KGI-XGIS SUPPORTING DECISION MAKING WITH KNOWLEDGE-BASED TECHNIQUES

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The development of spatial decision support system tool for marine spatial planning

A major problem associated with marine spatial planning (MSP) involves the difficult and time-consuming practice of creating a scenario that encompasses complex datasets in near real time via the use of a simple spatial analysis method. Moreover, decision-makers require a reliable, user-friendly system to quickly and accessibly acquire accurate spatial planning information. The development of national spatial data infrastructure (NSDI), which links the spatial data of a nation’s many diverse institutions, may pave the way for the development of a tool that can better utilize spatial datasets, such as a spatial decision support system (SDSS). Thus, this project aimed to develop an SDSS for MSP and to evaluate the feasibility of its integration within the NSDI framework. The seaweed culture was selected as an example due to its economic and technological acceptance by traditional fishers. Additionally, a multi-criteria analysis was used to develop the tool. Furthermore, a feasibility evaluation of its implementation within the NSDI framework was conducted based on the Delphi method. The results of the assessment indicated that the SDSS can be incorporated into the NSDI framework by addressing the policy issue – one map policy, updating custodians’ decree and data, and improve the standard and protocol.     

DATABASE STRUCTURE FOR THE INTEGRATION OF RS WITH GIS BASED ON SEMANTIC NETWORK

1　ＴｈｅｃｏｎｃｅｐｔｏｆｔｈｅｉｎｔｅｇｒａｔｉｏｎｏｆＲＳｗｉｔｈＧＩＳＴｈｅｉｎｔｅｇｒａｔｉｏｎｏｆｒｅｍｏｔｅｓｅｎｓｉｎｇ (ＲＳ)ｗｉｔｈｇｅｏ ｇｒａｐｈｉｃａｌｉｎｆｏｒｍａｔｉｏｎｓｙｓｔｅｍ (ＧＩＳ)ｉｓａｈｏｔｓｐｏｔｉｎｇｅｏｇｒａｐｈｉｃａｌｉｎｆｏｒｍａｔｉｏｎｓｃｉｅｎｃｅ .ＴｈｅｃｏｎｃｅｐｔｏｆｔｈｅｉｎｔｅｇｒａｔｉｏｎｏｆＲＳｗｉｔｈＧＩＳ ,ｉｎｔｈｅｖｉｅｗｏｆＰｒｏｆ.ＬｉＤｅｒｅｎ ,ｉｓｔｈａｔＲＳｉｓｔｈｅｗａｙｔｏｏｂｔａｉｎｔｈｅｉｎｆｏｒｍａ ｔｉ…     

Database structure for the integration of RS with GIS based on semantic network

The integration of remote sensing (RS) with geographical information system (GIS) is a hotspot in geographical information science. A good database structure is important to the integration of RS with GIS, which should be beneficial to the complete integration of RS with GIS, able to deal with the disagreement between the resolution of remote sensing images and the precision of GIS data, and also helpful to the knowledge discovery and exploitation. In this paper, the database structure storing the spatial data based on semantic network is presented. This database structure has several advantages. Firstly, the spatial data is stored as raster data with space index, so the image processing can be done directly on the GIS data that is stored hierarchically according to the distinguishing precision. Secondly, the simple objects are aggregated into complex ones. Thirdly, because we use the indexing tree to depict the relationship of aggregation and the indexing pictures expressed by 2-D strings to describe the topology structure of the objects, the concepts of surrounding and region are expressed clearly and the semantic content of the landscape can be illustrated well. All the factors that affect the recognition of the objects are depicted in the factor space, which provides a uniform mathematical frame for the fusion of the semantic and non-semantic information. Lastly, the object node, knowledge node and the indexing node are integrated into one node. This feature enhances the ability of system in knowledge expressing, intelligent inference and association. The application shows that this database structure can benefit the interpretation of remote sensing image with the information of GIS.     

