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RSS FeedsRemote Sensing, Vol. 15, Pages 811: Spatiotemporal Changes in Supply–Demand Patterns of Carbon Sequestration Services in an Urban Agglomeration under China’s Rapid Urbanization (Remote Sensing)

 
 

31 january 2023 16:05:16

 
Remote Sensing, Vol. 15, Pages 811: Spatiotemporal Changes in Supply–Demand Patterns of Carbon Sequestration Services in an Urban Agglomeration under China’s Rapid Urbanization (Remote Sensing)
 


Quantifying the urban supply and demand of carbon sequestration services is an important prerequisite for achieving global carbon neutrality goals. However, the spatiotemporal patterns for balancing the supply and demand of carbon sequestration services in urban agglomerations remain unclear. In this study, NPP/VIIRS nighttime light data were used to identify the carbon sequestration service demand and were then combined with the carbon sequestration service supply to analyze the spatiotemporal patterns of supply and demand for carbon sequestration services in the Harbin-Changchun urban agglomeration (HCUA) in Northeast China. Our results indicate that both the supply and demand of carbon sequestration services showed increasing trends from 2012 to 2020 in the HCUA. The regions with increasing supply and demand trends were mainly located in the eastern mountainous and western urban areas, respectively. The total supply and demand of carbon sequestration services in the HCUA were 2080.3 Mt–C yr−1 and 433.6 Mt–C yr−1, respectively. Carbon surpluses (supply > demand) were found in most areas (98%), although particularly in the southeastern mountainous region. However, with rapid urbanization, in most cities, the supply–demand ratio decreased from 2012 to 2020, and the proportion of carbon deficit regions showed a continuous increase, which was mainly distributed in newly developed urban areas. The low supply–high demand (L-H) pattern showed significant spatial mismatching for supply and demand in the HCUA. The proportion of regions with the L-H pattern also showed a rapidly increasing trend from 2012 to 2020, indicating a more obvious carbon deficit trend in the future. This study provides important guidelines for formulating effective policies for energy consumption and carbon sequestration to combat global warming under China’s rapid urbanization.


 
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Remote Sensing, Vol. 15, Pages 810: HCFPN: Hierarchical Contextual Feature-Preserved Network for Remote Sensing Scene Classification (Remote Sensing)
Remote Sensing, Vol. 15, Pages 812: Spatial Downscaling and Gap-Filling of SMAP Soil Moisture to High Resolution Using MODIS Surface Variables and Machine Learning Approaches over ShanDian River Basin, China (Remote Sensing)
 
 
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