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《Northern Horticulture》 2017-24
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Impact of Different Extracted Methods of Annual NDVI on Vegetation Cover Change and Their Response to Climate Change in Qinling Mountains

WANG Tao;TIAN Yang;XIANG Ru;College of Urban and Environmental Science,Northwest University;College of Geomatics,Xi′an University of Science and Technology;State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau/Institute of Water and Soil Conservation,Chinese Academy of Sciences and Ministry of Water Resources;The People′s Government of Hengshan Town Qijiang District Chongqing Municipal;  
On the basis of the MODIS NDVI images,temperature and precipitation data from 2000 to2014 in Qinling Mountains,the spatial and temporal variation of NDVI and the correlation between NDVI and temperature,precipitation were analyzed with 4 different extraction methods on annual NDVI value,such as AVM(Average Value Method),MVC(Maximum Value Composition),AMVC(Average-Maximum Value Composition)and RAVM method(Reconstruction-Average Value Method).This study would provide an information to accurate assessment of NDVI change in Qinling Mountains.The results showed that the RAVM was the best to extract annual value of NDVI,and the linear change trend was very significant,followed by the AMVC,while the annual value of NDVI extracted by MVC and AVM were higher and lower.Vegetation degradation was a hot issue for the monitoring of Qinling Mountains.The linear reduction trend area calculated by AMVC was the largest,followed by the MVC,RAVM and AVM.The correlation between NDVI and temperature was different to a certain extent,such as the spatial distribution of coefficient was relatively scattered(MVC and RAVM)or concentrated(AVM and AMVC),and the positive(AVM and RAVM)or negative correlation(MVC and AMVC).But the correlation between NDVI and precipitation was positive for the 4 different methods,which reflect the correlation between NDVI and precipitation was stable and unstable between NDVI and temperature.
【Fund】: 国家林业公益性行业科研专项资助项目(201304309);; 黄土高原土壤侵蚀与旱地农业国家重点实验室开放基金资助项目(A314021402-1616);; 陕西省大学生创新创业训练计划资助项目(201710704072)
【CateGory Index】: Q948
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