Spatial optimization for regionalization problems with spatial interaction: a heuristic approach

Spatial optimization techniques are commonly used for regionalization problems, often represented as p-regions problems. Although various spatial optimization approaches have been proposed for finding exact solutions to p-regions problems, these approaches are not practical when applied to large-size problems. Alternatively, various heuristics provide effective ways to find near-optimal solutions for p-regions problem. However, most heuristic approaches are specifically designed for particular geographic settings. This paper proposes a new heuristic approach named Automated Zoning Procedure-Center Interchange (AZP-CI) to solve the p-functional regions problem (PFRP), which constructs regions by combining small areas that share common characteristics with predefined functional centers and have tight connections among themselves through spatial interaction. The AZP-CI consists of two subprocesses. First, the dissolving/splitting process enhances diversification and thereby produces an extensive exploration of the solution space. Second, the standard AZP locally improves the objective value. The AZP-CI was tested using randomly simulated datasets and two empirical datasets with different sizes. These evaluations indicate that AZP-CI outperforms two established heuristic algorithms: the AZP and simulated annealing, in terms of both solution quality and consistency of producing reliable solutions regardless of initial conditions. It is also noted that AZP-CI, as a general heuristic method, can be easily extended to other regionalization problems. Furthermore, the AZP-CI could be a more scalable algorithm to solve computational intensive spatial optimization problems when it is combined with cyberinfrastructure.     

Multi-objective spatially constrained clustering for regionalization with particle swarm optimization

Regionalization is an important part of the spatial analysis process, and the solution should be contiguity-constrained in each region. In general, several objectives need to be optimized in practical regionalization, such as the homogeneity of regions and the heterogeneity among regions. Therefore, multi-objective techniques are more suitable for solving regionalization problems. In this paper, we design a multi-objective particle swarm optimization algorithm for solving regionalization problems. Towards this goal, a novel particle representation for regionalization is proposed, which can be expressed in continuous space and has flexible constraints on the number of regions. In the process of optimization, a contiguous-region method is designed that satisfies the constraints and improves the efficiency. The decision solution is selected in the Pareto set based on a trade-off between the objective functions, and the number of regions can be automatically determined. The proposed method outperforms six regionalization algorithms in terms of both the number and the quality of the solutions.     

Anchor uncertainty and space-time prisms on road networks

Space-time prisms capture all possible locations of a moving person or object between two known locations and times given the maximum travel velocities in the environment. These known locations or ‘anchor points’ can represent observed locations or mandatory locations because of scheduling constraints. The classic space-time prism as well as more recent analytical and computational versions in planar space and networks assume that these anchor points are perfectly known or fixed. In reality, observations of anchor points can have error, or the scheduling constraints may have some degree of pliability. This article generalizes the concept of anchor points to anchor regions: these are bounded, possibly disconnected, subsets of space-time containing all possible locations for the anchor points, with each location labelled with an anchor probability. We develop two algorithms for calculating network-based space-time prisms based on these probabilistic anchor regions. The first algorithm calculates the envelope of all space-time prisms having an anchor point within a particular anchor region. The second algorithm calculates, for any space-time point, the probability that a space-time prism with given anchor regions contains that particular point. Both algorithms are implemented in Mathematica to visualize travel possibilities in case the anchor points of a space-time prism are uncertain. We also discuss the complexity of the procedures, their use in analysing uncertainty or flexibility in network-based prisms and future research directions.     

中国地貌区划理论与分区体系研究

区划和类型是地貌学研究的两大核心内容。中国地貌区划已有诸多划分方案,比较而言,各种方案存在遴选指标不一、确定等级较少、反映特征各异、划分结果不同、成图尺度较小等不足。应中国地理国情普查等国家专项任务的需求,对较大尺度、多级地貌区划研究提出了新的要求。在梳理中国地貌区划的理论,包括板块构造与地貌圈特征、地貌形态与内外营力体系、地貌形态的类型组合与区域分异的基础上,基于2013年提出的中国地貌二级区划的新方案,归纳了全国多级地貌区划分的原则,提出了基于“大区—地区—区—亚区—小区”的全国五级地貌等级分区方案,建立了“大地构造控制下的地势阶梯特征—>区域宏观形态类型组合—>内外营力及基本形态类型组合—>区域内形态类型组合—>区域微地貌形态组合”的五级地貌分区指标体系,提出了五级地貌区划体系的命名规则和编码方式,构建了基于多源数据进行多级地貌区划单元精确定位的技术与方法,完成了全国1:25万尺度五级地貌区的划分,包括6个一级大区、36个二级地区、136个三级区、331个四级亚区、1500多个五级小区,并建立了全国地貌区划数据库。该研究对于促进中国区域地貌学的发展、基于地貌区划的应用研究等具有重要的指导意义。     

