Applying spectral mixture analysis (SMA) for soil information extraction on the airborne visible/infrared imaging spectrometer (AVIRIS) data

Persistent Link:
http://hdl.handle.net/10150/191221
Title:
Applying spectral mixture analysis (SMA) for soil information extraction on the airborne visible/infrared imaging spectrometer (AVIRIS) data
Author:
Accioly, Luciano Jose de Oliveira
Issue Date:
1997
Publisher:
The University of Arizona.
Rights:
Copyright © 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.
Abstract:
The research objectives of this study were formulated to produce the soil spectral maps using spectral mixture analysis on the AVMS data of the Walnut Gulch Experimental Watershed, Tombstone, Arizona. To accomplish this objective the spectral characteristics of eight soils of this Watershed were determined considering the effect of the source of illumination/sensor viewing geometry, degree of wetness (dry vs wet), surface roughness, and the source of the spectra (field, sieved samples and lab) on the selection of image and reference endmembers. The scale effect of the source of spectra was also studied in connection with AVIRIS spectral response. The soils presented anisotropic behavior which varied inversely with the wavelength, and it was reduced under wet conditions. Loss of information occurred when moving from large scale data set (lab, sieved sample, and field spectra) to small scale data (AVIRIS). Cluster analysis and factor analysis were used to extract information about how soil reference endmembers are grouped in relation to viewing angles, degree of wetness and the source of the spectra. Factor analysis was applied to identify the key set of bands that carried most of the information. Soil spectral classes varied as a result of scale effects, soil conditions (wet or dry), and viewing angles. Factor analysis showed that with four unique bands (located at 0.410, 1.310, 0.650, and 2.400 p.m) it was possible to reconstruct the four basic soil spectral curves (Epitaph, Graham, McAllister, and Baboquivari) from the lab dataset. AVERT S image was modeled using mixture analysis on the basis of image endmembers and reference endmembers. Based on the four dimensions of the AVIRIS data image endmembers were defined by three soil spectra (McAllister, Stronghold-3, and Graham) and by one spectra of green vegetation. The shade fractions were separated from dark soils (Graham and Epitaph)on the basis of the spatial context The target test identified at least seven reference endmembers in the AVIRIS scene of the Watershed however; mixture analysis failed in obtaining fraction images from these reference endmembers. Mixture analysis was able to produce fraction images with a relatively high error for a small set (3) of reference endmembers (McAllister and Graham soils, and walnut leaf). However when applied to a subset of pixel extracted from the AVIRIS image mixture analysis identified the reference endmembers and quantified their proportions.
Type:
Dissertation-Reproduction (electronic); text
Keywords:
Hydrology.; Infrared imaging.; Environmental sciences.
Degree Name:
Ph. D.
Degree Level:
doctoral
Degree Program:
Soil, Water and Environmental Science; Graduate College
Degree Grantor:
University of Arizona
Committee Chair:
Huete, A. R.

Full metadata record

DC FieldValue Language
dc.language.isoenen_US
dc.titleApplying spectral mixture analysis (SMA) for soil information extraction on the airborne visible/infrared imaging spectrometer (AVIRIS) dataen_US
dc.creatorAccioly, Luciano Jose de Oliveiraen_US
dc.contributor.authorAccioly, Luciano Jose de Oliveiraen_US
dc.date.issued1997en_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.description.abstractThe research objectives of this study were formulated to produce the soil spectral maps using spectral mixture analysis on the AVMS data of the Walnut Gulch Experimental Watershed, Tombstone, Arizona. To accomplish this objective the spectral characteristics of eight soils of this Watershed were determined considering the effect of the source of illumination/sensor viewing geometry, degree of wetness (dry vs wet), surface roughness, and the source of the spectra (field, sieved samples and lab) on the selection of image and reference endmembers. The scale effect of the source of spectra was also studied in connection with AVIRIS spectral response. The soils presented anisotropic behavior which varied inversely with the wavelength, and it was reduced under wet conditions. Loss of information occurred when moving from large scale data set (lab, sieved sample, and field spectra) to small scale data (AVIRIS). Cluster analysis and factor analysis were used to extract information about how soil reference endmembers are grouped in relation to viewing angles, degree of wetness and the source of the spectra. Factor analysis was applied to identify the key set of bands that carried most of the information. Soil spectral classes varied as a result of scale effects, soil conditions (wet or dry), and viewing angles. Factor analysis showed that with four unique bands (located at 0.410, 1.310, 0.650, and 2.400 p.m) it was possible to reconstruct the four basic soil spectral curves (Epitaph, Graham, McAllister, and Baboquivari) from the lab dataset. AVERT S image was modeled using mixture analysis on the basis of image endmembers and reference endmembers. Based on the four dimensions of the AVIRIS data image endmembers were defined by three soil spectra (McAllister, Stronghold-3, and Graham) and by one spectra of green vegetation. The shade fractions were separated from dark soils (Graham and Epitaph)on the basis of the spatial context The target test identified at least seven reference endmembers in the AVIRIS scene of the Watershed however; mixture analysis failed in obtaining fraction images from these reference endmembers. Mixture analysis was able to produce fraction images with a relatively high error for a small set (3) of reference endmembers (McAllister and Graham soils, and walnut leaf). However when applied to a subset of pixel extracted from the AVIRIS image mixture analysis identified the reference endmembers and quantified their proportions.en_US
dc.description.notehydrology collectionen_US
dc.typeDissertation-Reproduction (electronic)en_US
dc.typetexten_US
dc.subjectHydrology.en_US
dc.subjectInfrared imaging.en_US
dc.subjectEnvironmental sciences.en_US
thesis.degree.namePh. D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineSoil, Water and Environmental Scienceen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.chairHuete, A. R.en_US
dc.contributor.committeememberPost, D. F.en_US
dc.contributor.committeememberMatthias, A.en_US
dc.contributor.committeememberMarsh, S. E.en_US
dc.contributor.committeememberYool, S.en_US
dc.identifier.oclc213466995en_US
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