Investigation of Satellite Data Efficiency in Invader Species Zoning (Case Study: Vazroud Rangelands)

Invader species often drive ecological changes that may be irreversible and therefore preclude successful restoration of basins. Thus invasion prevention, early detection and removal of these plants play key roles for controlling and management of them. Remote sensing techniques in invader plants monitoring are memorable to avoid invasion and eradicate or control established invaders. The aim of this paper is investigating the efficiency of Landsat TM and IRS-LISS III data in zonation of invader species of Cirsiumarvense and Stachysbyzanthina in Vazroud rangelands. To gain the optimized results Cos(t) model was used for the atmospheric correction on images and then some vegetation indices were applied with extraction of digital average of pixels related to training samples of corrected images. Minimum distance of mean classifier has been used as classification technique which was evaluated with the ground truth map. The results showed that NDVI,Ratio, RVI, and TVIof TM image and AVI of IRS image are most suitable indices for discriminate the Cirsiumarvense but the best indices for the Stachysbyzanthina were NDVI, PVI 1, PVI 2, RVI and WDVI of TM image and NDVI of IRS image. Also out of the total indices analysed, WDVI and DVI of both images were able to discriminate these species but with varying degrees of separation and can produce well results as a measure separation in future studies.