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1.
DINGHong GUOQingsheng DUXiaochu 《地球空间信息科学学报》2004,7(3):225-230
Similarity for spatial directions plays an important role in GIS. In this paper, the conventional approaches are analyzed. Based on raster data areal objects, the authors propose two new methods for measuring similarity among spatial directions. One is to measure the similarity among spatial directions based on the features of raster data and the changes of distances between spatial objects, the other is to measure the similarity among spatial directions according to the variation of each raster cell centroid angle. The two methods overcome the complexity of measuring similarity among spatial directions with direction matrix model and solve the limitation of small changes in direction. The two methods are simple and have broader applicability. 相似文献
2.
空间数据模糊聚类的有效性(英文) 总被引：1，自引：0，他引：1
The validity measurement of fuzzy clustering is a key problem. If clustering is formed, it needs a kind of machine to verify its validity. To make mining more accountable, comprehensible and with a usable spatial pattern, it is necessary to first detect whether the data set has a clustered structure or not before clustering. This paper discusses a detection method for clustered patterns and a fuzzy clustering algorithm, and studies the validity function of the result produced by fuzzy clustering based on two aspects, which reflect the uncertainty of classification during fuzzy partition and spatial location features of spatial data, and proposes a new validity function of fuzzy clustering for spatial data. The experimental result indicates that the new validity function can accurately measure the validity of the results of fuzzy clustering. Especially, for the result of fuzzy clustering of spatial data, it is robust and its classification result is better when compared to other indices. 相似文献
3.
Three-dimensional (3D) land development and utilization has become the trend for urban planning in the current metropolis.This paper presents a method for building a 3D cadastral management system from survey plans with SketchUp.It concentrates on the geometric representation and topological consistent maintenance of 3D cadastral objects.In this system a complete topological model is built to express the body construction and spatial relationships among 3D property units.SketchUp is used to automatically construct 3D models with attributes and thematic information from 2D survey plans.Spatial topologic relationships and operations are analyzed with the programming and development of Ruby language.The resulting system can manage 3D cadastral objects and manipulate them with spatial operations to support spatial analysis. 相似文献
4.
WANG Yandong GONG Jianya WU Xiaohuang 《地球空间信息科学学报》2007,10(3):204-207
In GIS field, great varieties of information from different domains are involved in order to solve ac- tual problems. But usually spatial information is stored in diverse spatial databases, manipulated by different GIS platforms. Semantic heterogeneity is caused due to the distinctions of conception explanations among various GIS implements. It will result in the information obtaining and understanding gaps for spatial data sharing and usage. An ontology-based model for spatial information semantic interoperability is put forward after the comprehensive review of progress in ontology theory, methodology and application research in GIS domain. 相似文献
5.
Classification is always the key point in the field of remote sensing. Fuzzy c-Means is a traditional clustering algorithm that has been widely used in fuzzy clustering. However, this algorithm usually has some weaknesses, such as the problems of falling into a local minimum, and it needs much time to accomplish the classification for a large number of data. In order to overcome these shortcomings and increase the classification accuracy, Gustafson-Kessel （GK） and Gath-Geva （GG） algorithms are proposed to improve the traditional FCM algorithm which adopts Euclidean distance norm in this paper. The experimental result shows that these two methods are able to detect clusters of varying shapes, sizes and densities which FCM cannot do. Moreover, they can improve the classification accuracy of remote sensing images. 相似文献
6.
WULixin SHIWenzhong 《地球空间信息科学学报》2004,7(2):123-128
Engineering excavation GIS (E^2GIS) is a real-3D GIS serving for geosciences related to geo-engineering, civil engineering and mining engineering based on generalized tri-prism (GTP) model.As two instances of GTP model, G-GTP is used for the real-3D modeling of subsurface geological bodies, and E-GTP is used for the real-3D modeling of subsurface engineering excavations. In the light of the discussions on the features and functions of E2 GIS, the modeling principles of G-GTP and E-GTP are introduced. The two models couple together seamlessly to form an integral model for subsurface spatial objects including both geological bodies and excavations. An object-oriented integral real-3D data model and integral spatial topological relations are discussed. 相似文献
7.
A space-filling curve in 2,3,or higher dimensions can be thought as a path of a continuously moving point.As its main goal is to preserve spatial proximity,this type of curves has been widely used in the design and implementation of spatial data structures and nearest neighbor-finding techniques.This paper is essentially focused on the efficient representation of Digital Ele-vation Models(DEM) that entirely fit into the main memory.We propose a new hierarchical quadtree-like data structure to be built over domains of unrestricted size,and a representation of a quadtree and a binary triangles tree by means of the Hilbert and the Sierpinski space-filling curves,respectively,taking into account the hierarchical nature and the clustering properties of this kind of curves.Some triangulation schemes are described for the space-filling-curves-based approaches to efficiently visualize multiresolu-tion surfaces. 相似文献
8.
