Factors Influencing Changes in Forestry Carbon Sinks Under the 'Dual Carbon' Framework in Southwest China: Evidence from Satellite Remote Sensing Data

This study, grounded in the Ecological Environmental Systems Theory, commenced by extracting structured proxy variables from satellite remote sensing imagery spanning 2013 to 2022. Subsequently, a research data set was constructed by integrating annual statistical data from 38 cities in Southwest China with meteorological data sets. Finally, a Panel Vector Autoregression (PVAR) model was employed to examine the ecological and socioeconomic factors influencing forestry carbon sinks. The results demonstrate that annual average precipitation and economic development level positively influence forestry carbon sinks, whereas annual average temperature, forestry production value, urban heat island effects, urban scale, population urbanization rate, and road mileage exert significant negative impacts. In the short term, forestry production value, annual average temperature, and annual average precipitation account for the greatest proportion of variance, with forestry production value exhibiting a notable lag effect. Over the long term, population urbanization rate and economic development level emerge as the primary determinants of forestry carbon sinks, whereas road mileage and urban scale exhibit relatively stable effects. This study offers a rigorous analysis of the factors influencing forestry carbon sinks and provides practical implications, thereby laying a solid foundation for future research in this domain.