Regionalization with dynamically constrained agglomerative clustering and partitioning (REDCAP)

Regionalization is to divide a large set of spatial objects into a number of spatially contiguous regions while optimizing an objective function, which is normally a homogeneity (or heterogeneity) measure of the derived regions. This research proposes and evaluates a family of six hierarchical regionalization methods. The six methods are based on three agglomerative clustering approaches, including the single linkage, average linkage (ALK), and the complete linkage (CLK), each of which is constrained with spatial contiguity in two different ways (i.e. the first‐order constraining and the full‐order constraining). It is discovered that both the Full‐Order‐CLK and the Full‐Order‐ALK methods significantly outperform existing methods across four quality evaluations: the total heterogeneity, region size balance, internal variation, and the preservation of data distribution. Moreover, the proposed algorithms are efficient and can find the solution in O(n ²log n) time. With such data scalability, for the first time it is possible to effectively regionalize large data sets that have 10 000 or more spatial objects. A detailed comparison and evaluation of the six methods are carried out with the 2004 US presidential election data.     

宁夏农业综合开发战略转型区划研究

农业综合开发战略转型区划研究,是科学适应新形势下国家对农业综合开发提出的“坚持可持续、提升竞争力”要求的前提和基础。针对已有农业区划的单一目标和单一类型划分问题,以宁夏为例,基于农业相关的耕地、气候、水、地形、地貌、项目布局、生态规划等空间数据,采用地理学综合区划的方法,提出了动态与静态结合、定性与定量结合、农业与生态结合的13项多维指标体系,提出了合理且可操作的技术流程,科学划分了包含过渡类型的一级区划（7大类型：重点开发区、“重点+限制”开发区、保护性开发区、“保护+限制”开发区、“限制+重点”开发区、“限制+保护”开发区和限制性开发区）和二级区划（24个亚类）,实现了农业可持续和生态环境保护的双重目标。本文是国家财政部明确提出农业综合开发要科学划分重点开发区、保护性开发区和限制性开发区之后,首次实现在省（区）级以乡（镇）为单位的科学划分,可为今后农业综合开发战略转型项目的科学布局和精准投入提供重要依据,为宁夏农业综合开发战略转型工作的具体落地实施提供科学保障,同时也可为其他省份或地区的农业综合开发战略转型区划工作提供有益参考。     

Parallelization of a regionalization heuristic in distributed computing platforms – a case study of parallel-p-compact-regions problem

In this paper, we report efforts to develop a parallel implementation of the p-compact regionalization problem suitable for multi-core desktop and high-performance computing environments. Regionalization for data aggregation is a key component of many spatial analytical workflows that are known to be NP-Hard. We utilize a low communication cost parallel implementation technique that provides a benchmark for more complex implementations of this algorithm. Both the initialization phase, utilizing a Memory-based Randomized Greedy and Edge Reassignment (MERGE) algorithm, and the local search phase, utilizing Simulated Annealing, are distributed over available compute cores. Our results suggest that the proposed parallelization strategy is capable of solving the compactness-driven regionalization problem both efficiently and effectively. We expect this work to advance CyberGIS research by extending its application areas into the regionalization world and to make a contribution to the spatial analysis community by proposing this parallelization strategy to solve large regionalization problems efficiently.     

土壤区划类型的参比与属地化研究

文章以详细的1981年土壤分区资料为基础,将以发生分类(GSCC)为基础的土壤类型名称分别参比成中国土壤系统分类(CST)名称和美国土壤系统分类(ST)名称。同时利用G IS空间分析技术,确定了中国8个土壤大区在地级市(盟)和各县、区、旗(市)的行政归属,并以江南低山丘陵和台湾北部地区为例,探讨了二级分区的行政归属。     

Strategic transformation of regionalization for the agricultural comprehensive development: The example of Ningxia Hui Autonomous Region in China

Strategic transformation of regionalization for agricultural comprehensive development (ACD) was presented by the Ministry of Finance of the People’s Republic of China (MOF) in 2014. The regionalization is the premise and basis of the sustainable development and improved competitiveness for agriculture. Based on the environmental resources related to agriculture, such as cropland, climate, water resources, terrain, geomorphology, patterns of the ACD projects, distribution of ecological planning, etc., we devised 13 indices using the geographic comprehensive regionalization method. The indices took into account a combination of dynamic and static, qualitative and quantitative, as well as agricultural and ecological factors. The strategic transformation of regionalization for the ACD in Ningxia Hui Autonomous Region of China was performed; seven types were included: prioritized regions, prioritized and restricted regions, protected regions, protected and restricted regions, restricted and prioritized regions, restricted and protected regions, and restricted regions. A further 24 subtypes were used based on locations and ecological zones. The regionalization results showed that prioritized regions were mainly in northern Ningxia, the most suitable area for agriculture. The protected and restricted regions were in central and southern Ningxia. In the central part, drought was the limiting factor for agriculture, and water conservation projects there should be supported. The ecological environment is fragile in southern Ningxia, so there is a need for ecologically sound agriculture to be developed in this region. Such regionalization could achieve two goals, namely agricultural conservation and eco-environmental protection. It was performed following the requirement for scientific regionalization to include three types of regions (prioritized regions, protected regions, and restricted regions), and was applied at the township scale in a provincial or autonomous region for the first time. The results provide both guidance for the strategic transformation of the ACD in Ningxia, and a reference for similar work in other provinces.     

