Treffer: Using the variogram to explore imagery of two different spatial resolutions

The resolution of remotely sensed data is becoming increasingly fine, and there are now many sources of data with a pixel size of 1m x 1m. This produces huge amounts of data that have to be stored, processed and transmitted. For environmental applications this resolution possibly provides far more data than are needed: data overload. This poses the question: how much is too much? We have explored two resolutions of data-20m pixel SPOT data and 1 m pixel Computerized Airborne Multispectral Imaging System (CAMIS) data from Fort A. P. Hill (Virginia, USA), using the variogram of geostatistics. For both we used the normalized difference vegetation index (NDVI). Three scales of spatial variation were identified in both the SPOT and 1 m data: there was some overlap at the intermediate spatial scales of about 150m and of 500m-600m. We sub-sampled the 1 m data and scales of variation of about 30 m and of 300 m were identified consistently until the separation between pixel centroids was 15 m (or 1 in 225 pixels). At this stage, spatial scales of about 100m and 600m were described, which suggested that only now was there a real difference in the amount of spatial information available from an environmental perspective. These latter were similar spatial scales to those identified from the SPOT image. We have also analysed 1 m CAMIS data from Fort Story (Virginia, USA) for comparison and the outcome is similar. From these analyses it seems that a pixel size of 20 m is adequate for many environmental applications, and that if more detail is required the higher resolution data could be sub-sampled to a 10m separation between pixel centroids without any serious loss of information. This reduces significantly the amount of data that needs to be stored, transmitted and analysed and has important implications for data compression.