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1.
The calculation of ecological compensation and boundary identification of stakeholders represent the key challenges for Beijing-Tianjin-Hebei Region in its implementation of the trans-regional ecological compensation mechanism. Breaking administrative boundaries and spatially coordinating ecological resources helps to restructure an ecological compensation mechanism of the region based on the coordinated development of Beijing, Tianjin and Hebei. According to the estimated ecological assets in the counties of the region in 2000, 2005, 2010 and 2015, a quantitative model for total ecological compensation was built based on ecological assets and county-level economic development. Then, the spatiotemporal distribution characteristics of the total ecological compensation in the region were defined, and the boundaries of ecological surplus and deficit areas were identified. Results indicate:(1) The region's annual average ecological assets amounted to $1379.47 billion; in terms of annual total ecological assets, Hebei ranked first($1123.80 billion), followed by Beijing($157.46 billion) and Tianjin($98.21 billion); and in terms of ecological assets per unit area, Beijing ranked first, Tianjin second and Hebei last.(2) Among ecosystem services, hydrological regulation and climate regulation had the highest annual average value and contributed most to the increase in ecological assets. In 2015, the contribution of water and soil conservation to the total ecological assets decreased to –15.66%, showing the degradation of the function played by different ecosystems.(3) The ecological surplus of the region in four periods of 2000, 2005, 2010 and 2015 were $398.98 billion, $870.37 billion, $1254.93 billion and $2693.94 billion respectively, basically offsetting the ecological deficit of each corresponding period, but the urgency for ecological compensation was increased.(4) The ecological surplus and deficit areas showed a great fluctuation in different time periods. Larger time span means more noticeable convergence of deficit areas towards central and eastern areas. Public resources such as education, transportation and medical care in central urban areas should be decentralized to encourage population dispersal, weaken the agglomeration effect of deficit areas and finally achieve the ecological synergy of the region. 相似文献
2.
According to the highway data and some socioeconomic data of 1990, 1994, 2000, 2005 and 2009 of county units in the Pearl River Delta, this paper measured urban integrated power of different counties in different years by factor analysis, and estimated each county’s potential in each year by means of expanded potential model. Based on that, the spatio-temporal association patterns and evolution of county potential were analyzed using spatio-temporal autocorrelation methods, and the validity of spatio-temporal association patterns was verified by comparing with spatial association patterns and cross-correlation function. The main results are shown as follows:(1) The global spatio-temporal association of county potential showed a positive effect during the study period. But this positive effect was not strong, and it had been slowly strengthened during 1994–2005 and decayed during 2005–2009. The local spatio-temporal association characteristics of most counties’ potential kept relatively stable and focused on a positive autocorrelation, however, there were obvious transformations in some counties among four types of local spatio-temporal association(i.e., HH, LL, HL and LH).(2) The distribution difference and its change of local spatio-temporal association types of county potential were obvious. Spatio-temporal HH type units were located in the central zone and Shenzhen-Dongguan region of the eastern zone, but the central spatio-temporal HH area shrunk to the Guangzhou-Foshan core metropolitan region only after 2000; the spatio-temporal LL area in the western zone kept relatively stable with a surface-shaped continuous distribution pattern, new LL type units emerged in the south-central zone since 2005, the eastern LL area expanded during 1994–2000, but then gradually shrunk and scattered at the eastern edge in 2009; the spatio-temporal HL and LH areas varied significantly.(3) The local spatio-temporal association patterns of county potential among the three zones presented significant disparity, and obvious difference between the eastern and central zones tended to decrease, whereas that between the western zone and the central and eastern zones further expanded.(4) Spatio-temporal autocorrelation methods can efficiently mine the spatio-temporal association patterns of county potential, and can better reveal the complicated spatio-temporal interaction between counties than ESDA methods. 相似文献
3.
