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Estimating spatially distributed soil texture using time series of thermal remote sensing - A case study in central Europe

Müller, Benjamin; Bernhardt, Matthias; Jackisch, Conrad; Schulz, Karsten

For understanding water and solute transport processes, knowledge about the respective hydraulic properties is necessary. Commonly, hydraulic parameters are estimated via pedo-transfer functions using soil texture data to avoid cost-intensive measurements of hydraulic parameters in the laboratory. Therefore, current soil texture information is only available at a coarse spatial resolution of 250 to 1000 m. Here, a method is presented to derive high-resolution (15 m) spatial topsoil texture patterns for the meso-scale Attert catchment (Luxembourg, 288 km2) from 28 images of ASTER (advanced spaceborne thermal emission and reflection radiometer) thermal remote sensing. A principle component analysis of the images reveals the most dominant thermal patterns (principle components, PCs) that are related to 212 fractional soil texture samples. Within a multiple linear regression framework, distributed soil texture information is estimated and related uncertainties are assessed. An overall root mean squared error (RMSE) of 12.7 percentage points (pp) lies well within and even below the range of recent studies on soil texture estimation, while requiring sparser sample setups and a less diverse set of basic spatial input. ... mehr

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Volltext §
DOI: 10.5445/IR/1000059783
DOI: 10.5194/hess-20-3765-2016
Zitationen: 9
Web of Science
Zitationen: 7
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Wasser und Gewässerentwicklung (IWG)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2016
Sprache Englisch
Identifikator ISSN: 1027-5606, 1607-7938
KITopen-ID: 1000059783
Erschienen in Hydrology and earth system sciences
Band 20
Heft 9
Seiten 3765-3775
Nachgewiesen in Web of Science
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