Spatial decision support system for home-delivered services

 We present a spatial decision support system for the non-profit sector, designed to assist planning in the area of home-delivered services such as meals on wheels. Using data collected from existing programs, current and forecasted demographic data, and a set of algorithmic tools, we provide a system for evaluating current meals on wheels facilities, and for making incremental facility location decisions that satisfy coverage and equity requirements. Received: 27 September 2000 / Accepted: 22 March 2001     

Spatial analysis software testing tool based on object-oriented techniques

Object-oriented (OO) programming and system design have become the scalable methodology for large-scale enterprise and technology system designs. Spatial and geographic information system (GIS)-based systems are not exempt from this trend and have widely adopted object-oriented methodology. Testing strategies for systems developed with OO technologies need to be carefully evaluated. Specific features of OO technologies such as information hiding and close tying of data structures with class structures and the natural peculiarities of the spatial data require revisiting of test strategies for spatial applications built on OO technology. This article focuses on object-oriented testing trends and the development of associated tools in the GIS industry.     

基于过程的空间环境数据模型

针对现有时空数据模型的不足之处,该文在分析空间环境数据特点的基础上,将过程思想引入空间环境数据模型的研究中,将空间环境过程概括为点过程、线过程、面过程和场过程四类过程对象,并以此建立其逻辑模型和物理模型,并给出时空过程插值与聚合、查询和提取等时空分析方法,最后实例验证的结果表明:基于过程的空间环境数据模型可有效组织、管理空间环境数据。     

统计分析模型管理工具实现及其在空间辅助决策系统中的应用

本文分析了统计分析模型在空间辅助决策系统应用中存在的问题,以统计学知识为基础,借鉴软件发展的新技术,提出了统计分析模型管理工具实现策略,着重论述了如何实现统计分析模型管理工具、模型的存储方法以及应用接口,并给出了该工具的应用实例。该工具能够动态管理各种统计分析模型、管理统计数据以及统计分析结果显示表达等功能,在应用方面提供了工具型与服务型的两类应用接口,可以满足不同应用层次的用户需求,使统计分析模型可以更加方便的应用到空间辅助决策系统中。     

全球格网系统的元数据管理模型

空间元数据管理技术是海量空间数据组织和管理的关键技术之一,是全球格网系统中实现地理数据有效组织和快速搜索的主要解决途径之一,与空间数据的共享与分发关系十分密切。从全球格网系统角度出发,对空间元数据的定义、内容、理论体系等方面进行了较为详细的阐述,并根据球面剖分的特点,对元数据管理模型及其解决方案进行了深入研究,为海量数据的组织和分发提供行之有效的管理方法。     

RS与GIS一体化数据结构的研究

详细阐述了RS与GIS一体化的概念,通过对RS与GIS一体化方面的研究与分析,进一步明确RS与GIS一体化对空间数据存储结构的要求,着重探讨了几种典型的用于RS与GIS一体化的数据结构,针对现有数据结构存在的问题与不足,提出了一种具有普遍适用价值的基于语义网络的空间数据存储结构,并给出一个应用实例。     

智能化土地定级估价信息系统设计与实现

总结分析了当前系统中存在的主要问题,提出将GIS、SDM、ES和可视化等多种信息技术进行有机结合,共同构建具有智能特性和辅助决策功能的土地定级估价信息系统。给出了GIS、SDM、ES和可视化等技术集成的基本框架,设计了基于多种信息技术集成的土地定级估价信息系统的基本结构。采用VC++6.0和MO2.0结合开发了基于多种技术集成的土地定级估价信息系统。研究表明,系统定级估价工作流程简单,结果可靠,且具有良好的移植性、复用性、扩展性和广泛适应性,能较好地解决土地定级估价中土地信息缺失、定性因子量化困难等半结构和非结构化问题。     

一种GIS空间知识分析的影像纹理尺度提取算法

本文提出了一种基于GIS领域空间知识的影像纹理尺度提取方法:该方法分析了GIS领域知识辅助下人类对纹理特征的认知过程,对4个步骤的具体实现算法进行探讨;并选取海南省昌江县作为研究区域,实验证明了本方法的有效性,且与传统的枚举法相比,在性能相近的情况下其效率显著提高,更适合于大数据量遥感影像分类运算。     

