长江经济带市域生态环境质量空间分异与影响因素分析——基于三生空间的土地利用转型

doi:10.16258/j.cnki.1674-5906.2023.07.001

生态环境学报 ›› 2023, Vol. 32 ›› Issue (7): 1173-1184.DOI: 10.16258/j.cnki.1674-5906.2023.07.001

• 研究论文 • 下一篇

长江经济带市域生态环境质量空间分异与影响因素分析——基于三生空间的土地利用转型

田成诗(), 孙瑞欣^*()

东北财经大学统计学院，辽宁大连 116025

收稿日期:2023-02-03 出版日期:2023-07-18 发布日期:2023-09-27
通讯作者: * 孙瑞欣。E-mail: ruixinsunshine@163.com
作者简介:田成诗（1971年生），男，教授，博士，主要研究方向为资源经济学。E-mail: sctian71@163.com
基金资助:
国家自然科学基金项目(42276231);东北财经大学科研平台建设专项(PT-Z202208);辽宁省教育厅科研项目(LJKMZ20221578)

Spatial Heterogeneity and Its Influential Factors of Eco-environmental Quality in the Yangtze River Economic Belt: Based on Land Use Transformation of Production, Living and Ecological Spaces

TIAN Chengshi(), SUN Ruixin^*()

School of Statistics, Dongbei University of Finance and Economics, Dalian 116025, P. R. China

Received:2023-02-03 Online:2023-07-18 Published:2023-09-27

摘要/Abstract

摘要：

随着城镇化和工业化进程加快，长江经济带土地利用主导功能发生较大转变，生产、生活、生态空间（“三生空间”）转型对生态环境质量的影响日益增强，从“三生空间”角度研究长江经济带生态环境质量对于推动长江经济带高质量发展意义重大。基于土地利用遥感监测数据，通过生态环境质量指数模型、地理探测器等方法，定量分析长江经济带130个地级市生态环境质量的空间分异及其影响因素。结果表明，（1）2000-2020年长江经济带生态环境质量处于中等以上，其中2000-2010年生态环境质量等级保持不变，主要有中等和较高质量两种类型；2010-2020年生态环境质量等级发生变化，中等质量区和较高质量区面积减少，高质量区面积增加。（2）生态环境质量空间分布存在明显差异。长江经济带生态环境质量整体呈“东北部低、西部、中部和东南部高”。2000-2010年生态环境质量空间分布一致。2010-2020年多数地区的生态环境质量等级上升，主要趋势为中等质量转化为较高质量、较高质量转化为高质量。（3）不同因子对生态环境质量空间分异的影响程度具有显著差异。土地利用程度、人口密度和坡度对生态环境质量的影响占主导地位，对生态环境质量空间分异的解释力q值分别为0.776、0.409、0.406，其他因子对生态环境质量空间分异的影响相对较弱。（4）任意两因子间的交互作用均大于单因子对生态环境质量空间分异的影响，且土地利用程度与其他因子的结合是影响长江经济带生态环境质量空间分异的最主要因素。

关键词: 长江经济带, 生态环境质量, 空间分异, 地理探测器, 三生空间, 土地利用转型

Abstract:

With the acceleration of urbanization and industrialization, the dominant function of land use in the Yangtze River Economic Belt has changed dramatically, and the transformation of production, living, and ecological spaces (i.e., the three types of spaces) strengthens its influence on the eco-environmental quality. It is of great significance to study the eco-environmental quality in the Yangtze River Economic Belt from the perspective of the three types of spaces, which can promote the high-quality development of the Yangtze River Economic Belt. Based on the land use remote sensing monitoring data of 2000, 2010 and 2020, we quantitatively analyzed the spatial heterogeneity and its influential factors of 130 cities in Yangtze River Economic Belt by applying statistical methods including the index of eco-environmental quality and Geodetector. The empirical results showed that (1) during 2000-2020, the eco-environmental quality of the Yangtze River Economic Belt was above the average level. More specifically, the eco-environmental quality remained unchanged during 2000-2010 and mainly consisted of two types: medium and relatively high quality; from 2010 to 2020, the level of eco-environmental quality changed, with a decrease in the areas of medium and high quality and an increase in the areas of high quality. (2) There are significant differences in the spatial distribution of eco-environmental quality. The overall eco-environmental quality of the Yangtze River Economic Belt showed the trend of low in the northeast and high in the west, central and southeast. The spatial distribution of eco-environmental quality was consistent from 2000 to 2010. From 2010 to 2020, the eco-environmental quality level in most regions increased, with the medium quality transforming into higher quality and comparatively higher quality transforming into high quality. (3) There were significant differences among the driving factors that influenced the spatial heterogeneity of eco-environmental quality. The dominant driving factors included land use, population density, and slope, and the value of q were 0.776, 0.409 and 0.406, respectively, while the influence of other factors were relatively weak. (4) The mutual effects between any two factors were greater than the impact of a single factor on the spatial differentiation of eco-environmental quality, and the combination of land use degree and other factors was the most important factor affecting the spatial differentiation of eco-environmental quality in the Yangtze River Economic Belt.

