Unified Platform About Information Issuing,Integration and Management of Meta-Database and Spatial-Database Based on Geology Metadata Standard

With the deepening informationization of Resources & Environment Remote Sensing geological survey conducted,some potential problems and deficiency are:(1) shortage of unified-planed running environment;(2) inconsistent methods of data integration;and(3) disadvantages of different performing ways of data integration.This paper solves the above problems through overall planning and design,constructs unified running environment, consistent methods of data integration and system structure in order to advance the informationization

Integration of Geological, Geophysical and Seismological Data for Seismic Hazard Assessment Using Spatial Matching Index

Probabilistic seismic hazard assessment (PSHA) takes into account as much data as possible for defining the initial seismic source zone model. In response to this, an algorithm has been developed for integration of geological, geophysical and seismological data through a spatial index showing the presence or absence of a potential seismic source feature in the input data. The spatial matching index (SMI) is calculated to define the coincidence of independent data showing any indications for existence of a fault structure. It is applied for hazard assessment of Bulgaria through quantification of the seismic potential of 416 square blocks, 20 × 20 km in size covering the entire territory of Bulgaria and extended by 20 km outside of the country borders. All operations are carried out in GIS environment using its capabilities to work with different types of georeferenced spatial data. Results show that the highest seismic potential (largest SMI) is observed in 56 block elements (13% of the territory) clearly delineating cores of the source zones. Partial match is registered in 98 block elements when one of the features is missing. Not any evidence for earthquake occurrence is predicted by our calculation in 117 elements, comprising 28% of the examined area. The quantitative parameter for spatial data integration which is obtained in the present research may be used to analyze information regardless of its type and purpose.

Full feature data model for spatial information network integration

In allusion to the difficulty of integrating data with different models in integrating spatial information, the characteristics of raster structure, vector structure and mixed model were analyzed, and a hierarchical vector-raster integrative full feature model was put forward by integrating the advantage of vector and raster model and using the object-oriented method. The data structures of the four basic features, i.e. point, line, surface and solid, were described. An application was analyzed and described, and the characteristics of this model were described. In this model, all objects in the real world are divided into and described as features with hierarchy, and all the data are organized in vector. This model can describe data based on feature, field, network and other models, and avoid the disadvantage of inability to integrate data based on different models and perform spatial analysis on them in spatial information integration.

Multi-Source Spatial Data Distribution Model and System Implementation

The Multi-source spatial data distribution is based on WebGIS, and it is an important part of multi-source geographic information management system. a new multi-source spatial data distribution model is proposed on the basis of multisource data storage model and by combining existing map distribution technology, The author developed a multi-source spatial data distribution system which based on MapGIS K9 by using this model and taking full advantage of interfacecode separating thinking and high efficiency characteristic of .net, so high-speed distribution of multi-source spatial data realized.

Overview of global monthly surface temperature data in the past century and preliminary integration

This paper analyzes the status of existing resources through extensive research and international cooperation on the basis of four typical global monthly surface temperature datasets including the climate research dataset of the University of East Anglia(CRUTEM3), the dataset of the U.S. National Climatic Data Center(GHCN-V3), the dataset of the U.S. National Aeronautics and Space Administration(GISSTMP), and the Berkeley Earth surface temperature dataset(Berkeley). China's first global monthly temperature dataset over land was developed by integrating the four aforementioned global temperature datasets and several regional datasets from major countries or regions. This dataset contains information from 9,519 stations worldwide of at least 20 years for monthly mean temperature, 7,073 for maximum temperature, and 6,587 for minimum temperature. Compared with CRUTEM3 and GHCN-V3, the station density is much higher particularly for South America, Africa,and Asia. Moreover, data from significantly more stations were available after the year 1990 which dramatically reduced the uncertainty of the estimated global temperature trend during 1990e2011. The integrated dataset can serve as a reliable data source for global climate change research.

THE INTEGRATED SPATIAL DATABASES OF GEOSTAR

GeoStar is the registered trademark of GIS software made by WTUSM in China.By means of the GeoStar,multi_scale images,DEMs,graphics and attributes integrated in very large seamless databases can be created,and the multi_dimensional dynamic visualization and information extraction are also available.This paper describes the fundamental characteristics of such huge integrated databases,for instance,the data models,database structures and the spatial index strategies.At last,the typical applications of GeoStar for a few pilot projects like the Shanghai CyberCity and the Guangdong provincial spatial data infrastructure (SDI) are illustrated and several concluding remarks are stressed.

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.

