Fuzzy topological relations between fuzzy spatial objects

Fuzziness is an internal property of spatial objects.How to model fuzziness of a spatial object is a main task of next generation GIS.This paper proposes basic fuzzy spatial object types based on fuzzy topology.These object types are the natural extension of current nonfuzzy spatial object types.A fuzzy cell complex structure is defined for modeling fuzzy regions,lines and points.Furthermore,fuzzy topological relations between these fuzzy spatial objects are formalized based on the 9intersection approach.This model can be implemented for GIS applications due to its scientific theory basis.     

三个目标间空间方位关系表达模型及其GIS应用

空间方位是一类重要的空间关系,它不同于目前研究较多的方向关系。空间方位关系描述的是三个目标间的空间关系,它的理论基础是基于射影几何中的三点共线不变性。本文首先阐述了空间方位的基本定义、表达基础以及它与拓扑关系、方向关系的区别。然后,重点回顾了6种较为有代表性的方位关系描述模型,指出了这些模型的适用性,并对这些模型进行了比较分析。最后,简要地分析了空间方位关系在GIS中的应用前景以及有待进一步研究的若干问题。     

空间球状物体的数据采集与分析

本文推导了以球心三维坐标及半径为参数的平差模型,据此设计和完成了一个球面拟合程序,能够实现球半径已知或未知这两种情况的拟合计算。程序还可批量处理多个独立球体的观测数据,进行拟合结果与设计数据的自动匹配及对比。利用该程序对模拟数据进行分析,得出一些对采集方案有指导作用的结论。     

Dealing with spatial relations for spatial objects with randomness in GIS

To design retrieval algorithm of spatial relations for spatial objects with randomness in GIS, this paper builds up the membership functions based on set theory idea, used for determination of topological spatial relations between random objects, such as between point and point, point and line or polygon, which provides theoretical basis for retrieving spatial relations between certain and random objects. Finally, this paper interprets detailed methods and steps of realizing them by means of some simple examples under the GIS's environment.     

DEALING WITH SPATIAL RELATIONS FOR SPATIAL OBJECTS WITH RANDOMNESS IN GIS

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Behavior mining of spatial objects with data field

The advanced data mining technologies and the large quantities of remotely sensed Imagery provide a data mining opportunity with high potential for useful results. Extracting interesting patterns and rules from data sets composed of images and associated ground data can be of importance in object identification, community planning, resource discovery and other areas. In this paper, a data field is presented to express the observed spatial objects and conduct behavior mining on them. First, most of the important aspects are discussed on behavior mining and its implications for the future of data mining. Furthermore, an ideal framework of the behavior mining system is proposed in the network environment. Second, the model of behavior mining is given on the observed spatial objects, including the objects described by the first feature data field and the main feature data field by means of the potential function. Finally, a case study about object identification in public is given and analyzed. The experimental results show that the new model is feasible in behavior mining.     

基于数据场的空间目标行为挖掘

The advanced data mining technologies and the large quantities of remotely sensed Imagery provide a data mining opportunity with high potential for useful results. Extracting interesting patterns and rules from data sets composed of images and associated ground data can be of importance in object identification, community planning, resource discovery and other areas. In this paper, a data field is presented to express the observed spatial objects and conduct behavior mining on them. First, most of the important aspects are discussed on behavior mining and its implications for the future of data mining. Furthermore, an ideal framework of the behavior mining system is proposed in the network environment. Second, the model of behavior mining is given on the observed spatial objects, including the objects described by the first feature data field and the main feature data field by means of the potential function. Finally, a case study about object identification in public is given and analyzed. The experimental results show that the new model is feasible in behavior mining. Supported by the National 973 Program of China(No.2006CB701305,No.2007CB310804), the National Natural Science Fundation of China (No.60743001), the Best National Thesis Fundation (No.2005047), the National New Century Excellent Talent Fundation (No.NCET-06-0618).     

Measurement of similarity for spatial directions between areal objects

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.     

An improved direction relation detection model for spatial objects

Direction is a common spatial concept that is used in our daily life. It is frequently used as a selection condition in spatial queries. As a result, it is important for spatial databases to provide a mechanism for modeling and processing direction queries and reasoning. Depending on the direction relation matrix, an inverted direction relation matrix and the concept of direction pre- dominance are proposed to improve the detection of direction relation between objects. Direction predicates of spatial systems are also extended. These techniques can improve the veracity of direction queries and reasoning. Experiments show excellent efficiency and performance in view of direction queries.     

