Assessment Of Non-climate Triggered Vegetation Trends In China From Time Series Of Remotely Sensed Data

Vegetation plays a leading role in ecosystems.Plant communities are the main components of ecosystems.Green plants in ecosystems are the primary producers,and they provide the living organic matter for the survival of other organisms.The dynamics of vegetation are driven by both climate factors and non-climatic factors.Since the non-climatic factors are not time series and spatially distributed,we can‘t analyze the influence of non-climatic factors on vegetation change directly.Discerning the different impacts of these two general types of drivers is often formidable,but crucial for both understanding and managing landscapes.Distinguishing vegetation changes induced by unclimate fators from those by climatic variations is crucial to correctly identifying the underlying causes and designing appropriate land use policies.We can not simply attribute the vegetation restoration in China to climatic factors or non-climatic factors,but should use scientific methods to analyze and validate which vegetation changes are mainly affected by climatic factors,and which vegetation changes are mainly affected by non-climatic factors.In order to distinguish the influence of climate factors and non-climatic factors on vegetation change,we must first eliminate the influence of climatic factors,then analyze whether there is some significant vegetation change caused by non-climatic factors.In this study,the long time series remote sensing data,with the advantages of rapid and effective,was used to analyze the vegetation change and responses to climate and non-climatic factors from 1982 to 2013 in depth and quantitatively.Influence of China's major forestry construction projects on vegetation changes was assessed.This study will provide effective scientific basis and decision support for the ecosystem protection at national and regional scale.The main contents and conclusions of the study are as follows.Firstly,the consistency of NDVI trends for different satellite datasets was analyzed in China region.It is found that the time series consistency of different NDVI datasets doesn‘t reprensents the consistency of time series trends of different NDVI datasets.So the comparison and validation of time series NDVI trends are the first step for using NDVI dataset to make vegetation trend analyzing.Results showed that the trend of GIMMS NDVI3 g in the vegetation growing season was in good agreement with the trend of MODIS NDVI,except the bare and sparse vegetation areas.The least squares linear estimation model and the Mann-Kendall nonparametric estimation model have good agreement in GIMMS NDVI3 g slope and significance level.From 1982 to 2013,the vegetation in China shows overall greening and partical degradation,and the percentage of vegetation restoration is highest in croplands(45%),followed by evergreen broadleaf forest(43.9%)and savanna(39.3%).And the NDVI increase is more obvious during 1982 to 1991 and 2000 to 2013.No significant change was found during 1991 to 2000.Secondly,the influence of climatic factors on vegetation change from 1982 to 2013 was analyzed.Result showed that the minue between precipitation and evapotranspiration is more sensitive to NDVI spatial distribution compared with precipitation.And the influence of minus between precipitation and evaporation on NDVI distribution is even strong for the arid regions.Then the temperature,minues between precipitation and evaporation and cloud cover were selected as the three climatic facots to make further anlyzing.Result showed that from 1982 to 2013 temperature increased significantly,while and the water balance and solar radiation is relatively stable.The increase of temperature has positive influence on GIMMS NDVI3 g trend in the humid regions distributed in southern China.The increase of temperature has negative influence on GIMMS NDVI3 g trend in the dry regions distributed in northern and eastern China.According to the NDVI-climate multiple drivers regression analysis,temperature is the most important climatic factor that affects vegetation growth in China region,followed by minus between precipitation and evaporation and cloud cover.Thirdly,the influence of unclimatic factors on vegetation change was analyzed.The imporved NDVI-RESTREND method was used to extract unclimate triggered NDVI trend.There are two aspects of the main improvement.On the one hand,the influence of temperature,water and solar radiation on NDVI is taken into account,which makes the analysis method applicable to all climate zones.On the other hand,the time series trend of NDVI,the correlation and significant level of NDVI and multi-climatic factors,and the trend of NDVI residual were analyzed in combination to define the six kinds of drivers for vegetation significantly change..Based on the improved method,distribution map of drivers for significant change during 1982 to 2012 was obtained.Results showed that unclimatic factors play an important role in vegetation restoration in China.Non-climatic factors cause significant restoration of vegetation mainly in the central plains of China,the Yellow River plain mixed forest,the southern subtropical evergreen forest,and the northeastern region of the coniferous forest and Nenjiang River grassland.Finally,the influence of forest construction projects on vegetation was validated and analyzed.Result showed that the percent of provincial artificial forest area from the 8th national forest resource survey conduct shows good correlation with the percent of areas where NDVI significant NDVI increase is correlated with human activities,indicating that the large scale forest construction engineerings are the most important human activities influencing vegetation restoration in China.Besides,we select Loess Plateau and Muus Sandland as the two specific study areas and use the relative high spatial resolution MODIS NDVI data to make validation.Result show that the fractional vegetation cove in the regions we defined as vegetation restoration correlated with human activities change increased a lot from 2000 to 2013.Results showed that the NDVI-RESTREND method is reliable in detecting human-induced vegetation change.Besides,we select the planning regions of the three-north shelterbelt construction project,natural forest protection project,green for grain roject,national plain greening project and Beijing-Tianjin sandstorm source control project as the typical forest construction projects,to see how these projects influence the NDVI trends.Results showed that in the arid desert and semi-desert areas of the northwest,large scale forest projects did not work obviously.That is becausethe natural environment in that region is harsh and the rainfall over the last 30 years dis not increase,so the tree survival rates in is low and NDVI changes are not obvious.In addition,in the Loess Plateau region,the superposition effect of large scale forest construction projects on vegetation restoration is obvious.The main innovations of this thesis are as follows.(1)Consistency of NDVI trends for MODIS NDVI and GIMMS NDVI3 g was compared in China region for the first time.(2)Imporved NDVI residual trend method was used to analyze the influence of nonclimatic factors on vegetation change and the accuraty ws improved.(3)Contribute of non-climatic factors on NDVI trend during 1982 to 2013 were quantitatively analyzed for the first time.(4)Influence of big forest construction projects on vegetation restoration was analyzed by remote sensing diagnose method for the first time and the influence of different forest construction projects on vegetation change was analyzed.