首页 | 本学科首页   官方微博 | 高级检索  
相似文献
 共查询到20条相似文献，搜索用时 31 毫秒
1.
Moving object databases are designed to store and process spatial and temporal object data. An especially useful moving object type is a moving region, which consists of one or more moving polygons suitable for modeling the spread of forest fires, the movement of clouds, spread of diseases and many other real-world phenomena. Previous implementations usually allow a changing shape of the region during the movement; however, the necessary restrictions on this model result in an inaccurate interpolation of rotating objects. In this paper, we present an alternative approach for moving and rotating regions of fixed shape, called Fixed Moving Regions, which provide a significantly better model for a wide range of applications like modeling the movement of oil tankers, icebergs and other rigid structures. Furthermore, we describe and implement several useful operations on this new object type to enable a database system to solve many real-world problems, as for example collision tests, projections and intersections, much more accurate than with other models. Based on this research, we also implemented a library for easy integration into moving objects database systems, as for example the DBMS Secondo (1) (2) developed at the FernUniversität in Hagen.  相似文献   

2.
ABSTRACT

Geospatial data conflation is aimed at matching counterpart features from two or more data sources in order to combine and better utilize information in the data. Due to the importance of conflation in spatial analysis, different approaches to the conflation problem have been proposed ranging from simple buffer-based methods to probability and optimization based models. In this paper, I propose a formal framework for conflation that integrates two powerful tools of geospatial computation: optimization and relational databases. I discuss the connection between the relational database theory and conflation, and demonstrate how the conflation process can be formulated and carried out in standard relational databases. I also propose a set of new optimization models that can be used inside relational databases to solve the conflation problem. The optimization models are based on the minimum cost circulation problem in operations research (also known as the network flow problem), which generalizes existing optimal conflation models that are primarily based on the assignment problem. Using comparable datasets, computational experiments show that the proposed conflation method is effective and outperforms existing optimal conflation models by a large margin. Given its generality, the new method may be applicable to other data types and conflation problems.  相似文献   

3.
A spatial data set is consistent if it satisfies a set of integrity constraints. Although consistency is a desirable property of databases, enforcing the satisfaction of integrity constraints might not be always feasible. In such cases, the presence of inconsistent data may have a negative effect on the results of data analysis and processing and, in consequence, there is an important need for data-cleaning tools to detect and remove, if possible, inconsistencies in large data sets. This work proposes strategies to support data cleaning of spatial databases with respect to a set of integrity constraints that impose topological relations between spatial objects. The basic idea is to rank the geometries in a spatial data set that should be modified to improve the quality of the data (in terms of consistency). An experimental evaluation validates the proposal and shows that the order in which geometries are modified affects both the overall quality of the database and the final number of geometries to be processed to restore consistency.  相似文献   

4.
Systems for landscape visualization and geographical data handling require methods for efficient data access. Retrieval of data from large geographical databases, ten to thousands of Gbytes, is usually optimized with spatial indexing mechanisms. The simplest form of spatial indexing is achieved by dividing the database into congruent grid cells. The subsequent subdivision of the grid cells can be based on so-called quadtrees. Quadtrees for two-dimensional division and subdivision are appropriate for cartographical data. A geographical database, with objects stored in geocentric or geodetic (geographical) co-ordinates, requires indexing mechanisms that take into account the shape of the Earth. In this paper, we present a method for indexing of geographical data, named Ellipsoidal Quadtrees (EQT). In contrast to other global indexing methods, EQT is based on the Earth ellipsoid and not a spherical approximation. EQT division and subdivision make it possible to divide the Earth surface into a mesh of quadrangles with equal areas. We will demonstrate that EQT is flexible. It can be used for indexing databases of various sizes, including national and global databases. Tests on real data show that the performance of EQT is good.  相似文献   

5.
在研究分析地址模型的基础上,建立了存储标准地址数据集的标准地址库和自定义的地址匹配规则库,提出了一种基于规则的模糊中文地址编码方法。该方法在依据标准地址库分词的同时,也沿着自定义的地址匹配规则进行推理,从而缩小了下次分词所用到的目标数据集,提高了系统执行效率。另外,通过借助构建的规则树与歧义栈,提高了文中定义的两类模糊地址匹配的成功率。最后,基于该算法建立了一个地理编码原型系统,并利用经济普查项目中的相关数据对算法的可用性进行了验证。  相似文献   

6.
ABSTRACT

The analysis of geographically referenced data, specifically point data, is predicated on the accurate geocoding of those data. Geocoding refers to the process in which geographically referenced data (addresses, for example) are placed on a map. This process may lead to issues with positional accuracy or the inability to geocode an address. In this paper, we conduct an international investigation into the impact of the (in)ability to geocode an address on the resulting spatial pattern. We use a variety of point data sets of crime events (varying numbers of events and types of crime), a variety of areal units of analysis (varying the number and size of areal units), from a variety of countries (varying underlying administrative systems), and a locally-based spatial point pattern test to find the levels of geocoding match rates to maintain the spatial patterns of the original data when addresses are missing at random. We find that the level of geocoding success depends on the number of points and the number of areal units under analysis, but generally show that the necessary levels of geocoding success are lower than found in previous research. This finding is consistent across different national contexts.  相似文献   

