Skip to Main Content
 

Global Search Box

 
 
 
 

Files

File List


VanderJagt_Final.pdf (25.15 MB)

ETD Abstract Container

Abstract Header

On the characterization of subpixel effects for passive microwave remote sensing of snow in montane environments

Vander Jagt, Benjamin J
http://rave.ohiolink.edu/etdc/view?acc_num=osu1449233895

Abstract Details

2015, Doctor of Philosophy, Ohio State University, Geodetic Science and Surveying.
Snow and its water equivalent plays a vital role in global water and energy balances, with particular relevance in mountainous areas with arid and semi-arid climate regimes. Spaceborne passive microwave (PM) remote sensing measurements are attractive for snowpack characterization due to their continuous global coverage and historical record; over 30 years of research has been invested in the development of methods to characterize large-scale snow water resources from PM-based measurements. Historically, use of PM data for snowpack characterization in montane enviroments has been obstructed by the complex subpixel variability of snow properties within the PM measurement footprint. The main subpixel effects can be grouped as: the effect of snow microstructure (e.g. snow grain size) and stratigraphy on snow microwave emission, vegetation attenuation of PM measurements, and the sensitivity PM brightness temperature (Tb) observation to the variability of different subpixel properties at spaceborne measurement scales. This dissertation is focused on a systematic examination of these issues, which thus far have prevented the widespread integration of snow water equivalent (SWE) retrieval methods. It is meant to further our comprehension of the underlying processes at work in these rugged, remote, a hydrologically important areas. The role that snow microstructure plays in the PM retrievals of SWE is examined first. Traditional estimates of grain size are subjective and prone to error. Objective techniques to characterize grain size are described and implemented, including near infrared (NIR), stereology, and autocorrelation based approaches. Results from an intensive Colorado field study in which independent estimates of grain size and their modeled brightness temperature (Tb) emission are evaluated against PM Tb observations are included. The coarse resolution of the passive microwave measurements provides additional challenges when trying to resolve snow states via remote sensing observations. The natural heterogeneity of snowpack (e.g. depth, stratigraphy, etc) and vegetative states within the PM footprint occurs at spatial scales smaller than PM observation scales. The sensitivity to changes in snow depth given sub-pixel variability in snow and vegetation is explored and quantified using the comprehensive dataset acquired during the Cold Land Processes experiment (CLPX). Lastly, vegetation has long been an obstacle in efforts to derive snow depth and mass estimates from passive microwave (PM) measurements of brightness temperature (Tb). We introduce a vegetation transmissivity model that is derived entirely from multi-scale and multi-temporal PM Tb observations and a globally available vegetation dataset, specifically the Leaf Area Index (LAI). This newly constructed model characterizes the attenuation of PM Tb observations at frequencies typically employed for snow retrieval algorithms, as a function of LAI. Additionally, the model is used to predict how much SWE is observable within the major river basins of Colorado and the central Rockies.
Michael Durand (Advisor)
Howat Ian (Committee Member)
Alsdorf Doug (Committee Member)
164 p.
Hydrologic Sciences; Hydrology
Snow; Passive microwave remote sensing; Hydrology; Scaling

Recommended Citations

Citations

  • Vander Jagt, B. J. (2015). On the characterization of subpixel effects for passive microwave remote sensing of snow in montane environments [Doctoral dissertation, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1449233895

    APA Style (7th edition)

  • Vander Jagt, Benjamin. On the characterization of subpixel effects for passive microwave remote sensing of snow in montane environments. 2015. Ohio State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1449233895.

    MLA Style (8th edition)

  • Vander Jagt, Benjamin. "On the characterization of subpixel effects for passive microwave remote sensing of snow in montane environments." Doctoral dissertation, Ohio State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=osu1449233895

    Chicago Manual of Style (17th edition)

osu1449233895
232
© 2015, all rights reserved.
This open access ETD is published by The Ohio State University and OhioLINK.