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.