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Water Availability in the Aral Sea Basin: Derivation of Fractional Vegetation Covers from Multi-scale Remote Sensing Data for Hydrological Modeling in Central Asia

Asam, Sarah (2010) Water Availability in the Aral Sea Basin: Derivation of Fractional Vegetation Covers from Multi-scale Remote Sensing Data for Hydrological Modeling in Central Asia. Masterarbeit, Julius-Maximilians-Universität Würzburg.

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Kurzfassung

As Central Asia faces various water-related problems, a sustainable and transnational water management is needed, in particular for the regions specialized in the production of water-intensive crops, such as cotton. Regional hydrological models can provide an insight into water cycles and projections of the water availability under changing climatic conditions. Land cover information that describes the vegetation cover provides important input for the parameterization of such hydrologic models. Thereby, mostly rather rough and discrete land cover classes are used. However the percentage cover of woody and herbaceous life forms as well as bare soil fractions would meet this high information requirement, e.g. for the calculation of infiltration rates, better. The aim of this study is therefore to describe in detail the small-scale vegetation patterns of a high mountain ecosystem in Central Asia. For mapping fractions of vegetation cover, multi-scale remote sensing data is analyzed in conjunction with vegetation field data. Vegetation data was collected on a training site in the upper reaches of the Naryn River, Kyrgyzstan, providing water for the upper Syr Darya and the Fergana valley. The ground truth samples were used in a hybrid classification scheme applied to spatially very high resolution (0.6 m) satellite data, a QuickBird scene of 80 km2. The areas covered by woody vegetation are thereby detected as objects after a segmentation process. The open areas with varying fractions of herbaceous vegetation and bare soil are classified with the Maximum Likelihood algorithm to record this heterogeneity on a pixel base. A map for each single cover type is derived from this classification. By aggregating the results to the Landsat TM spatial resolution of 30 m, continuous cover fractions for each cover type are gained. Using the regression tree ensemble method „random forest‟, this land cover fraction information is extrapolated to the whole 180 x 190 km2 area of the Landsat TM tile. The resulting land cover product is validated with reference pixels from the QuickBird classification. The accuracy of the maps is between 85 and 92 % for the various cover types. The continuous cover fractions of woody, herbaceous and uncovered soil can be used as detailed input parameters for hydrological modeling. Besides modeling, the continuous cover can be applied for biodiversity research or vegetation pattern analysis and therefore on erosion risk assessment in mountainous areas, as it is shown in the last chapter of this thesis.

Dokumentart:Hochschulschrift (Masterarbeit)
Titel:Water Availability in the Aral Sea Basin: Derivation of Fractional Vegetation Covers from Multi-scale Remote Sensing Data for Hydrological Modeling in Central Asia
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID
Asam, Sarahsarah.asam@dlr.deNICHT SPEZIFIZIERT
Datum:Juni 2010
In Open Access:Nein
In SCOPUS:Nein
In ISI Web of Science:Nein
Seitenanzahl:117
Status:veröffentlicht
Stichwörter:Fernerkundung, fractional cover, Quickbird, Landsat, Random Forest
Institution:Julius-Maximilians-Universität Würzburg
Abteilung:Lehrstuhl für Fernerkundung
HGF - Forschungsbereich:Verkehr und Weltraum (alt)
HGF - Programm:Weltraum (alt)
HGF - Programmthema:W EO - Erdbeobachtung
DLR - Schwerpunkt:Weltraum
DLR - Forschungsgebiet:W EO - Erdbeobachtung
DLR - Teilgebiet (Projekt, Vorhaben):W - Vorhaben Geowissenschaftl. Fernerkundungs- und GIS-Verfahren (alt)
Standort: Oberpfaffenhofen
Institute & Einrichtungen:Deutsches Fernerkundungsdatenzentrum
Hinterlegt von: Kübert, Carina
Hinterlegt am:09 Mai 2011 12:51
Letzte Änderung:28 Nov 2016 12:50

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