Using counties as the basic analysis unit,this study established an evaluation index system for farmland function(FF) from economic,social,and ecological perspectives.The method combining entropy weighting and multiple correlation coefficient weighting was adopted to determine the weights,and the FF indices were calculated for each county.Subsequently,the spatio-temporal characteristics of farmland function evolution(FFE) were analyzed and the coupled relationships between the sub-functions were explored based on a coupling coordination model.At the same time,the dynamic mechanism of FFE was quantitatively analyzed using a spatial econometric regression analysis method.The following major conclusions were drawn:(1) The farmland economic function generally exhibited a declining trend during 1990–2010,and it is essential to point out that it was stronger in underdeveloped and agriculture-dominated counties,while it continuously weakened in developed areas.Farmland social function decreased in 60.29% of the counties,whereas some counties,which were mostly located in north of Zhengzhou and west of Dezhou and Cangzhou,Yantai,and Weihai,clearly increased.A dramatic decline in farmland ecological function occurred around Beijing,Tianjin,and Jinan.Areas located in the northern part of Henan Province and the central part of Shandong Province saw an increase in ecological function.(2) There was a significant spatial difference in the coupling degree and coordination degree of the sub-functions,and the decoupling phenomenon highlighted this.The changes in social function and ecological function lagged behind economic function in developed areas,but these were highly coupled in some underdeveloped areas.(3) FFE in the Huang-Huai-Hai Plain(HHHP) is resulted from the comprehensive effects of regional basic conditions and external driving factors.Furthermore,the transitions of population and industry under urbanization and industrialization played a decisive role in the evolution intensity and direction of farmland sub-systems,including the economy,society,and the ecology.According to the results mentioned above,promoting the transformation from traditional agriculture to modern agricultureshould be regarded as an important engine driving sustainable development in the HHHP.Taking different regional characteristics of FFE into account,differentiated and diversified farmland use and management plans should be implemented from more developed urban areas to underdeveloped traditional agricultural areas. 相似文献
4.
Uneven urban and rural development is one of the main reasons for the decline of the countryside. This imbalance could be measured by the urban-rural difference index(URDI). Existing studies on urban-rural differences have focused on single dimension between urban and rural areas, and lack a systematic multi-dimensional measurement. Based on the construction of an index system and model for measuring urban-rural differences, this study took the Huang-Huai-Hai Plain(HHHP) as the study area, explores the spatial pattern of urban-rural differences in the area, and used geographical weighted regression models to identify the factors affecting urban-rural development differences. Results show that the mean value of URDI in the HHHP was 0.295, and the URDI in its western region was higher than that in the east. The average URDI was relatively high in the western counties along the Beijing–Guangzhou Railway. The low level of urban-rural "population-land-industry" development in the HHHP is an important reason for the small differences between urban and rural areas. Improvements in road transportation infrastructure have led to an increase in the urban-rural development gap. However, the driving force of the road network on urban development is greater than that on rural areas. The role of county economic agglomeration is gaining strength. In the process of rapid economic development, more attention should be paid to the development of the rural economy and the overall revitalization of the countryside. The equivalent allocation of social service facilities is an effective way to solve the problem of urban-rural imbalance. Further analysis demonstrated that terrain factors have relatively little influence on the URDI. This study provides a new perspective and measurement method for understanding the integration of urban and rural development, and provides a useful reference for guiding the urban-rural integration development and the rural revitalization. 相似文献
5.
