Modeling the scale dependences of topological relations between lines and regions induced by reduction of attributes

The scale dependences of topological relations are caused by the changes of spatial objects at different scales, which are induced by the reduction of attributes. Generally, the detailed partitions and multi-scale attributes are stored in spatial databases, while the coarse partitions are not. Consequently, the detailed topological relations can be computed and regarded as known information, while the coarse relations stay unknown. However, many applications (e.g., multi-scale spatial data query) need to deal with the topological relations at multiple scales. In this study new methods are proposed to model and derive the scale dependences of topological relations between lines and multi-scale region partitions. The scale dependences of topological relations are modeled and used to derive the relations between lines and coarse partitions from the relations about the detailed partitions. The derivation can be performed in two steps. At the first step, the topological dependences between a line and two meeting, covered and contained regions are computed and stored into composition tables, respectively. At the second step, a graph is used to represent the neighboring relations among the regions in a detailed partition. The scale dependences and detailed relations are then used to derive topological relations at the coarse level. Our methods can also be extended to handle the scale dependences of relations about disconnected regions, or the combinations of connected and disconnected regions. Because our methods use the scale dependences to derive relations at the coarse level, rather than generating coarse partition and computing the relations with geometric information, they are more efficient to support scale-dependent applications.     

An inconsistency measure of spatial data sets with respect to topological constraints

An inconsistency measure can be used to compare the quality of different data sets and to quantify the cost of data cleaning. In traditional relational databases, inconsistency is defined in terms of constraints that use comparison operators between attributes. Inconsistency measures for traditional databases cannot be applied to spatial data sets because spatial objects are complex and the constraints are typically defined using spatial relations. This paper proposes an inconsistency measure to evaluate how dirty a spatial data set is with respect to a set of integrity constraints that define the topological relations that should hold between objects in the data set. The paper starts by reviewing different approaches to quantify the degree of inconsistency and showing that they are not suitable for the problem. Then, the inconsistency measure of a data set is defined in terms of the degree in which each spatial object in the data set violates topological constraints, and the possible representations of spatial objects are points, curves, and surfaces. Finally, an experimental evaluation demonstrates the applicability of the proposed inconsistency measure and compares it with previously existing approaches.     

Object-based spatial cluster analysis of urban landscape pattern using nighttime light satellite images: a case study of China

Previous studies have demonstrated urban built-up areas can be derived from nighttime light satellite (DMSP-OLS) images at the national or continent scale. This paper presents a novel object-based method for detecting and characterizing urban spatial clusters from nighttime light satellite images automatically. First, urban built-up areas, derived from the regionally adaptive thresholding of DMSP-OLS nighttime light data, are represented as discrete urban objects. These urban objects are treated as basic spatial units and quantified in terms of geometric and shape attributes and their spatial relationships. Next, a spatial cluster analysis is applied to these basic urban objects to form a higher level of spatial units – urban spatial clusters. The Minimum Spanning Tree (MST) is used to represent spatial proximity relationships among urban objects. An algorithm based on competing propagation of objects is proposed to construct the MST of urban objects. Unlike previous studies, the distance between urban objects (i.e., the boundaries of urban built-up areas) is adopted to quantify the edge weight in MST. A Gestalt Theory-based method is employed to partition the MST of urban objects into urban spatial clusters. The derived urban spatial clusters are geographically delineated through mathematical morphology operation and construction of minimum convex hull. A series of landscape ecologic and statistical attributes are defined and calculated to characterize these clusters. Our method has been successfully applied to the analysis of urban landscape of China at the national level, and a series of urban clusters have been delimited and quantified.     

Quantitative measures for spatial information of maps

The map is a medium for recording geographical information. The information contents of a map are of interest to spatial information scientists. In this paper, existing quantitative measures for map information are evaluated. It is pointed out that these are only measures for statistical information and some sort of topological information. However, these measures have not taken into consideration the spaces occupied by map symbols and the spatial distribution of these symbols. As a result, a set of new quantitative measures is proposed, for metric information, topological information and thematic information. An experimental evaluation is also conducted. Results show that the metric information is more meaningful than statistical information, and the new index for topological information is more meaningful than the existing one. It is also found that the new measure for thematic information is useful in practice.     

