
Spatial mismatch measurement and evolutionary characteristics of construction land use under undifferentiated land use comparison
SHI Hai-meng, CHEN Wei, LI Qiao, ZHANG Sun, WANG Ya-nan, ZHANG Heng
JOURNAL OF NATURAL RESOURCES ›› 2024, Vol. 39 ›› Issue (12) : 2962-2979.
Spatial mismatch measurement and evolutionary characteristics of construction land use under undifferentiated land use comparison
From the perspective of undifferentiated comparison of land use, the spatial and temporal evolution of the spatial mismatch of urban construction land in China is investigated based on the land comparable correction model and the extended HK model, with a view to providing reference for the efficient and scientific allocation of construction land. The results show that: (1) During the study period, the spatial mismatch of construction land generally showed a "W"-shaped fluctuating trend, which was characterized a predominantly over-allocation and a supplementary under-allocation. At the regional level, the degree of mismatch in the east fluctuated greatly and was higher than the national average after 2012, the central region was largely below the national average, the western region was always higher than the national average, and the northeast region showed an inverted "N"-shaped downward trend. (2) During the study period, the spatial under-allocation of construction land evolved from a belt-shaped distribution to a cluster-shaped distribution, and there was a characteristic of spreading from the southeastern coast to the inland areas. The spatial over-allocation always showed a pattern of contiguous distribution, and there was a tendency from peripheral distribution to internal aggregation. (3) From the perspective of different city sizes, small cities had the highest degree of mismatch, followed by megacities, then medium-sized cities, and finally large cities. However, the mismatch in megacities was more dominated by under-allocation, while other city sizes were mainly dominated by over-allocation. The results of the study help to improve the objectivity and scientificity of the identification of spatial mismatch of construction land and promote the optimization and improvement of the efficiency of construction land allocation.
construction land / spatial mismatch / undifferentiated land use comparison / spatio-temporal pattern {{custom_keyword}} /
Table 1 Descriptive statistics of variables表1 变量描述性统计 |
变量 | 指标选择 | 样本数/个 | 均值 | 标准差 | 最小值 | 最大值 |
---|---|---|---|---|---|---|
城市产出 | 地区生产总值/亿元 | 5700 | 729.21 | 1654.30 | 6.10 | 26174.68 |
资本投入 | 资本存量/亿元 | 5700 | 2599.01 | 5137.30 | 14.41 | 71502.67 |
劳动投入 | 有效劳动投入/(万人·年) | 5700 | 119.71 | 201.42 | 1.37 | 2803.173 |
土地投入 | 修正后建设用地面积/km2 | 5700 | 640.21 | 1548.42 | 12.48 | 23149.21 |
Table 2 Average spatial mismatch index of construction land in cities of different sizes表2 不同规模城市的建设用地平均空间错配指数 |
年份 | 特大城市 | 大城市 | 中等城市 | 小城市 | 年份 | 特大城市 | 大城市 | 中等城市 | 小城市 |
---|---|---|---|---|---|---|---|---|---|
2002 | 0.40 | 0.33 | 0.37 | 0.44 | 2013 | 0.38 | 0.31 | 0.33 | 0.37 |
2003 | 0.36 | 0.31 | 0.35 | 0.43 | 2014 | 0.39 | 0.31 | 0.34 | 0.38 |
2004 | 0.35 | 0.30 | 0.36 | 0.43 | 2015 | 0.40 | 0.32 | 0.34 | 0.37 |
