Filtering SPOT imagery by kriging analysis
Digital images are rich in data, but in many instances they are so complex as to require spatial filtering to distinguish the structures in them and facilitate interpretion. The filtering can be done geostatistically by kriging analysis. It proceeds in two stages. The first involves modelling the correlation structure in the imagery by decomposing the variogram into independent spatial components. The second takes each component in turn and kriges it, thereby filtering it from the others. The paper describes the theory and illustrates it with an example of an analysis of a SPOT image in a forested landscape of the south-eastern United States. Variograms of the three wavebands, originally recorded as digital numbers and for the red and infrared transformed to the logarithms, revealed spatial variation on two distinct scales with effective ranges of 300m and 3km. These variograms and that of the Normalized Difference Vegetation Index (NDVI) were fitted by nested (double) exponential models. The two spatial components in the scene were then estimated separately by kriging analysis and mapped. The maps of NDVI are displayed and compared with data from ground survey. The shortrange component represents an intricate pattern of dissection and its associated vegetation. The long-range component is that of the major landform units and associated ground cover classes.
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