Optical Remote Sensing for Monitoring Evolution of Ablation Season Mountain Snow Cover

Persistent Link:
http://hdl.handle.net/10150/193757
Title:
Optical Remote Sensing for Monitoring Evolution of Ablation Season Mountain Snow Cover
Author:
Lampkin, Derrick Julius
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:
The investigations contained in this body of work detail a viable proof-of-concept model for monitoring seasonal snow pack propensity for melt release based on time-variant snow surface optical and thermal properties. The model has been called the Near Surface Moisture Index- (Snow) (NSMI). The NSMI was developed based on time-variant snow surface optical and thermal properties. This research achieved three primary objectives: 1).development of theoretical foundation and surface moisture sensitive algorithm used to track both surface melt and pack discharge potential; 2.) time-dependent phases of coupling and decoupling between snow surface properties and melt discharge were characterized through analysis of long-term surface and sub-surface state variables; 3.) and sensitivity of optical satellite systems specifically, EOS TERRA-MODIS, to melting were was examined through radiative transfer simulations. Simulated at-sensor radiance was produced for various grain size changes to determine MODIS capacity to track melt onset. MODIS wavelengths greater than 667nm were sensitive to large changes in grain sizes, particularly bands with coarse spatial resolution (1000m). Longer wavelengths showed greater sensitivity to small changes in smaller grains than to small changes in larger grains. Shorter wavelengths at 500m spatial resolution appeared less effective overall for monitoring changes in grain size. NMSI feature space using Normalized Difference Snow Index (NDSI) on the abscissa and brightness temperature (Tb) on the ordinate was simulated. Simulated NDSI as a function of grain radius saturated approximately around 400-450 μm. ASTER derived NSMI demonstrated behavior consistent with simulations with deviations due to topography, vegetation, and regional heterogeneity. We examined NSMI performance during an entire melt season through tracking phases of coupling between snow surface properties and propensity for melt using two ground-base approaches; one with higher snow surface spectral information and low temporal resolution, the other with high temporal resolution and coarse spectral information. Phases of decoupling exhibited within ground-based time varying simulated NSMI were regulated by the temporal resolution specified to construct the feature space. Coarser temporal intervals on surface optical/thermal variables correlated the NSMI feature space various components of surface radiative variability. Coarser temporal optical and thermal resolution will tend to reduce variability within the NSMI feature space due to specific snowfall events.
Type:
text; Electronic Dissertation
Keywords:
snowmelt; remote sensing
Degree Name:
PhD
Degree Level:
doctoral
Degree Program:
Geography; Graduate College
Degree Grantor:
University of Arizona
Advisor:
Yool, Stephen R.
Committee Chair:
Yool, Stephen R.

Full metadata record

DC FieldValue Language
dc.language.isoENen_US
dc.titleOptical Remote Sensing for Monitoring Evolution of Ablation Season Mountain Snow Coveren_US
dc.creatorLampkin, Derrick Juliusen_US
dc.contributor.authorLampkin, Derrick Juliusen_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.abstractThe investigations contained in this body of work detail a viable proof-of-concept model for monitoring seasonal snow pack propensity for melt release based on time-variant snow surface optical and thermal properties. The model has been called the Near Surface Moisture Index- (Snow) (NSMI). The NSMI was developed based on time-variant snow surface optical and thermal properties. This research achieved three primary objectives: 1).development of theoretical foundation and surface moisture sensitive algorithm used to track both surface melt and pack discharge potential; 2.) time-dependent phases of coupling and decoupling between snow surface properties and melt discharge were characterized through analysis of long-term surface and sub-surface state variables; 3.) and sensitivity of optical satellite systems specifically, EOS TERRA-MODIS, to melting were was examined through radiative transfer simulations. Simulated at-sensor radiance was produced for various grain size changes to determine MODIS capacity to track melt onset. MODIS wavelengths greater than 667nm were sensitive to large changes in grain sizes, particularly bands with coarse spatial resolution (1000m). Longer wavelengths showed greater sensitivity to small changes in smaller grains than to small changes in larger grains. Shorter wavelengths at 500m spatial resolution appeared less effective overall for monitoring changes in grain size. NMSI feature space using Normalized Difference Snow Index (NDSI) on the abscissa and brightness temperature (Tb) on the ordinate was simulated. Simulated NDSI as a function of grain radius saturated approximately around 400-450 μm. ASTER derived NSMI demonstrated behavior consistent with simulations with deviations due to topography, vegetation, and regional heterogeneity. We examined NSMI performance during an entire melt season through tracking phases of coupling between snow surface properties and propensity for melt using two ground-base approaches; one with higher snow surface spectral information and low temporal resolution, the other with high temporal resolution and coarse spectral information. Phases of decoupling exhibited within ground-based time varying simulated NSMI were regulated by the temporal resolution specified to construct the feature space. Coarser temporal intervals on surface optical/thermal variables correlated the NSMI feature space various components of surface radiative variability. Coarser temporal optical and thermal resolution will tend to reduce variability within the NSMI feature space due to specific snowfall events.en_US
dc.typetexten_US
dc.typeElectronic Dissertationen_US
dc.subjectsnowmelten_US
dc.subjectremote sensingen_US
thesis.degree.namePhDen_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineGeographyen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorYool, Stephen R.en_US
dc.contributor.chairYool, Stephen R.en_US
dc.contributor.committeememberYool, Stephen R.en_US
dc.contributor.committeememberComrie, Andrew C.en_US
dc.contributor.committeememberNolin, Anneen_US
dc.contributor.committeememberMarsh, Stuart E.en_US
dc.identifier.proquest1120en_US
dc.identifier.oclc137354067en_US
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