基于GeoDatabase和ArcSDE的GIS数据库技术研究与应用

空间数据库是目前地理信息系统（GIS）应用的一个很重要的部分,其中空间数据库引擎（SDE）作为中间件连接GIS应用程序和关系数据库系统．较好地解决了空间数据和属性数据统一存储和管理的问题。本文以ArcSDE为空间数据引擎,用Oracle9i数据库管理数据,实现了空间数据和属性数据的有效组织和管理,在基础地理信息系统项目中得到了很好的应用。     

基于GIS的灾害应急管理系统的数据集成研究

常用的关系数据库缺乏直接管理空间数据的成熟通用方案。借助于空间数据库引擎(SDE)技术,扩展关系数据库功能,使关系数据库成为业务数据和空间数据的统一存储管理平台,并在此基础上建立基于Geodatabase模型的灾害应急管理系统数据库,对系统数据整体结构进行研究设计,解决了空间数据和业务数据的关联问题,实现灾害应急管理系统空间数据和业务数据的无缝集成和一体化存储。该方法已在省级应急管理信息示范平台上成功应用。     

基于ArcSDE的空间数据库技术的应用研究

空间数据库是目前地理信息系统(GIS)应用的一个很重要的部分，其中空间数据库引擎(SDE)作为中间件连接GIS应用程序和关系数据库系统，较好地解决了空间数据和属性数据统一存储和管理的问题。通过清江水情仿真和水电综合调度系统空间数据库的设计过程阐述了其中的一些关键技术。     

空间数据插件技术研究

利用数据库技术来管理海量的空间数据,有两种方法一种是在数据库和用户应用系统间建立中间层,称为空间数据引擎SDE,利用SDE作为中间接口使数据库操作系统能存储和管理空间数据;另一种是不需要中间接口而直接对数据库操作系统自身的功能进行扩展来存储管理空间数据,典型的代表就是Oracle公司提供的空间数据插件(Spatial).由此看SDE和Oracle Spatial好像是互斥的,取其一即可;实际上二者在处理空间数据的角度上定位不同,并不是互斥的,而是可以相互结合的,用户可以根据自己的具体应用来决定是选其一还是将二者结合.     

空间数据插件技术研究

利用数据库技术来管理海量的空间数据,有两种方法:一种是在数据库和用户应用系统间建立中间层,称为空间数据引擎SDE,利用SDE作为中间接口使数据库操作系统能存储和管理空间数据;另一种是不需要中间接口而直接对数据库操作系统自身的功能进行扩展来存储管理空间数据,典型的代表就是Oracle公司提供的空间数据插件(Spa-tial)。由此看SDE和OracleSpatial好像是互斥的,取其一即可;实际上二者在处理空间数据的角度上定位不同,并不是互斥的,而是可以相互结合的,用户可以根据自己的具体应用来决定是选其一还是将二者结合。     

GeoDB空间数据库存储体系设计与实现

1 引言 GeoDB的空间数据库方案基于多源空间数据无缝集成技术。为了适应不同层次存储和管理空间数据的需要,GeoDB空间数据库支持多种实现方案。根据源数据库的不同,空间数据库主要分为两种:(1)源数据库需自定义数据结构;(2)源数据库已提供空间存储方案(如Oracle、SDE)。本文主要探讨前一种空间数据库的存储体系的设计和实现。     

.NET下基于OO4O核心的Oracle Spatial空间数据互操作

Oracle Spatial是Oracle中内嵌的空间数据库索引技术(SDE),它扩展了Oracle数据库对空间数据的管理.讨论了在.NET框架下利用OO4O核心--OO4O进程内自动化服务器,实现对Oracle Spatial的空间数据读写操作,介绍了该方法的实现机理及关键技术,举例并给出了可视化互操作的结果.     

