Karst is among the most fragile environments worldwide. Southwest China has one of the largest continuous karst landscapes in the world, spanning an area about 540,000 km². From the 1950s to 1980s, the rapid disappearance of vegetation led to severe environmental degradation in the karst region of southwest China. Ecological restoration projects (i.e., Green for Grain program, mountain closure measure) to restore vegetation have been applied in this area since the 1990s. However, few studies have evaluated the effects of restoration on karst vegetation.

Vegetation succession, an ecological phenomenon involving predictable changes in plant communities, can serve as an indicator of environmental changes. Researchers in the Institute of Subtropical Agriculture(ISA), Chinese Academy of Sciences (CAS) employ remote sensing, geographic information systems (GIS) and statistical techniques to assess the effectiveness of restoration projects using vegetation succession mapping.

The developed geological process in the karst region had formed remarkable landforms with high terrain ruggedness and steep hillslopes. Shadows caused by the rough karst landforms in this area of China make the application of remotely sensed imagery challenging. Here, we used three Landsat Thematic Mapper images from 1990, 2004, and 2011 to examine whether various image pre-processing methods (vegetation indices, topographic correction, and minimum noise fraction [MNF] transformation) and a digital elevation model improved image classification. Using a maximum likelihood classifier, vegetation communities were classified into five classes (successional stages) of grass, grass-shrub, shrub, tree-shrub, and forest. The results indicated that a combination of inverse MNF transformed bands, the normalized difference moisture index (NDMI), and the moisture stress index (MSI) minimized topographic effects and consequently produced the best input for imagery classification and the accuracy of the vegetation successional stage classification increased by approximately 20%. Mapping results showed ongoing vegetation succession in the study area from 1990 to 2011. Dominant vegetation communities had shifted from early successional stages (i.e., grass and grass-shrub) in 1990 to late stages (i.e., forest and tree-shrub) in 2011. Increases in patch number and average patch area for forest and tree-shrub communities at the class level suggested the expansion of these two communities. Enhanced patch connectivity and aggregation at the landscape level indirectly signified decreases in disturbances to forest and tree-shrub communities. These results demonstrate that the implementation of the Green for Grain program, mountain closures, and migration program also reduced the dependence of farmers on logging, grazing, and farming on sloping land and contributed to vegetation recovery.

This study was supported by the Chinese Academy of Sciences Action Plan for the Development of Western China (KZCX2-XB3-10), the National Natural Science Foundation of China (41071340), the National Key Technology Research and Development Program of the Ministry of Science and Technology of China (2010BAE00739-02), and the Western Light Program of Talent Cultivation of the Chinese Academy of Sciences (O923085080).

The study entitled “Effectiveness of ecological restoration projects in a karst region of southwest China assessed using vegetation succession mapping” has been published in the ecological science journal of Ecological engineering (DOI: 10.1016/j.ecoleng.2013.01.002). （http://www.sciencedirect.com/science/article/pii/S0925857413000177）