Articles | Volume 20, issue 9
https://doi.org/10.5194/hess-20-3765-2016
https://doi.org/10.5194/hess-20-3765-2016
Research article
 | 
12 Sep 2016
Research article |  | 12 Sep 2016

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

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

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Manuscript not accepted for further review
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Cited articles

AAFC: Agriculture and Agri-Food Canada, The National Soil DataBase (NSDB), http://sis.agr.gc.ca/cansis/nsdb/index.html, last access: 17 July 2015.
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Short summary
A technology for the spatial derivation of soil texture classes is presented. Information about soil texture is key for predicting the local and regional hydrological cycle. It is needed for the calculation of soil water movement, the share of surface runoff, the evapotranspiration rate and others. Nevertheless, the derivation of soil texture classes is expensive and time-consuming. The presented technique uses soil samples and remotely sensed data for estimating their spatial distribution.