黄河流域城市化与生态系统服务价值协调性及障碍因素研究

doi:10.12118/j.issn.1000-6060.2021.436

Abstract

Abstract:

Investigating the coordinated and interactive relationship between ecosystem service value (ESV) and urbanization is beneficial for the high-quality development of the Yellow River Basin, China. This study uses entropy method, coupling coordination model, spatial autocorrelation model, and obstacle degree model to analyze the coupling coordination relationship between urbanization and ESV and identify dominant obstacle factors. Results show the following: (1) From 1995 to 2018, the ESV of the Yellow River Basin greatly improved, with an overall increase of 33.05×10⁹ yuan RMB, and is dominated by regulating services. The service value of grassland, woodland, and cultivated land has a higher contribution rate to the total ESV. The ESV per unit area (PE) presents a high and low spatial pattern in the south and north, respectively; further, the spatial pattern in the midstream is high and that in the upstream and downstream is low. (2) The coupling coordination degree (CCD) of PE and urbanization gradually improves, but it still exhibits an overall low level of coupling coordination. Light coupling coordination increases by 27.12%, serious disorder significantly decreases by 45.46%, and the coupling subtype develops from urbanization lagging to ESV lagging. Furthermore, the CCD shows a spatial pattern of high in the south and low in the north, with the midstream being superior to the upstream and downstream areas. The coordination degree has a significant positive spatial correlation, and an obvious high-high and low-low agglomeration characteristics are observed. The high-high agglomeration areas are mainly distributed in the middle reaches and downstream areas with high ESV and relatively high urbanization level, and the low-low agglomeration areas are mainly distributed in the upstream areas with low ESV. (3) The dominant barrier factors did not change significantly from 1995 to 2018; the ESV is dominated by regulating services, while the urbanization system is dominated by the economic and social subsystems. On the basis of these findings, the coupled and coordinated relationship between ESV and urbanization should be clarified and the impact of the urbanization process on ecosystem services and ecological security should be focused on for ensuring the overall quality and coordinated development of the Yellow River Basin.

Key words: ecosystem service value, urbanization, coupling and coordination, obstacle degree model, Yellow River Basin

ZHANG Kaili,FENG Rongrong,LIU Tan,ZHANG Zhicheng,HAN Jianing,LIU Kang. Coordination and obstacle factors of urbanization and ecosystem service value in the Yellow River Basin[J].Arid Land Geography, 2022, 45(4): 1254-1267.

Figures/Tables 16

Fig. 1

Tab. 1

Tab. 2

Research models and indicators"

