Separability of soils in a tallgrass prairie using SPOT and DEM data

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'Observation de le Terre (SPOT) satellite images and Digital Elevation Model (DEM) data to separate five major soils in a tallgrass prairie near Manhattan, Kansas. The high resolution SPOT satellite images were integrated with DEM data. The soils were sampled and classified using conventional soil survey procedures. A canonical transformation technique was used to extract the important soil features from SPOT and DEM data. A pairwise transformed divergence analysis was also conducted to evaluate the several canonical 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 second-order soil surveys in grasslands.

[1]  Donald R. Jantz,et al.  Soil survey of Riley County and part of Geary County, Kansas , 1975 .

[2]  M. E. Austin.  Land resource regions and major land resource areas of the United States (exclusive of Alaska and Hawaii) , 1965 .

[3]  F. Westin,et al.  LANDSAT-1 data, its use in a soil survey program , 1976 .

[4]  Soil Inventory From Digital Analysis of Satellite Scanner and Topographic Data1 , 1977 .

[5]  C. Owensby,et al.  Effects of dormant-season herbage removal on Flint Hills rangeland. , 1988 .

[6]  James V. Drew,et al.  Use of Satellite Imagery to Delineate Soil Associations in the Sand Hills Region of Nebraska , 1975 .

[7]  David R. Thompson,et al.  Variation in Alluvial-Derived Soils as Measured by Landsat Thematic Mapper 1 , 1984 .

[8]  W. Frye,et al.  Effects of Heating on Soil Chemical Properties and Growth and Nutrient Composition of Corn and Millet , 1983 .

[9]  Ashbindu Singh.  Some clarifications about the pairwise divergence measure in remote sensing , 1984 .

[10]  D. R. Thompson,et al.  Detecting Soils under Cultural Vegetation Using Digital Landsat Thematic Mapper Data1 , 1984 .

[11]  P. Sellers,et al.  The First ISLSCP Field Experiment (FIFE) , 1988 .

[12]  Ghassem R. Asrar,et al.  Assessing grassland biophysical characteristics from spectral measurements , 1986 .

[13]  E. T. Kanemasu,et al.  Detecting Soil Information on a Native Prairie Using Landsat TM and SPOT Satellite Data , 1989 .

[14]  Philip H. Swain,et al.  Remote Sensing: The Quantitative Approach , 1981, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[15]  M. H. Milford,et al.  Evaluation of Landsat Multispectral Scanner Data for Mapping Vegetated Soil Landscapes1 , 1981 .

[16]  B. F. Merembeck,et al.  Directed Canonical Analysis And the Performance of Classifiers under Its Associated Linear Transformation , 1980, IEEE Transactions on Geoscience and Remote Sensing.

[17]  Barry Haack,et al.  An assessment of Landsat MSS and TM data for urban and near-urban land-cover digital classification , 1987 .

[18]  E. J. Tyler,et al.  Thematic Mapper and Digital Elevation Modeling of Soil Characteristics in Hilly Terrain , 1988 .

[19]  Detection of surface soil variation using high-resolution satellite data: results from the U.K. SPOT-simulation investigation , 1986 .

[20]  J. Cipra,et al.  Investigation of digital landsat data for mapping soils under range vegetation , 1983 .

[21]  John R. Jensen,et al.  Introductory Digital Image Processing: A Remote Sensing Perspective , 1986 .