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To alleviate the severe rocky desertification and improve the ecological degradation conditions in Southwest China, the national and local Chinese governments have implemented a series of Ecological Restoration Projects (ERPs) since the late 1990s. This study proposed a remote sensing based approach to evaluate the long-term efforts of the ERPs started in 2000. The method applies a time-series trend analysis of satellite based vegetation data corrected for climatic influences to reveal human induced vegetation changes. The improved residual method is combined with statistics on the invested project funds to derive an index, Project Effectiveness Index (PEI), measuring the project effectiveness at county scale. High effectiveness is detected in the Guangxi Province, moderate effectiveness in the Guizhou Province, and low and no effectiveness in the Yunnan Province. Successful implementations are closely related to the combined influences from climatic conditions and human management. The landforms of Peak Forest Plain and Peak Cluster Depression regions in the Guangxi Province are characterized by temperate climate with sufficient rainfall generally leading to a high effectiveness. For the karst regions of the Yunnan and Guizhou Provinces with rough terrain and lower rainfall combined with poor management practices (unsuitable species selection, low compensation rate for peasants), only low or even no effect of project implementations can be observed. However, the effectiveness distribution is not homogeneous and counties with high project effectiveness in spite of complex natural conditions were identified, while counties with negative vegetation trends despite relatively favorable conditions and high investments were also distinguished. The proposed framework is expected to be of high relevance in general monitoring of the successfulness of ecological conservation projects in relation to invested funds.

Quantifying the effectiveness of ecological restoration projects on long-term vegetation dynamics in the karst regions of Southwest China