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Estimation of Forest Structure Metrics Relevant to Hydrologic Modelling Using Coordinate Transformation of Airborne Laser Scanning Data : Volume 16, Issue 10 (23/10/2012)

By Varhola, A.

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Book Id: WPLBN0004010570
Format Type: PDF Article :
File Size: Pages 18
Reproduction Date: 2015

Title: Estimation of Forest Structure Metrics Relevant to Hydrologic Modelling Using Coordinate Transformation of Airborne Laser Scanning Data : Volume 16, Issue 10 (23/10/2012)  
Author: Varhola, A.
Volume: Vol. 16, Issue 10
Language: English
Subject: Science, Hydrology, Earth
Collections: Periodicals: Journal and Magazine Collection, Copernicus GmbH
Publication Date:
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications


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Teti, P., Coops, N. C., Frazer, G. W., & Varhola, A. (2012). Estimation of Forest Structure Metrics Relevant to Hydrologic Modelling Using Coordinate Transformation of Airborne Laser Scanning Data : Volume 16, Issue 10 (23/10/2012). Retrieved from

Description: Department of Forest Resources Management, University of British Columbia, 2231-2424 Main Mall, Vancouver, BC, V6T 1Z4, Canada. 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.

Estimation of forest structure metrics relevant to hydrologic modelling using coordinate transformation of airborne laser scanning data

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