《地理学报(英文版)》2019,(12)
Whether economic agglomeration can promote improvement in environmental quality is of great importance not only to China's pollution prevention and control plans but also to its future sustainable development. Based on the COD(Chemical Oxygen Demand) and NH3-N(Ammonia Nitrogen) emissions Database of 339 Cities at the city level in China, this study explores the impact of economic agglomeration on water pollutant emissions, including the differences in magnitude of the impact in relation to city size using an econometric model. The study also examines the spillover effect of economic agglomeration, by conducting univariate and bivariate spatial autocorrelation analysis. The results show that economic agglomeration can effectively reduce water pollutant emissions, and a 1% increase in economic agglomeration could lead to a decrease in COD emissions by 0.117% and NH_3-N emissions by 0.102%. Compared with large and megacities, economic agglomeration has a more prominent effect on the emission reduction of water pollution in small-and medium-sized cities. From the perspective of spatial spillover, the interaction between economic agglomeration and water pollutant emissions shows four basic patterns: high agglomeration–high emissions, high agglomeration–low emissions, low agglomeration–high emissions, and low agglomeration–low emissions. The results suggest that the high agglomeration–high emissions regions are mainly distributed in the Beijing–Tianjin–Hebei region, Shandong Peninsula, and the Harbin-Changchun urban agglomeration; thus, local governments should consider the spatial spillover effect of economic agglomeration in formulating appropriate water pollutant mitigation policies. 相似文献
6.
Urban-rural integration (URI) is a new idea to guide the urban-rural transformation in China, and exploring the spatio-temporal characteristics and driving mechanism of URI in China is an urgent need to overcome the dilemmas of insufficient rural development and unbalanced urban and rural development. Based on the process framework of "foundation-motivation-result" of URI, an evaluation indicator system was constructed. The improved entropy evaluation model and the kernel density estimation method were used to quantitatively measure the spatiotemporal evolution characteristics of URI level of 31 provinces, autonomous regions, and municipalities in China's mainland from 2000 to 2020. This study further used the Geodetector to explore the heterogeneous evolution of driving factors for URI level in different regions of China. The main conclusions are as follows: 1) From 2000 to 2020, the URI level in China decreased first and then increased, showing a √-shaped trend, and its spatial differences narrowed. 2) The URI level in China presented a spatial pattern of high in the east and low in the west, divided by the Hu Huanyong Line. The high-value centers showed prominent polarization characteristics and presented a zonal aggregation trend. The medium-value areas were clustered but weakened,and showed a spreading trend from the eastern to the central and western parts. 3) At the national scale, the core influencing factors of URI level were population mobility, economic development level, urban-rural income gap, and educational supports, potential factors were the optimization of industrial structure and the opening-up level, and threshold effect existed in investment benefit and government intervention. At the regional scale, the core driving forces of URI level in China showed obvious spatial heterogeneity, and in 2020 they were economic development level, investment benefit, and government intervention in the eastern region, investment benefit, opening-up level, and urban-rural income gap in the central region, are educational supports, government intervention, and the optimization of industrial structure in the western region. The interaction of driving factors had far more influence on URI level in China than individual factors, and the interaction between traffic accessibility and other socioeconomic factors had been significantly enhanced. Research on the spatio-temporal evolution and mechanism of URI in China can provide theoretical basis for rural revitalization and high-quality urban and rural development. © 2023, Editorial office of PROGRESS IN GEOGRAPHY. All rights reserved. 相似文献
7.
《地理学报(英文版)》2016,(9)
Energy eco-efficiency is a concept integrating ecological and economic benefits arising from energy utilization and serves as a measure of efficiency in the energy–environment–economy system. Using the slacks-based measure(SBM) model considering undesirable output, this study first measures the energy eco-efficiency of provinces in China from 1997 to 2012. It then analyzes the spatial distribution and evolution of energy eco-efficiency from three aspects: scale, intensity, and grain of spatial patterns. Finally, it examines the spatial spillover effects and influencing factors of energy eco-efficiency in different provinces by means of a spatial econometric model. The following conclusions are drawn:(1) The overall energy eco-efficiency is relatively low in China, with energy-inefficient regions accounting for about 40%. Guangdong, Hainan and Fujian provinces enjoy the highest energy eco-efficiency, while Ningxia, Gansu, Qinghai, and Xinjiang are representative regions with low efficiency. Thus, the pattern of evolution of China's overall energy eco-efficiency is U-shaped. Among local regions, four main patterns of evolution are found: increasing, fluctuating, mutating, and leveling.(2) At the provincial level, China's energy eco-efficiency features significant spatial agglomeration both globally and locally. High–high agglomeration occurs mainly in the eastern and southern coastal regions and low–low agglomeration in the northwestern region and the middle reaches of the Yellow River. Changes in spatial patterns have occurred mainly in areas with high–low and low–high agglomeration, with the most remarkable change taking place in the Beijing–Tianjin–Hebei region.(3) There exist significant spatial effects of energy eco-efficiency among provinces in China. For the energy eco-efficiency of a given region, spatial spillovers from adjacent regions outweigh the influence of errors in adjacent regions. Industrial structure has the greatest influence on energy eco-efficiency. 相似文献
8.
