广州市城市边缘区土地利用优化配置(英文)

In response to the strong drive for social and economic development, local governments have implemented urban master plans, providing measures and timeframes to address the continuous demand for land and to alleviate urban problems. In this paper, a multi-objective model was constructed to discuss the problem, including economic benefits and ecological effectiveness, in terms of land use optimization. A genetic algorithm was then adopted to solve the model, and a performance evaluation and sensitivity analysis were conducted using Pareto optimality. Results showed that a set of tradeoffs could be acquired by the allocation of land use. In addition, the Pareto solutions proved the model to be efficient; for example, a limit of 13,500 ha of urban area conformed to plan recommendations. The reduction in crop land, orchard land, grassland, and unused land provided further efficiencies. These results implied that further potential regional land resources remain and that the urban master plan is able to support sustainable local development in the years to come, as well as verified that it is feasible to use land use allocation multi-objective modeling and genetic algorithms.     

广州市土地利用结构优化配置及其潜力

基于广州市土地利用结构、地区经济、生态与社会特点,结合广州城市总体规划(2010-2020),对广州市域土地利用结构进行生态经济效益-自然生态效益导向的多目标优化配置研究。结果表明：对广州市土地利用数量结构进行调整,一定时间内能够满足地区可持续发展;但是,土地仍然承担着巨大的压力,焦点是建设用地和农用地之间的数量转变,以耕地为主,也包括对未利用土地的利用;土地利用潜力度模型结果显示,通过优化土地利用结构,土地系统的协调度增大而潜力度减小：在生态经济效益目标下,潜力度分别为0.628～0.661,0.372～0.339;在自然生态效益目标下,分别为0.531～0.782,0.469～0.218,表明土地利用系统将趋于更高的协调状态,而其数量结构优化配置的潜力减小,优化各产业部门内部土地资源结构及其空间布局,将是广州市土地资源高效集约利用和进一步挖潜的主导方向。     

基于NSGA-Ⅱ的土地利用数量结构优化研究——以舟山市定海区为例

土地利用的数量结构优化问题是个典型的多目标优化问题。文章通过引入带精英策略的非支配排序遗传算法(NSGA-Ⅱ),构建基于NSGA-Ⅱ的土地利用数量结构优化模型。在参考Kanpur遗传算法实验室提供的NSGA-Ⅱ源代码的基础上,利用C/C⁺⁺语言进行程序的二次开发,获得土地利用数量结构优化的一系列Pareto解,并组成Pareto解集。最后,通过权重来近似地表达决策意愿,通过计算综合效益,来实现各种决策意愿下的方案择优决策。研究结果表明该模型能较好地解决土地利用的数量结构优化问题。     

基于“多规合一”的市级国土空间优化方法——以烟台市为例

针对现阶段各规划边界交叉、空间重叠的问题,本文从提高空间价值、减少空间破碎度和协调各类空间的角度出发,在梳理现有空间优化模型及智能算法的基础上,改进多目标规划模型并适应性改造遗传算法,以此二者构建市级国土空间优化模型。以烟台市为例,设置3种情景为决策者提供方案集进行3类规划主导下的2020年国土空间优化研究,结果显示：①优化后烟台市农业、城镇和生态空间价值分别增加了23.24%、29.27%、6.30%;②不同情景下空间分布合理且较为集中,生态保护情景有利于国土空间集合连片,经济发展情景更适合于多空间协调发展。研究表明：该模型能有效地解决国土空间内容重叠问题,明显提高了国土空间价值,同时优化模型适应性强,为“多规合一”背景下市级国土空间优化提供技术支撑。     

基于生态-经济权衡的京津冀城市群土地利用优化配置

探索生态保护与经济发展的权衡关系,并利用该权衡关系协调土地利用优化配置是解决城市群经济与生态协调发展难题的重要途径,已成为目前的一个研究热点。论文针对京津冀城市群生态友好型协同发展的需求,设置生态系统服务价值最大化和经济价值最大化2种优化目标,每种目标下再设置“生态保护”“统筹兼顾”“粮食安全”和“经济发展”4种土地利用情景,采用CLUE-S模型模拟2025年京津冀城市群在不同情景下的土地利用空间配置格局,及其生态系统服务价值、经济价值在不同目标的各种情景下的变化。研究结果表明：相比2015年,2025年在不同目标不同情景下,各类土地利用面积的数量变化和空间格局均有较大不同,且生态目标和经济目标下不同情景的土地利用配置不同。生态系统服务价值在生态目标生态保护情景下最大,为14423.58亿元;而经济价值则在经济目标经济发展情景下最大,为96771.49亿元。从土地利用变化的空间分布上来看,生态用地中林地与草地的增加多出现在坝上高原和燕山与太行山山地,水体的增加则主要分布在东部沿海地区。研究认为,生态效益与经济效益间存在权衡关系,基于生态-经济权衡的土地利用优化研究结果对未来京津冀城市群生态实践工作有较大的参考价值。     

