made it possible to assess a reduction in forest cover (from 14 470.11 ha to 5 203.26 ha) and an increase in buildings (from 6 033.69 ha to 9 515.61 ha), and agricultural land (from 9 517.59 ha to 12 338.19 ha). The results were validated by a kappa coefficient of 0.93, 0.91, and 0.96, which showed that the model had successfully predicted LULC changes. We anticipate that the results will provide a basis for decision-making as well as a starting point for further in-depth studies in sustainable management and development of natural resources in the study region.

Keywords: change detection; deforestation; dynamics; geographic information system (GIS) remote sensing (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:caa:jnljfs:v:70:y:2024:i:3:id:86-2023-jfs

DOI: 10.17221/86/2023-JFS

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