ADVANCED COMPUTATIONAL METHODS FOR SPATIAL INFORMATION EXTRACTION

A variety of mathematical approaches for spatial information extractio n using digitized aerial photography and satellite imagery have been d eveloped and implemented on serial computers. However, because of data volume and scale, the computational demands of spatial analysis proce dures frequently exceed the capacity of available serial processing te chnologies. One way of addressing this problem is through parallel pro cessing in which the power of multiple computing units can be used on a single problem. In this study we investigate the utility of parallel processing for spatial feature extraction. Our testing in the situati on of texture feature extraction using a cooccurrence matrix indicates that dramatic reductions in execution time are possible-an image that required about 34 min to process using one processor was solved in un der 2 min using nineteen processors. The availability of additional pr ocessors could result in smaller execution times. This speedup potenti al is a critical element in future studies focusing on more complex sp atial analysis procedures.