Articles | Volume 18, issue 12
https://doi.org/10.5194/hess-18-5345-2014
https://doi.org/10.5194/hess-18-5345-2014
Research article
 | 
19 Dec 2014
Research article |  | 19 Dec 2014

Identification of catchment functional units by time series of thermal remote sensing images

B. Müller, M. Bernhardt, and K. Schulz

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Cited articles

Arnold, J. G., Srinivasan, R., Muttiah, R. S., and Williams, J. R.: Large area hydrologic modeling and assessment Part I: Model development, J. Am. Water Resour. As., 34, 73–89, https://doi.org/10.1111/j.1752-1688.1998.tb05961.x, 1998.
Asner, G. P., Scurlock, J. M. O., and Hicke, J. A.: Global synthesis of leaf area index observations: implications for ecological and remote sensing studies, Global Ecol. Biogeogr., 12, 191–205, https://doi.org/10.1046/j.1466-822X.2003.00026.x, 2003.
Beven, K. J. and Kirkby, M. J.: A physically based, variable contributing area model of catchment hydrology, Hydrological Sciences Bulletin, 24, 43–69, https://doi.org/10.1080/02626667909491834, 1979.
Bolle, H.-J., Feddes, R. A., and Kalma, J. D. (Eds.): Exchange processes at the land surface for a range of space and time scales, in: Proceedings of Symposium J3.1, Joint Scientific Assembly of IAMAP and IAHS, Yokohama, Japan, 11–23 July 1993, 626 pp., 1993.
CAOS: CAOS – Catchments as Organised Systems, available at: http://www.caos-project.de (last access: 22 May 2014), 2014.
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Short summary
We present a method to define hydrological landscape units by a time series of thermal infrared satellite data. Land surface temperature is calculated for 28 images in 12 years for a catchment in Luxembourg. Pattern measures show spatio-temporal persistency; principle component analysis extracts relevant patterns. Functional units represent similar behaving entities based on a representative set of images. Resulting classification and patterns are discussed regarding potential applications.