研究模型	计算公式	模型释义	意义
极值标准化	$X m j = [x m j - m i n (x m j)] / [m a x (x m j) - m i n (x m j)] 正指标 X m j = [m a x (x m j) - x m j] / [m a x (x m j) - m i n (x m j)] 负指标$	X_mj为系统m,指标j归一化后的值;x_mj为各系统的原始取值;max(x_mj)与min(x_mj)分别为各系统j个指标的最大值和最小值	消除数据间屏蔽效应和量纲差异
熵权法	$μ p j = 1 + X p j ∑ i = 1 n (1 + X p j) e j = - 1 l n (n) ∑ i = 1 n μ p j × l n (μ p j) g j = 1 - e j W j = g j ∑ j = 1 m g j$	X_pj为第p个城市j指标的归一化值;W_j为各指标权重; $μ p j$ 为第p个城市j指标的比重;e_j为指标的信息熵;g_j为信息熵冗余度;n为城市样本数量;m为系统指标数量	客观确定指标权重
综合发展指数	$φ = ∑ j = 1 m W j × X p j$	当m取E时, $φ$ 为ESV系统;当m取U时, $φ$ 为城市化系统	获得子系统的综合效益
欧式距离耦合度	$C i t = 1 - ∑ 1 2 w i t - w' i t ∑ 1 2 Q i 2 k$	C_it为两系统耦合度,以w₁_t、 $w' 1 t$ 和w₂_t、 $w' 2 t$ 分别为城市化系统和ESV系统第t年水平的实际值和理想值,取Q₁=Q₂=1为调节系数,一般取k=2^[30-31]	C_it取值在（0, 1）之间,C_it值越大,说明系统实际耦合协调状态与理想状态距离更贴合,耦合度越高
耦合协调度	$C C D i t = C i t × T i t 1 / 2 T i t = α φ E + β φ U 1 / 2$	CCD_it为协调度;T_it为耦合协调发展水平指数,取 $α$ = $β$ =0.5; $φ E$ 为ESV系统; $φ U$ 为城市化系统	具体分级见表3
Moran’I检验	$I = ∑ i = 1 n ∑ j = 1 m w i j x i - x - x j - x - S 2 ∑ i = 1 n ∑ j = 1 m w i j$	I为全局莫兰指数,取值在（-1, 1）之间,大于0代表正相关,即高值与高值临近,小于0代表负相关,即高值与低值临近;w_ij为空间权重矩阵;x_i_、x_j分别为要素i、j的属性值; $x -$ 为要素属性值的平均值;S²为样本方差;m、n分别为相邻指标空间要素数量	空间自相关检验
局部Geary指数	$C = (n - 1) ∑ i = 1 n ∑ j = 1 n w i j (x i - x j) 2 2 (∑ i = 1 n ∑ j = 1 n w i j) ∑ i = 1 n (x i - x -) 2 C * = C - 1 V a r (C)$	C为吉尔里指数（Geary）指数,取值在（0, 2）之间,大于1表示负相关,小于1表示正相关,一般认为其比莫兰指数对局部空间相关更为敏感; $C *$ 为局部Geary指数;Var(C)为Geary指数的方差	局部空间自相关检验,识别空间集聚模式
障碍度	$Q j = I j W j / ∑ j = 1 n I j W j × 100 % I j = 1 - X i j$	Q_j为障碍度;W_j为因子贡献度,一般用指标权重表示;I_j为指标偏离度,指标实际值与最优值之间差距,用1与标准化值X_ij之差表示^[32]	识别影响两系统耦合协调关系的主导障碍因素