A Semantic-Sensitive Approach to Indoor and Outdoor 3D Data Organization

Building model data organization is often programmed to solve a specific problem,resulting in the inability to organize indoor and outdoor 3D scenes in an integrated manner.In this paper,existing building spatial data models are studied,and the characteristics of building information modeling standards(IFC),city geographic modeling language(CityGML),indoor modeling language(IndoorGML),and other models are compared and analyzed.CityGML and IndoorGML models face challenges in satisfying diverse application scenarios and requirements due to limitations in their expression capabilities.It is proposed to combine the semantic information of the model objects to effectively partition and organize the indoor and outdoor spatial 3D model data and to construct the indoor and outdoor data organization mechanism of“chunk-layer-subobject-entrances-area-detail object.”This method is verified by proposing a 3D data organization method for indoor and outdoor space and constructing a 3D visualization system based on it.

Enhanced permeability prediction in porous media using particle swarm optimization with multi-source integration

Accurately and efficiently predicting the permeability of porous media is essential for addressing a wide range of hydrogeological issues.However,the complexity of porous media often limits the effectiveness of individual prediction methods.This study introduces a novel Particle Swarm Optimization-based Permeability Integrated Prediction model(PSO-PIP),which incorporates a particle swarm optimization algorithm enhanced with dy-namic clustering and adaptive parameter tuning(KGPSO).The model integrates multi-source data from the Lattice Boltzmann Method(LBM),Pore Network Modeling(PNM),and Finite Difference Method(FDM).By assigning optimal weight coefficients to the outputs of these methods,the model minimizes deviations from actual values and enhances permeability prediction performance.Initially,the computational performances of the LBM,PNM,and FDM are comparatively analyzed on datasets consisting of sphere packings and real rock samples.It is observed that these methods exhibit computational biases in certain permeability ranges.The PSOPIP model is proposed to combine the strengths of each computational approach and mitigate their limitations.The PSO-PIP model consistently produces predictions that are highly congruent with actual permeability values across all prediction intervals,significantly enhancing prediction accuracy.The outcomes of this study provide a new tool and perspective for the comprehensive,rapid,and accurate prediction of permeability in porous media.

Integration system research and development for three-dimensional laser scanning information visualization in goaf

An integration processing system of three-dimensional laser scanning information visualization in goaf was developed. It is provided with multiple functions, such as laser scanning information management for goaf, cloud data de-noising optimization, construction, display and operation of three-dimensional model, model editing, profile generation, calculation of goaf volume and roof area, Boolean calculation among models and interaction with the third party soft ware. Concerning this system with a concise interface, plentiful data input/output interfaces, it is featured with high integration, simple and convenient operations of applications. According to practice, in addition to being well-adapted, this system is favorably reliable and stable.

Spatial data mining system for ore-forming prediction

The authors designed the spatial data mining system for ore-forming prediction based on the theory and methods of data mining as well as the technique of spatial database,in combination with the characteristics of geological information data.The system consists of data management,data mining and knowledge discovery,knowledge representation.It can syncretize multi-source geosciences data effectively,such as geology,geochemistry,geophysics,RS.The system digitized geological information data as data layer files which consist of the two numerical values,to store these files in the system database.According to the combination of the characters of geological information,metallogenic prognosis was realized,as an example from some area in Heilongjiang Province.The prospect area of hydrothermal copper deposit was determined.

THE STRATEGIES OF INTEGRATING SPATI AL DATA ANALYSIS AND GIS

The gap between SDA(Spatial Data Analysis)and GIS(Geographical Information Systems )existed for a long time.Presently this problem still remains in spite of a lot of theore tical and practical studies which tr y to find the solu-tion for it.The research background and current situation about how to in tegrate SDA and GIS are introduced at first.The main idea of this article is to make su re what is the best scheme to bridge th e gap between SDA and GIS and how to design it.There are a lot of factors to influ ence the standards to assess such a sc heme,for instance,the attitude of users and GIS developers,the framework and related functions of current available GI S software in the market and so on.But the two most important ones of them are effic iency and flexibility of the scheme i tself.Efficiency can be measured by the conve-nient extent and temporal length when it is used for carrying out SDA.Flex ibility means users can define their own SDA methods.The best integration schem e should satisfy the two standards at the same time.A group of functions,which can be combined to implement any SDA meth od,are defined in order to design such an integration scheme.The functio ns are divided into five classes according to their properties.