Attribution analysis for water yield service based on the geographical detector method: A case study of the Hengduan Mountain region 总被引：1，自引：0，他引：1
Ecosystem services, which include water yield services, have been incorporated into decision processes of regional land use planning and sustainable development. Spatial pattern characteristics and identification of factors that influence water yield are the basis for decision making. However, there are limited studies on the driving mechanisms that affect the spatial heterogeneity of ecosystem services. In this study, we used the Hengduan Mountain region in southwest China, with obvious spatial heterogeneity, as the research site. The water yield module in the In VEST software was used to simulate the spatial distribution of water yield. Also, quantitative attribution analysis was conducted for various geomorphological and climatic zones in the Hengduan Mountain region by using the geographical detector method. Influencing factors, such as climate, topography, soil, vegetation type, and land use type and pattern, were taken into consideration for this analysis. Four key findings were obtained. First, water yield spatial heterogeneity is influenced most by climate-related factors, where precipitation and evapotranspiration are the dominant factors. Second, the relative importance of each impact factor to the water yield heterogeneity differs significantly by geomorphological and climatic zones. In flat areas, the influence of evapotranspiration is higher than that of precipitation. As relief increases, the importance of precipitation increases and eventually, it becomes the most influential factor. Evapotranspiration is the most influential factor in a plateau climate zone, while in the mid-subtropical zone, precipitation is the main controlling factor. Third, land use type is also an important driving force in flat areas. Thus, more attention should be paid to urbanization and land use planning, which involves land use changes, to mitigate the impact on water yield spatial pattern. The fourth finding was that a risk detector showed that Primarosol and Anthropogenic soil areas, shrub areas, and areas with slope 5° and 25°–35° should be recognized as water yield important zones, while the corresponding elevation values are different among different geomorphological and climatic zones. Therefore, the spatial heterogeneity and influencing factors in different zones should be fully con-sidered while planning the maintenance and protection of water yield services in the Hengduan Mountain region. 相似文献
9.
Revealing ecosystem services relationships and their driving factors for five basins of Beijing 总被引：1，自引：1，他引：0
A clear understanding of the relationships among multiple ecosystem services(ESs) is the foundation for sustainable urban ecosystem management. Quantitatively identifying the factors that influence ES trade-offs and synergies can contribute to deepening ES research, from knowledge building to decision making. This study simulated soil conservation, water yield and carbon sequestration in Beijing, China, from 2015–2018. The spatial trade-offs and synergies of these three ESs within the five major river basins in Beijing were explored using geographically weighted regression. Furthermore, geographical detector was applied to quantitatively identify the driving mechanism of the environmental factors for the ES trade-offs and synergies. The results show the following:(1) the spatial relationships between soil conservation and water yield, as well as between water yield and carbon sequestration, were mainly trade-offs. There was a spatial synergy between soil conservation and carbon sequestration.(2) Regarding the spatial trade-off/synergy between soil conservation and water yield in Beijing, the dominant influencing factor was temperature/elevation, and the dominant interactions of the spatial trade-off and synergy between these two ESs in Beijing and the Chaobai River Basin are all manifested in the superposition of precipitation and potential evapotranspiration, temperature, and elevation.(3) Topographic factors were the dominant factors influencing the spatial relationship between soil conservation and carbon sequestration in Beijing and its five major river basins. As a result of the distribution of water systems and hydrological characteristics of the basins, differences were observed in the effects of different combinations of interaction factors on the spatial relationship between these two ESs in different basins.(4) Temperature had the strongest explanatory power in terms of the spatial trade-offs and synergies between water yield and carbon sequestration. The interactions between precipitation and temperature and between precipitation and elevation were the dominant interactions affecting the spatial relationship between water yield and carbon sequestration in Beijing. Overall, the explanatory power of influencing factors on the trade-offs and synergies and the degree of interaction between factors coexist in different basins with consistency and differences. Therefore, understanding the quantitative characteristics of basin-scale spatial trade-offs and synergies between ESs is important for ecosystem management and the promotion of synergy in different basins. 相似文献
10.