史前连续文化聚落的决策树分类挖掘研究——以郑州-洛阳地区为例

利用C4.5决策树分类算法和GIS组件Super Map Objects,开发实现了基于连续文化序列的空间数据挖掘系统,运用此系统对郑州-洛阳地区史前四个连续文化时期的聚落进行了数据挖掘,提取了聚落遗址面积的分类规则,并根据这些分类规则和聚落的空间分布情况对四个文化时期的I级聚落进行对比分析,得出了I级聚落的空间分布特点,即I级聚落中的一些特大面积的聚落朝着中心聚落的方向发展。     

一种新的基于空间数据库的空间数据编辑处理方法

分析了空间数据编辑的处理现状和存在的问题,介绍了一种新的处理方法,结合Geostar 4.0的Oracle和SQLServer空间数据库系统实现了该方法的设计。     

基于Python的ArcGIS空间数据格式批处理转换工具开发

ArcGIS仅提供了单个文件的空间数据格式转换工具。本文首先研究基于Python的ArcGIS空间分析工具开发方式,进而以栅格数据转ASCII工具为例,给出其批处理工具的具体实现过程。     

ARAMANI – Decision-Support Tool for Selecting Optimal Participatory Mapping Method

Participatory mapping is an emerging practice in the community development discourse. With its roots in the Participatory Rural Appraisal, it brings active involvement of the community and subjectivity of non-cartographers into the spotlight. The crucial question is how one can choose the most optimal method for participatory mapping, taking into account the specific needs and assets of the community. In this paper, the author presents the ARAMANI tool, expert knowledge-based decision support system operating with 10 participatory mapping methods and experience of 172 survey responders. ARAMANI tool allows users to describe their community assets and needs while combining them with a value-based system for deciding which method to select. The tool is designed as a user-friendly webpage with guidelines and examples of best practices for each method.     

构建面向个性化服务的特大城市云空间数据中心

特大城市测绘地理信息数据具有数据海量、增长快速、多源异构、频繁使用的特点。随着大数据和Web2.0时代的到来,传统的空间数据存储管理与共享服务模式存在成果缺乏整合和挖掘、空间信息服务被动且无差别性等缺点,难以满足用户不断提高的空间数据内容、服务响应速度和服务质量的要求,也难以适应因人而异的个性化空间信息服务的需求。本文对个性化服务和云空间数据中心构建的关键技术进行了研究,提出了个性化空间数据情境应用模式,以及一种基于Web客户端的个人异构空间数据在线集成方法,基于NoSQL实现了个人空间数据与传统空间数据服务集成,并以北京市为例基于私有云构建了安全可靠、高效运行、可扩展、用户参与度高、提供个性化服务的特大城市云空间数据中心。     

总电子含量赤道异常变化特性分析

利用国际GNSS服务组织提供的总电子含量格网数据,从全球角度分析了电离层赤道异常的变化规律,并结合相关研究结论做了比较分析。首先,利用2011年3月21日(春分)的总电子含量格网数据分析了电离层赤道异常区域随时间变化的规律;然后,利用2000—2012年的总电子含量格网数据和太阳黑子数据,统计分析了120°E上空电离层赤道异常出现的地理纬度和强度的变化规律,并以2002年(太阳活动高年)和2008年(太阳活动低年)为例做了进一步分析。结果发现:电离层赤道异常区域随太阳直射点位置的变化,自东向西移动,分布在地磁赤道的两侧,具有南北半球的非对称特性;电离层赤道异常出现在当地时间T 12:00:00—T 16:00:00,日落后持续2~3h;电离层赤道异常峰值强度与太阳活动强度存在正相关关系;电离层赤道异常具有明显的季节变化规律,表现出了"半年度异常"和"冬季异常"现象。     

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).