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Research Article Open access CC BY 4.0

Assessment of Vegetation Dynamics in a Semi-Arid Environment Using Fuzzy Logic and Geospatial Approach: Evidence from Ngala Local Government Area, Borno State, Northeastern Nigeria

Mustapha Shettima, Mariya Hasnat, Sania Rizvi, Habib Umar Badiya, Khalli Nasir Othman

International Journal of Environment and Climate Change · pp. 881–898 · Published 30 Dec 2025

10.9734/ijecc/2025/v15i125204

Abstract

Semi-arid areas, especially those in the conflict-prone areas like northeastern Nigeria, are remarkably susceptible to climatic variability as well as the anthropogenic disturbance, and the tracking of vegetation change is important to ecological resilience and sustainable resource management. In this research, fuzzy logic and geospatial methods was combined to determine the dynamics of the vegetation in Ngala Local Government Area, between 2009-2024, and five-year temporal analyses conducted to embrace spatiotemporal changes in the area. Google Earth Engine was used to analyse the nexus between vegetation dynamics and climate parameters using datasets of the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS). The ArcGIS 10.8 map visualization and layout was later performed. The analysis of the vegetation vulnerability and ecological responses was carried out using Fuzzy Vegetation Risk Index (FVRI) and regression analysis. Results of the study showed that rainfall increased from 527.07mm in 2009 to 692.85mm in 2019, before declining to 523.18mm in 2024, while LST decreased from 38.57°C to 35.27°C during the same period. Moreover, NDVI also showed the same trend with its highest in 2019 (0.351) and a decrease to 0.324 in 2024. The regression showed weak positive correlation between NDVI and rainfall (R2= 0.254) and strong negative correlation between NDVI and LST (R2= 0.696). The FVRI analysis also found three vegetation stages, including stability of 2009-2014 (82.8%), dramatic improvement (99%) of 2014-2019 and the period of reversed change towards 90 percent degradation in 2019-2024. The research determined that vegetation under semiarid conditions was prone to climatic variations and anthropogenic activity that identifies the necessity to interfere to enhance ecological stability to promote SDG 13 (Climate Action) and (SDG 15) Life on Land.

Google earth engine fuzzy logic NDVI semi-arid environment vegetation dynamics

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