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Digitized by Kansas State University Libraries

An airborne multispectral video system was used to collect soil spectral data over a four-square mile region in northeastern Arizona. Six multispectral video images were digitized. Using the red and blue bands of each image, an unsupervised classification was performed. Each was referenced to a digitized U.S. Soil Conservation Service map resulting in classification precisions ranging from 0-92.4 percent. Ground radiometric measurements were made to ascertain spectral separability of the soil samples. Soil color was determined to try to relate Munsell value to classification precision. Misclassification of soil map units was unrelated to soil brightness or areal extent of each soil. Rather, features such as slope, boundary complexity, and surface condition was responsible for misclassifications seen in this study. Best classification results occurred when soil mapping units were relatively homogeneous, possessed slight changes in slope, and had a regular surface with smooth and distinct boundaries.

Thesis (M. Inst. Agrar. (Soil Science))--University of Pretoria, 2000. / Includes bibliographical referencess.

Thesis (Ph. D. - Soils, Water and Engineering)--University of Arizona. / Includes bibliographical references.

Thesis (Ph. D.)--West Virginia University, 2009. / Title from document title page. Document formatted into pages; contains ix, 137 p. : ill. (some col.), maps (some col.). Includes abstract. Includes bibliographical references (p. 122-128).

Thesis (Ph. D.)--Ohio State University, 2006. / Title from first page of PDF file. Includes bibliographical references (p. 197-210).

No description available.

Pedology, like most other sciences, is facing a data explosion in which it is becoming increasingly difficult to organize, summarize and interpret large quantities of data. Coupled with this is an unprecedented demand for soils information for consideration in resource management and environmental considerations. Since decision making in these areas increasingly has to be justified by economic criteria, the need for evaluation of soils information for land use considerations in economic terms is paramount. In this study, the British Columbia Soil Survey Data File was used. The file contains only routine soil survey data. It was improved and modified to correct problems arising from earlier experiences. The identification, organization and coding techniques used in the data file are presented. In view of the interest in establishing national data bank systems a modified hierarchical organizational and identification system is proposed, which should be equally applicable at regional, provincial and national levels. The Data File was also used to explore by statistical techniques the inter-relationships between soil properties, the feasibility of predicting the values for dependent variables by multiple regression equations and to study the modal concept of soil which is basic to soil classification and subsequent statistical analysis. Numerical taxonomy techniques were used to determine the feasibility of using objective statistical techniques in the development of a model by which soils could be rated for a specific land use, as well as, determine on the basis of correlation and regression analysis an estimate of hypothetical treatments and costs that would make a given soil behave more like an ideal soil for the use in question. The study showed that, using cash cropping and road bed construction as two contrasting soil uses as examples, the derivation of cost estimates for soil manipulation is feasible. However, the derivation of the ideal soil (model) is critical. / Land and Food Systems, Faculty of / Graduate

No description available.