Key words: Yangtze River Economic Belt, eco-environmental quality, spatial heterogeneity, Geodetector, production-living-ecological spaces, land use transition

中图分类号:

田成诗, 孙瑞欣. 长江经济带市域生态环境质量空间分异与影响因素分析——基于三生空间的土地利用转型[J]. 生态环境学报, 2023, 32(7): 1173-1184.

TIAN Chengshi, SUN Ruixin. Spatial Heterogeneity and Its Influential Factors of Eco-environmental Quality in the Yangtze River Economic Belt: Based on Land Use Transformation of Production, Living and Ecological Spaces[J]. Ecology and Environment, 2023, 32(7): 1173-1184.

图/表 9

参考文献 46

[1]	AN M, XIE P, HE W J, et al., 2022. Spatiotemporal change of ecologic environment quality and human interaction factors in three gorges ecologic economic corridor, based on RSEI[J]. Ecological Indicators, 141(4): 109090. DOI URL
[2]	CHENG P, MIN M, ZHAO W, et al., 2021. Spatial differentiation pattern of habitat quality and mechanism of factors influencing in resource-based cities: A case study of Tangshan city, China[J]. Journal of Resources and Ecology, 12(5): 636-649. DOI
[3]	LÜ L G, LI Y L, SUN Y, 2017. The spatio-temporal pattern of regional land use change and eco-environmental responses in Jiangsu, China[J]. Journal of Resources and Ecology, 8(3): 268-276. DOI
[4]	SUDHIRA H S, RAMACHANDRA T V, JAGADISH K S, 2004. Urban sprawl: metrics, dynamics and modelling using GIS[J]. International Journal of Applied Earth Observation and Geoinformation, 5(1): 29-39. DOI URL
[5]	TIAN Y L, XU D X, SONG J X, et al., 2022. Impacts of land use changes on ecosystem services at different elevations in an ecological function area, northern China[J]. Ecological Indicators, 140(3): 109003. DOI URL
[6]	YAN Y B, CHAI Z Y, YANG X D, et al., 2021. The temporal and spatial changes of the ecological environment quality of the urban agglomeration on the northern slope of Tianshan Mountain and the influencing factor[J]. Ecological Indicators, 133(2): 108380. DOI URL
[7]	YANG H H, YU J, XU W Z, et al., 2023. Long-time series ecological environment quality monitoring and cause analysis in the Dianchi Lake Basin, China[J]. Ecological Indicators, 148(602): 110084. DOI URL
[8]	YANG X Y, MENG F, FU P J, et al., 2021. Spatiotemporal change and driving factors of the eco-environment quality in the Yangtze River Basin from 2001 to 2019[J]. Ecological Indicators, 131(1): 108214. DOI URL
[9]	安敏, 李文佳, 吴海林, 等, 2022. 三峡库区生态环境质量的时空格局演变及影响因素[J]. 长江流域资源与环境, 31(12): 2743-2755.
	AN M, LI W J, WU H L, et al., 2022. Evolution and influencing factors of the spatial-temporal pattern of ecological environment quality in the Three Gorges Reservoir Area[J]. Resources and Environment in the Yangtze Basin, 31(12): 2743-2755.
[10]	陈龙, 周生路, 周兵兵, 等, 2015. 基于主导功能的江苏省土地利用转型特征与驱动力[J]. 经济地理, 35(2): 155-162.
	CHEN L, ZHOU S L, ZHOU B B, et al., 2015. Characteristics and driving forces of regional land use transition based on the leading function classification: A case study of Jiangsu province[J]. Economic Geography, 35(2): 155-162.
[11]	陈万旭, 李江风, 曾杰, 等, 2019. 中国土地利用变化生态环境效应的空间分异性与形成机理[J]. 地理研究, 38(9): 2173-2187. DOI
	CHEN W X, LI J F, ZENG J, et al., 2019. Spatial heterogeneity and formation mechanism of eco-environmental effect of land use change in China[J]. Geographical Research, 38(9): 2173-2187. DOI
[12]	崔国屹, 张艳, 晁阳, 等, 2023. 秦岭地区近40年土地利用变化及其生态环境效应[J]. 水土保持研究, 30(1): 319-326.
