Remote Sensing of Reedbeds

Abstract submitted to "30th EARSeL Symposium: Remote Sensing for Science, Education and Culture"
Remote Sensing of Reedbeds
Remote sensing of reedbeds
Alex O. Onojeghuo
LANCASTER ENVIRONMENT CENTRE
United Kingdom
George A Blackburn
LANCASTER ENVIRONMENT CENTRE
United Kingdom
Keywords: Reedbed, classification, hyperspectral, Quickbird, LiDAR
Presentation preference: oral

In the UK reedbeds dominated by Phragmites australis have been identified as a priority habitat for most regional Biodiversity Partnerships. Information on the current distribution and quality of reedbed sites across the UK is lacking, yet such information is vital in developing suitable management plans for the conservation and expansion of this threatened habitat. The aim of this study was to develop a suitable methodology for accurately mapping the distribution and assessing the status of reedbed habitats using remotely-sensed imagery. Three study sites situated in the North West region of the UK were used: Leighton Moss nature reserve in Lancashire, and River Leven and Esthwaite Water situated in Cumbria. At each of the sites satellite and airborne imagery were acquired along with ground-based spectral and canopy biophysical data. The study demonstrated that a methodology based on analysis of image texture was able to accurately map reedbeds using high resolution QuickBird multispectral data acquired in winter (November 2008). By analysing multi-seasonal (winter and summer) QuickBird data it was possible to improve the accuracy of reedbed delineation. Using in situ data from a field spectroradiometer, variations in the spectral reflectance of reedbeds were measured throughout the seasonal phenological cycle and optimal spectral indices for quantifying canopy biophysical properties were identified. The potential for quantifying canopy biophysical properties from LiDAR data obtained during the leaf-off period was also investigated. While accurate estimates of canopy height could be derived from first return data, and this is a valuable indicator of habitat quality, the lack of any subsequent returns from reedbeds prevented the extraction of any further biophysical variables. Current work is investigating the combination of hyperspectral and LiDAR data for improving the accuracy of reedbed mapping and quantifying canopy biophysical properties.

Fulltext: c20-a1931-alex_onojeghuo_earsel_paper.doc