Spatiotemporal patterns of urban forest carbon sequestration capacity: Implications for urban CO2 emission mitigation during China's rapid urbanization

Abstract

Urban forests provide ecological functions and human well-being. However, spatiotemporal changes in urban forest carbon sequestration (CS) under rapid urbanization remain poorly understood. We established a model to predict the annual CS dynamics in urban forests based on plot-measured CS and Landsat images. Our results showed that the urban forest coverage in Changchun increased from 18.09 % to 24.01 % between 2000 and 2019, especially in the urban suburbs. However, urban forest patches became more fragmented and less connected, particularly in the urban center. The NDVI is better than other vegetation indices for mapping urban forest CS. We observed a gradual increase in urban forest CS capacity from 2000 to 2019, with higher CS capacity found in urban suburbs compared to urban centers. The class distribution of urban forest CS capacity was skewed toward low values (0–2 g·m−2·d−1), but this tendency diminished gradually. In 2000, the urban forest in Changchun offset approximately 2.11 % of carbon emissions but declined to 0.88 % by 2019 due to increased carbon emissions. Rapid urbanization was the main factor affecting CS, with impervious surface area accounting for 48.7 % of the variation. Urban landscape pattern indices also influenced the CS, with higher forest patch connectivity and lower patch density leading to greater CS capacity. Our study helps urban managers develop urban greening strategies for carbon neutrality and low-carbon city.