Separability of soils in a tallgrasss prairie using SPOT and DEM data
作者： H SU , E KANEMASU , M RANSOM , S YANG
DOI: 10.1016/0034-4257(90)90027-J
关键词: Digital elevation model 、 Remote sensing 、 Data processing 、 Satellite imagery 、 Satellite 、 Geology 、 Image processing 、 Soil survey 、 Soil science 、 Soil water 、 Soil map
摘要: Abstract A sufficient transformation technique is important in using computer-aided soil pattern recognition to interpret soils surveys. This study was conducted the Systeme Probatoire d'Observation de le Terre (SPOT) satellite images and Digital Elevation Model (DEM) data separate five major a tallgrass prairie near Manhattan, Kansas. The high resolution SPOT were integrated with DEM data. sampled classified conventional survey procedures. canonical used extract features from pairwise transformed divergence analysis also evaluate several variables order sufficiently soils. Consequently, two derived training samples selected. Our results suggest that canonically superior combined High can be aid second-order surveys grasslands.
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