Tab. 2

Tab. 3

Fig. 2

Tab. 4

Fig. 3

Fig. 4

Tab. 5

Fig. 5

Fig. 6

Tab. 6

Fig. 7

Tab. 7

Tab. 8

Tab. 9

References 42

[1]	Daily G C. Nature’s services: Societal dependence on natural ecosystems[M]. Washington DC: Island Press, 1997: 49-68.
[2]	Millennium Ecosystem Assessment. People and ecosystems: A framework for assessment[M]. Washington DC: Island Press, 2003: 26-48.
[3]	Millennium Ecosystem Assessment. Ecosystems and human well-being: Synthesis[M]. Washington DC: Island Press, 2005: 1-9.
[4]	Costanza R, D’arge R, Groot R D, et al. The value of the world’s ecosystem services and natural capital[J]. Nature, 1997, 25(1): 3-15. doi: 10.1038/025003a0
[5]	蒋明卓, 李殿生, 苏欢. 快速城市化地区生态系统服务价值演化及空间自相关特征分析--以河南省洛阳市为例[J]. 林业经济, 2020, 42(7): 51-61.
	[ Jiang Mingzhuo, Li Diansheng, Su Huan. Analysis on the evolution of ecosystem service value and its spatial autocorrelation pattern in rapid urbanization area: Taking Luoyang City in Henan Province as an example[J]. Forestry Economics, 2020, 42(7): 51-61. ]
[6]	Zhou D Y, Tian Y Y, Jiang G H. Spatio-temporal investigation of the interactive relationship between urbanization and ecosystem services: Case study of the Jingjinji urban agglomeration, China[J]. Ecological Indicators, 2018, 95: 152-164. doi: 10.1016/j.ecolind.2018.07.007
[7]	Grimm N B, Faeth S H, Golubiewski N E, et al. Global change and the ecology of cities[J]. Science, 2008, 319(5864): 756-760. doi: 10.1126/science.1150195
[8]	赵建吉, 刘岩, 朱亚坤, 等. 黄河流域新型城镇化与生态环境耦合的时空格局及影响因素[J]. 资源科学, 2020, 42(1): 159-171. doi: 10.18402/resci.2020.01.16
	[ Zhao Jianji, Liu Yan, Zhu Yakun, et al. Spatiotemporal differentiation and influencing factors of the coupling and coordinated development of new urbanization and ecological environment in the Yellow River Basin[J]. Resources Science, 2020, 42(1): 159-171. ] doi: 10.18402/resci.2020.01.16
[9]	Tian Y Y, Zhou D Y, Jiang G U. Conflict or coordination? Multiscale assessment of the spatio-temporal coupling relationship between urbanization and ecosystem services: The case of the Jingjinji Region, China[J]. Ecological Indicators, 2020, 117: 106543, doi: 10.1016/j.ecolind.2020.106543. doi: 10.1016/j.ecolind.2020.106543
[10]	Zhang Y S, Lu X, Liu B Y, et al. Spatial relationships between ecosystem services and socioecological drivers across a large-scale region: A case study in the Yellow River Basin[J]. Science of the Total Environment, 2021, 766: 142480, doi: 10.1016/j.scitotenv.2020.142480. doi: 10.1016/j.scitotenv.2020.142480
[11]	Breuste J, Qureshi S, Li J X. Applied urban ecology for sustainable urban environment[J]. Urban Ecosystems, 2013, 16(4): 675-680. doi: 10.1007/s11252-013-0337-9
[12]	Li B, Chen D, Wu S, et al. Spatio-temporal assessment of urbanization impacts on ecosystem services: Case study of Nanjing City, China[J]. Ecological Indicators, 2016, 71: 416-427. doi: 10.1016/j.ecolind.2016.07.017
[13]	Alam M, Dupras J, Messier C. A framework towards a composite indicator for urban ecosystem services[J]. Ecological Indicators, 2016, 60: 38-44. doi: 10.1016/j.ecolind.2015.05.035
[14]	Peng J, Liu Y, Wu J, et al. Linking ecosystem services and landscape patterns to assess urban ecosystem health: A case study in Shenzhen City, China[J]. Landscape Urban Plan, 2015, 143: 56-68. doi: 10.1016/j.landurbplan.2015.06.007
[15]	Yuan Y J, Chen D X, Wu S H, et al. Urban sprawl decreases the value of ecosystem services and intensifies the supply scarcity of ecosystem services in China[J]. Science of the Total Environment, 2019, 697: 134170, doi: 10.1016/j.scitotenv.2019.134170. doi: 10.1016/j.scitotenv.2019.134170