	CUI G Y, ZHANG Y, CHAO Y, et al., 2023. Land use change and eco-environmental effects in Qinling Mountains in recent 40 years[J]. Research of Soil and Water Conservation, 30(1): 319-326.
[13]	戴文远, 江方奇, 黄万里, 等, 2018. 基于 “三生空间” 的土地利用功能转型及生态服务价值研究——以福州新区为例[J]. 自然资源学报, 33(12): 2098-2109. DOI
	DAI W Y, JIANG F Q, HUANG W L, et al., 2018. Study on transition of land use function and ecosystem service value based on the conception of production, living and ecological space: A case study of the Fuzhou New Area[J]. Journal of Natural Resources, 33(12): 2098-2109. DOI URL
[14]	董建红, 张志斌, 笪晓军, 等, 2021. “三生” 空间视角下土地利用转型的生态环境效应及驱动力分析: 以甘肃省为例[J]. 生态学报, 41(15): 1-11.
	DONG J H, ZHANG Z B, DA X J, et al., 2021. Eco-environmental effects of land use transformation and its driving forces from the perspective of “production-living-ecological” spaces: A case study of Gansu Province[J]. Acta Ecologica Sinica, 41(15): 1-11. DOI URL
[15]	董建红, 张志斌, 刘奔腾, 等, 2023. “三生” 空间视角下西北地区生态环境质量分异机制的地理探测[J]. 干旱区地理, 46(4): 515-526.
	DONG J H, ZHANG Z B, LIU B T, et al., 2023. Geographical exploration of the spatial differentiation mechanism of eco-environmental quality in northwest China from the perspective of “production-living-ecological” space[J]. Arid Land Geography, 46(4): 515-526.
[16]	盖兆雪, 陈旭菲, 杜国明, 等, 2022. 松花江流域哈尔滨段三生空间演变的生态环境效应及驱动因素分析[J]. 水土保持学报, 36(1): 116-123.
	GAI Z X, CHEN X F, DU G M, et al., 2022. Analysis on eco-environmental effects and driving factors of ecological-production-living spatial evolution in Harbin section of Songhua River Basin[J]. Journal of Soil and Water Conservation, 36(1): 116-123.
[17]	高艺宁, 赵萌莉, 王宏亮, 等, 2019. 景观生态视角下草地生态质量的空间差异及其影响因素: 以内蒙古四子王旗为例[J]. 生态学报, 39(14): 5288-5300.
	GAO Y N, ZHAO M L, WANG H L, et al., 2019. Analysis of spatial differentiation of grassland ecological quality and its affecting factors based on landscape ecology perspective: A case study of Siziwang Banner[J]. Acta Ecologica Sinica, 39(14): 5288-5300.
[18]	郭泽呈, 魏伟, 张学渊, 等, 2019. 基于RS和GIS的石羊河流域生态环境质量空间分布特征及其影响因素[J]. 应用生态学报, 30(9): 3075-3086. DOI
	GUO Z C, WEI W, ZHANG X Y, et al., 2019. Spatial distribution characteristics and influencing factors of eco-environmental quality based on RS and GIS in Shiyang River Basin, China[J]. Chinese Journal of Applied Ecology, 30(9): 3075-3086.
[19]	韩美, 孔祥伦, 李云龙, 等, 2021. 黄河三角洲“三生”用地转型的生态环境效应及其空间分异机制[J]. 地理科学, 41(6): 1009-1018. DOI
	HAN M, KONG X L, LI Y L, et al., 2021. Eco-environmental effects and its spatial heterogeneity of “ecological-production-living” land use transformation in the Yellow River Delta[J]. Scientia Geographica Sinica, 41(6): 1009-1018.
[20]	黄金川, 林浩曦, 漆潇潇, 2017. 面向国土空间优化的三生空间研究进展[J]. 地理科学进展, 36(3): 378-391. DOI
	HUANG J C, LIN H X, QI X X, 2017. A literature review on optimization of spatial development pattern based on ecological-production-living space[J]. Progress in Geography, 36(3): 378-391. DOI
[21]	黄木易, 方斌, 岳文泽, 等, 2019. 近20a来巢湖流域生态服务价值空间分异机制的地理探测[J]. 地理研究, 38(11): 2790-2803. DOI
	HUANG M Y, FANG B, YUE W Z, et al., 2019. Spatial differentiation of ecosystem service values and its geographical detection in Chaohu Basin during 1995-2017[J]. Geographical Research, 38(11): 2790-2803. DOI
[22]	黄天能, 张云兰, 2021. 基于“三生空间”的土地利用功能演变及生态环境响应——以桂西资源富集区为例[J]. 生态学报, 41(1): 348-359.
	HUANG T N, ZHANG Y L, 2021. Transformation of land use function and response of eco-environment based on “production-life-ecology space”: A case study of resource-rich area in western Guangxi[J]. Acta Ecologica Sinica, 41(1): 348-359.
