MAPPING SURFACE SOIL MOISTURE AND ROUGHNESS BY RADAR REMOTE SENSING IN THE SEMI-ARID ENVIRONMENT

Persistent Link:
http://hdl.handle.net/10150/190930
Title:
MAPPING SURFACE SOIL MOISTURE AND ROUGHNESS BY RADAR REMOTE SENSING IN THE SEMI-ARID ENVIRONMENT
Author:
Rahman, Mohammed Magfurar
Issue Date:
2005
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:
Information about the distribution of surface soil moisture can greatly benefit the management of agriculture and natural resource. However, direct measurement of soil moisture over larger areas can be impractical and expensive, which has led scientists to develop satellite based remote sensing techniques for soil moisture assessments. Retrieving soil moisture from radar satellite imagery often associated with the collection and use of ancillary field data on surface roughness. However, field data that is meant to characterize surface roughness is often unreliable, is expensive to collect and is nearly impossible to acquire for large scale applications. These issues represent barriers to the adoption and of radar data for mapping soil moisture over large areas.The research presented in the dissertation is aimed at the development of an operational soil moisture assessment system based solely on radar satellite data and a radar model, eliminating the field data requirements altogether. The research is directed towards a so-called equation-based solution of the problem as an alternative to the approach that requires the use of extensive field-data sets on surface roughness. This approach is based on the concept that if the number of equations are equal to the number of unknowns, then explicit solutions of all unknowns are possible. My research derived the necessary equations to solve for soil moisture and surface roughness. The derivation of the equations and how to use them to estimate soil moisture without using ancillary field data was demonstrated by my research. Validation results showed that the equation-based method that was developed is capable of providing more precise estimates of surface soil moisture than that of ancillary field-data supported method.
Type:
Electronic Dissertation; text
Keywords:
Hydrology.; Soil -- Moisture; Surface -- Roughness; Radar; Radarsat; Integral Equation Model
Degree Name:
Ph. D.
Degree Level:
doctoral
Degree Program:
Arid Lands Resource Sciences; Graduate College
Degree Grantor:
University of Arizona
Committee Chair:
Marsh, Stuart E.

Full metadata record

DC FieldValue Language
dc.language.isoenen_US
dc.titleMAPPING SURFACE SOIL MOISTURE AND ROUGHNESS BY RADAR REMOTE SENSING IN THE SEMI-ARID ENVIRONMENTen_US
dc.creatorRahman, Mohammed Magfuraren_US
dc.contributor.authorRahman, Mohammed Magfuraren_US
dc.date.issued2005en_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.abstractInformation about the distribution of surface soil moisture can greatly benefit the management of agriculture and natural resource. However, direct measurement of soil moisture over larger areas can be impractical and expensive, which has led scientists to develop satellite based remote sensing techniques for soil moisture assessments. Retrieving soil moisture from radar satellite imagery often associated with the collection and use of ancillary field data on surface roughness. However, field data that is meant to characterize surface roughness is often unreliable, is expensive to collect and is nearly impossible to acquire for large scale applications. These issues represent barriers to the adoption and of radar data for mapping soil moisture over large areas.The research presented in the dissertation is aimed at the development of an operational soil moisture assessment system based solely on radar satellite data and a radar model, eliminating the field data requirements altogether. The research is directed towards a so-called equation-based solution of the problem as an alternative to the approach that requires the use of extensive field-data sets on surface roughness. This approach is based on the concept that if the number of equations are equal to the number of unknowns, then explicit solutions of all unknowns are possible. My research derived the necessary equations to solve for soil moisture and surface roughness. The derivation of the equations and how to use them to estimate soil moisture without using ancillary field data was demonstrated by my research. Validation results showed that the equation-based method that was developed is capable of providing more precise estimates of surface soil moisture than that of ancillary field-data supported method.en_US
dc.description.notehydrology collectionen_US
dc.typeElectronic Dissertationen_US
dc.typetexten_US
dc.subjectHydrology.en_US
dc.subjectSoil -- Moistureen_US
dc.subjectSurface -- Roughnessen_US
dc.subjectRadaren_US
dc.subjectRadarsaten_US
dc.subjectIntegral Equation Modelen_US
thesis.degree.namePh. D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineArid Lands Resource Sciencesen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.chairMarsh, Stuart E.en_US
dc.contributor.committeememberMoran, M. Susanen_US
dc.contributor.committeememberHutchinson, Charles F.en_US
dc.contributor.committeememberLangworthy, Mark W.en_US
dc.contributor.committeememberOrr, Barron J.en_US
dc.identifier.oclc137354302en_US
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