Abstract
Abstract. Tree crown size (CS) and stem number per hectare (SN) has become increasingly important for forest management and ecosystem monitoring. Tree crown size is also strongly related to other canopy structural parameters, such as diameter at breast height, tree height and biomass. For both issues, remote sensing data are attractive for their large-area and up-to-date mapping capacities. The QuickBird and ASTER imagery used in this study was acquired over Zagros Forests in southern Zagros region, Fars province of Iran on 1 August 2005 and 1 July 2005, respectively. For the forest site investigated in this study, we concentrated on stands of Quercus Persica which is the dominant species in Zagros region. This study was conducted to investigate the capabilities of ASTER-L1B data to estimate some of forest parameters at individual tree and stand level in dry area. The forest stand parameters are crown area, crown density, average crown area. Obtaining the accuracy of classification the ground truth map was prepared by tree crown delineation using the panchromatic band of QuickBird data. Individual tree crowns were automatically delineated by color segmentation of QuickBird imagery. Simple linear regression procedure was used to show the relationships between spectral variables and the individual trees and forest stand parameters. With decreasing the crown density the effects of background will increase. Our results indicated that crown size could be accurately extracted from panchromatic band of QuickBird images especially for open forest stands. This paper demonstrates that using high-resolution satellite imagery in the open forest offers a unique opportunity for deriving single tree attributes and allowing reliable ground truth map to estimate stand structure. ASTER data and its indices showed good capability to estimate crown area in this study.
Highlights
There is a growing need to extract forest biophysical parameters, for supporting sustainable forest management
This paper applied color image segmentation to delineate individual tree crowns from QuickBird images to estimate mean tree per hectare for one of the most common tree species in Zagros forest in Iran
The results indicated significant correlation between average crown area per ha and vegetation indices
Summary
There is a growing need to extract forest biophysical parameters, for supporting sustainable forest management These parameters are traditionally estimated using inventory data from field sample plots. Various studies have been done to delineate tree crowns using different methods such as valley following, template matching and region growing (Pinz, 1989; Gougeon, 1995; Culvenor, 2002; Pouliot et al, 2002; Erikson, 2003). Most of these segmentation techniques have been applied in dense coniferous forests using black and with or gray images
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