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Accueil du site → Doctorat → Royaume-Uni → 1999 → Passive microwave monitoring of snow cover and rainfall over Iran, using DMSP F-11 special sensor microwave/imager data

University of Bristol (1999)

Passive microwave monitoring of snow cover and rainfall over Iran, using DMSP F-11 special sensor microwave/imager data

Matkan, A.A

Titre : Passive microwave monitoring of snow cover and rainfall over Iran, using DMSP F-11 special sensor microwave/imager data

Auteur : Matkan, A.A

Université de soutenance : University of Bristol

Grade : Doctor of Philosophy (PhD) 1999

Résumé
The objective of this research was to investigate the potential remote sensing of precipitation over Iran, using passive microwave satellite imagery over Iran. To this end, satellite passive microwave data were analyzed to establish and demonstrate the utility of one particular remote sensing application.An appropriate algorithm (Grody and Basist, 1994) was used to separate the snow cover signature from all other atmospheric and surface parameters observed by the SSMI/I satellite, in order to establish than annual number of snow days. Maps of snow cover derived from this algorithm showed how both the distribution of snow cover and the number of snow days in Iran can be monitored from space by passive microwave emission. Since most parts of Iran are either cold desert or frozen ground in winter, especially at high elevations, results from this technique provide a promising way of retrieving accurate data on snow cover in this country.In the case of snow depth, possible relationships between ground-truth data and SSMI/I-derived snow depth observations over Iran were examined. Results derived from two existing algorithms (Chang, 1987 and Rott, 1991) were examined. A new snow depth algorithm (Matkan) based on a single channel (V37 GHz) was developed. To help identify appropriate method(s) for the best overall results, a statistical comparison was made between the results of these three algorithms and the available in situ data. Comparison of the three algorithm products with ground-truth data indicated that images from Chang and Matkan showed appreciably more snow than the Rott algorithm, and results from the Rott algorithm showed that snow depth was being underestimated throughout the snowy regions. One of the results of this research is that SSM/I has difficulty estimating the depth of fresh snow that is wet.

Présentation (EThOS)

Accès au document : Proquest Dissertations & Theses

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