A Multi Source Data-Based Method for Assessing Carbon Sequestration of Urban Parks from a Spatial–Temporal Perspective: A Case Study of Shanghai Century Park

As urbanization accelerates globally, urban areas have become major sources of greenhouse gas emissions. In this context, urban parks are crucial as significant components of carbon sinks. Using Shanghai Century Park as a case study, this study aims to develop an applicable and reliable workflow to accurately assess the carbon sequestration capacity of urban parks from a spatial–temporal perspective. Firstly, the random forest model is employed for biotope classification and mapping in the park based on multi-source data, including raw spectral bands, vegetation indices, and texture features. Subsequently, the Net Primary Productivity and biomass of different biotope types are calculated, enabling dynamic monitoring of the park’s carbon sequestration capacity from 2018 to 2023. Moreover, the study explores the main factors influencing changes in carbon sequestration capacity from the management perspective. The findings reveal: (1) The application of multi-source imagery data enhances the accuracy of biotope mapping, with winter imagery proving more precise in classification. (2) From 2018 to 2023, Century Park’s carbon sequestration capacity showed a fluctuating upward trend, with significant variations in the carbon sequestration abilities of different biotope types within the park. (3) Renovation and construction work related to biotope types significantly impacted the park’s carbon sequestration capacity. Finally, the study proposes optimization strategies focused on species selection and layout, planting density, and park management.