2005 | 0.37 | 0.30 | 0.35 | 0.42 | 2016 | 0.36 | 0.33 | 0.36 | 0.37 |
2006 | 0.35 | 0.28 | 0.34 | 0.43 | 2017 | 0.36 | 0.32 | 0.36 | 0.40 |
2007 | 0.39 | 0.28 | 0.34 | 0.42 | 2018 | 0.38 | 0.33 | 0.36 | 0.40 |
2008 | 0.34 | 0.28 | 0.33 | 0.40 | 2019 | 0.38 | 0.34 | 0.36 | 0.41 |
2009 | 0.36 | 0.29 | 0.34 | 0.40 | 2020 | 0.38 | 0.35 | 0.36 | 0.39 |
2010 | 0.38 | 0.29 | 0.34 | 0.41 | 2021 | 0.46 | 0.37 | 0.36 | 0.38 |
2011 | 0.39 | 0.29 | 0.33 | 0.38 | 平均值 | 0.38 | 0.31 | 0.35 | 0.40 |
2012 | 0.40 | 0.30 | 0.34 | 0.37 |
Table 3 Comparison with other findings表3 与其他研究结果的比较 |
作者 | 区域 | 时间/年 | 测度方法 | 平均错配程度 | 有无做可比性处理 | 错配特征 |
---|---|---|---|---|---|---|
本文 | 285个地级市 | 2002—2021 | 拓展的HK模型 | 0.38 | 是 | 建设用地空间错配总体呈现出“W”型波动变化趋势 |
李力行等[5] | 282个地级市 | 2003—2007 | 协议出让面积/出让土地面积 | 0.59 | 否 | — |
张俊峰等[36] | 235个地级市 | 2001—2016 | 划拨用地数量/土地供应总量 | 0.52 | 否 | 建设用地错配呈现先下降后上升的发展趋势和西高东低的空间格局 |
程开明等[11] | 279 个地级市 | 2003—2018 | 竞争性空间一般均衡模型 | 1.25 | 否 | 土地空间错配先缓解后加剧。东北和西部城市供给过度、东部城市供给不足的特征突出。东北的土地供给过度特征最为明显 |
孟宏玮等[19] | 280个地级市 | 2010—2019 | 土地投入与经济产出的欧氏距离 | 0.61 | 否 | 东部的土地错配指数最低,东北和西部的较高。中部的土地错配指数变化较平稳 |
Wang等[12] | 282个地级市和333个县 级市 | 2008—2017 | 人口和经济密 度变化的四象 限模型 | — | 否 | 与2008—2012年比,2013—2017年错配城市数量有所增加。后金融危机时代,地方政府的财政依赖加速了土地开发的错配,尤其是县级市,错配城市集中在东北和西北地区 |
彭山桂等[14] | 105个城市 | 2007—2019 | 拓展的HK模型 | 0.71 | 否 | — |
冯雨豪等[15] | 278个地级市 | 2003—2019 | 投入产出的错配模型 | 0.45 | 否 | 城市工业用地空间错配呈现先下降后上升的趋势 |
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产业转型升级是现代经济增长中区分发展中国家与发达国家的核心变量,政府的土地资源配置决策会引起产业结构与业态的演化,对产业转型升级产生重要影响。考察土地资源空间错配对城市产业转型升级的影响并刻画其具体作用机制,具有重要的政策意义。本文在系统地测度城市产业转型升级水平的基础上,构建空间面板计量模型与中介效应模型,从影响结果、影响机制2个维度,考察土地资源空间错配对城市产业转型升级的影响方式及其中间机制。研究发现:①土地资源空间错配对城市产业转型升级具有显著的负面影响。影响程度上,对土地供给相对短缺城市的影响大于土地供给相对过剩城市。结构层面上,在土地供给相对过剩的城市内,工业用地过剩的负面影响更为明显;在土地供给相对短缺的城市内,商住用地、工业用地短缺都有显著的负面影响。②对于土地供给相对过剩的城市,土地资源空间错配主要通过低端产业存活强化、制度环境破坏的中间机制,对城市产业转型升级产生负面影响。③对于土地供给相对短缺的城市,土地资源空间错配主要通过实体行业投融资挤出、居民需求与创新抑制的中间机制,对城市产业转型升级产生负面影响。本文研究结论的政策启示是,扎实稳步地推进土地资源空间错配的纠偏,是促进城市产业转型升级的有效措施与有力抓手。
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Industrial transformation and upgrading is the core variable that distinguishes developing and developed countries in modern economic growth, and the government’s allocation of land resources will lead to the change of industrial structure and format, which has an important impact on industrial transformation and upgrading. Therefore, it is of great policy significance to investigate the impact of spatial mismatch of land resources on urban industrial transformation and upgrading and examine its specific mechanism. On the basis of systematically measuring the level of urban industrial transformation and upgrading, this study constructed a spatial panel econometric model and a mediation effect model to investigate the impact of land resources spatial mismatch on urban industrial transformation and upgrading, and analyzed its mediation mechanism from the two dimensions of impact results and impact mechanism. This study found that: (1) Land resources spatial mismatch has a significant negative impact on industrial transformation and upgrading. With regard to the extent of impact, the impact on cities with relative shortage of land supply is greater than that of cities with relative