Spatial multi-objective land use optimization: extensions to the non-dominated sorting genetic algorithm-II

A spatial multi-objective land use optimization model defined by the acronym ‘NSGA-II-MOLU’ or the ‘non-dominated sorting genetic algorithm-II for multi-objective optimization of land use’ is proposed for searching for optimal land use scenarios which embrace multiple objectives and constraints extracted from the requirements of users, as well as providing support to the land use planning process. In this application, we took the MOLU model which was initially developed to integrate multiple objectives and coupled this with a revised version of the genetic algorithm NSGA-II which is based on specific crossover and mutation operators. The resulting NSGA-II-MOLU model is able to offer the possibility of efficiently searching over tens of thousands of solutions for trade-off sets which define non-dominated plans on the classical Pareto frontier. In this application, we chose the example of Tongzhou New Town, China, to demonstrate how the model could be employed to meet three conflicting objectives based on minimizing conversion costs, maximizing accessibility, and maximizing compatibilities between land uses. Our case study clearly shows the ability of the model to generate diversified land use planning scenarios which form the core of a land use planning support system. It also demonstrates the potential of the model to consider more complicated spatial objectives and variables with open-ended characteristics. The breakthroughs in spatial optimization that this model provides lead directly to other properties of the process in which further efficiencies in the process of optimization, more vivid visualizations, and more interactive planning support are possible. These form directions for future research.     

Optimal spatial land-use allocation for limited development ecological zones based on the geographic information system and a genetic ant colony algorithm

Limited development ecological zones (LDEZs) are often located in poverty-stricken, ecologically vulnerable areas where ethnic minorities reside. Studies on optimal spatial land-use allocation in LDEZs can promote economic and intensive land use, improve soil quality, facilitate local socioeconomic development, and maintain environmental stability. In this study, we optimized spatial land-use allocations in an LDEZ using the geographic information system (GIS) and a genetic ant colony algorithm (GACA). The multi-objective function considers economic benefits and ecological green equivalents, and improves soil erosion. We developed the GACA by integrating a genetic algorithm (GA) with an ant colony algorithm (ACA). This avoids a large number of redundant iterations and the low efficiency of the GA, and the slow convergence speed of the ACA. The study area is located in Pengyang County, Ningxia, China, which is a typical LDEZ. The land-use data were interpreted from remote sensing (RS) images and GIS. We determined the optimal spatial land-use allocations in the LDEZ using the GACA in the GIS environment. We compared the original and optimal spatial schemes in terms of economic benefits, ecological green equivalents, and soil erosion. The results of the GACA were superior to the original allocation, the ACA, and the multi-objective genetic algorithm, in terms of the optimum, time, and robust performance indexes. We also present some suggestions for the reasonable development and protection of LDEZs.     

中国资源型城市产业结构升级对土地利用效率的影响

在中国经济面临结构转型和空间重塑的关键时期,探究资源型城市产业结构升级对土地利用效率的影响机理,对于破解资源型城市产业发展路径依赖与土地低效利用困境具有重要意义。基于中国115座地级资源型城市面板数据,运用产业结构层次指数与基于DEA的超效率SBM-Undesirable模型刻画资源型城市产业结构升级与土地利用效率的时空演化特征,通过面板Tobit模型探究资源型城市产业结构升级对土地利用效率的异质性影响及作用渠道。结果表明：(1)中国资源型城市产业结构升级成效显著,再生型、煤炭型和钢铁型城市升级效果更为明显。土地利用效率呈波动上升趋势,高值城市数量显著增加,以经济基础较好的再生型和成长型城市为主。(2)资源型城市产业结构升级对土地利用效率提升尚未形成普遍的驱动效应,其影响机制在不同类型城市中具有显著的异质性,仅再生型城市呈现显著的正向影响。(3)资源型城市产业结构升级通过经济产出提升、要素配置优化与环境污染控制等渠道驱动土地利用效率的动态演化。现阶段,土地经济产出偏低、用地结构失调、环境污染负外部性过高是制约资源型城市土地利用效率提升的主要症结。资源型城市转型具有长期性、系统性特征,应...     

