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| Titel |
Spatial heterogeneity of satellite derived land surface parameters and energy flux densities for LITFASS-area |
| VerfasserIn |
A. Tittebrand, F. H. Berger |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1680-7316
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Chemistry and Physics ; 9, no. 6 ; Nr. 9, no. 6 (2009-03-23), S.2075-2087 |
| Datensatznummer |
250007095
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| Publikation (Nr.) |
 copernicus.org/acp-9-2075-2009.pdf |
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| Zusammenfassung |
Based on satellite data in different temporal and spatial resolution, the
current use of frequency distribution functions (PDF) for surface parameters
and energy fluxes is one of the most promising ways to describe subgrid
heterogeneity of a landscape. Objective of this study is to find typical
distribution patterns of parameters (albedo, NDVI) for the determination of
the actual latent heat flux (L.E) determined from highly resolved satellite data
within pixel on coarser scale.
Landsat ETM+, Terra MODIS and NOAA-AVHRR surface temperature and spectral
reflectance were used to infer further surface parameters and radiant- and
energy flux densities for LITFASS-area, a 20×20 km2 heterogeneous
area in Eastern Germany, mainly characterised by the land use types forest,
crop, grass and water. Based on the Penman-Monteith-approach L.E, as key
quantity of the hydrological cycle, is determined for each sensor in the
accordant spatial resolution with an improved parametrisation. However,
using three sensors, significant discrepancies between the inferred
parameters can cause flux distinctions resultant from differences of the
sensor filter response functions or atmospheric correction methods. The
approximation of MODIS- and AVHRR- derived surface parameters to the
reference parameters of ETM (via regression lines and histogram stretching,
respectively), further the use of accurate land use classifications
(CORINE and a new Landsat-classification), and a consistent parametrisation for the three sensors were
realized to obtain a uniform base for investigations of the spatial
variability.
The analyses for 4 scenes in 2002 and 2003 showed that for forest clear
distribution-patterns for NDVI and albedo are found. Grass and crop
distributions show higher variability and differ significantly to each other
in NDVI but only marginal in albedo. Regarding NDVI-distribution functions NDVI was
found to be the key variable for L.E-determination. |
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