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Spatial characteristics of vegetation index map in urban area derived by variogram analysis

It is important to keep monitoring the characteristics of vegetation in urban areas by remotely sensed data from an environmental viewpoint. Recent sensors on earth observation satellites have excellent and very high spatial resolution of a few meters on the surface of the earth. However, the higher the resolution of sensor becomes, the more difficult the analysis of land surface seems to be due to too fine aspects in the satellite imagery. The primary objective of the research presented here is to clarify the spatial characteristics of vegetation distribution in urban areas by analyzing properties of variograms . To depict the spatial patterns of the observed scenes, quantity measured by second-order statistics has been used in applications such as mining exploration and other engineering fields. Related practitioners call the field of spatial statistics 'geostatistics'. An important concept of the quantity inherent to the scenes is spatial continuity and is measured as covariance and semivariance. The semivariance plays a very important role in the analysis of data's spatial statistics in the present research. Among many vegetation indices, NDVI(normalized difference vegetation index) has been most widely used for investigation of environmental assessment. The NDVI data used for the current analysis is derived from the multi-spectral data of ‘QuickBird’ (earth observation satellite) with the resolution of 2.8m. The NDVI lies in its characteristics that can reduce the multidimensional data yielded from multi-spectral sensor systems to a single index which is sensitive to various characteristics related to vegetation activities such as biomass, productivity, leaf area, amount of photo-synthetically active radiation, and percent vegetative ground-cover etc.