[16]	Liu W, Zhan J Y, Zhao F. Impacts of urbanization-induced land-use changes on ecosystem services: A case study of the Pearl River Delta Metropolitan Region, China[J]. Ecological Indicators, 2019, 98: 228-238. doi: 10.1016/j.ecolind.2018.10.054
[17]	赵育恒, 曾晨. 武汉城市圈生态服务价值时空演变分析及影响因素[J]. 生态学报, 2019, 39(4): 1426-1440.
	[ Zhao Yuheng, Zeng Chen. Analysis of spatial-temporal evolution and factors that influences ecological service values in Wuhan urban agglomeration, China[J]. Acta Ecologica Sinica, 2019, 39(4): 1426-1440. ]
[18]	徐煖银, 郭泺, 薛达元, 等. 赣南地区土地利用格局及生态系统服务价值的时空演变[J]. 生态学报, 2019, 39(6): 1969-1978.
	[ Xu Xuanyin, Guo Luo, Xue Dayuan, et al. Land use structure and the dynamic evolution of ecosystem service value in Gannan Region, China[J]. Acta Ecologica Sinica, 2019, 39(6): 1969-1978. ]
[19]	Peng J, Tian L, Liu Y, et al. Ecosystem services response to urbanization in metropolitan areas: Thresholds identification[J]. Science of the Total Environment. 2017, 607: 706-714.
[20]	刘耕源, 杨青, 黄俊勇. 黄河流域近十五年生态系统服务价值变化特征及影响因素研究[J]. 中国环境管理, 2020, 12(3): 90-97.
	[ Liu Gengyuan, Yang Qing, Huang Junyong. The change characteristics and influence factors of ecosystem services valuation of the Yellow River Basin from 2000 to 2015[J]. Chinese Journal of Environmental Management, 2020, 12(3): 90-97. ]
[21]	谷佳贺, 薛华柱, 董国涛, 等. 黄河流域NDVI/土地利用对蒸散发时空变化的影响[J]. 干旱区地理, 2021, 44(1): 158-167.
	[ Gu Jiahe, Xue Huazhu, Dong Guotao, et al. Effects of NDVI/land-use on spatiotemporal changes of evapotranspiration in the Yellow River Basin[J]. Arid Land Geography, 2021, 44(1): 158-167. ]
[22]	谢高地, 肖玉, 甄霖, 等. 我国粮食生产的生态服务价值研究[J]. 中国生态农业学报, 2005, 13(3): 10-13.
	[ Xie Gaodi, Xiao Yu, Zhen Lin, et al. Study on ecosystem services value of food production in China[J]. Chinese Journal of Eco-Agriculture, 2005, 13(3): 10-13. ]
[23]	谢高地, 甄霖, 鲁春霞, 等. 一个基于专家知识的生态系统服务价值化方法[J]. 自然资源学报, 2008, 23(5): 911-919.
	[ Xie Gaodi, Zhen Lin, Lu Chunxia, et al. Expert knowledge based valuation method of ecosystem services in China[J]. Journal of Natural Resources, 2008, 23(5): 911-919. ]
[24]	谢高地, 张彩霞, 张雷明, 等. 基于单位面积价值当量因子的生态系统服务价值化方法改进[J]. 自然资源学报, 2015, 30(8): 1243-1254.
	[ Xie Gaodi, Zhang Caixia, Zhang Leiming, et al. Improvement of the evaluation method for ecosystem service value based on per unit area[J]. Journal of Natural Resources, 2015, 30(8): 1243-1254. ]
[25]	Sun Y X, Liu S L, Dong Y H, et al. Spatio-temporal evolution scenarios and the coupling analysis of ecosystem services with land use change in China[J]. Science of the Total Environment, 2019, 681: 211-225. doi: 10.1016/j.scitotenv.2019.05.136
[26]	Xu Z H, Wei H J, Fan W G, et al. Energy modeling simulation of changes in ecosystem services before and after the implementation of a Grain-for-Green Program on the Loess Plateau: A case study of the Zhifanggou Valley in Ansai County, Shaanxi Province, China[J]. Ecosystem Services, 2018, 31: 32-43. doi: 10.1016/j.ecoser.2018.03.013
[27]	南箔, 杨子寒, 毕旭, 等. 生态系统服务价值与人类活动的时空关联分析--以长江中游华阳河湖群地区为例[J]. 中国环境科学, 2018, 38(9): 3531-3541.
	[ Nan Bo, Yang Zihan, Bi Xu, et al. Spatial-temporal correlation analysis of ecosystem services value and human activities: A case study of Huayang Lakes area in the middle reaches of Yangtze River[J]. China Environmental Science, 2018, 38(9): 3531-3541. ]
[28]	谢高地, 张彩霞, 张昌顺, 等. 中国生态系统服务的价值[J]. 资源科学, 2015, 37(9): 1740-1746.
	[ Xie Gaodi, Zhang Caixia, Zhang Changshun, et al. The value of ecosystem services in China[J]. Resources Science, 2015, 37(9): 1740-1746. ]
[29]	周雷雷, 郑诗军, 尹捷, 等. 以“胡焕庸线”为界的中国东西部净初级生产力变化分析[J]. 遥感技术与应用, 2021, 36(4): 916-925.
	[ Zhou Leilei, Zheng Shijun, Yin Jie, et al. Analysis on the change of net primary productivity in the east and west of China bounded by “The Hu Huanyong Line”[J]. Remote Sensing Technology and Application, 2021, 36(4): 916-925. ]
