The application of geospatial techniques in monitoring karst vegetation recovery in southwest China

Author:

Zhang Chunhua1,Qi Xiangkun2,Wang Kelin2,Zhang Mingyang2,Yue Yueming2

Affiliation:

1. Department of Geography and Geology, Algoma University, Canada

2. Key Laboratory of Agro-ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Hunan, China; Huanjiang Observation and Research Station for Karst Ecosystem, Chinese Academy of Sciences, Huanjiang, China

Abstract

The karst region in southwestern China, one of the largest continuous karst areas in the world, is special for its high landscape heterogeneity, unique hydrology, high endemism among vegetation species and high intensity of human disturbance. The region had experienced severe degradation through karst rocky desertification (KRD) between the 1950s and 1990s. Starting in the late 1990s, various levels of the Chinese government conducted several ecological projects to recover degraded karst ecosystems. It was reported that the implementation of these projects had been successful in facilitating the recovery of karst vegetation in many areas. However, global climate changes may compromise the efficacy of recovery. Geospatial techniques had been employed to map and monitor karst ecosystem conditions during the recovery process. We examined the history and progress of the various geospatial techniques applied to monitor and evaluate karst vegetation conditions. In addition, we reviewed the techniques used to assess and monitor KRD, KRD influencing factors, vegetation community type, fractional vegetation cover, vegetation dynamics, vegetation productivity, ecosystem goods and services, vegetation biodiversity, ecosystem health and rural society changes. We also explored the potential to apply geospatial techniques for karst vegetation recovery in the future. It is projected that there will be more remotely sensed images for the vegetation dynamics monitoring at numerous scales. New techniques (e.g. image fusion and data assimilation) will be available to manage scale and heterogeneity issues in the karst landscape.

Funder

Chinese Academy of Sciences STS Program

Publisher

SAGE Publications

Subject

General Earth and Planetary Sciences,Earth and Planetary Sciences (miscellaneous),Geography, Planning and Development

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