Detection Fractional Vegetation Cover Changes Using MODIS Data

Monitoring seasonal changes in vegetation activity over wide areas is essential for many applications, Satellite remote sensing offers a systematic and objective means for detecting and monitoring ecological environment.A large amount of satellite remote sensing data at different spatial, spectral and temporal resolutions was proved to estimate Land cove change.One of the most widely used approaches is image differencing, according to which the images acquired at two dates are subtracted in order to produce a difference image to be analyzed. In this paper A new algorithm of Fractional vegetation cover (FVC) change detection is put forward to analyze the variability of vegetation cover dynamics using multitemporal analysis of  MODIS data, the difference image can therefore be divided into many classes: increase and decrease by the optimal threshold. In the result, the FVC change detection map is generated directly from satellite images without any ground truth about the considered area and available for monitoring and evaluation FVC change but improvement is still needed.