湘江新区土地利用结构多目标规划及决策偏好分析

土地利用规划需要综合考虑经济效益和生态效益。构建了经济最大化和生态效益最大化2个目标,并运用基于模糊集理论的最大(小)算子法求得兼顾经济效益和生态效益的土地利用模糊最优规划方案。随后重点探讨了不同决策偏好情景下的土地利用优化方案和综合效益的变化。研究结果表明:(1)对经济效益和生态效益的偏好程度不同,主要会导致林地、城镇建设用地和水域面积发生变化;(2)随着决策者对生态效益偏好程度的增加,城镇建设用地面积逐渐减少,林地和水域面积逐渐增加;(3)当经济效益比生态效益重要时,最优的用地规划方案主要是在城镇用地和水域面积之间进行权衡;当生态效益比经济效益重要时,最优的用地规划方案主要是在林地和城镇建设用地之间进行权衡。研究结果对湘江新区进行"资源节约型和环境友好型社会"建设中的多目标土地利用规划具有一定的决策参考价值。     

Urban land development intensity: New evidence behind economic transition in the Yangtze River Delta,China

Over the past 20 years, China has experienced multiple economic transitions characterized by marketization, globalization, decentralization, and urbanization; as a result, urban land development intensity (ULDI) has become a significant issue for sustainable development. As China’s largest globalized urban area, the rapid socio-economic development of the Yangtze River Delta has created a huge demand for urban land. We apply a theoretical framework for a four-dimensional analysis tool to understand the dynamic evolution of the ULDI in the context of economic transition. It reveals that marketization, globalization, decentralization, and urbanization affect the ULDI in the economic transition of Yangtze River Delta. Marketization, especially the continuous improvement of land marketization, optimizes the spatial allocation of land resources and encourages urban land users to improve ULDI. Globalization promotes the rapid growth of economy and population through an increase in foreign direct investment. In the process of decentralization, local governments rely on developing a mode of land finance, resulting in a disordered urban space and low ULDI. Population growth and agglomeration during urbanization stimulates residents’ consumption capacity and promotes economic growth, thus creating a greater demand for urban land. However, a low level of development and utilization restricts the improvement of development intensity. Economic development can improve the level of land-intensive use by promoting the adjustment, optimization, and upgrade of urban industrial structures.     

转型期省际城镇土地利用绩效格局演变与机理

以中国省域单元为例,在界定城镇土地利用绩效内涵基础之上,从结构、效益、效率及管理四维度构建城镇土地利用绩效评价体系,利用改进熵值法测度省际城镇土地利用绩效;并运用空间统计模型、R/S分析法及PCA模型,对2000-2012年中国省际城镇土地利用绩效格局时空演变及机理进行了初步的探讨。研究表明：① 2000年以来省际城镇土地利用绩效水平不断提升,区域差异较显著;绩效演变呈现出东西方向递增,南北方向倒“U”型分布格局。② 省际城镇土地利用绩效全局空间上表现出显著的正自相关,呈现绩效高(低)—高(低)集聚模式;局部Ⅰ绩效热点区主要集聚在东部沿海的京津及江浙沪,且不断向珠三角演化,Ⅱ绩效次热区主要集中在中原城市群、华北、华中及华南地区,Ⅲ绩效次冷区主要分布在西南地区及东北地区,而Ⅳ绩效冷点区主要集中在西部的藏疆蒙甘青地区,形成稳定“L”型塌陷形态;省际城镇土地利用绩效具有明显的分形特征,未来绩效值将呈现出继续增长的演化态势,且增长显著区分布在京津及长三角地区。③ 城镇化、产业升级、科技发展及市场化综合驱动转型期省际城镇土地利用绩效格局演变。     

Optimal spatial allocation of water resources based on Pareto ant colony algorithm

