摘要
通过耦合FLUS-InVEST模型和2010—2020年土地利用现状数据,核算并预测自然演变情景和绿色集约生态情景下2035年城市土地利用变化及其碳储量的影响,进行空间自相关分析,以期为“双碳”目标下土地利用管理和国土空间规划提供科学参考。结果表明:①2010—2020年地类转化整体以低碳密度地类向高碳密度地类转换为主,耕地无序流向林地问题较为突出;②10年间北海市碳储量整体呈现出先减后增的趋势,整体增加4.01×10^(5) t;③到2035年,北海市碳储量预测值在自然演变情景下仍将继续降低,而在绿色集约生态保护情景中,既可充分保障社会经济高质量发展的前提下使碳储量得到缓慢恢复,又可使碳储量在未来15年间比自然变化情景下少损失1.36×10^(5) t。
By coupling FLUS-InVEST models and the current data of land use from 2010 to 2020,this study calculated and predicted the spatio-temporal difference of land and carbon storage in Beihai city,and predicted the impact of natural evolution scenarios and green intensive ecological development scenarios on land use and carbon storage in 2035.The spatial autocorrelation model was used to reveal the future spatial distribution trend,of which can provide scientific reference for land use management and land spatial planning under the“dual carbon”goal.The results show that:①From 2010 to 2020,the overall transformation of land types was dominated by the conversion of land types with low carbon density to land types with high carbon density.The disordered flow of cultivated land to forest land is prominent;②Over the course of the study,the overall carbon storage of Beihai city decreased first and then increased,with an overall increase of 4.01×10^(5) t in the past 10 years;③By 2035,the predicted carbon reserves in Beihai city would further decrease in the natural evolution scenario.But in the green intensive ecological protection scenario,carbon reserves can still slowly recover under the premise of fully ensuring high-quality socio-economic development.In the next 15 years,carbon reserves can lose 1.36×10^(5) t less than in the natural change scenario.
作者
李小军
车良革
胡宝清
LI Xiaojun;CHE Liangge;HU Baoqing(Beihai City Land and Resources Information Center,Beihai 536000,China;Guangxi Zhihetiantai Geographic Information System Engineering Services Co.,Ltd.,Nanning 530201,China;The Key Laboratory of Environmental Evolution and Resources Utilization of Beibu Gulf,Ministry of Education,Nanning Normal University,Nanning 530001,China;Guangxi Key Laboratory of Surface Process and Intelligent Simulation,Nanning 530001,China)
出处
《测绘通报》
CSCD
北大核心
2023年第6期117-123,183,共8页
Bulletin of Surveying and Mapping
基金
国家自然科学基金重点项目(41930537)。
