II) Remote Sensing Monitoring of Vegetation phonological variations.
Based on the processing method described above, we obtain the vegetationindex images of every ten-day of China (including peripheral area), and then sum up the vegetation index of every ten-day of every month, thus get the vegetation index image of every month. NDVI maps are formed by ordering these images by time sequence (month, season, and year). Because the environmental changes and vegetation changes can reflect and indicate each other, we can analyses the changes of environment from these images. By analyzing the vegetation index images from 1989 to 1999 (fig., omitted), we can see its uptrend although NDVI undulate a little between years. By analyzing the vegetation index image in April of 1989, 1993, 1998 (fig.1, fig.2, fig.3), we can see the value of NDVI increase gradually and obviously year by year in most areas of China, particularly in north China. The change of later 5 years is greater than former 5 years; By analyzing the vegetation index images of north east Asia (fig. 4, fig.5), the greatest vegetation change areas from 1989 to 1998 are including north China, LiaoNing, JiLin, HeiLongJiang.Korean peninsula and Russian Baikal lake area. It is hard to discern whether this change is the inherent character of natural change, or is caused by the human activities. But many scientists think that the massive burning of mineral causes the increase of Carbon Dioxide, and warm effect increase temperature. The result from meteorological observation station shows meteorological observation station shows that the increase of air temperature often occurs in winter and spring. The change of temperature cause the vegetation phonological changes. Vegetation grows rather slowly in winter, it is hard to reflect the change of vegetational phenology; while in spring, vegetation is sensitive to temperature, thus the change of vegetational phenology shows very clearly in remote sense image.

III) Conclusion

1. Vegetation index NDVI is an important indicator in measuring environmental changes caused by globe warm effect.
2. The monitoring result obtained through meteorological satellite last decade (1989-1998) shows that the vegetation index changes, especially greatly in spring, which is very obvious in north and northeast China.

References

1. Xiao Qianguang, and Chen Weiying, 1991, Stuy on Montoring Vegetation Ecological vegetation index from meteorological satellit. (Environment monitor and crop yield estimate) Peking university press.
2. Xiao Qianguang etc, 1997, Monitoring the ecological transect in east Asia monsoon region by meteorological satellite remote sensing. (Acta Botanica Sinica) 1997, 39(9): 826-830
3. Xiao Qianguang,Chen WeiyingL Estimating the net primary productivity in China using meteorological satellite data (Acta Botanica Sinica) 1996, 38 91) :35-39.



Figure 1: China vegetation index of April, 1989


Figure 2: China vegetation index of April, 1993


Figure 3: China vegetation index of April, 1998


Figure 4: North Asia vegetation index of April, 1989


Figure 5: North Asia vegetation index of April, 1998

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