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| Titel |
Estimation of forest structure metrics relevant to hydrologic modelling using coordinate transformation of airborne laser scanning data |
| VerfasserIn |
A. Varhola, G. W. Frazer, P. Teti, N. C. Coops |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1027-5606
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| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 16, no. 10 ; Nr. 16, no. 10 (2012-10-23), S.3749-3766 |
| Datensatznummer |
250013527
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| Publikation (Nr.) |
 copernicus.org/hess-16-3749-2012.pdf |
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| Zusammenfassung |
| An accurate characterisation of the complex and
heterogeneous forest architecture is necessary to parameterise
physically-based hydrologic models that simulate precipitation interception,
energy fluxes and water dynamics. While hemispherical photography has become
a popular method to obtain a number of forest canopy structure metrics
relevant to these processes, image acquisition is field-intensive and,
therefore, difficult to apply across the landscape. In contrast, airborne
laser scanning (ALS) is a remote-sensing technique increasingly used to
acquire detailed information on the spatial structure of forest canopies
over large, continuous areas. This study presents a novel methodology to
calibrate ALS data with in situ optical hemispherical camera images to
obtain traditional forest structure and solar radiation metrics. The
approach minimises geometrical differences between these two techniques by
transforming the Cartesian coordinates of ALS data to generate synthetic
images with a polar projection directly comparable to optical photography.
We demonstrate how these new coordinate-transformed ALS metrics, along with
additional standard ALS variables, can be used as predictors in multiple
linear regression approaches to estimate forest structure and solar
radiation indices at any individual location within the extent of an ALS
transect. We expect this approach to substantially reduce fieldwork costs,
broaden sampling design possibilities, and improve the spatial
representation of forest structure metrics directly relevant to parameterising
fully-distributed hydrologic models. |
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