Comparison of pixel and sub-pixel based techniques to separate Pteronia incana invaded areas using multi-temporal high resolution imagery

Abstract

Remote Sensing using high resolution imagery (HRI) is fast becoming an important tool in detailed land-cover mapping and analysis of plant species invasion. In this study, we sought to test the separability of Pteronia incana invader species by pixel content aggregation and pixel content de-convolution using multi-temporal infrared HRI. An invaded area in Eastern Cape, South Africa was flown in 2001, 2004 and 2006 and HRI of 1x1m resolution captured using a DCS 420 colour infrared camera. The images were separated into bands, geo-rectified and radiometrically corrected using Idrisi Kilimanjaro GIS. Value files were extracted from the bands in order to compare spectral values for P. incana, green vegetation and bare surfaces using the pixel based Perpendicular Vegetation Index (PVI), while Constrained Linear Spectral Unmixing (CLSU) surface endmembers were used to generate sub-pixel land surface image fractions. Spectroscopy was used to validate spectral trends identified from HRI. The PVI successfully separated the multi-temporal imagery surfaces and was consistent with the unmixed surface image fractions from CLSU. Separability between the respective surfaces was also achieved using reflectance measurements.