实现ArcSDE向Oracle9i Spatial空间数据的转换

通过空间数据库引擎技术(SDE)可以有效地实现空间数据在数据库中的管理。但各种空间数据库引擎在储存数据格式上的不一致,影响各引擎相互间数据操作的效率。为了解决这一问题,以ESRI公司的ArcSDE和Oracle公司的Oracles Spatial为例,通过分析以上两种空间数据库引擎的数据格式,解决了从AreSDE向Oracle9i Spatial的空间数据的转换。     

基于RDBMS的地理信息集成数据库系统

在介绍空间数据库基本概念的基础上，分析了ESR的空间数据库引擎SDE（Spatial Database Engine)，提出了一种空间数据库结构模型，将空间数据和属性数据集成在数据库中，分析了数据模型体系结构，数据组织以及空间图形要素表达，进而根据该结构模型实现了在关系型数据库中对空间图形数据进行表示，存储和分析的操作。     

基于ArcSDE的空间数据库设计与实现

探讨了SDE技术的原理,提出了基于ArcSDE的“吐鲁番GIS数据库”系统的建设方案。通过有效的数据存储和数据库管理设计,依托GIS方法和数据库技术,所实现的数据库系统具备了完整的空间数据存储和管理功能。设计实现了基于MapObjects组件的功能客户端,最终形成了一个完整的空间数据库系统。     

多源地理大数据视角下的城市动态研究

海量具有个体标记和时空语义信息的地理大数据,为我们定量理解城市提供了手段。利用时空模式挖掘的方法,集成多源地理大数据中的个体时空间行为特征,在聚合层面揭示城市社会经济现象的分布、联系和过程等规律,可以实现城市的动态感知。本文梳理了目前城市研究中常见地理大数据的优缺点和应用场景,归纳了基于地理大数据感知城市动态的思路,介绍了相关的代表性研究成果,并对地理大数据的前景进行了探讨与展望。     

基于ArcSDE道路信息管理系统的设计与实现

空间数掂库引擎是实现空间数据库的核心，能有效存储和管理空间数据。文章以空间数据库引擎技术的研究为起点，对ArcSDE技术的理论体系进行阐述，并开发了基于ArcSDE的道路信息管理系统，证明了ArcSDE技术在道路信息系统中运用的可行性，解决了GIS应用与空间数据库集成的制约瓶颈问题，实现了海量、分布式空间数据的有效管理。     

A framework for extracting urban functional regions based on multiprototype word embeddings using points-of-interest data

Many studies are in an effort to explore urban spatial structure, and urban functional regions have become the subject of increasing attention among planners, engineers and public officials. Attempts have been made to identify urban functional regions using high spatial resolution (HSR) remote sensing images and extensive geo-data. However, the research scale and throughput have also been limited by the accessibility of HSR remote sensing data. Recently, big geo-data are becoming increasingly popular for urban studies since research is still accessible and objective with regard to the use of these data. This study aims to build a novel framework to provide an alternative solution for sensing urban spatial structure and discovering urban functional regions based on emerging geo-data – points of interest (POIs) data and an embedding learning method in the natural language processing (NLP) field. We started by constructing the intraurban functional corpus using a center-context pairs-based approach. A word embeddings representation model for training that corpus was used to extract multiprototype vectors in the second step, and the last step aggregated the functional parcels based on an introduced spatial clustering method, hierarchical density-based spatial clustering of applications with noise (HDBSCAN). The clustering results suggested that our proposed framework used in this study is capable of discovering the utilization of urban space with a reasonable level of accuracy. The limitation and potential improvement of the proposed framework are also discussed.     

Structured Development Environment Based on the Object-Oriented Concepts

The object-oriented software development is a kind of promising software methodology and leading to a wholly new way for solving problems.In the research on the rapid construction of Structured Development Environment(SDE)that supports detailed design and coding in software development,a generator that can generate the SE has been applied as a metatool.The kernel of SDE is a syntax-directed editor based on the object-oriented concepts.The key issue in the design of SDE is how to represent the elements of target language with the class concept and a program internally.In this paper,the key concepts and design of the SDE and its generator as well as the implementation of a prototype are to be discussed.     

Heuristics for a two-stage assembly flowshop with bicriteria of maximum lateness and makespan

We consider a two-stage assembly flowshop scheduling problem with the objective of minimizing a weighted sum of makespan and maximum lateness. The problem is known to be NP-hard, and therefore, we propose heuristics to solve the problem. The proposed heuristics are Tabu search (Tabu), particle swarm optimization (PSO), and self-adaptive differential evolution (SDE). An extensive computational experiment is conducted to compare performances of the proposed heuristics. The computational experiment reveals that both PSO and SDE are much superior to Tabu. Moreover, it is statistically shown that PSO performs better than SDE. The computation times of both PSO and SDE are close to each other and they are less than 40 and 45 s, respectively, for the largest size problem considered.     

