Sensitivity Analysis of Support Vector Machine Predictions of Passive Microwave Brightness Temperatures over Snow-Covered Terrain in High Mountain Asia
Başlık:
Sensitivity Analysis of Support Vector Machine Predictions of Passive Microwave Brightness Temperatures over Snow-Covered Terrain in High Mountain Asia
Yazar:
Ahmad, Jawairia Ashfaq, author.
ISBN:
9780438145870
Yazar Ek Girişi:
Fiziksel Tanımlama:
1 electronic resource (111 pages)
Genel Not:
Source: Masters Abstracts International, Volume: 57-06M(E).
Advisors: Barton A. Forman Committee members: Kaye L. Brubaker; Richard H. McCuen.
Özet:
Spatial and temporal variation of snow in High Mountain Asia is very critical as it determines contribution of snowmelt to the freshwater supply of over 136 million people. Support vector machine (SVM) prediction of passive microwave brightness temperature spectral difference (DeltaTb) as a function of NASA Land Information System (LIS) modeled geophysical states is investigated through a sensitivity analysis. AMSRE DeltaTb measurements over snow-covered areas in the Indus basin are used for training the SVMs. Sensitivity analysis results conform with the known first-order physics. LIS input states that are directly linked to physical temperature demonstrate relatively higher sensitivity. Accuracy of LIS modeled states is further assessed through a comparative analysis between LIS derived and Advanced Scatterometer based Freeze/Melt/Thaw categorical datasets. Highest agreement of 22%, between the two datasets, is observed for freeze state. Analyses results provide insight into LIS's land surface modeling ability over the Indus Basin.
Notlar:
School code: 0117
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Yer Numarası | Demirbaş Numarası | Shelf Location | Lokasyon / Statüsü / İade Tarihi |
---|---|---|---|
XX(690932.1) | 690932-1001 | Proquest E-Tez Koleksiyonu | Arıyor... |
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