Study On The Dynamic Change Of Vegetation In The Changbai Mountain Area Based On Multi-source Remote Sensing Data

This paper analyzed the intra-annual and inter-annual variation of vegetation types and vegetation cover in Changbai Mountain by using Landsat data, MODIS data, topographic map, climate data and et al. Principally, this paper included the research of inter-annual variation of vegetation types based on Landsat data and the research of intra-annual and inter-annual variation of vegetation cover based on MODIS data.Firstly, this paper analyzed the variation of vegetation types and the driving forces during the past 50 years in Changbai Mountain based on the Landsat data, topographic map, and statistical data of nature and human. The results show that: the vegetation types changed obviously during the past 50 years, and the variation modes were dissimilar in the Forestry Bureau, the National Reserve Bureau and the nearby DPRK border area caused by the different management systems. In the Forestry Bureau of China, the area of forest decreased obviously and the area of grassland increased rapidly during the initial 20 years. After the Reform and Opening in China, the vegetation types changed slowly. And the area of forest increased in some regions. In the Changbai Mountain National Reserve Bureau, the vegetation types changed insignificantly before 1986. Impacted by the No.15 typhoon in 1986, the typhoon-striked area was appeared in the west and south slope where the virgin forest was destroyed seriously and the area was larger than 10 thousand hectare. Therefore, during the past 20 years after the typhoon, the vegetation had been recovered significantly in the Changbai Mountain National Reserve Bureau. In the nearby DPRK border area, the vegetation types changed frequently before 1999 impacted by the related policy in DPRK. During the past 50 years, the variation of vegetation types mainly included the decrease of forest and the increase of farmland. Otherwise, the prime driving force of vegetation change was terrain. And distinguished from the other region, the forest and grassland were developed in high elevation and slope area to adapt the production planning in the nearby DPRK border area.Secondly, based on the MODIS-NDVI 250m resolution data, regional map and vegetation map, this paper analyzed the intra-annual and inter-annual variation of vegetation cover and responses of the vegetation cover to climate change in Changbai Mountain by using the HANTS, imagery processing methods and statistical methods. Then further analyses were carried into different sub-regions and different vegetation types. The results show that:the vegetation variation trends were increased from 2000 to 2008 as a whole; the increase was particular obvious in Autumn, otherwise, the vegetation variation was insignificant in Summer and the NDVI decreased slowly in Spring; the NDVI was much higher and increased more rapidly in the Helong Forestry Bureau, Lushuihe Forestry Bureau and Changbai Mountain National Reserve Bureau than Quanyang Forestry Bureau, Changbai Forestry Bureau and the nearby DPRK border area; though the NDVI of the grassland, marsh, betula ermanii forest and tundra were less than the coniferous forest, broadleaf forest and, the former grow faster than the later in vegetation cover.In the Changbai Mountain area, the annual temperature and precipitation were on the ascendance; among the main responses to climate change, the temperature was the dominant factor. The vegetation cover had significant positive correlations with the temperature in spring and autumn while the high temperature had negative effects on plant growth in summer. Though vegetation cover had some correlations with the precipitation, the pixels of significant correlations were limited. In the analysis of the intra-annual responses, the correlation statistics in different months could reveal changes in a more detailed way. According to the progressive average of the first three seasons, the correlation of vegetation cover with temperature and precipitation were not significant, nevertheless, the vegetation cover had significant positive correlations with the temperature in spring and autumn, and negative correlation with the precipitation in spring. In the statistics by month, the vegetation cover had significant positive correlations with the temperature in March, April, May, August, October and November, and negative correlations with the temperature in June and July. Moreover, the vegetation cover had strong negative correlations with precipitation in March, May, October and November, and significant positive correlations with precipitation in April and August.