The spatial allocation of water resources is optimised using the multi-objective functions and multi-constrained conditions of the Pareto ant colony algorithm (PACA). The objective function is the highest benefit to the economy, society and the environment, while the constraints include water supply, demand and quality. The PACA is improved by limiting local pheromone scope and dynamically updating global pheromone levels. Since both strategies guide the ant towards borders of high-pheromone concentration, the new approach enhances the global search capability and convergence speed. Programming, database management and interface tools are then integrated into geographic information systems (GIS) software. The study area is located in Zhenping County, Henan Province, China, and water resource data are obtained using remote sensing (RS) and GIS technology. The improved PACA is solved in the GIS environment. Optimal spatial allocation schemes are obtained for surface, ground and transferred water and the model yields optimal spatial benefit schemes of water resources, embracing economic, social and ecological benefits. The results of improved PACA are superior to those of other intelligent optimisation algorithms, including the ant colony algorithm, multi-objective genetic algorithm and back-propagation artificial neural network. Therefore, the integration of RS, GIS and PACA can effectively optimise the large-scale, multi-objective allocation of water resources. The model also enhances the global search capability, convergence speed and result precision, and can potentially solve other optimal spatial problems with multi-objective functions.     

土地利用冲突的时空格局刻画与多情景模拟研究——以长江三角洲城市群为例

科学刻画与模拟土地利用冲突的时空演化格局是精准认知区域土地利用结构进而寻求人地关系协调的基础。采用景观格局指数构建土地利用冲突模型,借助GIS等手段分析长江三角洲城市群1980—2020年间土地利用冲突的时空演化特征,并结合斑块生成土地利用变化模拟模型和多目标规划法多情景模拟2035年的土地利用冲突格局。结果表明：①长江三角洲城市群土地利用冲突受地形等因素影响呈现“北高南低”的分布格局,且在高速城镇化和城市无序蔓延等因素作用下,人地关系趋于不协调发展,土地利用冲突程度逐年加剧。②受人口迁徙和城镇化发展阶段的影响,土地利用冲突的热点区域由乡村空间转移至了城市空间。③在土地利用过程中,耕地是各利益主体争夺的核心区域,也是权衡土地利用冲突的“关键地带”。④可持续发展情景兼顾了经济发展与生态保护两方面的用地需求,是缓和土地利用冲突的一种合理选择。     

Urban expansion in Auckland,New Zealand: a GIS simulation via an intelligent self-adapting multiscale agent-based model

ABSTRACT

Abstract: When modelling urban expansion dynamics, cellular automata models focus mostly on the physical environments and cell neighbours, but ignore the ‘human’ aspect of the allocation of urban expansion cells. This limitation is overcome here using an intelligent self-adapting multiscale agent-based model. To simulate the urban expansion of Auckland, New Zealand, a total of 15 urban expansion drivers/constraints were considered over two periods (2000–2005, 2005–2010). The modelling takes into consideration both a macro-scale agent (government) and micro-scale agents (residents of three income levels), and their multi-level interactions. In order to achieve reliable simulation results, ABM was coupled with an artificial neural network to reveal the learning process and heterogeneity of the multi-sub-residential agents. The ANN-ABM accurately simulated the urban expansion of Auckland at both the global and local scales, with kappa simulation value at 0.48 and 0.55, respectively. The validated simulation result shows that the intelligent and self-adapting ANN-ABM approach is more accurate than an ABM with a general type of agent model (kappa simulation = 0.42) at the global scale, and more accurate than an ANN-based CA model (kappa simulation = 0.47) at the local scale. Simulation inaccuracy stems mostly from the outdated master land use plan.     

CLUE-S模型的改进在亚热带城市边缘区的应用——以福州市仓山区为例

由于土地利用矛盾突出和地理位置独特,城市边缘区是中国目前土地利用变化最为剧烈的地域单元,是土地利用变化研究关注的热点区域,在土地资源的可持续利用、规划的科学制定上也具有重要意义．本研究以中国典型的亚热带城市边缘区——福州市仓山区为研究对象,引入Tietenberg资源分配模型改进目前国际上广泛应用的CLUE-S土地利用动态模拟模型的非空间需求模块,在研究区土地利用变化驱动机制分析的基础上,选择合适参数回溯了研究区2004年的土地利用现状、模拟了2020年的土地利用时空变化格局,拟合精度良好（Kappa指数为0．72）．研究结果表明：以Tietenberg资源配置模型作为CLUE—S模型的非空间需求计算方法在一定意义上是合理的,同时,模拟结果也进一步证明了城市边缘区以非农建设用地占用耕地为主的用地矛盾．在此基础上,对该区域发展合理的用地空间布局提出了针对性的建议,该方法和成果可以作为城市边缘区制定土地利用规划和发展管理政策的参考依据．     

Book Review

In this paper, we examine the applicability of spatial optimization as a generative modelling technique for sustainable land‐use allocation. Specifically, we test whether spatial optimization can be used to generate a number of compromise spatial alternatives that are both feasible and different from each other. We present a new spatial multiobjective optimization model, which encourages efficient utilization of urban space through infill development, compatibility of adjacent land uses, and defensible redevelopment. The model uses a density‐based design constraint developed by the authors. The constraint imposes a predefined level of consistent neighbourhood development to promote contiguity and compactness of urban areas. First, the model is tested on a hypothetical example. Further, we demonstrate a real‐world application of the model to land‐use planning in Chelan, a small environmental amenity town in the north‐central region of the State of Washington, USA. The results indicate that spatial optimization is a promising method for generating land‐use alternatives for further consideration in spatial decision‐making.     

