Presentation of Suitable Model to Estimate Vegetation Fraction Using Satellite Images in Arid Region (Case Study: Sadough-Yazd, Iran)

One of the influential tools concerning the rangeland and vegetation sciences is the technology of remote sensing and satellite data. Satellite data have played essential roles in preparing the needed information for studying the vegetation. Vegetation has been widely recognized as one of the best indicators for determining the land conditions. Using vegetation indices is one of the techniques of remote sensing to study the vegetation. The purpose of this research is to study the vegetation indices and also provide an appropriate mathematical model for estimating the vegetation fraction using the mentioned indicators. In this research, different vegetation indices were calculated by Landsat TM (2006) satellite images in order to evaluate their capability to estimate the vegetation in the arid regions. At the outset, vegetation fraction was measured using the sample quadrates and then the measured data were compared with the values of digital numbers for the site pixels. Multiple regression analysis was utilized for the actual values and parameters to select the validation and optimization models. Indices which have been calculated include MSR, DVI, TRVI, SARVI, SR, RDVI, DVI, NDVI, SAVI, ARVI and MSAVI. The results showed that the model in which ARVI was used had the highest accuracy (R2=0.86) and therefore, it was chosen as the most suitable model for the estimation of vegetation fraction in the study area. One accomplishment of the above results is to suggest some mathematical equations with those indices to estimate the amount of vegetation. These results provide a strong foundation for the use of some vegetation indices for assessing the vegetation cover in central Iran.