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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2014-12-01
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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 |
work_keys_str_mv |
AT bmuller identificationofcatchmentfunctionalunitsbytimeseriesofthermalremotesensingimages AT mbernhardt identificationofcatchmentfunctionalunitsbytimeseriesofthermalremotesensingimages AT kschulz identificationofcatchmentfunctionalunitsbytimeseriesofthermalremotesensingimages |
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