[30]	汤铃, 李建平, 余乐安, 等. 基于距离协调度模型的系统协调发展定量评价方法[J]. 系统工程理论与实践, 2010, 30(4): 594-602. doi: 10.12011/1000-6788(2010)4-594
	[ Tang Ling, Li Jianping, Yu Le’an, et al. Quantitative evaluation methodology for system coordination development based on distance coordnation degree model[J]. Systems Engineering-Theory & Practice, 2010, 30(4): 594-602. ] doi: 10.12011/1000-6788(2010)4-594
[31]	方创琳, 崔学刚, 梁龙武. 城镇化与生态环境耦合圈理论及耦合器调控[J]. 地理学报, 2019, 74(12): 2529-2546. doi: 10.11821/dlxb201912008
	[ Fang Chuanglin, Cui Xuegang, Liang Longwu. Theoretical analysis of urbanization and eco-environment coupling coil and coupler control[J]. Acta Geographica Sinica, 2019, 74(12): 2529-2546. ] doi: 10.11821/dlxb201912008
[32]	赵书虹, 白梦, 阮梦枝, 等. 云南省旅游资源与生态安全协调发展的时空演化特征及障碍因子分析[J]. 地理科学, 2021, 41(3): 493-503. doi: 10.13249/j.cnki.sgs.2021.03.014
	[ Zhao Shuhong, Bai Meng, Ruan Mengzhi, et al. Spatio-temporal evolution characteristics and obstacle factors of coordinated development of tourism resources and ecological security in Yunnan Province[J]. Scientia Geographica Sinica, 2021, 41(3): 493-503. ] doi: 10.13249/j.cnki.sgs.2021.03.014
[33]	Tammi I, Mustajärvi K, Rasinmäki J. Integrating spatial valuation of ecosystem services into regional planning and development[J]. Ecosystem Services, 2016, 26: 329-344. doi: 10.1016/j.ecoser.2016.11.008
[34]	Ouyang Z Y, Zheng H, Xiao Y, et al. Improvements in ecosystem services from investments in natural capital[J]. Science, 2016, 352(6292): 1455-1459. doi: 10.1126/science.aaf2295
[35]	Zhou D, Xu J C, Lin Z L. Conflict or coordination? Assessing land use multi-functionalization using production-living-ecology analysis[J]. Science of the Total Environment, 2017, 577: 136-147. doi: 10.1016/j.scitotenv.2016.10.143
[36]	Chen W X, Zeng J, Zhong M X, et al. Coupling analysis of ecosystem services value and economic development in the Yangtze River Economic Belt: A case study in Hunan Province, China[J]. Remote Sensing, 2021, 13: 1552, doi: 10.3390/rs13081552. doi: 10.3390/rs13081552
[37]	Xing L, Zhu Y M, Wang J P. Spatial spillover effects of urbanization on ecosystem services value in Chinese cities[J]. Ecological Indicators, 2021, 121: 107028, doi: 10.1016/j.ecolind.2020.107028. doi: 10.1016/j.ecolind.2020.107028
[38]	谷昊鑫, 秦伟山, 赵明明, 等. 黄河流域旅游经济与生态环境协调发展时空演变及影响因素探究[J]. 干旱区地理, 2022, 45(2): 628-638.
	[ Gu Haoxin, Qin Weishan, Zhao Mingming, et al. Spatial and temporal evolution and influencing factors of coordinated development of tourism economy and ecological environment in the Yellow River Basin[J]. Arid Land Geography, 2022, 45(2): 628-638. ]
[39]	宋永永, 薛东前, 夏四友, 等. 近40a黄河流域国土空间格局变化特征与形成机理[J]. 地理研究, 2021, 40(5): 1445-1463. doi: 10.11821/dlyj020191065
	[ Song Yongyong, Xue Dongqian, Xia Siyou, et al. Change characteristics and formation mechanism of the territorial spatial pattern in the Yellow River Basin from 1980 to 2018, China[J]. Geographical Research, 2021, 40(5): 1445-1463. ] doi: 10.11821/dlyj020191065
[40]	杨锐, 曹越. “再野化”: 山水林田湖草生态保护修复的新思路[J]. 生态学报, 2019, 39(23): 8763-8770.
	[ Yang Rui, Cao Yue. Rewilding: New ideas for ecological protection and restoration projects of mountains-rivers-forests-farmlands-lakes-grasslands[J]. Acta Ecologica Sinica, 2019, 39(23): 8763-8770. ]
[41]	Grossi G, Trunova O. Are UN SDGs useful for capturing multiple values of smart city?[J]. Cities, 2021, 114: 103193, doi: 10.1016/J.CITIES.2021.103193. doi: 10.1016/J.CITIES.2021.103193
[42]	李龙, 吴大放, 王芳, 等. 中国快速城市化区域生态系统服务价值预测及权衡研究--以佛山市为例[J]. 生态学报, 2020, 40(24): 9023-9036.
	[ Li Long, Wu Dafang, Wang Fang, et al. Prediction and trade off analysis of ecosystem service value in the rapidly urbanizing Foshan City of China: A case study[J]. Acta Ecologica Sinica, 2020, 40(24): 9023-9036. ]

