MEASUREMENT OF BEIJING'S URBAN COMPREHENSIVE RESILIENCE BASED ON DISSIPATIVE STRUCTURE THEORY

doi:10.13776/jcnki.resourcesindustries.20240528.001

Abstract

Abstract: Quantitative measurement of urban comprehensive resilience is a basic step in marking urban resilience level and leading urban eco-civilization construction. This paper, viewing from dissipative structure theory, selects social, economical, ecological and infrastructural resilience and their 21 sub-categories and uses entropy TOPSIS model to quantitatively measure Beijing's 2016 to 2019 urban comprehensive resilience based on urban giant system entropy. Beijing's 2016 to 2019 urban comprehensive resilience has been rising over time with its average showing a trend of “rising-stabilizing-rising”, resilience index between 0.30 to 0.76. Beijing's top 3 in urban comprehensive resilience index are Chaoyang, Haidian and Xicheng districts, at 0.76, 0.74 and 0.55 respectively. Beijing urban comprehensive level can be divided into five levels, low, relatively low, middle, relatively high and high based on the resilience index, of which low and relatively low are 82% of the total districts, suggesting an overall low resilience level and varying spatially, in a distributing pattern of “north-low, southeast-relatively-high, center-high”. Their resilience levels are impacted by governmental investments and natural resources abundance of advantages and disadvantages, of which Chaoyang and Haidian districts are relatively high, and Chaoyang's infrastructural resilience level is much higher than others, while Mentougou, Fangshan and Huairou districts are of more ecological resilience. This paper presents approaches to urban comprehensive resilience on controlling producing system's internal entropy, increasing inputting system's negative entropy, promoting urban reviving, upgrading infrastructures and ecological construction.

Key words: urban resilience, entropy, TOPSIS model, dissipative structure theory, Beijing city

摘要： 城市综合韧性定量测度是衡量城市韧性发展水平、指导城市生态文明建设的重要基础性工作。基于耗散结构理论视角，在分析城市巨系统的系统熵构成特征的基础上，选择社会韧性、经济韧性、生态韧性和基础设施韧性4大类21小类指标，运用熵权-TOPSIS模型开展北京市2016—2019年城市综合韧性定量测度。研究结果表明：1）2016—2019年北京市城市综合韧性水平逐年增长，韧性平均值呈“上升—平稳—上升”趋势，韧性指数介于0.30～0.76。2）北京市综合韧性指数最高的前3个区分别为朝阳区、海淀区和西城区，韧性指数分别为0.76、0.74和0.55；根据韧性指数高低，全市综合韧性水平可划分为低韧性、较低韧性、中等韧性、较高韧性和高韧性5级，其中低韧性与较低韧性辖区数占区总数的82%，全市总体韧性水平较低，且空间上不同区的韧性水平存在明显差异，呈“北低、东南较高、中心最高”的分布特点。3）全市各区不同类型的韧性水平受政府资金投入和自然资源本底条件影响，各具优势和不足，其中，朝阳区和海淀区社会、经济韧性水平较高，且朝阳区基础设施韧性水平相较其他区明显较高，而门头沟区、房山区和怀柔区等区的生态韧性更有优势。基于上述研究结果，提出如下政策建议：北京市应从控制系统内熵产生、增加系统负熵流输入两方面增强城市发展综合韧性，促进城市更新、基础设施改造升级与生态文明建设。

关键词: 城市韧性, 熵权法, TOPSIS模型, 耗散结构理论, 北京市

CLC Number:

F290

WEN Hanzhi, TIAN Yi, LI Jiaqi, et al.. MEASUREMENT OF BEIJING'S URBAN COMPREHENSIVE RESILIENCE BASED ON DISSIPATIVE STRUCTURE THEORY[J]. Resources & Industries, 2024, 26(4): 147-.

问瀚之, 田毅, 李嘉琪, 等. 耗散结构理论视野下北京城市综合韧性测度研究[J]. 资源与产业, 2024, 26(4): 147-.

References

陈长坤, 陈以琴, 施波, 等, 2018. 雨洪灾害情境下城市韧性评估模型[J]. 中国安全科学学报, 28（4）: 1-6.〔CHEN C K, CHEN Y Q, SHI B, et al., 2018. A model for evaluating urban resilience to rainstorm flood disasters[J]. China Safety Science Journal, 28(4): 1-6.〕

陈鹏, 赵洪阳, 张继权, 等, 2020. 城市内涝灾害受灾人口评估方法与实证研究: 以哈尔滨市道里区为例[J]. 地理科学, 40（1）: 158-164.〔CHEN P, ZHAO H Y, ZHANG J Q, et al., 2020. Assessment method and empirical study on the population affected by urban waterlogging disaster: Daoli district of Harbin as an example[J]. Scientia Geographica Sinica, 40(1): 158-164.〕

郭羽羽, 罗福周, 钟兴润, 2021. 基于熵权-正态云模型的城市安全韧性评估研究[J]. 灾害学, 36（4）: 168-174.〔GUO Y Y, LUO F Z, ZHONG X R, 2021. Study on urban safety resilience assessment based on entropy weightnormal cloud model[J]. Journal of Catastrophology, 36(4): 168-174.〕