[23]	何青泽, 谢德体, 王三, 等, 2019. 重庆市北碚区土地利用转型及生态环境效应[J]. 水土保持研究, 26(2): 290-296.
	HE Q Z, XIE D T, WANG S, et al., 2019. Land use transformation and its eco-environmental effects in Beibei District, Chongqing[J]. Research of Soil and Water Conservation, 26(2): 290-296.
[24]	孔冬艳, 陈会广, 吴孔森, 2021. 中国“三生空间”演变特征、生态环境效应及其影响因素[J]. 自然资源学报, 36(5): 1116-1135. DOI
	KONG D Y, CHEN H G, WU K S, 2021. The evolution of “production-living-ecological” space, eco-environmental effects and its influencing factors in China[J]. Journal of Natural Resources, 36(5): 1116-1135. DOI URL
[25]	李晓文, 方创琳, 黄金川, 等, 2003. 西北干旱区城市土地利用变化及其区域生态环境效应: 以甘肃河西地区为例[J]. 第四纪研究, 23(3): 280-290.
	LI X W, FANG C L, HUANG J C, et al., 2003. The urban land use transformations and associated effects on eco-environment in northwest China arid region: A case study in Hexi region, Gansu province[J]. Quaternary Sciences, 23(3): 280-290.
[26]	刘春芳, 王川, 刘立程, 2018. 三大自然区过渡带生境质量时空差异及形成机制——以榆中县为例[J]. 地理研究, 37(2): 419-432. DOI
	LIU C F, WANG C, LIU L C, 2018. Spatio-temporal variation on habitat quality and its mechanism within the transitional area of the Three Natural Zones: A case study in Yuzhong county[J]. Geographical Research, 37(2): 419-432.
[27]	刘纪远, 匡文慧, 张增祥, 等, 2014. 20世纪80年代末以来中国土地利用变化的基本特征与空间格局[J]. 地理学报, 69(1): 3-14.
	LIU J Y, KUANG W H, ZHANG Z X, et al., 2014. Spatiotemporal characteristics, patterns and causes of land use changes in China since the late 1980s[J]. Acta Geographica Sinica, 69(1): 3-14. DOI
[28]	刘纪远, 宁佳, 匡文慧, 等, 2018. 2010-2015年中国土地利用变化的时空格局与新特征[J]. 地理学报, 73(5): 789-802. DOI
	LIU J Y, NING J, KUANG W H, et al., 2018. Spatio-temporal patterns and characteristics of land-use change in China during 2010-2015[J]. Acta Geographica Sinica, 73(5): 789-802. DOI
[29]	刘彦随, 李进涛, 2017. 中国县域农村贫困化分异机制的地理探测与优化决策[J]. 地理学报, 72(1): 161-173. DOI
	LIU Y S, LI J T, 2017. Geographic detection and optimizing decision of the differentiation mechanism of rural poverty in China[J]. Acta Geographica Sinica, 72(1): 161-173. DOI
[30]	司晓君, 崔佳, 2022. 中原城市群“三生”用地转型及其生态环境效应[J]. 水土保持通报, 42(2): 284-290, 299.
	SI X J, CUI J, 2022. Transformation of productive-living-ecological land use and its eco-environmental effects in urban agglomeration of central plains[J]. Bulletin of Soil and Water Conservation, 42(2): 284-290, 299.
[31]	孙东琪, 张京祥, 朱传耿, 等, 2012. 中国生态环境质量变化态势及其空间分异分析[J]. 地理学报, 67(12): 1599-1610.
	SUN D Q, ZHANG J X, ZHU C G, et al., 2012. An assessment of China’s ecological environment quality change and its spatial variation[J]. Acta Geographica Sinica, 67(12): 1599-1610.
[32]	田智慧, 尹传鑫, 王晓蕾, 2023. 鄱阳湖流域生态环境动态评估及驱动因子分析[J]. 环境科学, 44(2): 816-827.
	TIAN Z H, YIN C X, WANG X L, 2023. Dynamic monitoring and driving factors analysis of ecological environment quality in Poyang Lake Basin[J]. Environmental Science, 44(2): 816-827.
[33]	王宾, 于法稳, 2019. 长江经济带城镇化与生态环境的耦合协调及时空格局研究[J]. 华东经济管理, 33(3): 58-63.
	WANG B, YU F W, 2019. Research on coupling coordination degree and spatial-temporal evolution between urbanization and ecological environment in the Yangtze River Economic Belt[J]. East China Economic Management, 33(3): 58-63.
[34]	王劲峰, 徐成东, 2017. 地理探测器: 原理与展望[J]. 地理学报, 72(1): 116-134. DOI
	WANG J F, XU C D, 2017. Geodetector: Principle and prospective[J]. Acta Geographica Sinica, 72(1): 116-134. DOI
[35]	王静, 周伟奇, 许开鹏, 等, 2017. 京津冀地区的生态质量定量评价[J]. 应用生态学报, 28(8): 2667-2676. DOI