基于居住环境的常州城市居民生活质量空间结构

第六次全国人口普查数据面世以后,基于因子生态分析的中国城市社会空间结构研究虽取得较多成果,但方法创新还有待推进。本文以常州作为实证研究地区,将人口普查数据与大数据（城市POI数据）相结合,借助网格化处理和公共服务设施可达性计算方法,从居住内部环境（住房条件）和居住外部环境（设施可达性）两方面综合衡量城市居民生活质量,进而探讨城市居民生活质量空间结构及其与居民社会经济属性之间的关系。结果表明,常州城市居民生活质量空间结构呈现出较为明显的圈层结构与扇形结构叠加的模式,城市生活质量空间结构与居民社会经济属性在空间上存在一定的耦合关系,即不同类型居民属性区的生活质量存在较为明显的差异,各类居民属性区均有与之重叠度较高的相对应的生活质量区,这种空间关系的揭示对城市规划和管理具有一定的借鉴意义,同时也从居民社会空间与实体空间互动关系的角度对社会—空间辩证法进行了诠释。     

近20年珠三角城市群城市空间相互作用时空演变

利用改进的引力模型和潜力模型,结合GIS空间分析方法,从地级市和县域两个空间尺度分析了近20 a珠三角地区城市间相互作用的时空演变。结果表明:珠三角地级城市空间联系总体逐步加强,并充分体现出广州的中心城市地位;县域尺度上,空间联系强度较大的主要是各地市市区之间及广-佛都市区的县市间和各地市市区与其所辖县市之间,其它县市间联系强度则较小;珠三角核心区内大部分县市之间联系总体呈逐渐增强趋势,核心区外的县市之间及其与核心区内的县市间联系强度有升有降,规律性不明显。广-佛都市区和深圳-东莞-惠州都市区的城市潜力较大且变动较大,对外辐射带动作用强,其它城市潜力相对较小且变化不明显;珠三角城市潜力的区域不平衡态势明显,城市潜力的空间分异和空间辐射的特征与演变规律明显。     

甘肃省畜牧产业集聚的空间格局研究

运用引力模型及其拓展测度指标,对甘肃省所辖14个市（州）畜牧业综合质量、区域间引力值和断裂点距离值进行测算,分析畜牧产业集聚的空间格局,集聚中心形成机理及其辐射范围。结果表明：甘肃省畜牧业区域发展不平衡,整体呈现出"西高东低"的梯度特征,并可划分为5级梯度。畜牧产业发展的空间集聚特征明显,已形成以白银市和甘南州为二级集聚中心的"双核心"空间结构：以白银为中心,辐射带动兰州、定西两个三级集聚中心构成了甘肃中部畜牧产业集聚区;以甘南为中心,连同三级集聚中心临夏带动陇南、辐射天水成为甘肃南部产业集聚区。以武威为三级集聚中心,辐射张掖、金昌等市形成河西走廊产业集聚区;以庆阳为中心,联动平凉市的陇东产业集聚热点区初步显现。本研究对分析产业空间结构特征和制定推动产业集聚策略具有重要意义。     

长江中游城市群城市竞争力的空间演化

构建城市竞争力多指标体系,从空间分布视角,对长江中游城市群城市竞争力的结构演变进行定量分析,发现:(1)长江中游城市群城市竞争力空间格局整体呈三大"核心(一主两副)—边缘"板块结构,且保持时间惯性和空间惰性,时空演变呈"总体锁定,局部变动"特征;(2)长江中游城市群竞争力分布具有总体格局的均衡性、空间分异的规律性和内部竞争结构的异质性;(3)5个主因子空间分异显著,仅第一主因子与综合竞争力空间耦合良好,第一、第三主因子重心迁移轨迹趋向几何中心"均衡点位"。     

A region-based,graph-theoretic data model for the inference of second-order thematic information from remotely-sensed images

A graph-theoretic data model, XRAG (eXtended Relational Attributed Graph), is described. The model and its associated data structure can be used to represent the structural properties (morphological and symbolic) of, and relations (spatial, topological, non-topological, quantitative and symbolic) between, discrete regions identified in a digital remotely-sensed image. The objective in developing this model is to allow second-order thematic information about the scene to be inferred from an analysis of these properties and relations. The paper briefly outlines the application of this model and an associated set of analytical techniques to infer land use from an initial land cover map derived from a digital remotely-sensed image.     

Analysis of surface changes using primitive events

This paper develops a method for analysing changes in a surface, a scalar function defined over a two-dimensional region. The method is based on the topological method for static surfaces that uses critical points (peaks, bottoms, and cols) and their connecting lines. To extend the topological method to spatiotemporal domain, four types of primitive events are proposed: (1) generation, (2) disappearance, (3) movement, and (4) switch. The change of a surface is described by a combination of these primitives. From surfaces of two times a set of primitive events that cause the change is deduced. They are stored in GIS as spatial objects with attributes, and their spatio-temporal pattern is visually analysed. To test the validity of the method, the change of a retail cluster in Shinjuku and Shibuya area in Tokyo is analysed. The empirical study yielded some interesting findings that help us understand changes in the spatial structure of retailing.     

