The vegetation fractional coverage (VFC), which represents the horizontal density of live vegetation, is of particular importance for regional and global carbon modeling, ecological assessment, and agricultural monitoring. In this paper, we compared a set of methods for estimating major changes of VFC dynamics during the years of 2000 to 2015 of the whole Iran. The dates of the remote sensing imagery used for this study coincide temporally, and fall within a period of the growing season (April to October). Plus, the main method was performed using a cloud-free Modis NDVI images. The VFC was directly acquired on NDVI images, and time series analysis of VFC was predicted subsequently. To develop models to estimate VFC, the spatial pattern of VFC changes were classified into four categories in 2000, 2005, 2010 and 2015 separately, and we were accordingly derived different coverage, on different VFC ranges. Further, Compounded Night Light Index (CNLI) was computed by meteorological satellite program/optical line-scan system (DMSP/OLS) datasets to monitoring human activity. Forasmuch as, the driving factors of VFC dynamics were based on human activities and climatic factors; Pearson correlation confirmed the relationship between driving factors with predicted VFC and accuracy of description distinctly. Consequently the result showed that VFC is moderately correlated with rainfall (mm) and temperature (°C) annually, and specially related to CNLI at wide scale over research period of about 16 years, thus the driving forces of vegetation degradation such as drought, urbanization and industrialization can be effective on the change of VFC periodically.
Key words: NDVI; VFC; DMSP/OLS; CNLI; Driving Factor; Iran.
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