QUANTITATIVELY IDENTIFYING THE DOMINANT HUMAN DRIVING FORCES OF VEGETATION VARIATION IN THE THREE GORGES RESERVOIR REGION, CHINA

. Quantitatively analyzing the role of human activity in vegetation change has been a hot topic in the field of ecological research. Taking the Three Gorges Reservoir Region (TGRR) of China as study area, under the support of the geographic information system (GIS) technology and residual trends method (RESTREND), the spatial-temporal characteristics of vegetation change and its human driving forces in the TGRR from 2000 to 2020 were quantitively explored. It was found that, the vegetation cover had shown an overall increasing trend and strong spatial heterogeneity over the past 20 years. The vegetation restoration trend in the north-eastern region of the TGRR were more obvious than that in the south-western region. RESTREND analysis showed that human activity produced an overall positive effect on vegetation change. The areas persistently covered by forested land and farmland contributed the most to the vegetation change (83.3% in total), whereas the contribution of returning farmland to forest was only 3.92%. In the persistent forested land, there was a highly significant positive correlation (R 2 = 0.84) between the implementation area of the ecological restoration project called “closing hillsides to facilitate afforestation” (CHFA) and the change amount of normalized difference vegetation index (NDVI). The implementation of the project CHFA could proximately explain the change of residual between the observed and estimated NDVI. This paper quantitatively revealed the important role of the CHFA project on vegetation restoration and conducted the first attempt to specify the residual of the RESTREND method. Achievements could provide valuable references for regional study on the driving mechanism behind vegetation cover change.

• Publication year

  2023

• Venue

  Applied Ecology and Environmental Research

• Publication date

  Unknown publication date

• Fields of study

  Not labeled

• Identifiers
  DOI 10.15666/aeer/2102_14851498
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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