excess of land supply. At the structural level, for cities with relative excess land supply, the negative impact of relative excess industrial land on industrial transformation and upgrading is more obvious. For cities with relative shortage of land supply, the relative shortage of commercial and residential land or industrial land has a significant negative impact on industrial transformation and upgrading. (2) For cities with relative excess of land supply, the negative impact mainly occurs through the mediation mechanism of sustainance of low-end industry and institutional environment deterioration. (3) For cities with relative shortage of land supply, the negative impact mainly occurs through the mediation mechanism of crowding out of real industrial sector investment and financing, and residents’ demand and innovation inhibition. The policy implication is that steadily promoting the rectification of land resources spatial mismatch is an effective measure to promote the industrial transformation and upgrading. {{custom_citation.content}}
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邓楚雄, 赵浩, 谢炳庚, 等. 土地资源错配对中国城市工业绿色全要素生产率的影响. 地理学报, 2021, 76(8): 1865-1881.
基于价格扭曲效应拓展资源错配模型,使用中国285个城市2004—2017年的工业投入产出数据,测算土地资源错配导致的城市工业绿色全要素生产率(GTFP)损失,并分析其时空变化。结果表明:① 土地资源错配对中国城市工业GTFP损失的年均贡献率为10.05%,已与能源错配并列成为继资本错配之后城市工业GTFP损失的重要贡献者。② 土地资源错配导致中国城市工业GTFP损失呈现“先小幅下降,再大幅上升,后较大幅度下降”的时序变化特征,但总体趋于上升,损失值介于1.10%~2.48%之间,纠正土地资源错配,中国现有城市的工业GTFP有望实现年均2%左右的再增加;东、中部地区土地资源错配导致的城市工业GTFP损失呈现出与全国层面类似的变化特征,西部地区的城市工业GTFP损失整体保持高位,总体稍有下降,东部地区是中国城市工业发展的主要阵地,其土地资源错配导致的城市工业GTFP损失主导着全国层面的城市工业GTFP损失变化。③ 土地资源错配导致中国城市工业GTFP损失的空间格局呈连片集聚化的发展特征,城市工业GTFP损失较高和高等级省份的数量有所增加,逐渐集中到以黄河流域为主的北方地区,损失低和中等等级省份的数量相应减少,逐渐集中到长江流域及东部沿海地区;土地资源错配导致中国城市工业GTFP损失的总差异呈缩小态势,三大地区内城市工业用地配置效率不均衡是土地资源错配导致中国城市工业GTFP损失差异的根本原因,其中西部地区内城市工业用地配置效率不均衡是主要原因,近年来的区域协同发展有利于三大地区间城市工业用地配置效率差距的缩小。
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This paper expands the resource misallocation model based on the effect of price distortion. It measures the green total-factor productivity (GTFP) loss of urban industry due to land misallocation and analyzes its spatial and temporal changes by using the industrial input-output data of 285 cities in China from 2004 to 2017. The main results are as follows: (1) Capital misallocation still plays the most important role in the urban industrial GTFP loss, followed by land misallocation (10.5%) and energy misallocation. (2) The characteristics of industrial GTFP loss in Chinese cities induced by land misallocation can be summarized as "initially a small decline, then a large increase, and finally a large decline". Overall, the urban industrial GTFP loss increased, ranging from 1.10% to 2.48%. A correction in land misallocation is expected to bring about a 2% increase of industrial GTFP among Chinese cities. The characteristics of urban industrial GTFP loss due to land misallocation in the eastern and central regions are similar as that at the national level, while the loss in the western region maintains a high value with a slight overall decline. The eastern region is at the forefront of China's urban industrial development, and its industrial GTFP loss due to land misallocation dominates changes