Application of Remote Sensing and GIS in the Investigating Vegetation Coverage

Rate of change and the destruction of resources of previous years and the feasibility and predict changes of future could be an important step in planning and optimum use of resources and control of non-normative changes for the future. In the last few years due to vegetation changes in the country's western regions fine dusts entry has created many problems for residents in western and central. For this reason, this work focuses on the westernmost region of the country. We apply ETM Landsat satellite images of 2002 and 2012 to predict vegetation changes. Vegetation changes zoning map of the area of study was prepared after geometric correction and radiometric images through combining comparison of images classifications of every two years Using matrix multiplication applications method and appropriate vegetation indices. Our results show among vegetation indices, the SAVI index has the highest correlation coefficient between the quantitative data of canopy cover and its numerical values based on which this index was used to investigating the region vegetation coverage. The vegetation coverage can be categorized in three classes of poor, medium, and fine. In the period of 2002-2012, area of the poor and fine vegetation coverage classes has increased whereas that of the medium class has decreased. The greatest reduction has been occurred in the medium class where the area of coverage decreased from 304 km2 to 173 km2 and the reason for this is the conversion of vegetation areas to desserts. Areas with poor vegetation are the source of fine dusts to the country that require attentions to prevent their extension.