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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
Sprache Englisch
ISSN 1027-5606
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
Publikation (Nr.) Volltext-Dokument vorhandencopernicus.org/hess-16-3749-2012.pdf
 
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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