The objective of this research is to develop KDD (knowledge discovery in databases) techniques for spatio-temporal geo-data, and use these techniques to examine inter-annual vegetation health signals. The underlying hypothesis of the research is that the signatures of inter-annual variability of climate on vegetation dynamics, as represented by the statistical descriptors of vegetation index variations, depend upon a variety of attributes related to the topography, hydrology, physiography, and climate. NDVI (Normalized Differential Vegetation Index) is enlisted to represent vegetation health and relationships between this index and topographic attributes such as elevation, slope, aspect, compound topographic index (CTI), and the proximity to a stream, are analyzed. Several scientific questions related to the identification and characterization of the inter-annual variability ensue as a consequence of our hypothesis.