SOIL SPECTRAL EFFECTS ON VEGETATION DISCRIMINATION (REMOTE SENSING).

Persistent Link:
http://hdl.handle.net/10150/187724
Title:
SOIL SPECTRAL EFFECTS ON VEGETATION DISCRIMINATION (REMOTE SENSING).
Author:
HUETE, ALFREDO RAMON.
Issue Date:
1984
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 spectral behavior of a cotton canopy with four different soil types inserted underneath, respectively, was examined at various levels of vegetation density. Measured composite spectra, representing mixtures of vegetation with different soil backgrounds were compared with existing measures of greenness, including the NIR-Red band ratios, the perpendicular vegetation index and the green vegetation index. Observed spectral patterns involving constant vegetation amounts with different soil backgrounds could not be explained nor predicted by either the ratio or the orthogonal greenness measures. All greenness measures were found to be strongly dependent on soil brightness. Furthermore, soil-induced greenness changes became greater with increasing amounts of vegetation up to 60% green cover. Three versions of factor analysis were subsequently utilized to determine if soil background influences could be filtered from canopy spectral data sets. In R-mode factor analysis, canopy spectra were decomposed into orthogonal features called brightness and greenness. The greenness feature, however, was found to be dependent, not only on vegetation density, but on soil background spectral properties. Of most concern were soil brightness influences which resulted in lowered greenness values with wet or dark soil backgrounds and identical vegetation conditions. The Q-mode version of factor analysis decomposed canopy spectra into additive, soil and vegetation, reflectance components. Although soil spectral response was found to contribute and mix into the derived greenness measure, significant improvements in vegetation discrimination occurred, especially at low vegetation densities. Finally, the T-mode version of factor analysis successfully separated the spectral influences of soil background from the larger response due to vegetation canopy development. Canopy spectra were decomposed into soil-dependent and soil-independent canopy components. The soil-dependent component was found to resemble the spectral response of green vegetation due to the scattering and transmittance properties of the overlying vegetation canopy. Results showed how the soil-dependent signal mixed into various measures of greenness and hampered vegetation discrimination. The filtering of soil background response from spectral data sets significantly improved greenness indices and vegetation analyses.
Type:
text; Dissertation-Reproduction (electronic)
Keywords:
Plant-soil relationships.; Soils -- Optical properties.
Degree Name:
Ph.D.
Degree Level:
doctoral
Degree Program:
Soils, Water, and Engineering; Graduate College
Degree Grantor:
University of Arizona

Full metadata record

DC FieldValue Language
dc.language.isoenen_US
dc.titleSOIL SPECTRAL EFFECTS ON VEGETATION DISCRIMINATION (REMOTE SENSING).en_US
dc.creatorHUETE, ALFREDO RAMON.en_US
dc.contributor.authorHUETE, ALFREDO RAMON.en_US
dc.date.issued1984en_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 spectral behavior of a cotton canopy with four different soil types inserted underneath, respectively, was examined at various levels of vegetation density. Measured composite spectra, representing mixtures of vegetation with different soil backgrounds were compared with existing measures of greenness, including the NIR-Red band ratios, the perpendicular vegetation index and the green vegetation index. Observed spectral patterns involving constant vegetation amounts with different soil backgrounds could not be explained nor predicted by either the ratio or the orthogonal greenness measures. All greenness measures were found to be strongly dependent on soil brightness. Furthermore, soil-induced greenness changes became greater with increasing amounts of vegetation up to 60% green cover. Three versions of factor analysis were subsequently utilized to determine if soil background influences could be filtered from canopy spectral data sets. In R-mode factor analysis, canopy spectra were decomposed into orthogonal features called brightness and greenness. The greenness feature, however, was found to be dependent, not only on vegetation density, but on soil background spectral properties. Of most concern were soil brightness influences which resulted in lowered greenness values with wet or dark soil backgrounds and identical vegetation conditions. The Q-mode version of factor analysis decomposed canopy spectra into additive, soil and vegetation, reflectance components. Although soil spectral response was found to contribute and mix into the derived greenness measure, significant improvements in vegetation discrimination occurred, especially at low vegetation densities. Finally, the T-mode version of factor analysis successfully separated the spectral influences of soil background from the larger response due to vegetation canopy development. Canopy spectra were decomposed into soil-dependent and soil-independent canopy components. The soil-dependent component was found to resemble the spectral response of green vegetation due to the scattering and transmittance properties of the overlying vegetation canopy. Results showed how the soil-dependent signal mixed into various measures of greenness and hampered vegetation discrimination. The filtering of soil background response from spectral data sets significantly improved greenness indices and vegetation analyses.en_US
dc.typetexten_US
dc.typeDissertation-Reproduction (electronic)en_US
dc.subjectPlant-soil relationships.en_US
dc.subjectSoils -- Optical properties.en_US
thesis.degree.namePh.D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineSoils, Water, and Engineeringen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.identifier.proquest8421972en_US
dc.identifier.oclc691322986en_US
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