	WANG J, ZHOU W Q, XU K P, et al., 2017. Quantitative assessment of ecological quality in Beijing-Tianjin-Hebei urban megaregion, China[J]. Chinese Journal of Applied Ecology, 28(8): 2667-2676.
[36]	王晓君, 吴敬学, 蒋和平, 2017. 中国农村生态环境质量动态评价及未来发展趋势预测[J]. 自然资源学报, 32(5): 864-876. DOI
	WANG X J, WU J X, JIANG H P, 2017. Dynamic assessment and trend prediction of rural eco-environmental quality in China[J]. Journal of Natural Resources, 32(5): 864-876.
[37]	王兆峰, 陈青青, 2021. 长江经济带旅游产业与生态环境交互胁迫关系验证及协调效应研究[J]. 长江流域资源与环境, 30(11): 2581-2593.
	WANG Z F, CHEN Q Q, 2021. Study on the verification and coordination effect of the interactive stress of tourism industry and ecological environment in the Yangtze River Economic Belt[J]. Resources and Environment in the Yangtze Basin, 30(11): 2581-2593.
[38]	吴宜进, 赵行双, 奚悦, 等, 2019. 基于MODIS的2006-2016年西藏生态质量综合评价及其时空变化[J]. 地理学报, 74(7): 1438-1449. DOI
	WU Y J, ZHAO X S, XI Y, et al., 2019. Comprehensive evaluation and spatial-temporal changes of eco-environmental quality based on MODIS in Tibet during 2006-2016[J]. Acta Geographica Sinica, 74(7): 1438-1449. DOI
[39]	武燕, 吴映梅, 陈云娟, 等, 2022. 基于 “三生” 空间演变的高原湖泊流域生态环境效应及影响因素分析——以滇池流域为例[J]. 西南农业学报, 35(10): 2265-2275.
	WU Y, WU Y M, CHEN Y J, et al., 2022. Eco-environmental effects and driving factors of ecological-production-living spatial evolution in plateau lake basin: A case study in the Dianchi basin, Southwest China[J]. Journal of Agricultural Sciences, 35(10): 2265-2275.
[40]	谢花林, 2008. 基于景观结构和空间统计学的区域生态风险分析[J]. 生态学报, 28(10): 5020-5026.
	XIE H L, 2008. Regional eco-risk analysis of based on landscape structure and spatial statistics[J]. Acta Ecologica Sinica, 28(10): 5020-5026.
[41]	杨清可, 段学军, 王磊, 等, 2018. 基于 “三生空间” 的土地利用转型与生态环境效应: 以长江三角洲核心区为例[J]. 地理科学, 38(1): 97-106. DOI
	YANG Q K, DUAN X J, WANG L, et al., 2018. Land use transformation based on ecological-production-living spaces and associated eco-environment effects: A case study in the Yangtze River Delta[J]. Scientia Geographica Sinica, 38(1): 97-106. DOI
[42]	苑韶峰, 唐奕钰, 申屠楚宁, 2019. 土地利用转型时空演变及其生态环境效应: 基于长江经济带127个地级市的实证研究[J]. 经济地理, 39(9): 174-181.
	YUAN S F, TANG Y Y, SHENTU C N, 2019. Spatiotemporal change of land-use transformation and its eco-environmental response: A case of 127 counties in Yangtze River Economic Belt[J]. Economic Geography, 39(9): 174-181.
[43]	章程焱, 杨少康, 董晓华, 等, 2023. 基于RSEI指数的长江上游流域生态环境质量时空演变及影响因子研究[J]. 水土保持研究, 30(1): 356-363.
	ZHANG C Y, YANG S K, DONG X H, et al., 2023. Research on spatiotemporal evolution and influencing factors of ecological environment quality in the Upper Yangtze River Basin Based on RSEI index[J]. Research of Soil and Water Conservation, 30(1): 356-363.
[44]	张杨, 刘艳芳, 顾渐萍, 等, 2011. 武汉市土地利用覆被变化与生态环境效应研究[J]. 地理科学, 31(10): 1280-1285.
	ZHANG Y, LIU Y F, GU J P, et al., 2011. Land use /land cover change and its environmental effects in Wuhan city[J]. Scientia Geographica Sinica, 31(10): 1280-1285.
[45]	郑晓豪, 陈颖彪, 郑子豪, 等, 2023. 湖北省生态系统服务价值动态变化及其影响因素演变[J]. 生态环境学报, 32(1): 195-206. DOI
	ZHENG X H, CHEN Y B, ZHENG Z H, et al., 2023. Dynamic changes of ecosystem service value and evolution of its influencing factors in Hubei province[J]. Ecology and Environmental Sciences, 32(1): 195-206.
[46]	周沙, 黄跃飞, 王光谦, 2014. 黑河流域中游地区生态环境变化特征及驱动力[J]. 中国环境科学, 34(3): 766-773.
	ZHOU S, HUANG Y F, WANG G Q, 2014. Changes in the ecological environment and there determining factors in the middle Heihe River Basin[J]. China Environmenta1 Science, 34(3): 766-773.