at the national level. (3) The spatial pattern of urban industrial GTFP loss in China due to land misallocation is characterized by contiguous clustering. The number of provinces with higher- and high-grade urban industrial GTFP loss has increased, gradually clustering in the northern region, mainly in the Yellow River basin. The number of provinces with low- and medium-grade loss has decreased and are mainly concentrated in the Yangtze River basin and the eastern coastal region. The total variation in urban industrial GTFP loss due to land misallocation among Chinese cities has been narrowed. The unbalanced allocation efficiency of urban industrial land in the three regions is the fundamental cause for the contrasting loss in urban industrial GTFP from land misallocation. In particular, the unbalanced allocation efficiency of urban industrial land in the western region is the main reason. The collaborative regional development in recent years is conducive to bridging the gap in the allocation efficiency of urban industrial land among the three regions. {{custom_citation.content}}
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基于拓展的三要素空间一般均衡模型,测度2003―2018年中国地级以上城市资本、劳动力和土地资源空间错配程度,通过时空核密度和综合协调指数解析城市资源空间错配的集聚模式及协调度,以准确反映城市资源空间错配程度及时空演变规律。研究发现:① 样本期内不同资源的城市空间错配程度变动趋势差异明显。城市资本和劳动力空间错配持续改善,但土地空间错配先缓解后加剧,行政力量阻碍资源市场化流动是加剧土地错配的重要因素。② 3种资源在城市间的空间集聚模式具有明显差异。城市资本和土地资源的空间配置具有强烈的区域偏向性和共聚性,相邻城市资源配置呈现高–高、低–低型正向集聚模式;户籍壁垒和非均等化公共服务阻碍城市劳动力自由流动,使得相邻城市劳动力配置呈现出高–低型负向集聚模式。③ 相邻城市在资本市场化改革和土地政策调整方面具有一致性,但城市之间劳动力错配的协调度呈恶化趋势;东北地区要素市场化改革协同性最低。研究结论为完善要素市场化配置体制机制、明晰城市层面资源配置的演化路径和优化策略提供了参考。
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Since the reform and opening up, China has gradually formed a more sound commodity market, but the reform of factor market allocation has lagged behind relatively. The markets for capital, labor, land and other factors of production are still not perfect, and the problem of resource allocation significantly affects the transformation of China's productive forces and production relations. Due to the significant differences in resource endowments in different regions and the restrictions on the free flow of factors by administrative barriers, the cost of factor flow and access to regions is high and resources cannot flow smoothly to advantageous locations. This leads to uneven resource allocation between regions and spatial misallocation of resources. The spatial misallocation of resources not only triggers competition for regional resources, intensifies local protectionism, and leads to more serious structural imbalances such as industrial structure convergence, duplication of major facilities construction and excessive market competition in various regions, but also aggravates problems such as urban traffic congestion, housing tension and environmental pollution due to unbalanced resource allocation. Therefore, a comprehensive and in-depth exploration of the characteristics of resource misallocation in China and its spatial and temporal evolution pattern is of great theoretical and practical significance for the government to re-examine the characteristics of factor mismatch, clarify the direction of optimising resource allocation and promote