Hyperspectral Remote Sensing of Vegetation Using Red Edge Position Techniques

Abstract

Two red edge position (REP) techniques, Linear and Lagrangian, were applied on hyperspectral data acquired from the HyMap sensor for a forested area in Thetford Forest, UK. Red edge positions of different vegetation covers were extracted with the two approaches from the hyperspectral data. Based on the estimated REPs, the Linear and Lagrangian interpolation methods were compared with ground reference image to analyse different vegetation types and ages. Experimental results of both interpolation techniques indicate that the wavelength and reflectance of REP for younger plants (higher chlorophyll content) shift towards longer wavelength and of higher reflectance in comparison with older plants (lower chlorophyll content).