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dc.contributor.authorNolin, Anne Walden, 1958-
dc.creatorNolin, Anne Walden, 1958-en_US
dc.date.accessioned2013-03-28T10:08:43Z
dc.date.available2013-03-28T10:08:43Z
dc.date.issued1987en_US
dc.identifier.urihttp://hdl.handle.net/10150/276549
dc.description.abstractAn 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.
dc.language.isoen_USen_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.subjectSoils -- Classification.en_US
dc.subjectSoil mapping.en_US
dc.subjectSoil surveys.en_US
dc.subjectRemote sensing.en_US
dc.titleCLASSIFICATION AND MAPPING OF SOILS USING A MULTISPECTRAL VIDEO SYSTEM AND COMPUTER-AIDED ANALYSISen_US
dc.typetexten_US
dc.typeThesis-Reproduction (electronic)en_US
dc.identifier.oclc18792636en_US
thesis.degree.grantorUniversity of Arizonaen_US
thesis.degree.levelmastersen_US
dc.identifier.proquest1332236en_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.disciplineSoil and Water Scienceen_US
thesis.degree.nameM.S.en_US
dc.identifier.bibrecord.b16640354en_US
refterms.dateFOA2018-06-28T02:23:07Z
html.description.abstractAn 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.


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