东北地区要素空间集聚与不平衡发展研究

基于2000—2017年东北地区县域尺度生产要素与GDP数据，借助空间分析法，考察东北地区要素集聚与不平衡发展的时空特征和空间关系。结果表明：① 2000年以来，东北地区要素集聚度总体呈下降趋势且区域差异缩小，经济发展水平呈持续上升趋势且区域差异逐步缩小。② 要素空间集聚与经济发展水平由以中心城市为主的高值区，逐渐演变为以中心城市为核心，及其临近地域组成的城市群高值集聚区。二者空间耦合性较好，形成了中南部地区要素集聚与经济发展的空间高度一致性；但北部地区存在显著的空间错位，特别是北部地区的鹤岗、伊春等市的市辖区虽然要素集聚度高于其他地区，但经济发展水平却处于中低水平。可以看出，以哈长城市群和辽中南城市群为主的城市群，正日渐成为东北地区经济发展的核心带动区。③ 区位差异、偏向城市的发展政策，以及产业转型升级等因素共同作用，主导了东北地区要素集聚与不平衡发展的空间分异。     

基于村域尺度的乡村性评价及乡村发展模式研究——以江苏省金坛市为例

在梳理乡村性研究成果基础上,探索微观尺度乡村性评价方法,并对江苏省金坛市分村域土地利用指数、人口聚落指数、产业结构指数、城乡联系指数以及乡村性综合指数进行评价研究。结果表明,金坛市乡村地域的土地利用、人口聚落、产业结构以及城乡联系特征均呈现显著的空间集聚特征,且彼此差异明显;乡村性综合发展水平则呈现出显著的西部山丘地区高、东部城市周边地区低的空间分异特征。在此基础上,进一步揭示乡村性与乡村发展之间的逻辑关系,提炼出乡村发展的3种模式：资源置换型、特色发展型、城乡融合型。     

产业与地形因素影响下的山地城市职住空间关系——以重庆市主城九区为例

选择重庆主城九区作为典型案例,基于百度慧眼识别的就业人口与居住人口数据,通过测算就业－居住偏离度指数分析其人口分布特征与职住空间关系,划分就业主导区、基本匹配区与居住主导区。并基于全国第四次经济普查数据,在对产业进行综合因子分析基础上,定量化识别产业综合因子和地形因子对重庆主城九区职住空间匹配性影响。结果表明：1）重庆市主城区的就业与居住人口空间分布趋势具有一致性特征,整体上呈现“中间高、四周低”的特征;2）重庆市主城区的职住空间基本平衡,街道尺度上职住偏离特征不显著,但城市多组团的中心地区职住空间匹配特征稍有差异,呈现主中心（解放碑）职住平衡度低、4个副中心职住平衡度高的格局;3）空间回归模型表明,综合性服务产业因子和生产性服务产业因子强化了职住分离程度,社会性服务产业因子、制造业因子和地形起伏度降低了职住空间差异。总体上,产业布局与地形地貌是重庆主城区职住空间关系的重要影响因素,二者与政府规划、交通条件和居民生活相互补充、共同作用,塑造了重庆主城现今协调发展的就业－居住空间格局。     

复杂地貌区域生态敏感区综合评价与保护对策--以钦州市为例

复杂地貌区域国土开发受生态环境因素影响较单一地貌地区更复杂,其境内生态敏感区类型较多,且空间分布比较杂乱,不同生态敏感区之间又相互影响。文章选择山、水、林、田、城互为镶嵌的广西钦州市作为案例城市,以小流域为评价单元,建立集“地”、“水”、“绿”三位于一体的评价体系,在遥感和GIS技术的支持下,将单因子定性分级和多因子空间叠加模型相结合,对整个区域的生态敏感区进行综合评价及分区。从研究结果来看,这种评价技术能够较好地反映这些生态敏感区的综合分异规律,有助于当地政府在区域开发中制定更为科学的生态安全防范对策。     

A spatial data model design for feature-based geographical information systems

Abstract

In state-of-the-art GIS, geographical features are represented as geometric objects with associated topological relations and classification attributes. Semantic relations and intrinsic interrelations of the features themselves are generally neglected. In this paper, a feature-based model that enhances the representation of geographical features is described. Features, as the fundamental depiction of geographical phenomena, encompass both real world entities and digital representation. A feature-based object incorporates both topological relations among geometric elements and non-topological (semantic) relations among features. The development of an object-oriented prototype feature-based GIS that supports relations between feature attributes and feature classes is described. Object-oriented concepts such as class inheritance and polymorphism facilitate the development of feature-based GTS.     

