Vegetation-cover Variation In The Dongting Lake Watershed Based On Different Remote Sensing Datasets And The Main Causes

Dongting Lake Watershed is the most significant part in response to climate change in the Yangtze River basin, as the effects of global warming, vegetation inevitably change accordingly to the basin, however, what changes occur, an increase or decrease or little change or fluctuation growth, there is few studies existing,and the impact of factors is also not clear. Understanding these will contribute to the future development of rational utilization of climate resources, forest plants and land resources in the Dongting Lake watershed, to protect the integrity and diversity of the region’s natural ecosystems, and then take targeted measures for ecological protection and construction, resulting resources, environment, socio-economic and human development in harmony. Trend and interannual variability of growing season vegetation cover are examined for the Dongting Lake Watershed over the period of 1982-2010, using GIMMS 3g together with other AVHRR NDVI products and MODIS vegetation index products based on MVC and per-pixel unary Linear Model. The data set which can reflect the vegetation change in Dongting Lake Watershed better will be used in the temporal analysis and correlation analysis with possible influencing factors (precipitation, temperature, sunshine hours and vegetation cover). Results indicated:(1) The four datasets of AVHRR show a great similarity in spatial distribution of NDVI trends from 1982 to 1999, while comparison of MODIS EVI/NDVI and GIMMS 3g during 2000-2010 shows significant difference in NDVI trends between MODIS NDVI and GIMMS 3g. This is likely owing to MODIS NDVI saturation in the study area. Spatial distribution of trends resulting from GIMMS 3g and MODIS EVI have some consistency. Thus GIMMS 3g is selected for detailed analysis because of its long temporal coverage and consistency with other products.(2) An increasing NDVI trend occurred in the study area during the past 29 years, only 9.5% pixels in the Dongting Lake Watershed shows some NDVI reduction. The eastern, western and southern part of the region covered by mountain forests experienced a large decrease in NDVI during 1998-2000; Growing season precipitation in the eastern and northwestern regions is more than the lake district and central basin(Heng-Shao), some Guizhou area also shows low precipitation. In the past 29 years, precipitation growth curve turned very slowly; The average temperature in the growing season showed a significant increase at a rate of 0.39/10a, the overall spatial distribution presentation a gradually decreasing from south to north; 1982-2010 annual sunshine hours appeared a reduce trend at a moderate speed, its spatial distribution shows that the Northeast have high number of sunshine hours generally, regions in western basin is significantly lower than others.(3) Extract the wavelet coefficient process line of the growing season average NDVI under 5a and 9a time cycle, and than do a correlation analysis with the wavelet coefficient process line of the growing season cumulative rainfall, average temperature of and month sunshine hours at the same time cycle. It shows that an obvious positive correlation between growing season average NDVI and growing season average temperature, month sunshine hours under 5 a cycle;At 9a time cycle, month sunshine hours have better correlation.According to these analysis, month sunshine hours seems do the lagerst contribution to the NDVI changes.(4) De-trended NDVI monthly anomaly is significantly correlated with de-trended concurrent precipitation anomaly, concurrent sunshine duration and cumulative three-month temperature anomaly. The three climate factors explain 37% temporal variability of de-trended growing season monthly NDVI of the study watershed.(5) While climate factors fail to explain the overall NDVI increase during 1982-2010, this suggests that the increase in NDVI is more likely associated with an increase in vegetation cover over the period, supported by the good correlation between the NDVI trend and the government reported forest cover change.