Monitoring urban growth and landscape fragmentation in Kaduna, Nigeria, using remote sensing approach
2024
Kabir Musa | Muhammad Lawal Abubakar
This study assessed urban growth in Kaduna using remote sensing indices, landscape metrics, and Landsat images (2003, 2013, and 2023). Land use/land cover was carried out using the decision tree algorithm, while the transition matrix was computed using ArcGIS 10.8. Landscape fragmentation was assessed using Fragstat 4.3. The results revealed that between 2003 and 2023, bare land, built-up areas, and water bodies increased by 596 km2, 121.04 km2, and 0.22 km2, respectively, while cultivated land and tree cover decreased by 525.54 km2 and 191.91 km2, respectively. For the rate of change, bare lands, built-up areas, and water bodies increased by 29.81 km2, 6.05 km2, and 0.01 km2 annually, respectively, while cultivated lands and water bodies decreased by 26.28 km2 and 9.60 km2, respectively. For the land-use transition, 112.71 km2 of the built-up areas remained persistent. Cultivated lands, tree cover, and water bodies transitioned to built-up areas, losing 85.43 km2, 13.91 km2, and 0.91 km2, respectively. Landscape fragmentation analysis revealed that the number of patches increased from 405 in 2003 to 614 in 2023. Patch density, largest patch index, total edge, edge density, area-weighted mean shape index, and fractal dimension index decreased between 2003 and 2013 but increased between 2013 and 2023, indicating urban sprawl. However, the area-weighted mean contiguity index consistently increased between 2003 and 2023. The study concluded that urbanization is the leading driver of landscape fragmentation. This study recommends that development should be controlled to reduce encroachment on agricultural lands and habitats, thereby reducing landscape fragmentation and land degradation.
Afficher plus [+] Moins [-]Mots clés AGROVOC
Informations bibliographiques
Cette notice bibliographique a été fournie par Directory of Open Access Journals
Découvrez la collection de ce fournisseur de données dans AGRIS