factor market-oriented reforms. To accurately reflect the spatial mismatch degree and spatial-temporal evolution law of city resources, this paper measures the mismatch degree of capital, labor, and land resources in cities at the prefecture level and above in China from 2003 to 2018 based on the extended three-factor spatial general equilibrium model. We use spatio-temporal kernel density and comprehensive coordination index to analyze the changing trend of city resources spatial mismatch, spatial agglomeration pattern, and the coordination degree of factor marketization reform. The results show that: 1) The variation trend of city spatial mismatch degree of different resources is different. The misallocation of capital and labor space continues to improve, but the misallocation of land space first alleviates and then intensifies. The administrative force hindering the market flow of resources is an important factor aggravating the land misallocation. 2) The spatial agglomeration patterns of the three resources among cities are different. The spatial allocation of city capital and land resources has strong regional bias and convergence, and the resource allocation of neighboring cities shows a high-high, low-low positive agglomeration pattern. However, household registration barriers and unequal public services hinder the free flow of city labor, making it difficult to achieve a balanced allocation of labor resources between cities, and the labor resources in neighboring cities show a high-low negative agglomeration pattern. 3) Neighboring cities have consistency in capital market reform and land policy adjustment. However, the coordination degree of labor mismatch between cities is worsening. Northeast China has the lowest degree of synergy in factor marketization reform. The research conclusion of this paper provides a reference for improving the mechanism of market-oriented allocation of factors and clarifying the evolution path and optimization strategy of resource allocation at the city level. {{custom_citation.content}}
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彭山桂, 李敏, 王健, 等. 土地资源错配的全要素生产率损失效应与形成机制. 中国土地科学, 2022, 36(8): 55-65.
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冯雨豪, 王健, 邵子南, 等. 中国城市工业用地空间错配对工业全要素生产率的影响. 资源科学, 2022, 44(12): 2511-2524.
众所周知,资源的空间错配会带来全要素生产率的降低,但二者之间的影响路径却鲜有研究深入探讨。因此,为探讨中国城市工业用地空间错配对工业全要素生产率影响的“黑箱”,本文基于2003—2019年278个地级及以上城市面板数据,构建“工业用地空间错配—工业产业集聚—工业全要素生产率”理论分析框架,采用纳入中介效应的GMM动态面板计量经济模型,从全国、区域以及错配类型3个维度,分析工业用地空间错配如何通过工业产业集聚影响工业全要素生产率。研究表明:①样本考察期内中国城市工业用地空间错配总体呈加剧趋势,东部城市大多呈短缺型错配,中西部城市大多呈过度型错配。②全国层面,工业用地空间错配不仅直接对工业全要素生产率产生负向影响,而且通过降低工业产业集聚度,间接降低工业全要素生产率。③区域层面,工业用地空间错配的加剧抑制了东部地区工业全要素生产率的提升。但是,由于工业用地短缺促进了工业产业合理集聚一定程度上缓解了这种抑制效应。中西部地区工业用地空间错配的加剧导致工业产业集聚度的降低,二者同时对工业全要素生产率产生负向影响。④不同错配类型下,过度型错配地区与中西部地区结果一致。短缺型错配地区与东部地区结果稍有差异,其错配的恶化导致工业产业过度集聚,降低了工业全要素生产率。本文主要政策启示为:应立足不同地区工业经济发展阶段,合理配置工业用地,促进工业产业适度集聚,激发用地效率。