准则层	指标层	单位	权重
人口城市化	人口密度	人∙km^-2	0.041
	城镇人口密度	人∙km^-2	0.054
	非农人口比重	%	0.022
空间城市化	建成区占土地总面积百分比	%	0.063
	每万人的市区面积	km²	0.070
	人均铺装道路面积	m²	0.039
	人均绿地面积	人∙m^-2	0.051
	建成区绿化覆盖率	%	0.013
经济城市化	人均国内生产总值	元	0.063
	二、三产业占GDP比重	%	0.005
	限额以上工业总产值	10⁴元	0.103
	固定资产投资总额	10⁴元	0.088
	人均财政收入	元	0.080
	职工平均工资	元	0.059
社会城市化	人均消费品零售总额	元	0.075
	中小学生在校人数	10⁴人	0.035
	人均公共图书馆藏书	册	0.045
	万人拥有医疗床位	张	0.016
	万人互联网用户	10⁴人	0.076

协调大类	耦合协调度	对比关系	亚类型
严重失调型	0.0≤CCD≤0.2	U-E>0.1	严重失调ESV滞后型
		\|E-U\|≤0.1	严重失调同步型
		E-U>0.1	严重失调城市化滞后型
轻度失调型	0.2<CCD≤0.4	U-E>0.1	轻度失调ESV滞后型
		\|E-U\|≤0.1	轻度失调同步型
		E-U>0.1	轻度失调城市化滞后型
轻度耦合协调	0.4<CCD≤0.6	U-E>0.1	轻度耦合协调ESV滞后型
		\|E-U\|≤0.1	轻度耦合协调同步型
		E-U>0.1	轻度耦合协调城市化滞后型
良好耦合协调	0.6<CCD≤0.8	U-E>0.1	良好耦合协调ESV滞后型
		\|E-U\|≤0.1	良好耦合协调同步型
		E-U>0.1	良好耦合协调城市化滞后型
优质耦合协调	CCD>0.8	U-E>0.1	优质耦合协调ESV滞后型
		\|E-U\|≤0.1	优质耦合协调同步型
		E-U>0.1	优质耦合协调城市化滞后型

土地利用面积变化	年份	耕地	林地	草地	水体	湿地	建筑用地	未利用地
土地利用面积/10⁵hm²	1995	348.65	121.75	369.54	3.75	11.59	36.39	77.50
	2005	348.25	129.00	353.46	4.00	13.00	41.31	80.16
	2015	341.95	129.15	348.40	4.65	12.35	54.34	78.31
	2018	337.29	129.34	348.32	4.99	14.04	58.47	76.62
变化量/10⁵hm²	1995—2005	-0.40	7.25	-16.08	0.25	1.41	4.92	2.66
	2005—2015	-6.30	0.15	-5.06	0.65	-0.65	13.03	-1.85
	2015—2018	-4.66	0.19	-0.08	0.34	1.69	4.13	-1.69
	1995—2018	-11.36	7.59	-21.22	1.24	2.45	22.08	-0.88
变化率/%	1995—2005	-0.11	5.95	-4.35	6.67	12.17	13.52	3.43
	2005—2015	-1.81	0.12	-1.43	16.25	-5.00	31.54	-2.31
	2015—2018	-1.36	0.15	-0.02	7.31	13.68	7.60	-2.16
	1995—2018	-3.26	6.23	-5.74	33.07	21.14	60.68	-1.14

