SPATIOTEMPORAL DYNAMICS OF VEGETATION COVER IN THE NAZINON WATERSHED: EVIDENCE FROM LANDSAT NDVI MULTI-DATE ANALYSIS (2006, 2015 AND 2025)
Authors: KAFANDO Halidou, KOUETA T. Roland and SAWADOGO Abdoulaye
KAFANDO Halidou: WASCAL Programme on Climate Change and Education, University of The Gambia, Department of Agriculture and Environmental Sciences, P.O. Box 3530, Kanifing, The Gambia.
KOUETA T. Roland: Joseph KI-ZERBO University, Department of Geography, 01 BP 85, Ouagadougou 01, Burkina Faso.
SAWADOGO Abdoulaye: Joseph KI-ZERBO University, Department of Geography, Laboratory for the Study and Research of Environments and Territories (LERMIT), 01 BP 85, Ouagadougou 01, Burkina Faso.
ABSTRACT
Understanding vegetation dynamics is essential for assessing ecosystem responses to climate variability and anthropogenic pressure in semi-arid environments. This study analyzes the spatiotemporal evolution of vegetation cover in the Nazinon Watershed, central-southern Burkina Faso, based on Landsat-derived Normalized Difference Vegetation Index (NDVI) over a multi-date period (2006, 2015 and 2025).
Multi-temporal Landsat imagery (TM, ETM+, OLI) acquired during peak vegetation seasons (August–October) with minimal cloud cover (<10%) was processed using Google Earth Engine. Standard pre-processing steps including atmospheric correction, cloud masking and geometric harmonization were applied to ensure inter-sensor comparability. NDVI was computed from red and near-infrared spectral bands and annual composites were generated for the selected years to characterize vegetation conditions.
Statistical descriptors (NDVI_max, NDVI_mean, NDVI_min, NDVI_stdDev) were extracted to assess spatial and temporal variations. Results show a gradual increase in mean NDVI from 0.14 (2006) to 0.18 (2025), indicating a slight variation in vegetation greenness over time. Maximum NDVI values increase slightly from 0.37 to 0.40, suggesting localized changes in vegetation vigor. However, minimum NDVI values decrease from -0.13 to -0.24, reflecting expansion of non-vegetated or highly disturbed surfaces. The standard deviation remains stable at 0.03, indicating relatively constant spatial variability across the study period. Overall, the findings reveal contrasting vegetation dynamics characterized by localized increases in vegetation greenness alongside persistent degradation in other areas. These results highlight the importance of integrated land management strategies and provide useful insights for sustainable watershed management under changing climatic and anthropogenic pressures in the Nazinon basin.
Keywords: NDVI, vegetation dynamics, Landsat image, Nazinon Watershed, Burkina Faso, GIS, remote sensing