Abstract
Vegetation indices enhance vegetation spectral signatures by combining bands of red (630–700 nm) and near-infrared wavelengths (700–1100 nm). This can be best suited to study vital activity of vegetation on land surface. Kurnool district is chosen to assess the capability of continuous spatial and temporal coverage; MODIS-derived enhanced vegetation indices (EVI) data were utilized to monitor the vegetation seasonal dynamics and their relationship with precipitation. Statistical analysis of mandal-wise mean EVI and corresponding seasonal rainfall data show the proportional relation with positive correlation. MODIS EVI is a good indicator of vegetation change with respect to rainfall. Further study is needed to refine the correlation between EVI and rainfall. This work enables demarcation of areas on the basis of density of forest; also, it helps in identifying the effect of rainfall for the healthy growth of vegetation. Finally, the drought prone area can be identified for timely remedial action. The results also show the possibility of predicting vegetation change in the study area due to rainfall using the derived relationships among vegetation and rainfall with the use of public domain low-resolution satellite data and ground observations.
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