Study On Vegetation Dynamic Based On Vegetation Phenology And NOAA/AVHRR NDVI In The North South Transect Of Eastern China

Phenology refers to seasonal biological life stages driven by environmental factors, and is considered to be a sensitive and precise indicator of climate change. Vegetation phenology detection methods based on remote sensing overcome conventional ground observation's shortcomings, such as limited observation sites and missing data, and realize the spatial scale transition of observation methods from points to coverage. Remote sensing technology greatly promotes a study on vegetation ecosystem response to climate changes at regional, continental, even global scales.Therefore, we developed a"bottom-up"method for first determining the phenological growing season at sample stations, and based on NOAA/AVVHRR, meteorological data, ground phenology observation data, vegetation category data, and so on, the essay build a Logistic fitting model on cumulative frequency of NDVI to determine turning green date(TGD)in spring, wilting date(WD) in autumn and length of greenness period (LGP) since 1982,then analyze the spatio-temporal pattern and change trends of TGD, WD, LGP,analyze correlation between NDVI and air temperature, precipitation, mainly discuss spatio-temporal dynamics of TD and WD and their response and feedback to regional air temperature and precipitation in different vegetation types and different bioclimatic regions, primarily reveal the dynamic mechanism of climate on vegetation..Using phenological and NDV I data from 1982 to 2003 at seven sample stations in the North South Transect of Eastern China, we calculated the cumulative frequency of leaf unfolding and leaf coloration dates for deciduous species every five days throughout the study period. Then, we determined the growing season beginning and end dates by computing times when 50% of the species had undergone leaf unfolding and leaf coloration for each station 2 year. Next, we used these beginning and end dates of the growing season as time markers to determine corresponding threshold NDV I values on NDV I curves for the pixels overlaying phenological stations. Based on a cluster analysis, we determined extrapolation areas for each phenological station in every year, and then, implemented the spatial extrapolation of growing season parameters from the seven sample stations to all possible meteorological stations in the study area. The results show: ( 1 ) the spatial pattern of average turning green and wilting dates of the growing season correlates significantly with the spatial pattern of average temperatures in sp ring and winter across the North South Transect of Eastern China during 1982 to 2003; the growing season extended on average by 5 to 8 days ;(2) On an interannual basis, correlation analysis shows that TGD were mainly influenced by mean air temperature from last winter to spring in all vegetation types. A negative correlation indicates that higher mean temperature in late winter and spring trigger an earlier onset of TGD. In contrast to TGD, the correlations of WD and seasonal mean air temperature before it are not significant in mostly vegetation types. It indicates that the delay or advance of WD in autumn mainly lied on a temperature threshold under which WD arise. Precipitation has a weak influence on TGD and WD In contrast to temperature.(3) a insignificant advance of wilting dates but a significant advance of turning green dates of the growing season were detected in different latitudinal zones and the whole area, which is different from findings in Europe and North America (where a significant advance of beginning dates and an insignificant delay of end dates of the growing season were observed) ; (4) An increase in air temperature in North China may tend to result in less temperate forest but more shrubs and grasses in the transect area.