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dc.rights.licenseUsers may download and share copies with attribution in accordance with a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License. No commercial use or derivatives are permitted without the explicit approval of the author.
dc.contributorIsaacson, David
dc.contributorCheney, Margaret, 1955-
dc.contributorSiegmann, W. L.
dc.contributorKovacic, Gregor
dc.contributorMiranda, Analee
dc.contributorAlatishe, Jimmy
dc.contributor.authorLorenzo, Nicholas Angelo
dc.date.accessioned2021-11-03T09:15:43Z
dc.date.available2021-11-03T09:15:43Z
dc.date.created2020-08-06T16:04:50Z
dc.date.issued2019-12
dc.identifier.urihttps://hdl.handle.net/20.500.13015/2490
dc.descriptionDecember 2019
dc.descriptionSchool of Science
dc.description.abstractI apply my method to a set of experimentally collected SAR data, finding reasonable agreement with results reported in the literature.
dc.description.abstractSynthetic aperture radar (SAR) is a form of remote sensing capable of providing high-resolution images, day or night, independent of weather. Monostatic SAR involves a moving, airborne or spaceborne antenna that periodically transmits electromagnetic pulses and measures the resulting backscattered signal. Specific applications include planetary exploration, climate change research, environmental monitoring, land-use monitoring, and terrain mapping, as well as military and agricultural applications.
dc.description.abstractIn general, the problem of Earth remote sensing is to extract as much information as possible about some region of interest via some remotely sensed signal. In this dissertation, I focus on rough-surface scattering. In particular, I use monostatic, polarimetric SAR data to estimate three parameters characterizing the rough surface under investigation: the (frequency-dependent) complex-valued permittivity, the correlation length, and the root-mean-square (RMS) height. The permittivity is of interest, for example, in estimating soil moisture content in an agricultural context and in the improvement of numerical weather predictions and climate simulations. The correlation length and RMS height are of interest, for example, in monitoring soil erosion, which has implications in agricultural land management.
dc.language.isoENG
dc.publisherRensselaer Polytechnic Institute, Troy, NY
dc.relation.ispartofRensselaer Theses and Dissertations Online Collection
dc.subjectMathematics
dc.titleInversion of rough-surface parameters via polarimetric synthetic aperture radar data
dc.typeElectronic thesis
dc.typeThesis
dc.digitool.pid179945
dc.digitool.pid179946
dc.digitool.pid179947
dc.rights.holderThis electronic version is a licensed copy owned by Rensselaer Polytechnic Institute, Troy, NY. Copyright of original work retained by author.
dc.description.degreePhD
dc.relation.departmentDept. of Mathematical Sciences


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