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

The identification of catchment functional behavior with regards to water and energy balance is an important step during the parameterization of land surface models. <br><br> An approach based on time series of thermal infrared (TIR) data from remote sensing is developed and investigated...

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Main Authors: B. Müller, M. Bernhardt, K. Schulz
Format: Article
Language:English
Published: Copernicus Publications 2014-12-01
Series:Hydrology and Earth System Sciences
Online Access:http://www.hydrol-earth-syst-sci.net/18/5345/2014/hess-18-5345-2014.pdf
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spelling doaj-640ec98a1c15411d830e01ee43e824a92020-11-24T23:28:17ZengCopernicus PublicationsHydrology and Earth System Sciences1027-56061607-79382014-12-0118125345535910.5194/hess-18-5345-2014Identification of catchment functional units by time series of thermal remote sensing imagesB. Müller0M. Bernhardt1K. Schulz2Institute of Water Management, Hydrology and Hydraulic Engineering, University of Natural Resources and Life Sciences, Vienna, AustriaDepartment of Geography, Ludwig-Maximilians-Universität, Munich, GermanyInstitute of Water Management, Hydrology and Hydraulic Engineering, University of Natural Resources and Life Sciences, Vienna, AustriaThe identification of catchment functional behavior with regards to water and energy balance is an important step during the parameterization of land surface models. <br><br> An approach based on time series of thermal infrared (TIR) data from remote sensing is developed and investigated to identify land surface functioning as is represented in the temporal dynamics of land surface temperature (LST). <br><br> For the mesoscale Attert catchment in midwestern Luxembourg, a time series of 28 TIR images from ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) was extracted and analyzed, applying a novel process chain. <br><br> First, the application of mathematical–statistical pattern analysis techniques demonstrated a strong degree of pattern persistency in the data. Dominant LST patterns over a period of 12 years were then extracted by a principal component analysis. Component values of the two most dominant components could be related for each land surface pixel to land use data and geology, respectively. The application of a data condensation technique ("binary words") extracting distinct differences in the LST dynamics allowed the separation into landscape units that show similar behavior under radiation-driven conditions. <br><br> It is further outlined that both information component values from principal component analysis (PCA), as well as the functional units from the binary words classification, will highly improve the conceptualization and parameterization of land surface models and the planning of observational networks within a catchment.http://www.hydrol-earth-syst-sci.net/18/5345/2014/hess-18-5345-2014.pdf
collection DOAJ
language English
format Article
sources DOAJ
author B. Müller
M. Bernhardt
K. Schulz
spellingShingle B. Müller
M. Bernhardt
K. Schulz
Identification of catchment functional units by time series of thermal remote sensing images
Hydrology and Earth System Sciences
author_facet B. Müller
M. Bernhardt
K. Schulz
author_sort B. Müller
title Identification of catchment functional units by time series of thermal remote sensing images
title_short Identification of catchment functional units by time series of thermal remote sensing images
title_full Identification of catchment functional units by time series of thermal remote sensing images
title_fullStr Identification of catchment functional units by time series of thermal remote sensing images
title_full_unstemmed Identification of catchment functional units by time series of thermal remote sensing images
title_sort identification of catchment functional units by time series of thermal remote sensing images
publisher Copernicus Publications
series Hydrology and Earth System Sciences
issn 1027-5606
1607-7938
publishDate 2014-12-01
description The identification of catchment functional behavior with regards to water and energy balance is an important step during the parameterization of land surface models. <br><br> An approach based on time series of thermal infrared (TIR) data from remote sensing is developed and investigated to identify land surface functioning as is represented in the temporal dynamics of land surface temperature (LST). <br><br> For the mesoscale Attert catchment in midwestern Luxembourg, a time series of 28 TIR images from ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) was extracted and analyzed, applying a novel process chain. <br><br> First, the application of mathematical–statistical pattern analysis techniques demonstrated a strong degree of pattern persistency in the data. Dominant LST patterns over a period of 12 years were then extracted by a principal component analysis. Component values of the two most dominant components could be related for each land surface pixel to land use data and geology, respectively. The application of a data condensation technique ("binary words") extracting distinct differences in the LST dynamics allowed the separation into landscape units that show similar behavior under radiation-driven conditions. <br><br> It is further outlined that both information component values from principal component analysis (PCA), as well as the functional units from the binary words classification, will highly improve the conceptualization and parameterization of land surface models and the planning of observational networks within a catchment.
url http://www.hydrol-earth-syst-sci.net/18/5345/2014/hess-18-5345-2014.pdf
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