非洲国旗文化的地域特征与演变机制

传统的专题文化区研究是以文字描述为主的定性区划模式。由于其在精确度及可信度上的不足,迫切需要探求以定性描述与定量分析相结合的区划模式。本文以非洲国旗文化为例,运用GIS和统计分析方法。试图探求这种模式。研究结果表明：存在定性与定量综合模式且具有较强可行性;非洲国旗文化受地势地貌、气候条件、海陆位置、宗教信仰、殖民、种族构成、历史文化个性、岛国文化等因素的影响;依据非洲各国国旗嬗变的机理、调整次数、变更形式,非洲国旗文化可得出五种演变模式。最终从功能文化区的角度将非洲国旗文化划分为四个大区、六个亚区。     

A data-synthesis-driven method for detecting and extracting vague cognitive regions

Cognitive regions and places are notoriously difficult to represent in geographic information science and systems. The exact delineation of cognitive regions is challenging insofar as borders are vague, membership within the regions varies non-monotonically, and raters cannot be assumed to assess membership consistently and homogeneously. In a study published in this journal in 2014, researchers devised a novel grid-based task in which participants rated the membership of individual cells in a given region and contrasted this approach to a standard boundary-drawing task. Specifically, the authors assessed the vague cognitive regions of Northern California and Southern California. The boundary between these cognitive regions was found to have variable width, and region membership peaked not at the most northern or southern cells but at substantially less extreme latitudes. The authors thus concluded that region membership is about attitude, not just latitude. In the present work, we reproduce this study by approaching it from a computational fourth-paradigm perspective, i.e., by the synthesis of high volumes of heterogeneous data from various sources. We compare the regions which we identify to those from the human-participants study of 2014, identifying differences and commonalities. Our results show a significant positive correlation to those in the original study. Beyond the extracted regions themselves, we compare and contrast the empirical and analytical approaches of these two methods, one a conventional human-participants study and the other an application of increasingly popular data-synthesis-driven research methods in GIScience.     

THE IDENTIFICATION OF REGIONAL BOUNDARIES ON COGNITIVE MAPS*

This study investigates regions on cognitive maps and methods used to identify their boundaries. Subjects either drew regional boundaries on a map or decided in which region sample points were located. These methods produced similar results with differences associated more with regional boundaries than cores. The amount of time needed to make point decisions demonstrated the subjects' cognitive process and corroborated boundaries and cores for the cognitive regions. Differences among subjects' maps were greater when boundaries were drawn.     

宁夏农业综合开发战略转型区划研究（英文）

Strategic transformation of regionalization for agricultural comprehensive development(ACD) was presented by the Ministry of Finance of the People's Republic of China(MOF) in 2014. The regionalization is the premise and basis of the sustainable development and improved competitiveness for agriculture. Based on the environmental resources related to agriculture, such as cropland, climate, water resources, terrain, geomorphology, patterns of the ACD projects, distribution of ecological planning, etc., we devised 13 indices using the geographic comprehensive regionalization method. The indices took into account a combination of dynamic and static, qualitative and quantitative, as well as agricultural and ecological factors. The strategic transformation of regionalization for the ACD in Ningxia Hui Autonomous Region of China was performed; seven types were included: prioritized regions, prioritized and restricted regions, protected regions, protected and restricted regions, restricted and prioritized regions, restricted and protected regions, and restricted regions. A further 24 subtypes were used based on locations and ecological zones. The regionalization results showed that prioritized regions were mainly in northern Ningxia, the most suitable area for agriculture. The protected and restricted regions were in central and southern Ningxia. In the central part, drought was the limiting factor for agriculture, and water conservation projects there should be supported. The ecological environment is fragile in southern Ningxia, so there is a need for ecologically sound agriculture to be developed in this region. Such regionaliza-tion could achieve two goals, namely agricultural conservation and eco-environmental protection. It was performed following the requirement for scientific regionalization to include three types of regions(prioritized regions, protected regions, and restricted regions), and was applied at the township scale in a provincial or autonomous region for the first time. The results provide both guidance for the strategic transformation of the ACD in Ningxia, and a reference for similar work in other provinces.     

