The Studies On Dynamic Of Vegetation Based On NDVI Time Series

Desertification is one of the most serious ecological and environmental problems in the world. It directly influences regional economic development and social stability. Desertification(especially desertification by wind erosion), in some extent, exhibits as vegetation degrade. So vegetation dynamic can reflects desertification dynamic, in some extent. We can know desertification dynamic, if we study vegetation dynamic. Reserching the relationship between vegetation dynamic and climate factor (precipitation, temperature) is in favor of the study on the relationship between desertification and climate (precipitation, temperature). It is in favor of desertification dynamic monitor by remote sensing. This paper ,based on NDVI times series ,analysis the space-time distribution principle and the relationship between NDVI and precipitation, temperature by using NOAA/AVHRR 8km resolution data , modis 500m resolution data and precipitation, temperature data in the same term. Based on anylysing multiple beeline regression, tries to distinguish the climate factor and human behavior in the vegetation dynamic process. Lastly, this paper introduces how to apply ndvi index to monitor and appraise desertification.Main research results in this thesis include as following:(1) Vegetation, as a indicator of entiroment, can directly reflect the condition of entironment. By choosing NDVI as a indicator to weigh vegetation condition, can reflect the vegetation dynamic. It can extract the information of vegetation dynamic by using RS and GIS technology.(2) The principle of NDVI space-time distribution: Vegetation move form south part to north part during 1～7, namely green band phenomenon, but,vegetation condition is decreasing from north part to south part,namely brown band phenomenon.The vegetation condition is the most in august.Analysis the space distribution principle of NDVI,by analyzing the distribution of ndvi along longitude 115,108degree and latitude 40,30 degree. The macro distribution principle of ndvi is increasing from east to west, from south to north part.(3) NDVI dynamic trend: the lowness value of NDVI is in 1992,but the maximal value of NDVI is in 1982, 1990, 1994 during 1982～2000. It maybe relates to ENSO phenomenon rooting in EI Nino and southern Oscillation.Statistic data indicate: vegetation increasing regions occupy 59.8% of country area, but famously increasing regions occupy 8.2%. vegetation decreasing regions occupy 40.2%, but famously decreasing regions occupy 1.4%.(4) Precipitation and temperature has a remarkable influence on NDVI. But, the major influence factor is different in different regions.In south part, the major influence factor is temperature because of the abundance of precipitation in this region, while, in north part, the main influence factor is precipitation, especially in Agro-pastoral Transition Area. Reserch results indicate that there exsist a remarkable lag coefficient between precipitation and NDVI, namely the coefficient of NDVI and two preceding month periods is best. Meanwhile, the coefficient between NDVI and temperature is not lag.Results demonstrate that precipitation is a strong predictor of regional spatial patterns of NDVI, but the relationship between the spatial patterns of temperature and the spatial patterns of NDVI is not remarkable.(5) The trend of NDVI, precipitation, temperature in north province is consistent with the disturibution rule of coefficient between NDVI and precipitation, temperature in Country by analyzing the relationship between NDVI and precipitation, temperature in province scale.(6) Take yanchi county as a example in county scale, result indicate that NDVI is positively correlated with precipitation, while NDVI is negative correlated with temperature.There exsist a remarkable lag coefficient between NDVI and precipitation.The relationship between NDVI and the sum of precipitation during two preceding month periods and current month.The trend of vegetation in yanchi county during the last twenty year is increasing by analyzing the remote sensing data. This phenomenon maybe correlated with climate and human interfere.(7) Based on analyzing the relationship between NDVI and precipitation, temperature ,the regression equation of NDVI and precipitation, temperature in each pixel by multiple line regression analyzing. Based on this result, the trend of NDVI regression equation can be gained.Meanwhile, the trend of the difference of NDVI and NDVI regression value can be computed. So, we can distinguish the role of the climate factor and human factor in the process of vegetation dynamic.