黄亚江, 李书全, 项思思, 2021. 基于AHP-PSO模糊组合赋权法的地铁火灾安全韧性评估[J]. 灾害学, 36（3）: 15-20, 40.〔HUANG Y J, LI S Q, XIANG S S, 2021. Evaluation of subway fire safety resilience based on AHP-PSO fuzzy combination weighting method[J]. Journal of Catastrophology, 36(3): 15-20, 40.〕

李亚, 翟国方, 2017. 我国城市灾害韧性评估及其提升策略研究[J]. 规划师, 33（8）: 5-11.〔LI Y, ZHAI G F, 2017. China's urban disaster resilience evaluation and promotion[J]. Planners, 33(8): 5-11.〕

孟晓静, 陈鑫, 陈佳静, 等, 2023. 组合赋权-TOPSIS在洪涝灾害下城市区域韧性评估中的应用[J]. 安全与环境学报, 23（5）: 1465-1473.〔MENG X J, CHEN X, CHEN J J, et al., 2023. Application of combination weighting and TOPSIS in the assessment of urban regional resilience under flood disaster[J]. Journal of Safety and Environment, 23(5): 1465-1473.〕

彭翀, 林樱子, 吴宇彤, 等, 2021. 基于“成本-能力-能效”的长江经济带城市韧性评估[J]. 长江流域资源与环境, 30（8）: 1795-1808.〔PENG C, LIN Y Z, WU Y T, et al., 2021. Urban resilience evaluation of the Yangtze River economic belt based on “cost-capacity-efficiency”[J]. Resources and Environment in the Yangtze Basin, 30(8): 1795-1808.〕

屈金芝, 张艳松, 张艳, 等, 2022. 基于熵权法TOPSIS模型中国钛资源供应安全评价[J]. 资源与产业, 24（1）: 26-36.〔QU J Z, ZHANG Y S, ZHANG Y, et al., 2022. Supply security of China’s titanium resource based on entropy TOPSIS model[J]. Resources & Industries, 24(1): 26-36.〕

王光辉, 刘怡君, 王红兵, 2014. 基于耗散结构理论的城市风险形成及演化机理研究[J]. 城市发展研究, 21（11）: 81-86.〔WANG G H, LIU Y J, WANG H B, 2014. Study on formation and evolution mechanism of urban risk based on dissipative structure theory[J]. Urban Development Studies, 21(11): 81-86.〕

肖圣, 多玲花, 邹自力, 2023. 基于“风险-连通性-潜力”的南昌市生态韧性评估[J]. 应用生态学报, 34（3）: 733-741.〔XIAO S, DUO L H, ZOU Z L, 2023. Assessment of ecological resilience in Nanchang based on “riskconnectivitypotential”[J]. Chinese Journal of Applied Ecology, 34(3): 733-741.〕

徐江, 邵亦文, 2015. 韧性城市: 应对城市危机的新思路[J]. 国际城市规划, 30（2）: 1-3.〔XU J, SHAO Y W, 2015. Resilient cities: a new shift to urban crisis management[J]. Urban Planning International, 30(2): 1-3.〕

徐姗, 员鑫淼, 邓羽, 2023. 北京城市功能空间演进的结构模式与聚合规律[J]. 地理学报, 78（8）: 2092-2104.〔XU S, YUAN X M, DENG Y, 2023. Evolution of urban functional space in Beijing: modes and aggregation laws[J]. Acta Geographica Sinica, 78(8): 2092-2104.〕

徐志胜, 冯凯, 白国强, 等, 2004. 关于城市公共安全可持续发展理论的初步研究[J]. 中国安全科学学报, 14（1）: 3-6.〔XU Z S, FENG K, BAI G Q, et al., 2004. Preliminary study on sustainable development theory of urban community safety[J]. China Safety Science Journal, 14(1): 3-6.〕

叶进, 曹陇华, 常丽霞, 2008. 耗散结构对生态风险管理的启示[J]. 科学·经济·社会（2）: 70-74, 78.〔YE J, CAO L H, CHANG L X, 2008. Enlightenment of dissipative structure on the ecological risk management[J]. Science Economy Society(2): 70-74, 78.〕

湛垦华, 沈小峰, 1982. 普利高津与耗散结构理论[M]. 西安: 陕西科学技术出版社.

张振, 张以晨, 张继权, 等, 2023. 基于熵权法和TOPSIS模型的城市韧性评估: 以长春市为例[J]. 灾害学, 38（1）: 213-219.〔ZHANG Z, ZHANG Y C, ZHANG J Q, et al., 2023. Urban resilience assessment based on entropy weight method and TOPSIS model: take Changchun city as an example[J]. Journal of Catastrophology, 38(1): 213-219.〕

郑艳, 2017. 新型城镇化背景下我国韧性城市建设的思考[J]. 城市与减灾（4）: 61-65.

CUTTER S L, ASH K D, EMRICH C T, 2014. The geographies of community disaster resilience[J]. Global Environmental Change, 29: 65-77.