Spatial pattern reconstruction of regional habitat quality based on the simulation of land use changes from 1975 to 2010 总被引：3，自引：0，他引：3
Reconstruction of the spatial pattern of regional habitat quality can revivify the ecological environment background at certain historical periods and provide scientific support for revealing the evolution of regional ecological environmental quality.In this study,we selected 10 driving factors of land use changes,including elevation,slope,aspect,GDP,population,temperature,precipitation,river distance,urban distance,and coastline distance,to construct the CA-Markov model parameters and acquired the land use spatial data for 1975,1980,1985,1990,and 1995 by simulation based on the land use status map for 2010.On this basis,we used the InVEST model to reconstruct the spatial pattern of habitat quality in the study area and conducted classification division and statistical analysis on the computed habitat degradation degree index and the habitat quality index.(1)The results showed that from 1975 to 2010,the habitat degradation degree gradually increased,and the habitat degradation grade spatially presented a layered progressive distribution.Habitat quality presented a constantly decreasing trend.The high-value zones were mainly distributed in the mountainous areas,while the low-value zones were mostly located in built-up areas.During the period of 1975-2010,low-value zones gradually expanded to their surrounding high-value zones,and the high-value zones of habitat quality tended to be fragmented.(2)The spatial-temporal variation characteristics of habitat quality from 1975 to 2010 showed that the regions with low habitat quality were difficult to be restored and mostly maintained their original state;the regions with poor habitat quality,which accounted for 6.40%of the total study area,continued to deteriorate,mainly around built-up areas;the regions with good and superior habitat quality,which accounted for 5.68%of the total study area,were easily converted to regions with bad or poor habitat quality,thus leading to the fragmentation of the regional habitat.(3)From 1975 to 2010,land use changes in the study area were significant and had a huge influence on habitat quality;the habitat quality in the study area decreased consistently,and the area of the regions with bad and poor habitat quality accounted for more than 60%of the total study area.Construction land was the largest factor threatening habitat quality. 相似文献
11.
京津冀地区县域环境胁迫时空格局及驱动因素 总被引：1，自引：0，他引：1
环境胁迫反映人类生产生活过程中污染物输出对区域环境系统产生的综合压力。本文基于县域污染物排放和人口社会经济数据库,运用熵权法综合测度县域环境胁迫指数（ESI）,解析2012—2016年京津冀地区环境胁迫的时空格局及各类主体功能区环境胁迫特征,并针对县域环境胁迫的空间效应,在STIRPAT模型框架基础上,运用地理加权回归方法定量估计县域环境胁迫的社会经济驱动力。结果表明：① 京津冀地区面临的环境胁迫态势显著缓解,2012年以来ESI降幅达到54.68%。其中,以北京、唐山、天津、石家庄等中心城区以及滨海新区下降最为显著,县域环境胁迫程度由中心城区向外围呈梯度递减,到2016年环境胁迫高等级县域已经消除;② 5年间京津冀地区县域环境胁迫的空间溢出效应趋强,并在津唐地区呈现空间锁定和路径依赖;③ 优化开发和重点开发区域两类城市化地区是京津冀水气环境的主要承压区,其环境胁迫程度占京津冀地区全域的65.98%,仍然是环境污染防治与管控的重点区域;④ 人口规模和经济发展水平是县域环境胁迫的控制性因素,此外还受环境处理技术水平、农业生产投入强度、国土开发强度以及城镇化等因素影响;⑤ 各驱动因素对县域环境胁迫的驱动作用存在空间异质性,需针对驱动力作用强度及其空间差异,采取差别化环境治理与源头减排对策,精准提升京津冀地区环境协同管制效果。 相似文献
12.
