@article {KNZ00297, title = {Separability of soils in a tallgrass prairie using SPOT and DEM Data}, journal = {Remote Sensing of the Environment}, volume = {32}, year = {1990}, pages = {10 -17}, abstract = {

A sufficient transformation technique is important in using computer-aided soil pattern recognition to interpret soils in soil surveys. This study was conducted using the Systeme Probatoire d\&$\#$39;Observation de la Terre (SPOT) satellite images and Digital Elevation Model (DEM) data to seperate five major sils in a tallgrass prairie near Manhattan, Kansas. The high resolution SPOT satellite im;ages were integrated with DEM data. the soils were sampled and classified using conventional soil survey procedures to extract the important soil features from SPOT and DEM data. A pairwise transformed divergence analysis was also conducted to evaluate the several aanonical variables in order to sufficiently separate the soils. Consequently, two canonical variables derived from training samples were selected. Our results suggest that canonically transformed data were superior to combined SPOT and DEM data. High resolution SPOT images and DEM data can be used to aid secondd- order soil surveys in grasslands

}, keywords = {LTER-KNZ, tallgrass prairie}, doi = {10.1016/0034-4257(90)90027-J}, author = {Su, H. and Kanemasu, E.T. and Ransom, M.D. and Yang, S.} }