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The new round of the Grain for Green Project (GGP) has unified the subsidy standards for economic and ecological forests. However, due to the difference between the afforestation density effect and management effect, the project’s ecological effect is different. Uniform payment standards may decouple afforestation investment from its ecological benefits, consequently affecting the cost-effectiveness of investment. This study combines a geographic information system and remote sensing technology to explore the optimal forest types investment structure of the GGP from the cost-effectiveness perspective. We used dynamic panel models to estimate the number of lag periods for species investment and an individual fixed-effects model to estimate the optimal structure of species investment. The conclusions are as follows: The lag period of the effect of ecological forest investment on the normalized difference vegetation index (NDVI) is shorter than that of economic forest investment. When the proportion of ecological forest investment is 53%−62%, the unit investment in afforestation leads to the largest NDVI. This study promotes the process of vegetation restoration effects from phenomenological analysis to mechanism analysis and incorporates forest types characteristics and natural meteorological factors into the afforestation investment efficiency evaluation system, providing a theoretical basis for GGP optimization.

Cost-effectiveness and optimization of the forest types investment structure of the Grain for Green Project: a case study of Shaanxi Province, China