GRIMM N B, FAETH S H, GOLUBIEWSKI N E, et al., 2008. Global change and the ecology of cities[J]. Science, 319: 756760.

OUYANG M, DUE-AS-OSORIO L, MIN X, 2012. A three-stage resilience analysis framework for urban infrastructure systems[J]. Structural Safety, 36/37(1): 23-31.

[1]	WANG Chengjun, YANG Qian, FENG Tao, et al.. DEVELOPMENT-ECONOMY-ENVIRONMENT COUPLING COORDINATED DEVELOPMENT AND TEMPORAL-SPATIAL EVOLUTION OF#br# YELLOW RIVER'S MINERAL RESOURCES [J]. Resources & Industries, 2024, 26(4): 10-20.
[2]	ZHAO Min, CHU Peipei. SPATIAL CONVERGENCE AND DIFFERENTIATED CHARACTERISTICS OF CHINA'S PROVINCIAL RURAL INDUSTRIAL INTEGRATION LEVEL [J]. Resources & Industries, 2023, 25(1): 51-66.
[3]	SUN Minghao, LIAO Qiumin. RISK ASSESSMENT OF MINERAL RESOURCES INVESTMENT IN “THE BELT AND ROAD” NATIONS UNDER ANTI-GLOBALIZATION [J]. Resources & Industries, 2022, 24(3): 169-180.
[4]	LÜ Tiangui, KONG Anni, WANG Li. TEMPORAL-SPATIAL EVOLUTION AND FACTORS OF REGIONAL ECOLOGICAL SECURITY BASED ON DPSIR-TOPSIS MODEL [J]. Resources & Industries, 2022, 24(2): 30-41.
[5]	ZHANG Ying, LI Xiaoge. CARBON SINK POTENTIAL OF BEIJING'S FOREST UNDER CARBON PEAK AND CARBON NEUTRALITY [J]. Resources & Industries, 2022, 24(1): 15-25.
[6]	QU Jinzhi, ZHANG Yansong, ZHANG Yan, et al. SUPPLY SECURITY OF CHINA'S TITANIUM RESOURCE BASED ON ENTROPY TOPSIS MODEL [J]. Resources & Industries, 2022, 24(1): 26-36.
[7]	MA Rui. RESEARCH ON EVALUATION AND SPATIAL DISTRIBUTION OF HIGH-QUALITY DEVELOPMENT IN 9 PROVINCES OF THE YELLOW RIVER BASIN FROM THE PERSPECTIVE OF NEW DEVELOPMENT CONCEPTS [J]. Resources & Industries, 2022, 24(1): 160-171.
[8]	PANG Dongyan, ZHAO Lin, YU Wei, et al. RESILIENCE MEASUREMENT AND OBSTACLE FACTORS OF TOURISM ECONOMY IN SHANDONG PROVINCE [J]. Resources & Industries, 2021, 23(3): 50-59.
[9]	CUI Wenjing, YAN Jingjing, SHA Jinghua, et al. EVALUATION OF TIANJIN'S OCEANIC RESOURCES ENVIRONMENTAL CARRYING CAPACITY BASED ON ENTROPY-WEIGHTED TOPSIS MODEL [J]. Resources & Industries, 2020, 22(6): 9-17.
[10]	华坚, 庞丽. QUALITY DEVELOPMENT OF YANGTZE RIVER ECONOMIC ZONE FROM PERSPECTIVE OF SCIENTIFIC FINANCE [J]. Resources & Industries, 2020, 22(4): 12-22.
[11]	DI Qianbin, XU Lixiang. TEMPORAL-SPATIAL VARIANCE OF INNOVATIVE DEVELOPMENT OF CHINA'S MARINE ECONOMY [J]. Resources & Industries, 2020, 22(3): 65-73.
[12]	SHEN Jüqin, ZHANG Ling, SUN Fuhua. SOCIAL STABILITY RISK ASSESSMENT OF VITAL HYDROLOGICAL PROJECTS BASED ON ENTROPY EXTENSIBLE MATERIAL ELEMENT MODEL ON AN EXAMPLE OF W RIVER CHANNEL CONSOLIDATION PROJECT [J]. Resources & Industries, 2020, 22(1): 52-60.
[13]	PENG Wei. REGIONAL TECHNICAL INNOVATION COMPREHENSIVE EVALUATION BASED ON DPSIR-ENTROPY-TOPSIS WITH EMPIRICAL EVIDENCES FROM GUANGDONG'S 21 CITIES [J]. Resources & Industries, 2019, 21(5): 101-112.
[14]	NI Wenqing. MEASUREMENT AND FEASIBILITY STUDY OF BEIJING-TIANJIN-HEBEI(JJJ)‘S INDUSTRIAL INTEGRATION [J]. Resources & Industries, 2019, 21(3): 31-37.
[15]	XU Changxin, HU Liyuan, SUN Yangyang. COUPLED COORDINATION BETWEEN URBANIZATION EFFICIENCY AND ECONOMIC DEVELOPMENT IN ANHUI PROVINCE [J]. Resources & Industries, 2019, 21(2): 24-33.