Inferring demographics from human trajectories and geographical context

The advances of positioning technologies and the widespread use of mobile devices bring us massive data with location information, or so-called big geo-data. One important part of big geo-data is massive digital human trajectories recorded by location-enabled mobile terminals and social apps. Digital human trajectories have been studied to learn more about human mobility and human activity. Existing research has shown that there exist strong associations between trajectory patterns and demographics. Given that demographics are essential information to various domains but not easy to acquire timely and on a large scale, inferring demographics from human trajectories has attracted attention from academia. In this paper, we proposed a demographics inferring framework suitable for big geo-data processing. Trajectory patterns were quantified from both spatiotemporal and semantic perspectives. Spatiotemporal features extracted from trajectories directly were used for capturing how people traveled in space and time. Semantic features obtained by attaching geographical context to trajectories were to reflect activities people conducted. Spatiotemporal and semantic features were organized into feature vectors and then input to supervised classification models to infer demographics. GPS trajectories and land use data in Beijing were used to validate the framework. Results show that the inference accuracies of marital status and residency status achieve 80% and thus prove the feasibility of our framework. This study can facilitate decision making in both business and social studies, such as personalized recommendation, commercial site selection and urban planning.     

多源GIS数据关联集成技术研究——以市政管线行业为例

分析了现有多源GIS数据集成模式的原理与不足,提出了一种新的集成技术,即多源GIS数据关联集成技术,该技术通过空间数据直接读取引擎和属性数据导入引擎将地理数据集成到GIS系统中,并且通过空间和属性关联机制实现了多源GIS数据图形、属性和功能的一体化集成.     

Opposition-based learning in the shuffled differential evolution algorithm

This paper proposes using the opposition-based learning (OBL) strategy in the shuffled differential evolution (SDE). In the SDE, population is divided into several memeplexes and each memeplex is improved by the differential evolution (DE) algorithm. The OBL by comparing the fitness of an individual to its opposite and retaining the fitter one in the population accelerates search process. The objective of this paper is to introduce new versions of the DE which, on one hand, use the partitioning and shuffling concepts of SDE to compensate for the limited amount of search moves of the original DE and, on the other hand, employ the OBL to accelerate the DE without making premature convergence. Four versions of DE algorithm are proposed based on the OBL and SDE strategies. All algorithms similarly use the opposition-based population initialization to achieve fitter initial individuals and their difference is in applying opposition-based generation jumping. Experiments on 25 benchmark functions designed for the special session on real-parameter optimization of CEC2005 and non-parametric analysis of obtained results demonstrate that the performances of the proposed algorithms are better than the SDE. The fourth version of proposed algorithm has a significant difference compared to the SDE in terms of all considered aspects. The emphasis of comparison results is to obtain some successful performances on unsolved functions for the first time, which so far have not been reported any successful runs on them. In a later part of the comparative experiments, performance comparisons of the proposed algorithm with some modern DE algorithms reported in the literature confirm a significantly better performance of our proposed algorithm, especially on high-dimensional functions.     

Stability of regime-switching stochastic differential equations

The main result is reduction of the asymptotic stability problem for a stochastic differential equation (SDE) with sufficiently rapid Markovian switching to the analogous wellstudied problem for the ??averaged?? SDE without switching. Applications to the switching stabilization problem and to ordinary differential equations (ODE) with switching are also considered.     

Design and development of Distributed Virtual Geographic Environment system based on web services

This paper aims to design and develop a Distributed Virtual Geographic Environment (DVGE) system. A DVGE system is an Internet-based virtual 2D and 3D environment that provides users with a shared space and a collaborative platform for publishing multidimensional geo-data, and for simulating and analyzing complex geo-phenomena. Users logging into the system from different clients can share distributed geo-information resources, including geo-data and geo-models, and can complete collaborative tasks. Web service technology provides effective solutions for constructing DVGE systems because of its ability to support multi-platform, multi-architecture, and multi-program-language interoperability on the Internet, but also because of its ability to share programs, data, and software. This paper analyzes the characteristics, relevant technologies, and specifications of web services, such as grid services, Open Geo-data Interoperability Specifications (OpenGIS), and Geography Markup Languages (GML). The architecture and working mechanisms of the DVGE system based on web services are then elaborated. To demonstrate DVGE systems based on web services, we examine a case study of water pollution in Yangzhou City, Jiangsu Province, China, using a prototype DVGE system that is developed with Jbuilder9.0 and Java3D 1.0 packages, and the Weblogic platform 8.1.