Spatial patterns of vegetation coverage change in giant panda habitat based on MODIS time-series observations and local indicators of spatial association

Abstract

Measures to characterize the spatial patterns of vegetation change can provide important information for understanding and assessing habitat fragmentation and its causes. This study developed a new framework to assess fragmentation by integrating the spatial patterns of vegetation coverage and its change across the giant panda habitat ecosystem of China. Based on Moderate Resolution Imaging Spectroradiometer (MODIS) time-series data, we detected the historical vegetation disturbances and used “abrupt,” “gradual,” and “total” to characterize the vegetation change processes from 2000 to 2017. The spatial patterns of vegetation coverage and its change were described by spatial clusters and outliers, and the framework was established to find the potential area for reduction of habitat fragmentation. The results indicated that 1.9% of the study area experienced disturbances during 2000–2017. Most of the disturbed area (78.9%) experienced negative abrupt vegetation change, and the undisturbed area mainly showed an increase in vegetation (85.8%). The spatial clusters of high and low total changes accounted for 22.7% and 18.2% of the study area, respectively. The high change clusters were primarily along the northern and southeastern borders of the giant panda habitat, while the low change clusters spread over the central and southern areas. Considering the spatial patterns of both vegetation coverage and its change, 12.7% of the study area, located mainly in southern Minshan and eastern Qionglaishan, needs careful management to reduce habitat fragmentation. This study provides new insight to understand habitat fragmentation in terms of spatial and temporal characteristics of vegetation status and change, and will benefit future habitat management efforts.