基于Spatial OLAP的城市交通综合管理系统设计与实现

空间联机分析处理技术将GIS与联机分析处理技术OLAP相结合,提供在空间维度上进行不同尺度钻取的解决方案——SOLAP。该文基于SOLAP技术,构建一个城市交通的综合管理系统,并在电子地图上展示不同区域、路段、时段的交通流信息,为交通管理者进行决策提供技术支持。

数据要素配置、区域一体化与经济高质量发展

选取2013—2022年我国30个省份面板数据为研究样本,运用空间计量模型、中介效应模型与门槛模型,分析数据要素配置与经济高质量发展的关系及区域一体化在其中的作用机制。结果表明:(1)数据要素配置与经济高质量发展均存在空间自相关性。(2)数据要素配置能够显著驱动经济高质量发展,且存在正向空间溢出效应。(3)数据要素配置能够提高区域一体化水平,进而助力经济高质量发展。(4)随着区域一体化水平不断提升,数据要素配置对经济高质量发展的促进作用渐趋增强。(5)数据要素配置对东部地区经济高质量发展的促进作用更显著。基于此,提出优化数据要素配置体系、完善区域一体化发展布局、制定区域差异化发展方针的建议,以期为缩小区域经济差距、助力经济高质量发展提供有效支持。

信息生态理论视角下城市数据要素市场就绪度评估

数据要素市场建设是落实数字中国和数字经济发展战略的重要基石。当前我国数据要素市场处于发展初期,数据资源储备丰富但市场发展存在高度的不均衡性,清楚认识数据要素市场发展状态具有重要的理论和实践意义。本文根据数据要素市场发展的初期性特征,提出数据要素市场就绪度概念,基于信息生态理论的“三元构成”设计指标框架,以城市为分析单元科学测度国内298个城市数据要素市场就绪度水平,进一步分析城市空间均衡性,评估区域竞争力与协调度发展水平。研究结果客观反映了当前我国数据要素市场发展的总体状况、问题和区域特征,为后续制定数据要素市场政策、推动全国数据要素市场一体化建设提供了依据。

基于WebGIS的油气勘探开发数据集成检索方法

数据集成检索是油气勘探开发数据信息化的重要手段,然而现行方法检索效果并不理想,且查准率也低。提出了基于WebGIS技术的油气勘探开发数据集成检索方法,采用网络爬虫技术采集油气勘探开发数据,通过转换及标准化处理数据格式,建立数据索引,采用对数据语义特征提取和分析的方法,检索到与检索语义相似的油气勘探开发数据。实验证明:新的数据集成检索方法折扣累计收益值在9以上,查准率在95%以上,在油气勘探开发数据基础检索方面具有良好的应用前景。

地质灾害多源基础数据结构体系及应用

地质灾害基础数据具有多源性、异构性、多尺度等特点,大量的数据没有形成统一的管理模式,共享程度较低。当前普遍施行的地质灾害数据管理,采用的是从多角度、多层面、多空间等对地质灾害体及其孕育环境表达的多尺度数据集,因此各类数据的表达形式、数据精度、数据质量、时间表达等多方面存在着较大的差异性。构建了地质灾害多源异构数据集成方法体系,系统总结了数据的结构特征与管理方法,结合数据结构特征,使用PostgreSQL数据库管理属性数据,使用MongoDB数据库集群进行管理,使用GeoServer平台进行空间数据服务发布。研发地质灾害大数据ETL工具,集成数据库驱动、数据库适配器、数据模型等模块,实现对多源异构地质灾害大数据的有效管理。研发了一体化数据管理可视化平台,实现对各类数据进行统一管理与集成,为地质灾害基础数据的统一管理提供了综合数据平台,为地质灾害的防灾减灾、应急决策等提供数据和平台支撑。

基于Oracle Spatial技术的地理信息管理与优化

针对MapX组件在管理地理信息时空间数据与属性数据相分离、数据管理及查询效率不高的问题,通过引入OracleSpatial空间数据管理技术,实现了属性数据和空间数据的一体化存储与管理。利用空间操作符进行空间邻近分析,提高了系统的稳定性和数据的查询速率,并针对空间数据转换时造成的信息丢失问题提出解决方法。该技术方案在航油公司EAM(enterprise asset management)系统中得到应用,并取得较好效果。

基于OO4O和VisualC++6.0实现Oracle9i Spatial中空间数据的操作

从OracleSpatial9i管理空间数据的优良特性出发,利用Oracle的OLE对象OO4O和VisualC++6.0的集成实现了对Oracle数据库中空间对象的读取和存储,以及空间对象拓扑关系和空间对象的查询,因此对深入研究基于OracleSpatial空间数据的管理方法有一定的指导作用。

基于兴趣点(POI)数据的产业链创新链空间布局及空间匹配性分析——以浙江省为例

基于POI数据,构建引入了服务能力和类别差异、服务半径和距离衰减效应的改进潜力模型,以浙江“415”先进制造业集群为样本测度产业链创新链的空间布局及空间匹配性。结果表明,世界级先进产业集群相比特色产业集群、传统优势产业相比新兴产业与创新链空间匹配性更高,省级相比国家级、基础研究和成果转化环节相比其他环节空间匹配性更高,且各集群在不同层级、环节上的空间匹配性差异较大。为此,从优化创新平台载体空间布局、重点产业“一群一策”及不同产业间强化协同方面提出了推进“双链”深度融合的相关建议。