县域城镇化的有序发展和优化布局,对于推进城乡要素平等交换、产业结构优化调整、资源与市场优化配置、促进城乡融合发展与乡村振兴具有重要战略意义。研究表明：① 2000—2020年中国县域城镇化快速发展且区域差异显著,东部沿海地区、中部城郊地区和北方边境地区的县域城镇化率相对较高,而西南地区、中部农区、西藏及新疆大部分地区的县域城镇化率偏低;2020年沿“胡焕庸线”东侧的东北地区、冀北及晋陕豫地区、川东及云贵地区成为县域城镇化率高值区,珠三角地区、长三角地区、京津冀地区、成渝地区、长江中下游地区、内蒙古边境地区,以及江浙闽东南沿海一带城镇化率超过50%的县域达716个,占比38.3%。② 县域城镇化是人口、经济、社会、文化等要素综合作用的结果,经济发展水平、自然环境条件、基础设施建设、地理区位条件、公共资源供给、专业创业集群与宏观政策等影响县域城镇化的方向、范围和深度。预测到2035年中国城镇化率为76.04%,县域城镇化率为64.38%。未来要重视强化县域人口、经济、社会和空间组织结构的调整优化。③ 县域城镇化发展可分为大城市周边县域要素集聚型城镇化、专业功能县域产业集聚带动型城镇化、农产品主产区县域农业现代化引领型城镇化、重点生态功能区县域生态保育型城镇化、人口流失县域异地转移集中型城镇化等5种类型。④ 县域城镇化以县城和重点镇作为要素集聚的重要空间载体,形成居业协同与产城融合的多级体系。通过构建产业全价值链、主导产业关联集群、公共服务融合配置体系等创新路径,将推动城乡要素平等交换与公共资源均衡配置、城乡产业融合与等值化发展,促进城乡融合网络化、城乡治理体系化与资源利用集约化,为优化县域人地关系和城镇化空间体系提供持久动力。 相似文献
13.
京津冀城市群县域尺度生态效率评价及空间格局分析 总被引：6，自引：3，他引：3
京津冀城市群地区是国家经济发展的战略核心区之一,其经济发展与资源环境关系是近年来地理研究的重点领域。本文以京津冀城市群县域为单元,利用PM2.5、NO2遥感反演等数据,设计资源投入—经济效益—环境影响复合生态效率评价指标体系,构建县域单元生态效率评价模型,并利用非期望产出SBM模型对生态效率进行了评价,运用空间自相关分析方法对生态效率的空间效应与空间关联模式进行了检验与分析。结果显示：①资源投入、经济效益与环境影响格局存在明显时空分异,高值区主要分布在京津唐三市及周边部分县区;②2006、2010、2014年3个时期京津冀城市群县域单元生态效率均值分别为0.324、0.305、0.347,总体水平较低,并呈现先下降后改善态势,区位、自然本底条件是导致生态效率空间差异的主要原因。③全局Moran's I指数分别为0.2539、0.3007、0.3088,表明县域单元生态效率存在空间正向集聚趋势;④县域单元生态效率正向集聚程度越来越显著,邻域单元生态效率差距则有所缩减。 相似文献
14.
