摘要
“双碳”背景下城市空间碳汇结构与布局的提升与优化是重要的研究内容。作为碳汇效益的主要载体,城市蓝绿空间在增汇减碳方面具有协同作用,但当下对于城市蓝绿空间整体格局对其碳固存的影响关联研究不足。文章以合肥中心城区为例,基于2000、2010、2020年的数据,在量化城市蓝绿空间格局特征的基础上,采用机器学习XGBoost-SHAP模型测度与解译城市蓝绿空间格局对碳固存的影响及关键指标。结果表明:1)城市蓝绿空间格局对碳固存具有影响,且不同格局特征的影响程度不同。2)影响碳固存的城市蓝绿空间格局关键指标有斑块层的FRAC、CONTIG、AREA和ENN,类型层的ED、COHESION、DIVISION和LSI。3)蓝绿斑块形状复杂度越高,越有利于碳汇效益的发挥;蓝绿空间分布的聚集度越高、距离越近、连通度越高,碳汇效益越好。据此,提出以碳增汇为目标的城市蓝绿空间格局规划优化策略,以期为城市蓝绿空间规划与管理提供参考。
In the context of"dual carbon goals",enhancing and optimizing the structures and layouts of carbon sink in urban spaces is a significant research topic.Urban blue-green space(UBGS),serving as the primary facilitators of carbon sink benefits,exerts a synergistic influence on carbon sequestration and emissions reduction.Taking Hefei's city core as an illustrative case study,this paper employs the machine learning model,XGBoost-SHAP,to gauge and elucidate the influence of the UBGS pattern on carbon sequestration and their pivotal indicators after quantifying the characteristics of the UBGS pattern with the data spanning the years 2000,2010,and 2020.The findings unveil:1)The UBGS pattern has a discernible influence on carbon sequestration,and patterns with different characteristics have varied extent of influence at that;2)The pivotal indicators of the UBGS pattern for assessing the influence on carbon sequestration include the patch-level metrics like FRAC,CONTIG,AREA and ENN,and the class-level metrics such as ED,COHESION,DIVISION and LSI;and 3)Higher complexity in the shape of blue and green patches will bring higher benefits from carbon sequestration,and linear patches exhibit substantially lower carbon sink benefits in comparison to area-shaped patches.Enhanced aggregation,closer proximity,and heightened connectivity of blue and green spaces correlate with superior carbon sink benefits.Based on this,the optimization strategies for UBGS pattern planning are proposed with the carbon sequestration and emission reduction as the goal,with the aim to provide references for the planning and management of the UBGS.
作者
袁旸洋
郭蔚
汤思琪
杨明珠
汪瑞军
Yuan Yangyang;Guo Wei;Tang Siqi;Yang Mingzhu;Wang Ruijun(School of Architecture,Southeast University,Nanjing 210096,China;Jiangsu Provincial Urban and Rural Digital Technology Engineering Center,Nanjing 210096,China;College of Architecture and Art,Hefei University of Technology,Hefei 230601,China)
出处
《中国城市林业》
2023年第6期6-16,共11页
Journal of Chinese Urban Forestry
基金
国家自然科学基金重点项目(51838003)
东南大学“至善青年学者”支持计划(2242023R40002)。