“三生空间” 主导功能		土地利用二级分类	生态环境属性因子
一级地类	二级地类	土地利用二级分类	2000年	2010年	2020年
生产用地	农业生产用地	水田、旱地	0.275	0.275	0.275
生产用地	工矿生产用地	工矿建设用地	0.150	0.150	0.150
生活用地	城镇生活用地	城镇用地	0.200	0.200	0.200
生活用地	农村生活用地	农村居民点	0.200	0.200	0.200
生态用地	林地生态用地	有林地、灌木林、疏林地、其他林地	0.757	0.756	0.761
	草地生态用地	高覆盖度草地、中覆盖度草地、低覆盖度草地	0.551	0.552	0.551
	水域生态用地	河渠、湖泊、水库坑塘、滩涂、滩地	0.621	0.618	0.612
	其他生态用地	沙地、盐碱地、沼泽地、裸土地、裸岩石砾地	0.170	0.167	0.193

“三生空间” 主导功能		土地利用二级分类	生态环境属性因子
一级地类	二级地类	土地利用二级分类	2000年	2010年	2020年
生产用地	农业生产用地	水田、旱地	0.275	0.275	0.275
生产用地	工矿生产用地	工矿建设用地	0.150	0.150	0.150
生活用地	城镇生活用地	城镇用地	0.200	0.200	0.200
生活用地	农村生活用地	农村居民点	0.200	0.200	0.200
生态用地	林地生态用地	有林地、灌木林、疏林地、其他林地	0.757	0.756	0.761
	草地生态用地	高覆盖度草地、中覆盖度草地、低覆盖度草地	0.551	0.552	0.551
	水域生态用地	河渠、湖泊、水库坑塘、滩涂、滩地	0.621	0.618	0.612
	其他生态用地	沙地、盐碱地、沼泽地、裸土地、裸岩石砾地	0.170	0.167	0.193