基于主体功能区规划的中国城市化地区生态功能评估 总被引：1，自引：0，他引：1
从县域尺度对中国主要城市化地区生态功能开展后评估研究,分析城市化地区生态功能指数与第三级指标的相关性,对生态功能明显衰退地区提出政策建议。结果表明：2009?2015年,“两横三纵”城市化战略格局生态功能中高水平区县占比从78.68%降低至68.13%;优化开发区域生态功能中高水平区县占比由53.85%减少至37.28%,明显降低区域主要分布于京津冀东南部、环渤海地区;重点开发区域生态功能中高水平区县占比由73.78%降低至69.21%,明显降低区域分布在中原城市群和东北地区。生态退化的城市化地区均伴随不同程度的生境质量指数降低、生态空间减少、开发强度以及人口密度增加现象。生态功能与第三级指标的相关性由大到小依次为生态空间占比＞生境质量指数＞开发强度＞人口密度。建议强调发展控制,加强生态保护,实施分区分类管控,健全不同主体功能区差异化协同发展长效机制。 相似文献
15.
中国沿海城市群环境规制效率时空变化及影响因素分析 总被引：6，自引：5，他引：1
基于2003~2016年中国沿海三大城市群的面板数据,采用基于非期望产出的超效率SBM模型测度城市群环境规制效率,结合变异系数、基尼系数、空间自相关和广义最小二乘法（GLS）分析城市群环境规制效率空间演变特征,识别环境规制低效运行城市,探究环境规制效率变动的驱动因素。研究表明：① 京津冀城市群注重产业结构调整,环境规制效率上升最为显著;长三角城市群注重末端治理,环境规制效率下降趋势明显;珠三角城市群注重清洁生产技术的引进,环境规制效率明显优于其他两大城市群。② 三大城市群环境规制效率内部差异明显,珠三角城市群最为突出,长三角城市群环境规制下降型城市占比高达38.64%,集中分布在安徽、江苏交界处。③ 珠三角城市群是高环境规制效率空间集聚区,空间溢出效应显著;京津冀、长三角城市群是低环境规制效率空间集聚区,空间溢出效应不显著。④ 经济发展水平、产业结构、市场环境、城镇化水平和对外开放水平是东部沿海城市群环境规制效率变动的影响因素。 相似文献
16.
在京津冀协同发展战略背景下,以建设京津冀世界级城市群为引领,遵循城市发展规律,优化城市空间布局,明确京津冀城市群等级结构及其空间特征具有重要意义。本文以京津冀城市群156个区县为研究对象,从经济中心性、交通中心性、信息中心性、人口中心性4个角度,利用4种空间聚类方法进行5个等级的聚类分析,并基于克氏中心地理论对京津冀城市群等级划分结果进行空间结构分析。结果显示,自组织特征映射神经网络算法(SOM)较适合京津冀城市群的等级划分;京津冀城市群正从以北京城区为单核心的圈层空间结构向3条带型空间结构转变,其中京津都市发展走廊发育成熟,沿海都市发展带也初具规模,而包括雄安新区在内的京石都市发展带正在孕育。 相似文献
17.
京津冀地区制造业空间格局演化及其驱动因素 总被引：2，自引：2，他引：0
京津冀地区产业转移升级、协同发展和先进制造业深度融合发展战略对制造业产业集群的空间布局提出更高要求.论文基于2000-2013年京津冀地区规模以上工业企业微观数据,运用核密度分析法和面板数据回归模型等方法,探究京津冀地区制造业空间格局演化特征及其驱动因素.结果表明:①京津冀地区全部制造业总体格局相对稳定,高值区集聚于京... 相似文献
18.
