Monitoring and spatiotemporal pattern analysis of natural resource carbon sinks at county scale coupled with remote sensing correction

Abstract

Taking a county in Jiangsu Province as a case study, this paper proposes a monitoring method for natural resource carbon sinks that integrates remote sensing inversion factors. By incorporating multi-source remote sensing datasets (including Sentinel-2, Landsat and MODIS series from 2008 to 2023) to calibrate carbon sequestration rates, we achieved the quantitative estimation of carbon storage in forests, grasslands, croplands, wetlands, and other terrestrial ecosystems. Spatial autocorrelation analysis was applied to characterize the spatiotemporal evolution patterns of regional carbon sinks. The results indicate that over the past 15 years (2008-2023), the net carbon storage of natural resources in the study area has increased significantly, exhibiting a distinct spatial pattern of “higher in the west and lower in the east, higher in rural areas and lower in urban areas, and higher on the periphery and lower in the center.” This spatial pattern is highly consistent with the implementation effects of local ecological restoration projects. The technical system proposed and applied in this study features both high accuracy and cost-effectiveness, effectively enriching the meso-scale carbon sink monitoring data products. It thereby provides a robust scientific decision-making basis for regional achievement of the “dual carbon” goals (carbon peaking and carbon neutrality) and the advancement of ecological civilization construction.