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The spatial misallocation of resources will lead to the reduction of total factor productivity (TFP), but there are few in-depth studies on the influence path. Based on the panel data of 278 cities in China from 2003 to 2019, this study explored the “black box” of the urban industrial land spatial misallocation impact on the TFP of industries. By constructing the theoretical framework of industrial land spatial misallocation-industrial agglomeration-industrial TFP, this study examined how spatial misallocation of industrial land affects its utilization efficiency through industrial agglomeration and dispersion from three dimensions of national, inter-regional, and misallocation type. The generalized method of moments (GMM) dynamic panel econometric model incorporating the mediation effect was employed for the analysis. The results show that: (1) Urban industrial land spatial misallocation in China generally presents a worsening trend. Most of the eastern cities showed a shortage-type misallocation, and most of the central and western cities showed an excessive-type misallocation. (2) At the national level, the spatial misallocation of industrial land not only directly and negatively affected industrial TFP, but also indirectly reduced the TFP of industries by reducing the degree of industrial agglomeration. (3) At the regional level, the worsening of the spatial misallocation of industrial land in the eastern region inhibited the improvement of industrial TFP. However, due to the shortage of industrial land, a certain degree of industrial agglomeration has alleviated this inhibitory effect; The worsening of the spatial misallocation of industrial land in the central and western regions led to the dispersion of industrial allocation, and both have a negative impact on the industrial TFP. (4) For the different misallocation types, excessive misallocation is consistent with the regression results in the central and western regions. Shortage misallocation is slightly different from the regression results in the eastern region. The worsening of the misallocation not only directly and negatively affected the industrial TFP, but also reduced its efficiency through the excessive agglomeration of industries. The main conclusions are that based on the different stages of industrial economic development in different regions, rational allocation of industrial land should be made to promote appropriate agglomeration of industries and stimulate land use efficiency. {{custom_citation.content}}
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毛文峰, 陆军. 土地资源错配、城市蔓延与地方政府债务: 基于新口径城投债数据的经验证据. 经济学家, 2020, (4): 80-88.
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陈恭军. 土地资源错配、产业结构与雾霾污染: 基于空间计量和动态面板门槛模型的实证分析. 中国软科学, 2022, (12): 143-152.
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白东北, 张营营, 唐青青. 开发区设立与地区资源错配: 理论机制与经验辨识. 财经研究, 2020, 46(7): 49-63.
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陈伟, 彭建超, 吴群. 基于容积率指数和单要素DEA方法的工业用地利用效率区域差异研究. 自然资源学报, 2015, 30(6): 903-916.
从土地利用无差异比较的角度出发,在阐释土地利用差异性比较的思路后,构建容积率指数(VRI)分析了不同区域工业用地利用强度变化,并消除工业产业结构对不同区域工业用地面积的影响,在此基础上利用单要素DEA方法分析了全国不同区域工业用地利用效率的特征及变化趋势.研究结果表明:VRI高的区域多分布在东南沿海地区,VRI低的区域多分布在中西部地区,并且东部地区VRI呈下降趋势;工业用地面积修正后,工业用地利用效率增大的区域多集中在中西部地区,工业用地利用效率下降的区域主要出现在东南沿海地区;以长江三角洲和珠江三角洲为主的东南沿海经济发达地区工业用地利用效率明显高于中西部地区;变异系数反映出区域间工业用地利用效率的差异程度正在逐渐缩小,工业产出的不均衡程度大于工业用地配置的不均衡程度.
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徐勇, 赵燊, 樊杰. 中国城市规划建设用地标准及气候和地形地貌修订. 地理学报, 2020, 75(1): 194-208.