京津冀地区耕地利用转型时空分异及驱动机制 总被引：2，自引：0，他引：2
耕地利用转型代表耕地利用形态的趋势性变化。论文以京津冀地区157个县域空间为基本研究单元,从显性形态与隐性形态双重属性出发构建耕地利用形态指标体系,运用冷热点、空间变差函数等方法分析1990—2015年耕地利用形态变化的时空特征,在此基础上,利用空间误差模型(spatial error model, SEM)对耕地利用转型的驱动机制进行了定量分析。结果表明：① 京津冀地区耕地利用形态指数空间分布呈东南高、西北低的格局,与该地区地形分布格局基本一致,且因坝上高原特色农业发展形成独立高值区。② 京津冀地区耕地利用形态指数空间分异呈现逐渐缩小的趋势,显著热点区与显著冷点区分布相对稳定且面积不断缩小,耕地利用转型较为平稳。显性形态值普遍呈现先升高后降低趋势,隐性形态值则呈升高趋势,表明京津冀耕地出现空间收缩、功能优化式转型。③ 高程是影响京津冀地区耕地利用形态空间特征的主要自然环境因素,二三产业占比、地均固定资产投资与城镇化率等经济发展和城镇建设因素则是驱动1990—2015年京津冀地区耕地转型的主导因素,但不同时段、不同县域单元耕地转型动力机制存在差异,各驱动因子作用强度也不完全一致。 相似文献
19.
资源环境承载能力预警评价中,除基础评价外,还需针对城市化地区存在的特殊问题开展专项评价。但现有相关研究大多较为复杂、难以操作,且较少考虑目前中国城市化地区之间存在的发展水平差异,难以满足实际应用需求。本文根据近年来中国城市化地区资源环境凸显的主要问题,从城市人居环境入手,选取城市黑臭水体和PM2.5超标天数2个要素设计城市水气环境黑灰指数,作为城市化地区专项评价的主要指标;同时考虑到优化开发区域和重点开发区域的主体功能导向差异,以京津冀城市化地区为例开展试评价分析,结果显示：京津冀城市化地区的104个区县中,47个区县为重警,46个中警,仅11个为轻警,整体形势不容乐观。其中,重警区县主要集中在京广高铁沿线,与地区主要交通线路分布及钢铁工业聚集格局一致;轻警区县主要分布在北部的张承地区及东部沿海,工业相对较少,且地理位置有利于污染物迅速扩散。城市化地区专项评价作为基础评价的补充,能更清晰地反映现阶段影响城市人居环境的主要制约因子以及不同发展水平地区间的差异,评价结果可为城市化地区开展国土空间规划、城镇发展战略研究和产业结构调整等提供科学依据。 相似文献
20.
京津冀城镇体系与水系结构的时空关系研究 总被引：2，自引：1，他引：1
京津冀地区人水关系矛盾突出,分形可以有效描述城镇体系和水系时空演化特征,从而揭示两者演化关系,为城市问题的解决提供一些理论和经验依据。论文采用分形理论中的网格维数和多分维谱,首先分别刻画了两者的时空演化特征,其次探讨了城镇体系和水系结构之间的时空关系,最后探究了水系结构退化的影响因素。主要结论有：① 1990—2010年,京津冀地区建设用地的网格维数升高、自相似性增强、从集聚向分散转变,意味着建设用地朝着空间填充程度增强、有序、分散的方向发展,而水系反之,证明两者具有不同的时空演化方向;② 21世纪10年代,京津冀的人水关系十分紧张,南水北调虽然缓和了京津冀用水问题,改善了大尺度上的水系结构,但在小尺度上改善有限;③ 越靠近城市中心,建设用地分形形态发育越成熟,结构越有序,越靠近外围越混乱无序;④ 京津冀地区水系退化,由自然和人为两方面因素造成,21世纪以后人为因素的影响较为显著。针对京津冀地区水系退化,提出如下政策建议：在城市建设过程中,一方面科学规划城市水系,重视低等级水系的保护;另一方面节约集约利用水资源,完善水资源管理机制。未来,需要进一步探索城市发展和水系的非线性关系,为城市可持续发展提供依据。 相似文献