面积/ km²	2000年		2010年		2020年
面积/ km²	中等质量	较高质量	中等质量	较高质量	中等质量	较高质量	高质量
浙江省	9.86×10³	9.19×10⁴	9.86×10³	9.19×10⁴	3.99×10³	1.47×10⁴	8.31×10⁴
重庆市	-	8.11×10⁴	-	8.11×10⁴	-	8.11×10⁴	-
贵州省	-	1.81×10⁵	-	1.81×10⁵	-	4.66×10⁴	1.35×10⁵
湖北省	7.43×10⁴	1.10×10⁵	7.43×10⁴	1.10×10⁵	4.05×10⁴	5.27×10⁴	9.15×10⁴
湖南省	4.64×10⁴	1.70×10⁵	4.64×10⁴	1.70×10⁵	-	6.18×10⁴	1.55×10⁵
江苏省	9.80×10⁴	-	9.80×10⁴	-	9.80×10⁴	-	-
江西省	7.72×10³	1.63×10⁵	7.72×10³	1.63×10⁵	7.72×10³	3.24×10³	1.60×10⁵
上海市	6.15×10³	-	6.15×10³	-	6.15×10³	-	-
四川省	1.21×10⁵	3.59×10⁵	1.21×10⁵	3.59×10⁵	5.96×10⁴	1.10×10⁵	3.10×10⁵
云南省	-	4.04×10⁵	-	4.04×10⁵	-	3.00×10⁴	3.74×10⁵
安徽省	1.09×10⁵	3.00×10⁴	1.09×10⁵	3.00×10⁴	7.32×10⁴	3.53×10⁴	3.00×10⁴

面积/ km²	2000年		2010年		2020年
面积/ km²	中等质量	较高质量	中等质量	较高质量	中等质量	较高质量	高质量
浙江省	9.86×10³	9.19×10⁴	9.86×10³	9.19×10⁴	3.99×10³	1.47×10⁴	8.31×10⁴
重庆市	-	8.11×10⁴	-	8.11×10⁴	-	8.11×10⁴	-
贵州省	-	1.81×10⁵	-	1.81×10⁵	-	4.66×10⁴	1.35×10⁵
湖北省	7.43×10⁴	1.10×10⁵	7.43×10⁴	1.10×10⁵	4.05×10⁴	5.27×10⁴	9.15×10⁴
湖南省	4.64×10⁴	1.70×10⁵	4.64×10⁴	1.70×10⁵	-	6.18×10⁴	1.55×10⁵
江苏省	9.80×10⁴	-	9.80×10⁴	-	9.80×10⁴	-	-
江西省	7.72×10³	1.63×10⁵	7.72×10³	1.63×10⁵	7.72×10³	3.24×10³	1.60×10⁵
上海市	6.15×10³	-	6.15×10³	-	6.15×10³	-	-
四川省	1.21×10⁵	3.59×10⁵	1.21×10⁵	3.59×10⁵	5.96×10⁴	1.10×10⁵	3.10×10⁵
云南省	-	4.04×10⁵	-	4.04×10⁵	-	3.00×10⁴	3.74×10⁵
安徽省	1.09×10⁵	3.00×10⁴	1.09×10⁵	3.00×10⁴	7.32×10⁴	3.53×10⁴	3.00×10⁴

因子	X₁	X₂	X₃	X₄	X₅	X₆	X₇	X₈	X₉	X₁₀	X₁₁
q值	0.046	0.406	0.159	0.117	0.776	0.409	0.108	0.066	0.085	0.071	0.060
P值	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000

长江经济带市域生态环境质量空间分异与影响因素分析——基于三生空间的土地利用转型

Spatial Heterogeneity and Its Influential Factors of Eco-environmental Quality in the Yangtze River Economic Belt: Based on Land Use Transformation of Production, Living and Ecological Spaces

