Authors : Vincent Hategekimana; Richard Mind J. E.; Aboubakar Gasirabo; Didier Ntwali

Volume/Issue : Volume 11 - 2026, Issue 10 - October

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Google Scholar : https://tinyurl.com/3m4n3mvp

DOI : https://doi.org/10.38124/ijisrt/26Oct696

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

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Abstract : This study analyzed the impact of land use and land cover (LULC) change on vegetation cover loss in Muhoza Sector, Musanze District, Rwanda, between 2015 and 2025. A quantitative geospatial research design was adopted using multi-temporal Landsat and Sentinel-2 satellite imagery, field-based GPS validation, Geographic Information Systems, and Normalized Difference Vegetation Index (NDVI) analysis. Six land-cover classes—forestland, grassland, cropland, urbanized land, wetland, and water bodies—were mapped using supervised classification and post-classification change detection.

Keywords : Land Use and Land Cover; Vegetation Cover Loss; NDVI; Remote Sensing; GIS; Urbanization; Muhoza Sector; Musanze District; Rwanda.

References :

1. Akinyemi, F. O., Nolte, C., Glover, E. K., & Maitre, D. C. (2013). Land use change and vegetation degradation in Nigeria. Journal of Environmental Management, 117, 119–130.
2. Belgiu, M., & Drăguţ, L. (2016). Random forest in remote sensing: A review of applications and future directions. ISPRS Journal of Photogrammetry and Remote Sensing, 114, 24–31. https://doi.org/10.1016/j.isprsjprs.2016.01.011
3. Bewket, W., & Teferi, E. (2009). Assessment of soil erosion hazard and prioritization for treatment at the watershed level: Case study in the Chemoga watershed, Blue Nile basin, Ethiopia. Land Degradation & Development, 20(6), 609–622. https://doi.org/10.1002/ldr.944
4. Borrelli, P., et al. (2017). An assessment of the global impact of 21st century land use change on soil erosion. Nature Communications, 8, 2013. https://doi.org/10.1038/s41467-017-02142-7
5. Food and Agriculture Organization of the United Nations. (2020). Global Forest Resources Assessment 2020: Main report. FAO.
6. Foody, G. M. (2002). Status of land cover classification accuracy assessment. Remote Sensing of Environment, 80(1), 185–201. https://doi.org/10.1016/S0034-4257(01)00295-4
7. Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., & Moore, R. (2017). Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sensing of Environment, 202, 18–27. https://doi.org/10.1016/j.rse.2017.06.031
8. Ichangi, D. W., Mugo, R., Wahome, A., & Ndegwa, G. (2021). Monitoring land use and land cover changes in rapidly urbanizing Nakuru, Kenya using Landsat imagery, 2000–2019. Remote Sensing Applications: Society and Environment, 23, 100558. https://doi.org/10.1016/j.rsase.2021.100558
9. Intergovernmental Panel on Climate Change. (2019). Climate change and land. IPCC.
10. Jensen, J. R. (2015). Introductory digital image processing: A remote sensing perspective (4th ed.). Pearson.
11. Lambin, E. F., & Geist, H. J. (2006). Land-use and land-cover change: Local processes and global impacts. Springer.
12. Lambin, E. F., & Meyfroidt, P. (2011). Global land use change, economic globalization, and the looming land scarcity. Proceedings of the National Academy of Sciences, 108(9), 3465–3472. https://doi.org/10.1073/pnas.1100480108
13. Rawat, J. S., & Kumar, M. (2015). Monitoring land use/cover change using remote sensing and GIS techniques: A case study of Hawalbagh block, district Almora, Uttarakhand, India. The Egyptian Journal of Remote Sensing and Space Sciences, 18(1), 77–84.
14. Rwanda Environment Management Authority. (2020). State of environment and outlook report. REMA.
15. Rwanda Land Management and Use Authority. (2020). National Land Use and Development Master Plan. Government of Rwanda.
16. Seto, K. C., Güneralp, B., & Hutyra, L. R. (2012). Global forecasts of urban expansion to 2030 and direct impacts on biodiversity and carbon pools. Proceedings of the National Academy of Sciences, 109(40), 16083–16088.
17. Tucker, C. J. (1979). Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment, 8(2), 127–150.
18. UN-Habitat. (2022). World Cities Report 2022: Envisaging the future of cities. United Nations Human Settlements Programme.