城市规划建设用地标准是科学配置城市各类建设用地的技术规范和编制、修订城市总体规划的基础。针对中国现行城市规划建设用地标准存在的用地指标控制阈值高低差距较大、气候修订缺乏地域分异和地形地貌因素缺失等问题,本文按照“总量—结构”控制的建标思路,提出了标准建立、修订的分步式流程框架和定量测算方法,通过条件设定建立了普适性的建设用地基础标准,进而选择城市人口规模、日照间距系数、河谷地(山间盆地)宽度、地形坡度等关键指标,定量分析了各指标与基础标准之间的关系,形成与基础标准配套的气候和地形地貌修订标准。主要研究结果包括:确定了设定条件下适用于全国不同地区的由人均建设用地面积和人均单项用地类型结构控制的建设用地基础标准;按城市人口规模等级对基础标准进行了量化修订;定量测算了人均居住用地面积随日照间距系数变化的情况,提出了按纬度方向变化的人均建设用地气候修订标准;阐释了河谷地(山间盆地)宽度变化与公园绿地的配置,量化分析了地形坡度与人均建设用地面积变化的关系,建立了针对山地、丘陵地区城市规划建设用地的地形地貌修订标准。
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Urban planning construction land standard is the technical specification for allocating various types of urban construction land scientifically, and is the basis for drawing up and revising the overall urban planning as well. In view of China's current urban planning construction land standard, there are many problems such as the big gap of land use control threshold, the lack of regional differences in climate revision, and ignorance of the topographical and geomorphological factors. To solve these problems, this paper proposed a step-by-step process framework and quantitative calculation method for the establishment and revision of standards in accordance with the principle of "total-structure" control. Through the setting of conditions, a universal basic standard for construction land was established. Then quantitative analysis was made for the relations between each index and the basic standard with the selected key indicators such as urban population size, sunshine spacing coefficient, valley area (intermountain basin) width and terrain slope. Finally we formed a revision standard for climate, topography and geomorphology which is matched with the basic standard. The main results are as follows: (1) The per capita construction land area of 95 m 2/person can be used as the total indicator for the basic standard of urban planning in China. The percentage of corresponding per capita for each type of construction land is 32.5% for residential land, 7.42% for public administration and public service land, 22.5% for industrial land, 17.5% for transport facilities, 12.5% of green land, and 7.58% of other types of land. The results of revision value of urban population scale shows that the impact of population size difference on the per capita construction land is relatively weak. (2) The climate revision results of per capita residential land and per capita construction land in major cities show that the climate revision value varies greatly between northern and southern China. The climate revision value of the per capita area of construction land varies by latitude as follows: the figure for 20° north latitude is 93 m 2/person; the figure for 30° north latitude is 97 m 2/person; the figure for 40° north latitude is 103 m 2/person; and the figure for 50° north latitude is 115 m 2/person. The basic standard value of 95 m 2/person is roughly distributed along the Xiamen - Guilin - Kunming line. (3) The cities located in mountainous areas, hilly valleys or intermontane basins can reduce the allocation of community parks and comprehensive parks when the average width of river valley or intermontane basin is less than 2 km. When the average width of the valley or intermontane basins is between 2 km and 4 km, the allocation of the comprehensive parks can be reduced. The revised results of per capita land for construction use on slopes indicate that the terrain slope has a great impact on the revised value of per capita construction land. The revised value at 3° is 3.68% higher than the baseline value, and the increases of 8°, 15° and 25° are 11.25%, 26.49% and 68.47%, respectively. {{custom_citation.content}}
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中华人民共和国住房和城乡建设部. 城市居住区规划设计标准(GB 50180—2018). https://www.mohurd.gov.cn/gongkai/zhengce/zhengcefilelib/201811/20181130_238590.html, 2023-09-08.
[Ministry of Housing and Urban-Rural Development of the People's Republic of China. Urban residential area planning and design standard (GB 50180—2018). https://www.mohurd.gov.cn/gongkai/zhengce/zhengcefilelib/201811/20181130_238590.html, 2023-09-08.]
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[Ministry of Natural Resources of the People's Republic of China. Industrial project construction land control indicators. https://www.gov.cn/zhengce/zhengceku/202306/content_6888447.htm, 2023-09-08.]
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中华人民共和国住房和城乡建设部. 城市用地分类与规划建设用地标准(GB 50137-2011). https://www.mohurd.gov.cn/gongkai/zhengce/zhengcefilelib/201201/20120104_208247.html, 2023-09-10.
[Ministry of Housing and Urban-Rural Development of the People's Republic of China. Urban land classification and planning construction land standard (GB 50137-2011). https://www.mohurd.gov.cn/gongkai/zhengce/zhengcefilelib/201201/20120104_208247.html, 2023-09-10.]
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中华人民共和国交通运输部. 公路工程项目建设用地指标(建标〔2011〕124 号). https://xxgk.mot.gov.cn/2020/jigou/glj/202006/t20200623_3312366.html, 2023-09-10.