ZHANG Jingxiong R. P. Kirby LU Jiangbin ZHANG Jingxiong Associate Professor National Laboratory for Information Engineering In Surveying Mapping Remote Sensing WTUSM Luoyu Road Wuhan China 《地球空间信息科学学报》1999,2(1):42-48
This paper endeavours to put the discussion on errors and uncertainties in geographical information systems (GISs) in a more systematic way by examining the strength and weakness of discrete objects and continuous fields, the two distinct schools of spatial data modelling. In doing so, it argues that neither discrete objects nor continuous fields alone provide objective and complete representations of highly complex geographical phenomena, though there are good reasons for asserting that continuous fields are better suited to modelling spatial dependence, heterogeneity and fuzziness significant in geographical reality than discrete objects. Thus, there seems to be merit in adopting an integrated model incorporating analytical capabilities of fields and generalization functions of objects, for which extended TIN(triangulated irregular network) models along with their duals (Voronoi diagrams) provide a pragmatical solution. 相似文献
9.
WU Dingxue PENG Daiqiang TIAN Jinwen 《地球空间信息科学学报》2007,10(3):196-199
Rather than attempting to separate signal from noise in the spatial domain, it is often advanta- geous to work in a transform domain. Building on previous work, a novel denoising method based on local adaptive least squares support vector regression is proposed. Investigation on real images contaminated by Gaussian noise has demonstrated that the proposed method can achieve an acceptable trade off between the noise removal and smoothing of the edges and details. 相似文献
10.
Spatial object and spatial relationship are two basic concepts of GIS.Spatial object is the digital representation of geographical entity or phenomenon,which forms the basis for data management and analysis;spatial relationship is theconnexion between spatial objects when geometric properties are considered.Thecommonly used classification of spatial objects as points,lines and areas is mathe-matically strict,and suitable for data management,but a bit too generalized forrepresenting real entities and extracting spatial relationships.A good classificationmodel should not only be good for representing real entities,but also good for re-vealing spatial relationships,therefore good for formalizing spatial analyses. 相似文献
11.
Spatial objects have two types of attributes: geometrical attributes and non-geometrical attributes, which belong to two different attribute domains (geometrical and non-geometrical domains). Although geometrically scattered in a geometrical domain, spatial objects may be similar to each other in a non-geometrical domain. Most existing clustering algorithms group spatial datasets into different compact regions in a geometrical domain without considering the aspect of a non-geometrical domain. However, many application scenarios require clustering results in which a cluster has not only high proximity in a geometrical domain, but also high similarity in a non-geometrical domain. This means constraints are imposed on the clustering goal from both geometrical and non-geometrical domains simultaneously. Such a clustering problem is called dual clustering. As distributed clustering applications become more and more popular, it is necessary to tackle the dual clustering problem in distributed databases. The DCAD algorithm is proposed to solve this problem. DCAD consists of two levels of clustering: local clustering and global clustering. First, clustering is conducted at each local site with a local clustering algorithm, and the features of local clusters are extracted. Second, local features from each site are sent to a central site where global clustering is obtained based on those features. Experiments on both artificial and real spatial datasets show that DCAD is effective and efficient. 相似文献
12.
一种基于双重距离的空间聚类方法 总被引：10，自引：1，他引：9
传统聚类方法大都是基于空间位置或非空间属性的相似性来进行聚类,分裂了空间要素固有的二重特性,从而导致了许多实际应用中空间聚类结果难以同时满足空间位置毗邻和非空间属性相近。然而,兼顾两者特性的空间聚类方法又存在算法复杂、结果不确定以及不易扩展等问题。为此,本文通过引入直接可达和相连概念,提出了一种基于双重距离的空间聚类方法,并给出了基于双重距离空间聚类的算法,分析了算法的复杂度。通过实验进一步验证了基于双重距离空间聚类算法不仅能发现任意形状的类簇,而且具有很好的抗噪性。 相似文献
13.
针对Delaunay三角网空间聚类存在的不足,提出一种顾及属性空间分布不均的空间聚类方法。首先将Delaunay三角网空间位置聚类作为约束条件,采用广度优先搜索方法,以局部参数"属性变化率"作为阈值识别非空间属性相似簇的聚类过程。以城市商业中心为例,验证了该方法能够更客观地识别非空间属性相似的簇,且自适应属性阈值可以满足不同聚类需求,为城市商业中心等空间实体的提取提供了一种有效方法。 相似文献
14.
