Evaluation of vegetation changes in desertification projects using remote sensing techniques in Bam, Shahdad and Garmsar regions, Iran

The face of the earth is always changing due to human activities and natural phenomena. Therefore, to optimize the management of the natural areas, knowledge of the trend, extent and estimation of land cover / use changes is considered necessary. Reviewing these changes through satellite images and evaluating their potential through modeling can help environmental planners and natural resource managers to make more informed decisions. In the present study, quantitative detection and evaluation of changes in vegetation were performed in the areas with combat desertification projects, Shahdad, Bam and Garmsar in Iran, during a 30-year period within 1987, 2002 and 2017. The Normalized Difference Vegetation Index (NDVI) and land use maps were produced using the Enhanced Thematic Mapper Plus (ETM+), Thematic Mapper (TM) and Operational Land Imager (OLI) satellite images in the three corresponding periods for the vegetation/non-vegetation, and agricultural lands. The Kappa coefficient of 0.83 to 0.86, 0.91 to 0.92, and 0.94 to 0.95 was calculated for 1987, 2002, and 2017 respectively, and the total accuracy was between 88 and 97. After providing the land use maps in different years, the monitoring of land use changes was investigated using the Change Detection method. According to the trend of changes during the periods, the results exhibited that the vegetated lands in these three areas had an increasing trend in average 31.33%, and the non-vegetated lands were turned to vegetated lands over time. In other words, they have declined by an average of 35%. Moreover, an increasing trend was found for the agricultural lands during the periods in average 4%. Eventually, the cost-effectiveness of projects implemented in the studied areas was calculated.

Evaluation of vegetation changes in desertification projects using remote sensing techniques in Bam, Shahdad and Garmsar regions, Iran Keywords:

Vegetation changes , remote sensing , Trend determination , change detection