This paper aimed to investigate the influence of climatic and topographic factors on the distribution of vegetation in the Virunga Volcanoes Massif using GIS and remote sensing techniques. The climatic variables considered were precipitation, Land Surface Temperature (LST), and evapotranspiration (ET), whereas the topographic factors considered were elevation and aspect. The dataset consisted of MODIS NDVI data, satellite-delivered precipitation, ET, and the LST. A 2014 Landsat 8 OLI image was used to produce a vegetation map of the study area, while DEM was used to derive the elevation attributes and to calculate the aspect angles. Moran’s I and Geographically Weighted Regression (GWR) Model was used to analyze the relationships between the climatic factors and NDVI changes over elevation and aspect. The results indicated that among the nine vegetation types inventoried in the area, the Mean NDVI varied from 0.33 to 0.59 and the optimal vegetation growth was found at an elevation between 2000 and 3900 m, with mean NDVI values larger than 0.50. The peak mean NDVI value of 0.59 was found at the elevation from 2100 to 2800 m. Vegetation growth was found to be more sensitive to elevation, as NDVI values were more varied at a lower elevation (<4000 m) than at a higher elevation (>4000 m). Considering the aspect, the greater vegetation growth was found in SE (132°, 148°), SW (182°, 186°), and NW (309.5°–337.5°), with mean NDVI values larger than 0.56. This indicated that vegetation was susceptible to better growth conditions in the lower elevation ranges and in shady areas. The vegetation NDVI in this study area was mostly uncorrelated with precipitation (R2
= 0.34), but was strongly correlated with LST (R2
= 0.99) and ET (R2
= 98). LST (≥18 °C) and ET (1286 mm/year−1
) were found to provide optimal conditions for vegetation growth in the Virunga Volcanoes Massif. Empirically, the results concluded that elevation, aspect, LST, and ET are the main factors controlling the spatial distribution and vegetation growth in this area. This information is significantly helpful for biodiversity conservation and constitutes a valuable input to environmental and ecological research.
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