An adaptive dual clustering algorithm based on hierarchical structure: A case study of settlement zoning 
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下载免费PDF全文 Traditional dual clustering algorithms cannot adaptively perform clustering well without sufficient prior knowledge of the dataset. This article aims at accommodating both spatial and non‐spatial attributes in detecting clusters without the need to set parameters by default or prior knowledge. A novel adaptive dual clustering algorithm (ADC+) is proposed to obtain satisfactory clustering results considering the spatial proximity and attribute similarity with the presence of noise and barriers. In this algorithm, Delaunay triangulation is utilized to adaptively obtain spatial proximity and spatial homogenous patterns based on particle swarm optimization (PSO). Then, a hierarchical clustering method is employed to obtain clusters with similar attributes. The hierarchical clustering method adopts a discriminating coefficient to adaptively control the depth of the hierarchical architecture. The clustering results are further refined using an optimization approach. The advantages and practicability of the ADC+ algorithm are illustrated by experiments on both simulated datasets and real‐world applications. It is found that the proposed ADC+ algorithm can adaptively and accurately detect clusters with arbitrary shapes, similar attributes and densities under the consideration of barriers. 相似文献
15.
空间和属性双重约束下的自组织空间聚类研究 总被引：2，自引：0，他引：2
形式化定义了双重聚类的聚类准则及其判定方法,提出了双重聚类的两步法求解思路和自组织双重聚类算法。通过实例验证了该算法的可行性,自组织双重聚类可以发现非空间属性的聚集、延伸等空间分布特征,可以发现任意复杂形状的聚类,并降低了人为影响。 相似文献
16.
多层次空间同位模式自适应挖掘方法 总被引：1，自引：1，他引：0
空间同位模式挖掘旨在从空间数据中发现频繁发生在邻近位置的事件集合,对于揭示地理现象间的共生规律具有重要价值。由于地理现象的空间异质特质,空间同位模式也存在区域性分异的特点,在不同空间层次上的分析结果各异。然而,现有方法仅从全局视角挖掘空间同位模式,发现局部空间同位模式依然是一个亟待解决的难题。为此,本文基于由整体到局部的思想,提出了一种多层次空间同位模式自适应挖掘方法。首先,从全局视角提取频繁的空间同位模式,将全局不频繁的空间同位模式作为候选的局部空间同位模式;然后,通过对候选局部同位模式进行自适应聚类自动识别其局部分布区域,并在这些局部区域内度量候选模式的频繁程度;进而,提出了一种叠置推绎的方法,从频繁子模式的局部区域中进一步推绎获得超模式的局部分布区域,最终生成所有频繁的局部空间同位模式集合。通过试验分析与比较发现,本文方法不仅可以发现全局的空间同位模式,还能有效提取具有区域性分布特征的局部空间同位模式,可以从多个空间层次上反映地理事件间的共生规则。 相似文献
17.
空间聚类不仅应考虑GIS对象属性特征的相似性,还应考虑对象的空间邻近性。不同属性、位置特征在聚类中起到的作用不同。采用信息熵方法计算空间距离中各属性距离、位置距离的权重,权值大小用于度量相应特征在fuzzy c-means隶属度计算时的作用大小,并引入相似性指标,当两个聚类之间的相似度高于某个合并阈值时,则对应的一对聚类进行合并,从而克服需预先设置聚类类数的问题。通过应用实例的聚类有效性分析,与普通空间距离相比,基于空间加权距离的FCM算法具有稳定性和有效性。 相似文献
18.
分布式环境下空间数据的索引是空间数据处理中一个关键性的基础问题,引入了控制点及四叉树划分结构,并通过Hash函数把控制点映射到Chord网络中,在此基础上提出了基于语义的分簇聚类分布式四叉树的空间数据索引机制(spatial data index based on clustering distributed quad-tree,SDI-CDQT),该机制主要包含四叉树划分、空间数据查询和分簇聚类3个子算法。实验表明,SDI-CDQT机制是可行和有效的。 相似文献
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20.
Urban buildings are an integral component of urban space, and accurately identifying their spatial configurations and grouping them is vital for various urban applications. However, most existing building clustering methods only utilize the original spatial and nonspatial features of buildings, disregarding the potential value of complementary information from multiple perspectives. This limitation hinders their effectiveness in scenarios with intricate spatial configurations. To address this, this article proposes a novel multi-view building clustering method that captures cross-view information from spatial and nonspatial features. Drawing inspiration from both spatial proximity characteristics and nonspatial attributes, three views are established, including two spatial distance graphs (centroid distance graph and the nearest outlier distance graph) and a building attribute graph (multiple-attribute graph). The three graphs undergo iterative cross-diffusion processes to amplify similarities within each predefined graph view, culminating in their fusion into a unified graph. This fusion facilitates the comprehensive correlation and mutual enhancement of spatial and nonspatial information. Experiments were conducted using 10 real-world community-building datasets from Wuhan and Chengdu, China. The results demonstrate that our approach achieves 21.27% higher accuracy and 22.28% higher adjusted rand index in recognizing diverse complex arrangements compared to existing methods. These findings highlight the importance of leveraging complementary and consensus information across different feature dimensions for improving the performance of building clustering. 相似文献