Chin J Plant Ecol ›› 2021, Vol. 45 ›› Issue (4): 355-369.

• Research Articles •

Vegetation change of giant panda habitats in Qionglai Mountains through dense Landsat Data

ZHOU Ming-Xing1, LI Deng-Qiu2,*(), ZOU Jian-Jun1

1. 1School of Environmental and Resource Sciences, Zhejiang A&F University, Key Laboratory of Carbon Cycling in Forest Ecosystem and Carbon Sequestration of Zhejiang Province, Lin’an, Zhejiang 311300, China
2State Key Laboratory for Subtropical Mountain Ecology of the Ministry of Science and Technology and Fujian Province, School of Geographical Sciences, Fujian Normal University, Fuzhou 350007, China
• Received:2020-07-08 Accepted:2021-02-04 Online:2021-04-20 Published:2021-03-27
• Contact: LI Deng-Qiu
• Supported by:
National Key R&D Program of China(2016YFC0503302);National Natural Science Foundation of China(41701490)

Abstract:

Aims Understanding the processes and drivers of vegetation change in giant panda habitats plays an important role in their conservation and management.

Methods Based on the long-term normalized difference vegetation index (NDVI) time series that was constructed by all available Landsat TM/ETM/OLI images from 1986 to 2018, we employed the BFAST (Breaks For Additive Seasonal and Trend) method and harmonic model to monitor the vegetation change during the period of 1986-2018. Three types of NDVI changes (i.e. vegetation accumulated abrupt change, accumulated gradual change, and total change) were built to reveal the spatial distribution characteristics of vegetation change. The effects of different factors (i.e. mean annual precipitation, mean annual air temperature, elevation, slope, aspect, distance to rivers, soil type, land cover type, distance to roads and distance to engineering disturbance area) on the spatial distribution of the three types of vegetation change were evaluated by Geodetector.

Important findings 1) A total of 9.13% of vegetation abrupt change in the study area was detected, which was mainly distributed around the eastern boundary of the habitats, and the largest abrupt change areas occurred in 2011 and 2013. 2) The proportion of vegetation accumulated abrupt change showing degradation accounted for 40.17% of the vegetation accumulated abrupt change area, and the accumulated gradual change and total change which presented increasing trends accounted for 94.58% and 97.02% of the study area, respectively. 3) The spatial distribution of vegetation changes was mainly affected by four factors: mean annual precipitation, mean annual air temperature, elevation, and soil type. The strongest explanatory factors of vegetation accumulated abrupt change, accumulated gradual change, and total change were mean annual precipitation, elevation, and soil type, respectively. The interactions between driving factors were mutually enhanced and nonlinearly enhanced.