摘要
GIMMS NDVI产品因其长时间序列的优势,一直以来被广泛应用于植被特征分析。本文利用1982-2012年该数据集,研究了我国NDVI时间和空间的分布状况及空间变化率,同时选用双变量相关与偏相关2种方法分析了我国不同植被类型区域NDVI与6种气候因子(年降水量、平均气温、平均风速、平均水汽压、平均相对湿度和日照时数)的相关性。结果表明,全国NDVI的年内变化显著,其中2月下半月数值最小,8月上半月达到峰值。31年间,全国NDVI呈缓慢增长趋势,其年平均增长率为0.0003。针对8种不同的植被类型,其NDVI与6种气候因子的相关性程度不同,总体而言,与年降水量、平均气温、平均水汽压及平均相对湿度多具有正相关性,而与平均风速和日照时数多具有负相关性。
Because of the advantage of long time series of GIMMS NDVI,the datasets are used to study the characteristics of vegetation widely.In this study,dataset from 1982 to 2012 were used to analyze the temporal and spatial changes of NDVI in China,and the bivariate and partial correlation between NDVI and climatic factors（precipitation,average temperature,average wind velocity,average vapour pressure,mean relative humidity and sunshine duration）in different vegetation types.The results showed that the change of NDVI was significant within a year,and the minimum and maximum values appeared in late February and early August,respectively.The increasing trend of NDVI was observed from 1982 to 2012,and the annual increasing rate was 0.0003.The correlation between NDVI and climatic factors was different due to various vegetation types.Generally,NDVI had the positive correlation with precipitation,average temperature,average vapour pressure and mean relative humidity,and showed negative correlation with average wind velocity and sunshine duration.
出处
《草地学报》
CAS
CSCD
北大核心
2017年第4期691-700,共10页
Acta Agrestia Sinica
基金
贵州省农业科学院专项基金([2016]032号)
贵州省农业科学院科研项目([2016]基于蛋白组学技术对高羊茅低氮胁迫下蛋白调控机制的研究)
贵州省农业科学院科研项目([2016]贵州省近三十年来植被生长特征分析)资助