移动目标空间拓扑关系的度量描述

针对传统9交模型对移动目标空间拓扑关系表达及量化描述的不足,基于格网化思想,提出了度量参数量化描述的方法。首先对移动目标和参考目标进行格网化,划分为固定大小的格网阵列;然后利用9交模型确定空间目标间拓扑关系的形式化描述;最后引入内部分量、边界分量、外部分量3种度量参数对移动目标空间拓扑关系进行度量化描述。试验证明,该方法计算简单、直观,能更加有效地度量移动目标间的拓扑关系。     

基于HCMOST的移动目标模型构建

在改进的移动目标空间模型-HCMOST基础上,建立移动目标管理模型,组织和管理监控数据,该优化模型采用三次Hermite插值方法模拟移动目标每个历史单元中的运动轨迹,并把运动函数预先计算出来存放在共享列表中,从而使模型在精度和效率方面有了很大提高。本文基于该模型构建了移动目标管理模型,并分析了构建模型的性能。     

An improved direction relation detection model for spatial objects

Direction is a common spatial concept that is used in our daily life. It is frequently used as a selection condition in spatial queries. As a result, it is important for spatial databases to provide a mechanism for modeling and processing direction queries and reasoning. Depending on the direction relation matrix, an inverted direction relation matrix and the concept of direction pre- dominance are proposed to improve the detection of direction relation between objects. Direction predicates of spatial systems are also extended. These techniques can improve the veracity of direction queries and reasoning. Experiments show excellent efficiency and performance in view of direction queries.     

Measurement of similarity for spatial directions between areal objects

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.     

空间数据模糊聚类的有效性(英文)

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.     

3D GIS中空间对象的存储与快速查询

空间对象的存储和快速查询是三维地理信息系统研究的基本问题。本文采用面向对象的方法将三维空间对象抽象为点、线、面、体四类,点对象用一个坐标点(x,y,z)来表示,线对象用一组首尾相接的线段表示,面对象与体对象用三角网表示,然后采用SQL Server 2005来组织存储数据。为了提高空间数据库的检索速度,作者编程实现了线性八叉树空间索引,应用程序采用目前比较流行的ADO.net技术来访问数据库。     

Modelling the spatial evolution of map objects by map agents

To overcome the weakness of modelling the relationships between map objects that represent the same geographic entities or phenomena at different times and scales, an agent-based approach is presented to modelling of the spatial evolution of map objects for better understanding of the evolutional process of different maps. Map agents are used to establish and manage the many-to-many corresponding relationships between map objects, and they render map objects active rather than traditionally passive. The evolutions of map objects are modelled by map agents using association and generation relationships to model the connectivity between map objects. This effort reduces the workload of multi-scale map updating by avoiding update of the entire map; instead, it simply allows map agents to detect, perceive and choose suitable behaviours on which to operate and update a spatially evolving object. Experiments of specific examples are presented to demonstrate the feasibility and the effectiveness of our approach.     

多尺度空间线状实体形状相似关系的表达与度量

本文对空间数据多尺度表达中线状实体综合前后的形状相似性进行了描述、分析和研究。通过调查统计,得出了衡量线状实体形状相似程度的两个重要参量SIMⅠ、SIMⅡ,基于这两个参量给出了空间线状实体形状相似性的定义以及在不同尺度下线状实体形状相似性的度量方法,并用实例进行验证。为空间数据多尺度表达时线状实体的形状表达提供了一种分析和评价手段。     

Quantitative fuzzy topological relations of spatial objects by induced fuzzy topology

This paper presents a study on the modeling of fuzzy topological relations between uncertain objects in Geographic Information Systems (GIS). Based on the recently developed concept of computational fuzzy topological space, topological relations between simple fuzzy spatial objects are modeled. The fuzzy spatial objects here cover simple fuzzy region, simple fuzzy line segment and fuzzy point. To compute the topological relations between the simple spatial objects, intersection concepts and integration methods are applied and a computational 9-intersection model are proposed and developed. There are different types of intersection, and we have proposed different integration methods for computation in different cases. For example, surface integration method is applied to the case of the fuzzy region-to-fuzzy region relation, while the line integration method is used in the case of fuzzy line segment-to-fuzzy line segment relation. Moreover, this study has discovered that there are (a) sixteen topological relations between simple fuzzy region to line segment; (b) forty-six topological relations between simple fuzzy line segments; (c) three topological relations between simple fuzzy region to fuzzy point; and (d) three topological relations between simple fuzzy line segment to fuzzy point.     

基于模糊贴近度分析的不确定拓扑关系表达模型

根据人类对模糊空间关系的认知层次性特点,将不确定拓扑关系的表达归结为求解不确定空间关系实例与基本拓扑关系概念之间的隶属度。基于贴近度分析的基本方法建立不确定地理目标之间空间拓扑关系模糊表达模型方法。结合具体的算例说明基于该模型方法的拓扑关系模糊表达推算过程,并通过与经典的Egg—Yolk以及宽边界模型方法表达的拓扑关系表达结果进行对比分析,验证模型的合理性。     

结合地物空间特性的高光谱图像分类方法研究

以往的高光谱或多光谱图像分类与识别,往往只关注像元光谱维上的特性,其一切特征统计也只在光谱及波段维上展开。但是自然界的复杂性、混合像元问题的存在,仅靠像元的光谱特性是不够的,常会出现"麻点"现象。针对这一问题,本文提出一种结合地物空间特性的高光谱图像分类方法,其分类过程可以分为两个阶段,第一阶段是基于像元光谱特性的图像分类,获得影像分类图;第二阶段是针对第一阶段的分类结果,结合地物空间特性进行空间后分类处理。试验研究结果表明,该方法能够保持地块的连续性和均一性,同时克服了"麻点"现象,大大提高分类的精度。