基于GIS的黄河三角洲盐碱地改良分区

黄河三角洲盐碱地面积超过总面积的70％，而盐碱地改良分区是因地制宜，综合治理盐域地的前提，通过综合运用地理信息系统的各种空间数据分析功能，将黄河三角洲土地盐碱化现状分为：非盐碱地，轻度盐碱地，中度盐碱地，重度盐碱地，滩涂5个区，并结合地下水长期观测资料，进行成因分析，建立了黄河三角洲盐碱地改良分区模型，立足土地盐碱化的现状，充分考虑地下水埋深和矿化度，把黄河三角洲盐碱地按改良难易程度分为：易改良区，较难改良区，难改良区，近期不宜作改良区，并针对不同的盐碱地改良区提出了相应的土壤改良对策。     

U.S. Religious Regions Revisited

Religion continues to play an important role in the public and private lives of Americans. Therefore, a reexamination of U.S. religious regions is necessary in light of the rapid demographic changes that have occurred in the past few decades. This article presents a new regionalization of religion in the United States for 1980 and 2000, produced using multivariate cluster analysis. Comparing this new regionalization with earlier attempts, it demonstrates that religious regions continue to exist today and have undergone various levels of stability and change. Furthermore, religious regions continue to be relevant because they provide scholars with a method for identifying and characterizing the societal context in which individual religious communities function.     

盐城开发空间区划及其思考

在国家“十一五”规划纲要中, 将国土空间划分为优化开发、重点开发、限制开发和禁止开发四类主体功能区, 这是新时期传统区划理论和方法为国民经济和社会发展服务的一次重要创新。作者认为: 主体功能区划主要在于解决区域问题, 用科学发展观协调区域发展。 因此, 功能区区划的理论和方法也需要与时俱进的创新。文章通过盐城沿海开发空间区划实例进行功能区区划的理论和方法探索。首先, 综合经济区划。运用传统的综合经济区划理论与方法进行经济区划分, 大致确定不同经济区的经济发展布局方向; 其次, 控制开发区划。 综合考虑上述综合经济区的功能, 景观生态体系建设需要, 土地利用现状、辐射沙洲分布、近海海域污染、海港分布、水源保护地以及自然保护区和生态保护区等, 确定相关的禁止开 发区和限制开发区; 第三, 开发潜力区划。以乡镇为基本单元, 运用多因子分析方法, 按照资源环境承载力、现有开发密度强度、未来发展潜力3 个主因子进行开发潜力区划; 最后, 在上述三个区划的基础上, 进行主体功能区划。文章也认为: 主体功能区实质是一种区域发展政策区, 其区划也只是一种纯粹的区域划分, 是目前经济社会发展规划、土地利用规划和城市总体规划“三规”分立走向“三规”合一的空间平台。     

基于格网的甘肃省生态经济分区研究

在讨论以往生态经济分区研究方法与理论的基础上,提出了新的研究思路--基于网格的生态经济分区。利用GIS格网技术和相关统计软件,从甘肃省生态与经济两大系统耦合发展的历程分析入手,选取2010年甘肃省的26个生态经济指标,以6 km×6 km的规则格网,将整个甘肃省分为12 243个研究单元。经过分析比较,甘肃省被分为4个生态经济区即西北干旱区(Ⅰ)、陇中冷温带半湿润区(Ⅱ)、甘南高寒带湿润区(Ⅲ)、陇南暖温带湿润区(Ⅳ)和21个生态经济亚区。结合DEM,进一步对研究区进行分区,以期为促进形成甘肃省可持续发展格局提供科学依据。研究表明,格网技术提高了分区的精度和速度,是进行生态经济分区的有效方式之一。     

A new algorithm based on Region Partitioning for Filtering candidate viewpoints of a multiple viewshed

Selecting the set of candidate viewpoints (CVs) is one of the most important procedures in multiple viewshed analysis. However, the quantity of CVs remains excessive even when only terrain feature points are selected. Here we propose the Region Partitioning for Filtering (RPF) algorithm, which uses a region partitioning method to filter CVs of a multiple viewshed. The region partitioning method is used to decompose an entire area into several regions. The quality of CVs can be evaluated by summarizing the viewshed area of each CV in each region. First, the RPF algorithm apportions each CV to a region wherein the CV has a larger viewshed than that in other regions. Then, CVs with relatively small viewshed areas are removed from their original regions or reassigned to another region in each iterative step. In this way, a set of high-quality CVs can be preserved, and the size of the preserved CVs can be controlled by the RPF algorithm. To evaluate the computational efficiency of the RPF algorithm, its performance was compared with simple random (SR), simulated annealing (SA), and ant colony optimization (ACO) algorithms. Experimental results indicate that the RPF algorithm provides more than a 20% improvement over the SR algorithm, and that, on average, the computation time of the RPF algorithm is 63% that of the ACO algorithm.