Acta Geographica Sinica ›› 2019, Vol. 74 ›› Issue (9): 1758-1776.doi: 10.11821/dlxb201909005

• Climate Change • Previous Articles     Next Articles

Influence of natural factors on vegetation NDVI using geographical detection in Sichuan Province

PENG Wenfu1,2,ZHANG Dongmei1,2,LUO Yanmei1,2,TAO Shuai1,2,XU Xinliang3   

  1. 1. The Institute of Geography and Resources Science, Sichuan Normal University, Chengdu 610068, China
    2. Key Lab of Land Resources Evaluation and Monitoring in Southwest, Ministry of Education, Sichuan Normal University, Chengdu 610068, China
    3. Data Center for Resources and Environmental Sciences, Chinese Academy of Sciences, Beijing 100101, China
  • Received:2018-04-19 Revised:2019-07-25 Online:2019-09-25 Published:2019-09-25
  • Supported by:
    Humanities and Social Science Fund of the Ministry of Education of China(17YJA850007);NationalNatural Science Foundation of China(41371125)


Many studies have shown the importance of using remote sensing to establish a vegetation index for land surface processes and global change research, it is of great significance to understand the driving factors of vegetation change, but the causes for vegetation change and the impact of geographical factors on vegetation change remain elusive. In this study, we examined the geographical factors and spatial patterns of vegetation change and the interactive effects of the geographical factors on vegetation change, and identified the most suitable characteristics of the main geographical factors that promote vegetation growth using the Geographical Detector Model, a new method of spatial counting to detect spatial variability and identify the driving factors. Our results showed that the vegetation cover was in good condition, the coverage area was of medium height, and there was more than 94% of high height vegetation. The spatiotemporal change in vegetation cover was significant from 2000-2015; the transformation of the normalized differential vegetation index (NDVI) was manifested as the transformation of NDVI > 0.4, and the cover area of medium and high height vegetation had a significant decreasing and increasing trend, respectively. The vegetation cover was better in the western and northern Sichuan plateau, while it was poor in the central urban areas of the Sichuan Basin and the Panxi area. Soil type, elevation, and the average annual temperature change could well explain the variability in vegetation condition. The influence of geographical factors on NDVI was interactive; the synergistic effect of the geographical factors on NDVI showed mutual and non-linear enhancement, and the interaction of the two factors enhanced the influence of a single factor on NDVI. This study reveals the most suitable characteristics and the main factors that promote vegetation growth, which is helpful to better understand the influence of natural factors and the driving mechanisms of vegetation NDVI change.

Key words: NDVI, natural factors, geographical detector model, Sichuan Province