1. College of Earth Science, Chengdu University of Technology, Chengdu 610059, China 2. Institute of Ecoenvironment and Agrometeorology, Chinese Academy of Meteorological Sciences, Beijing 100081, China 3. College of the Engineering and Technical, Chengdu University of Technology, Leshan 614000, China 4. College of Management Science, Chengdu University of Technology, Chengdu 610059, China
The correlation analysis between climatic factors and vegetation indexes can not only reflect the impact of climate change on vegetation but also predict the trend of vegetation in the future. Based on the data of MODIS13A1 C6 NDVI of the Three River headwater region and combined with 1∶1 000 000 map of vegetation types and meteorological data, the authors analyzed spatial-temporal characteristics of NDVI and the relationship between vegetation indexes and climatic factors by using correlation analysis from 2000 to 2016. The results are as follows: ① NDVI increased with a rate of 0.8%/10a in Three River headwater region during 2000—2016, whereas vegetation cover increased from the northwest to southeast. ② Climate factors had a greater influence on vegetation growth in the early and middle growing season, but the correlation between NDVI and climate factors was not obvious in the later growing season. ③ The partial correlation between NDVI and climate factors in the vegetation growing season of the study area showed that the influence of the air temperature on NDVI of the alpine meadow grasslands and alpine grasslands was greater than that of precipitation in the early growing season. However, during the middle of the growing season, the precipitation had a greater impact on the growth of three different types of vegetation.
徐嘉昕,房世波,张廷斌,朱永超,吴东,易桂花. 2000—2016年三江源区植被生长季NDVI变化及其对气候因子的响应[J]. 国土资源遥感, 2020, 32(1): 237-246.
Jiaxin XU,Shibo FANG,Tingbin ZHANG,Yongchao ZHU,Dong WU,Guihua YI. NDVI changes and its correlation with climate factors of the Three River-Headwater region in growing seasons during 2000—2016. Remote Sensing for Land & Resources, 2020, 32(1): 237-246.
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