1996~2011年安徽省产业结构演进对城镇土地集约利用影响测度与分析

采用主成分分析综合评价方法,对1996~2011年安徽省城镇土地集约状况进行了综合评价;运用Perloff的产业结构测度模型,对安徽省产业结构的构成效应（MIX）、竞争效应（DIF）进行了测算;借鉴STIRPAT模型,采用偏最小二乘回归分析方法,从产业结构的结构效应、竞争效应考察了其对城镇土地集约利用影响,结果表明：① 1996~2011年,安徽省城镇土地利用综合指数呈递增态势,1996~2006年,城镇土地利用指数均值为53.09,2007~2011年,均值为75.2;② 1996~2011年,安徽省产业结构构成效应指数均值为0.012 4,其变化轨迹呈“N”型,而竞争效应指数整体呈上升态势,均值为0.012 8;③ 1996~2011年,安徽省产业结构构成效应、竞争效应对城镇土地集约利用弹性系数分别为-0.002 5和0.004 9。     

基于POI的土地利用与轨道交通客流的空间特征

城市轨道交通及其沿线土地一体化发展是城市可持续发展的关键问题。提高城市轨道交通可持续性和土地资源配置合理性的关键需掌握轨道交通客流与土地功能之间的依赖关系,而回归分析是研究二者关系的主要方法。既有研究对于土地利用的描述多基于用地面积等概略数据,难以揭示各类属性的用地对客流的影响机理及其空间效应。采用百度地图POI数据以刻画用地信息,提出城市轨道交通车站吸引范围内用地功能的细粒度描述方法,基于全局常参数和局部变参数的回归模型研究车站早高峰出站客流与粗细粒度土地利用的相互依赖关系及其空间效应。针对北京地铁的案例研究表明：车站出站客流与不同功能用地及POI的依赖程度和空间特征存在显著差异。早高峰出站客流更多地受到与就业通勤相关的商业服务业设施用地、公共管理与公共服务用地的影响。在细粒度层面上,出站客流对写字楼和政府机构的依赖性更大,二者显著分布在就业岗位密集的中心城区功能分区和城市核心区。基于细粒度POI的局部变参数模型能较好地识别各类土地利用对车站客流的影响及其空间异质性,案例研究表明车站客流与土地利用的依赖关系是各类属性功能用地影响及其空间效应的叠加。     

The Decoupling Relationship between the Expansion of Urban Construction Land and Economic Growth in Jilin Province

In order to explore the relationship between urban construction land and economic development, this paper uses a decoupling model to analyze the decoupling relationship between expansion of urban construction land and economic growth in Jilin Province. The results show that from 2000 to 2015, the decoupling of urban construction land expansion and economic growth in Jilin province tended to be reasonable. The paper divides urban decoupling into three categories. The first type consists of ideal cities, including Liaoyuan and Baishan. The second type includes basic ideal cities like Changchun, Tonghua, Songyuan, Baicheng, and Yanbian. The third type consists of non-ideal cities, including Jilin and Siping. This paper puts forward relevant measures to promote the further decoupling of construction land expansion and economic growth in order to realize the sustainable use of land resources.     

会宁县城镇土地分等定级的研究

文章运用定量和定性相结合的方法,对影响会宁县城镇土地质量的经济、社会、自然等各项因素进行综合分析,评定城镇等级,揭示城镇之间以及城镇内部的地域差异.根据会宁县城镇土地的自然、社会、经济属性,结合城镇土地分等规程,运用特尔菲法确定研究区域的因素因子及其权重,收集分等定级所需资料,计算了分等定级因素的综合分值,土地等级进行初步划分,最终取得会宁县城镇土地分等定级的成果,把会宁县的城镇土地分为4等,并确定会宁县城区的土地级别,可进一步摸清各镇区的基本情况,掌握各城镇之间的差异原因.