新型城镇化背景下中国地级以上城市综合承载力空间格局研究

在分析城市综合承载力内涵基础上,通过建立评价指标体系,运用函数模型计算2015 年中国地级以上城市综合承载力水平,利用探索性空间数据分析方法探讨了地级以上城市综合承载力的空间分布特征。结果表明：中国地级以上城市综合承载力存在较大差距,整体呈现从东部沿海向西部内陆递减的空间分布趋势;地级以上城市综合承载力呈现明显正向全局空间自相关关系,从局域空间自相关和冷热点结果来看,呈现出自东向西由热点逐步过渡为冷点的空间格局,H-H型城市主要分布在热点区,H-L型城市以西部地区直辖市和省会城市居多,L-H型城市数量只有河源市,L-L型城市集中分布在冷点区。研究结果可为解决当前城镇化问题、推进新型城镇化进程提供指导和借鉴。     

社区尺度的北京儿童服务设施可达性分析

儿童服务设施是建设儿童友好性城市的重要内容。基于北京城区社区人口数据及儿童服务设施数据,通过两步移动搜寻法,以社区为单元分析儿童服务设施可达性的空间格局及分布模式。结果显示,不同类别儿童服务设施空间可达性服务水平差异较大,在1000米阈值范围内小学的空间可达性水平优于幼儿园,3000米阈值范围内儿童诊所的空间可达性优于公园。受儿童人口和儿童服务设施分布的影响,小学、幼儿园、儿科门诊的可达性均呈现“中心高、边缘低”的分布格局,空间分布不均衡;公园分布则相对分散,其可达性呈现边缘区域优于中心区域分布特征。北京城区儿童服务设施可达性情况可分为五种类型区,类型区之间以同心圆的结构进行组合,局部体现出扇形的特征。据此提出针对不同区域儿童服务设施的改善策略。     

大城市低收入邻里社会贫困的测度差异与成因

社会贫困是对居民的社会保障和福利的享有情况、社会参与和融合等生活状况的测度。利用中国3 大典型地域、6 个代表城市、3 类邻里的1809 份个体问卷调查数据, 本文选取13 个相关指标, 判定个体是否处于社会贫困状态, 利用回归模型探究其影响因素, 并分析社会贫困现象在不同邻里、不同城市集聚的分异特征。研究发现, 6 个城市间的社会贫困集聚程度顺序为东部、中部和西部;3 大类邻里中, 社会贫困在城中村表现最为明显, 内城居住区次之, 企业配套居住区最低。中国城市居民是否处于社会贫困状态是体制(户口类型) 和家庭(教育程度、年龄等) 因素共同作用的结果。代表体制因素的户口类型对3 类城市的社会贫困均起到影响, 东中部城市中家庭因素也有一定作用。体制因素对城中村的社会贫困起显著影响, 而家庭因素在内城居住区和企业配套居住区中作用更大。     

广州市居民网络购物频率的影响因素及其空间差异

基于广州市居民网络购物行为调查问卷和电子地图兴趣点（POI）数据，从全市和不同区位2个空间尺度，运用有序多分类Logistic回归模型探讨了个人社会经济属性、商品特征、空间环境及物流快递4类因素对居民网购频率的影响。研究发现：① 影响因素在不同空间尺度和不同区位产生作用的因子个数、作用强度和作用方向存在差异。影响因子数量在全市域范围最多，远郊区最少。各因子总体上在近郊区和全市域作用强度大，在远郊区最弱。退货服务重要性在近郊区和中心区作用方向相反；② 部分空间环境因子对网购频率有影响，城市化水平、商业中心可达性在全市域范围有影响，居住地城市化水平越高、离商业中心距离越近的居民网购频率越高，支持了创新扩散假说。快递点数量在中心区有影响，居住地快递点数量越多的居民网购频率越高。其它空间环境因子没有显著影响。③ 个人社会经济属性因素对网购频率影响较大，性别、年龄是最重要的影响因子，其次是学历、职业，月收入影响最小。商品特征、快递物流因素各因子在不同区域对网购频率产生较大影响。     

基于多源数据的城市活力空间特征及建成环境对其影响机制研究

采用城市POI、手机信令数据及夜间灯光遥感数据,以深圳市为例,构建城市活力度量指标分析城市活力的空间特征。构建“5D”指标体系度量城市建成环境,并运用地理探测器,探究建成环境对城市活力的影响机制。结果表明：1）深圳市城市综合活力显示出“南强北弱,西强东弱”的空间分异特征,空间分布极不均衡。城市综合活力最主要反映的是社会活力。2）城市综合活力、经济活力、社会活力、文化活力均受到建成环境的显著影响。高POI密度、高建筑密度、高平均建筑层数和高土地利用混合度对城市活力具有显著促进作用。3）居住人口密度与路网密度、土地利用混合度与路网密度等交互作用对城市活力产生更为积极的影响。4）在影响机制中,建筑密度、平均建筑层数为底层支撑因素,POI密度、土地利用混合度为直接驱动因素,居住人口密度为诱发因素,距行政区中心距离、交叉口密度、路网密度、地铁站点密度和公交站点密度为调节因素。