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27 September 2006 The vegetation cover changes of regress analysis on using time-serial images of remote sensing
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Abstract
There are many means to monitor the Land Use and Land Cover Change (LUCC) in time. Phase difference Image, is one of these means that is often used. By using gaps images to analyze the changes, errors in result images happen easily by accident. Another disadvantage of Phase difference Image is not adequately using the time-serial images. The pixel at the same position in time-serial images will structure a sequence change of points, this sequence include information of LUCC, and it is important to describe the change process of those points for understanding the change of Land Cover. In this paper, we use Fractional Vegetation Cover (FVC) images that were derived from NOAA/AVHRR time series data from 1982 to 2000 and time (year) is the independent variable. Every pixel is an attributive variable, using the regress method to analyze the change of vegetaion cover in Westen China. Meanwhile, we discuss the results and significance of the F-test and t-test for this regression. Through the above work: 1) the result of the regression method for time series data is more stabilizing than Phase Difference Image; 2) Regression method can be used to forecast the change of vegetation and Phase difference image can not; 3) By the regression image, we can find that the increase of vegetation cover is close relationship with old oasis, and that human activities is obviously one of the most important factors contributing to the change of vegetation cover in the arid lands in Westen China. In Qaidam High Basin, there are few signs of human habitation, the vegetation cover decreased, indicating the environment has degraded in this area.
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Qingdong Shi, Guanghui Lv, Jiagou Qi, and Hamid Yimit "The vegetation cover changes of regress analysis on using time-serial images of remote sensing", Proc. SPIE 6298, Remote Sensing and Modeling of Ecosystems for Sustainability III, 62981D (27 September 2006); https://doi.org/10.1117/12.680303
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