ESV	年份	耕地	林地	草地	水体	湿地	未利用地	汇总
ESV/10⁹元	1995	156.76	183.79	293.68	9.91	82.92	1.09	728.15
	2000	158.98	195.16	283.86	9.56	84.40	1.08	733.04
	2005	157.27	193.59	282.20	10.04	88.34	1.08	732.52
	2010	156.33	201.44	293.60	12.90	78.60	1.04	743.91
	2015	154.76	198.64	288.63	12.67	80.46	0.99	736.15
	2018	152.32	198.99	304.99	13.23	90.58	1.09	761.20
变化量/10⁹元	1995—2000	2.22	11.37	-9.82	-0.35	1.48	-0.01	4.89
	2000—2005	-1.71	-1.57	-1.66	0.48	3.94	0.00	-0.52
	2005—2010	-0.94	7.85	11.40	2.86	-9.74	-0.04	11.39
	2010—2015	-1.57	-2.80	-4.97	-0.23	1.86	-0.05	-7.76
	2015—2018	-2.44	0.35	16.36	0.56	10.12	0.10	25.05
	1995—2018	-4.44	15.20	11.31	3.32	7.66	0.00	33.05
变化率/%	1995—2000	1.42	6.19	-3.34	-3.53	1.78	-0.92	0.67
	2000—2005	-1.08	-0.80	-0.58	5.02	4.67	0.00	-0.07
	2005—2010	-0.60	4.05	4.04	28.49	-11.03	-3.70	1.55
	2010—2015	-1.00	-1.39	-1.69	-1.78	2.37	-4.81	-1.04
	2015—2018	-1.58	0.18	5.67	4.42	12.58	10.10	3.40
	1995—2018	-2.83	8.27	3.85	33.50	9.24	0.00	4.54

全局莫兰检验	1995年	2000年	2005年	2010年	2015年	2018年
Moran’I	0.562	0.570	0.621	0.636	0.651	0.638
Z	5.893	6.086	6.824	7.001	7.267	7.042
P	0.001	0.001	0.001	0.001	0..001	0.001

Coordination and obstacle factors of urbanization and ecosystem service value in the Yellow River Basin

RichHTML

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 16

References 42

Related Articles 15

Metrics

Comments

Recommended 0

全局莫兰检验	1995年	2000年	2005年	2010年	2015年	2018年
Moran’I	0.418	0.425	0.386	0.281	0.355	0.324
Z	5.034	5.171	4.644	3.503	4.338	3.945
P	0.001	0.001	0.001	0.001	0..001	0.001

年份	ESV系统/%
年份	原料生产	气候调节	净化环境	水文调节	美学景观
1995	18.46	19.89	15.87	13.89	16.43
2000	18.60	20.02	16.03	13.19	16.58
2005	18.68	20.12	16.05	12.89	16.61
2010	18.60	20.01	16.01	13.03	16.50
2015	18.62	20.04	16.02	12.98	16.51
2018	18.64	20.05	15.97	12.68	16.49
年份	城市化系统/%
年份	限额以上工业总产值	固定资产投资总额	人均财政收入	人均消费品零售总额	万人互联网用户
1995	11.06	9.44	8.59	7.97	8.17
2000	11.11	9.52	8.67	7.98	8.07
2005	11.11	9.55	8.77	7.88	8.15
2010	10.90	9.59	9.02	7.64	8.27
2015	10.59	9.36	9.34	6.88	8.19
2018	10.58	9.03	9.90	6.70	7.24