[Ministry of Transport of the People's Republic of China. Highway engineering project construction land index. https://xxgk.mot.gov.cn/2020/jigou/glj/202006/t20200623_3312366.html, 2023-09-10.]
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梁建飞, 陈松林. 环境约束下的福建省城市建设用地利用效率及驱动因素. 自然资源学报, 2020, 35(12): 2862-2874.
研究环境约束下的城市建设用地利用效率地区差异特征及其驱动机理,对于引导城市建设用地高效利用、缓解快速城镇化进程中经济社会发展与生态环境之间的矛盾、实现区域协调发展具有重要现实意义。将环境污染作为非期望产出纳入城市建设用地利用效率评价体系,运用非期望产出SE-SBM模型、变异系数、GML指数和灰色关联度模型,系统研究2006—2016年福建省城市建设用地利用效率的时空分异特征、动态趋势演变及其驱动因素。研究表明:(1)2006—2016年福建城市建设用地利用效率总体呈正弦函数式样波动,2012—2016年投入产出效率始终位于有效前沿面。各地区效率差异明显,效率的高低与经济发展水平之间并非是正相关关系。(2)空间格局整体上呈现东部沿海地区的效率值高于西部内陆地区的分布态势,形成明显的集群效应。漳州虽属于东南部沿海地区,但2016年其效率值仍处于无效状态,未发生根本性转变,这进一步说明高效率城市的辐射带动作用较弱。(3)福建全要素生产率表现为正弦函数式样增长态势,整体发展趋势向好。技术进步引起的集聚规模效应是造成地区全要素生产增长率差异的主要原因,技术因素是缩小地区间全要素增长率差距的关键。(4)城镇化水平、生态投入、政府规制、耕地资源禀赋、科技研发投入和产业结构高级化是影响福建省城市建设用地利用效率时空分异与演变的主要驱动因素。
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张俊峰, 王聪聪, 徐磊, 等. 中国建设用地错配时空特征、驱动机制及空间效应: 基于235个城市的实证分析. 热带地理, 2021, 41(2): 217-228.
在阐述建设用地错配机制的基础上,构建建设用地错配测度模型和错配机制计量模型,重点探讨中国2001-2016年城市建设用地错配时空特征、驱动机制及其空间效应。结果表明:1)中国建设用地错配呈现先下降后上升的发展趋势和西高东低的空间分布格局;2)中国建设用地错配及其影响因素呈现空间集聚与关联特征,但空间关联效应有减弱态势;3)土地财政依赖、产业结构优化、市场发育完善对建设用地错配具有显著的负向影响;4)政府腐败和经济发展对建设用地错配具有显著的正向影响且存在空间溢出效应。中国建设用地错配普遍存在且有上升态势,转变经济发展方式、加大政府腐败治理力度、完善市场机制和区域一体化建设能够有效缓解区域建设用地错配。
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曹祺文, 顾朝林, 管卫华. 基于土地利用的中国城镇化SD模型与模拟. 自然资源学报, 2021, 36(4): 1062-1084.
中国正处在快速推进的城镇化进程中,耕地与林地、牧草地和水域等生态用地将如何变化,以及建设用地是否仍将快速增长?这不仅是国家宏观政策制定者关心的问题,也是广大学者和普通民众面临的具体问题。通过构建基于土地利用的中国城镇化系统动力学(System dynamics,SD)模型,尝试对上述问题作出分析。研究结果表明:(1)本文构建的模型是有效的,具备可靠性和稳定性。(2)若要保持国家耕地保有量不少于18.25亿亩,到2050年需补充83.17万~412.67万hm<sup>2</sup>耕地资源。(3)到2050年,如果中国城镇化水平达到78%左右,建设用地总量将达到4007.29万~4214.25万hm<sup>2</sup>,较2020年净增加了155.87万~342.88万hm<sup>2</sup>。(4)2020—2050年生态用地数量表现为先增加后减少,其中,林地显著增加,牧草地减少,水域略有增加。研究成果可为全国国土空间规划多方案模拟、评估和决策提供科学服务。
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