Spatially varying patterns of afforestation/reforestation and socio-economic factors in China: a geographically weighted regression approach

Afforestation and reforestation play an important role in reducing global greenhouse gas emissions, and they are a component of the Reducing Emissions from Deforestation and Degradation-plus program. Within a theoretical analysis framework, we identified the key factors of afforestation and reforestation using a global regression model. Spatial non-stationarity of the key factors required the use of a geographically-weighted regression approach. Results indicated that afforestation and reforestation were affected by five main factors in China: population density, the gross output value of forestry, forest area, sown area of crops, and burned area due to forest fires. The gross output value of forestry had a negative correlation with afforestation and reforestation, which showed a decreasing trend from southeast to northwest in China. The population density and forest area were positively correlated with afforestation and reforestation in the northwest of China, but negatively correlated with those activities in other parts of China. The sown area of crops had a significantly positive correlation with afforestation and reforestation with an increasing trend from west to east. Forest fires also had a positive correlation with afforestation and reforestation, with an increasing trend from east to west in China. Policy-making should consider the spatial heterogeneity of the factors of afforestation and reforestation in designing REDD+ of China.