[1]	REN Guixiu, LIU Kai. Spatiotemporal evolution characteristics and influencing factors of green innovation in the Yellow River Basin [J]. Arid Land Geography, 2024, 47(1): 158-169.
[2]	PENG Ya, WANG Juanjuan, WANG Shanshan, TIAN Liulan, LIU Jie, WU Zhaopeng. Spatiotemporal pattern evolution of land use conflict in Urumqi City from the perspective of ecological security [J]. Arid Land Geography, 2024, 47(1): 81-92.
[3]	WANG Songmao, NING Wenping, NIU Jinlan, AN Kang. Spatiotemporal differentiation and convergence of urban ecological resilience in the Yellow River Basin: An empirical analysis based on 61 cities in seven major urban agglomerations [J]. Arid Land Geography, 2024, 47(1): 93-103.
[4]	ZHOU Cheng, ZHAO Yaling, ZHANG Xuhong, ZHOU Lin, REN Minmin. Spatiotemporal evolutionary characteristics and coordinated development of urban ecological resilience and efficiency in the Yellow River Basin [J]. Arid Land Geography, 2023, 46(9): 1514-1523.
[5]	LI Jianhui, CHEN Lin, DANG Zheng. Spatial pattern and influencing factors of patriotic education bases in the Yellow River Basin [J]. Arid Land Geography, 2023, 46(9): 1536-1544.
[6]	ZHANG Hao, HAN Zenglin, QIAO Guorong, WANG Hui, WANG Hongye, DUAN Ye. Patterns and influencing factors of tourism economic linkages between cities in the Yellow River Basin [J]. Arid Land Geography, 2023, 46(8): 1344-1354.
[7]	BAI He, MING Yisen, LIU Qihang, HUANG Chang. Downscaling of GPM satellite precipitation data in the Yellow River Basin based on MGWR model [J]. Arid Land Geography, 2023, 46(7): 1052-1062.
[8]	GU Chaolin, SU Hefang, GU Jiang, GAO Zhe, CHEN Lelin, GUO Li. On the new era of earth science [J]. Arid Land Geography, 2023, 46(7): 1176-1195.
[9]	SU Hang, GU Jiao, ZHAO Jinli. Spatial structure evolution of urban information network in the Yellow River Basin from multi-scale perspective [J]. Arid Land Geography, 2023, 46(7): 1206-1216.
[10]	CHEN Shujun,XU Guochang,LYU Zhiping,MA Mingyue,LI Hanyu,ZHU Yuyan. Spatiotemporal variations of fractional vegetation cover and its response to climate change and urbanization in China [J]. Arid Land Geography, 2023, 46(5): 742-752.
[11]	DONG Jiefang, ZHANG Kaili, QU Xueshu, RUAN Zheng. Measurement and influencing factors of ecological well-being performance of cities in Yellow River Basin [J]. Arid Land Geography, 2023, 46(5): 834-845.
[12]	MENG Wangsheng,LIU Huazhen,ZHANG Yang. Measurement and characterization of green development efficiency in seven urban agglomerations in the Yellow River Basin [J]. Arid Land Geography, 2023, 46(5): 846-856.
[13]	ZOU Yafeng, ZHANG Qian, RAO Yufei, DEND Min, WANG Qi. Evolution of new urbanization of provincial capitals in western China [J]. Arid Land Geography, 2023, 46(4): 636-648.
[14]	XU Xintong,ZHU Li,LYU Xiaoyu,GUO Hao. Applicability evaluation of MSWEP product for meteorological drought monitoring in the Yellow River Basin [J]. Arid Land Geography, 2023, 46(3): 371-384.
[15]	TIAN Xiaobo,HU Jing,JIA Yaoyan,ZHU Lei. Exploring the causes of spatial differentiation of tourism development level in the high-quality development stage: Empirical evidence of Yellow River Basin based on factor decomposition [J]. Arid Land Geography, 2023, 46(3): 460-470.

年份	城市化系统/%				ESV系统/%
年份	人口城市化	空间城市化	经济城市化	社会城市化	供给服务	调节服务	文化服务
1995	10.25	22.82	42.23	24.70	23.82	59.75	16.43
2000	10.47	22.76	42.30	24.47	24.00	59.42	16.58
2005	10.53	22.95	41.93	24.58	24.10	59.29	16.61
2010	10.59	23.83	40.78	24.80	24.20	59.29	16.50
2015	10.93	25.44	39.17	24.47	24.21	59.28	16.51
2018	11.13	27.24	38.04	23.59	24.49	59.03	16.49