RichHTML

PDF

可视化

摘要/Abstract

引用本文

使用本文

图/表 9

参考文献 46

相关文章 13

编辑推荐

Metrics

本文评价

[1]	王琳, 卫伟. 黄土高原典型县域生态系统服务变化特征及驱动因素[J]. 生态环境学报, 2023, 32(6): 1140-1148.
[2]	李建辉, 党争, 陈琳. 黄河几字弯都市圈PM_2.5时空特征及影响因素分析[J]. 生态环境学报, 2023, 32(4): 697-705.
[3]	王成武, 罗俊杰, 唐鸿湖. 基于InVEST模型的太行山沿线地区生态系统碳储量时空分异驱动力分析[J]. 生态环境学报, 2023, 32(2): 215-225.
[4]	付蓉, 武新梅, 陈斌. 城市地表温度空间分异及驱动因子差异性分析——以合肥市为例[J]. 生态环境学报, 2023, 32(1): 110-122.
[5]	陈文裕, 夏丽华, 徐国良, 余世钦, 陈行, 陈金凤. 2000—2020年珠江流域NDVI动态变化及影响因素研究[J]. 生态环境学报, 2022, 31(7): 1306-1316.
[6]	李梦华, 韩颖娟, 赵慧, 王云霞. 基于地理探测器的宁夏植被覆盖度时空变化特征及其驱动因子分析[J]. 生态环境学报, 2022, 31(7): 1317-1325.
[7]	高思琦, 董国涛, 蒋晓辉, 聂桐, 郭欣伟, 党素珍, 李心宇, 李昊洋. 黄河源植被覆盖度变化及空间分布自然驱动力分析[J]. 生态环境学报, 2022, 31(3): 429-439.
[8]	赵锐, 詹梨苹, 周亮, 张军科. 地理探测联合地理加权岭回归的PM_2.5驱动因素分析[J]. 生态环境学报, 2022, 31(2): 307-317.
[9]	杨艳, 周德成, 宫兆宁, 刘子源, 张良侠. 基于植被生产力的黄土高原地区生态脆弱性及其控制因子分析[J]. 生态环境学报, 2022, 31(10): 1951-1958.
[10]	聂桐, 董国涛, 蒋晓辉, 郭欣伟, 党素珍, 郑嘉昊, 李立缠, 王江. 榆林地区植被时空分异特征及其影响因素研究[J]. 生态环境学报, 2022, 31(1): 26-36.
[11]	刘强, 杨众养, 陈毅青, 雷金睿, 陈宗铸, 陈小花. 基于CA-Markov多情景模拟的海南岛土地利用变化及其生态环境效应[J]. 生态环境学报, 2021, 30(7): 1522-1531.
[12]	王金杰, 赵安周, 胡小枫. 京津冀植被净初级生产力时空分布及自然驱动因子分析[J]. 生态环境学报, 2021, 30(6): 1158-1167.
[13]	张军, 高煜, 王国兰, 金梓函, 杨明航. 典型河谷城市土壤重金属含量空间分异及其影响因素[J]. 生态环境学报, 2021, 30(6): 1276-1285.

q值	X₁	X₂	X₃	X₄	X₅	X₆	X₇	X₈	X₉	X₁₀	X₁₁
X₁	0.046
X₂	0.439	0.406
X₃	0.185	0.540	0.159
X₄	0.175* ¹⁾	0.484	0.297*	0.117
X₅	0.781	0.788	0.808	0.830	0.776
X₆	0.430	0.541	0.485	0.454	0.778	0.409
X₇	0.143	0.463	0.230	0.181	0.777	0.415	0.108
X₈	0.111	0.411	0.224	0.170	0.776	0.421	0.153	0.066
X₉	0.130	0.436	0.237	0.200	0.808	0.424	0.173	0.128	0.085
X₁₀	0.114	0.424	0.224	0.177	0.782	0.425	0.152	0.112	0.139	0.071
X₁₁	0.112*	0.450	0.219	0.178*	0.780	0.440	0.154	0.125	0.142	0.165*	0.060

q值	X₁	X₂	X₃	X₄	X₅	X₆	X₇	X₈	X₉	X₁₀	X₁₁
X₁	0.046
X₂	0.439	0.406
X₃	0.185	0.540	0.159
X₄	0.175* ¹⁾	0.484	0.297*	0.117
X₅	0.781	0.788	0.808	0.830	0.776
X₆	0.430	0.541	0.485	0.454	0.778	0.409
X₇	0.143	0.463	0.230	0.181	0.777	0.415	0.108
X₈	0.111	0.411	0.224	0.170	0.776	0.421	0.153	0.066
X₉	0.130	0.436	0.237	0.200	0.808	0.424	0.173	0.128	0.085
X₁₀	0.114	0.424	0.224	0.177	0.782	0.425	0.152	0.112	0.139	0.071
X₁₁	0.112*	0.450	0.219	0.178*	0.780	0.440	0.154	0.125	0.142	0.165*	0.060