7.
魏希文  缪丽娟  江源  崔雪锋 《地理学报》2016,71(7):1144-1156
网格化历史耕地数据集能为历史时期耕地变化研究提供更精确的支持,并且为全球环境气候变化研究模型模拟提供驱动数据。本文综合考虑了中国历代土地利用开发的特点及自然人文因子对耕地的影响,设计了一套对中国耕地先分区再分层分配的网格化方法。基于国内3个主流区域耕地数据研究成果,采用上述方法建立了1820年（清仁宗嘉庆二十五年）和1936年（民国二十五年）中国10 km×10 km分辨率的耕地数据集,并绘制了分布图。本文还利用国内具有代表性的区域数据集对重建结果进行对比验证。结果表明,该方法可以保证耕地数量的权威性,并且建立具有区域性的高精度历史耕地数据集。  相似文献   

8.
Data modelling is a critical stage of database design. Recent research has focused upon object-oriented data models, which appear more appropriate for certain applications than either the traditional relational model or the entity-relationship approach. The object-oriented approach has proved to be especially fruitful in application areas, such as the design of geographical information systems which have a richly structured knowledge domain and are associated with multimedia databases. This article discusses the key concepts in object-oriented modelling and demonstrates the applicability of an object-oriented design methodology to the design of geographical information systems. In order to show more clearly how this methodology may be applied, the paper considers the specific object-oriented data model IFO. Standard cartographic primitives are represented using IFO, which are then used in the modelling of some standard administrative units in the United Kingdom. The paper concludes by discussing current research issues and directions in this area.  相似文献   

9.
通过对极地海洋数据的特征及应用需求分析,基于"一种架构支持多类应用"的传统数据库模式已无法满足需求,本文提出采用"多种架构支持多类应用"模式的数据库设计理念,通过研究极地海洋数据分类分层管理体系,开展极地海洋原始数据层、基础数据层、综合数据层、成果数据层的存储管理机制、数据库体系架构设计、数据库模型设计等关键技术研究,开发数据库查询检索功能,满足用户对极地海洋数据的多样化查询检索、空间可视化展示、关联分析等需求,实现极地海洋数据的有效存储、高效应用和开放共享。  相似文献   

10.
Map databases traditionally capture snapshot representations of the world following strict data collection and representation guidelines. The content of these map databases is often assessed using data quality metrics focusing on accuracy, completeness and consistency. The success of volunteered geographic information, supporting evolving representations of the world based on fluid guidelines, has rendered these measures insufficient. In this paper, we address the need to capture the variability in quality of a map database. We propose a new spatial data quality measure – dataset maturity – enabling assessment of the database based on temporal trends in feature definitions, specifically geometry-type definitions. The proposed measure can be (1) efficiently used to identify feature definition patterns reflecting community consensus that could be formalised in community guidelines and (2) deployed to identify regions that would benefit from increased editorial activity to achieve greater map homogeneity. We demonstrate the measure based on the content of the OpenStreetMap database in four regions of the world and show how the proposed dataset maturity measure captures a distinct quality of the datasets, distinct to data completeness and consistency.  相似文献   

11.
In many applications of Geographical Information Systems (GIS) a common task is the conversion of addresses into grid coordinates. In many countries this is usually accomplished using address range TIGER-type files in conjunction with geocoding packages within a GIS. Improvements in GIS functionality and the storage capacity of large databases mean that the spatial investigation of data at the individual address level is now commonly performed. This process relies on the accuracy of the geocoding mechanism and this paper examines this accuracy in relation to cadastral records and census tracts. Results from a study of over 20 000 addresses in Sydney, Australia, using a TIGER-type geocoding process suggest that 5-7.5% (depending on geocoding method) of addresses may be misallocated to census tracts, and more than 50% may be given coordinates within the land parcel of a different property.  相似文献   

12.
Environmental simulation models need automated geographic data reduction methods to optimize the use of high-resolution data in complex environmental models. Advanced map generalization methods have been developed for multiscale geographic data representation. In the case of map generalization, positional, geometric and topological constraints are focused on to improve map legibility and communication of geographic semantics. In the context of environmental modelling, in addition to the spatial criteria, domain criteria and constraints also need to be considered. Currently, due to the absence of domain-specific generalization methods, modellers resort to ad hoc methods of manual digitization or use cartographic methods available in off-the-shelf software. Such manual methods are not feasible solutions when large data sets are to be processed, thus limiting modellers to the single-scale representations. Automated map generalization methods can rarely be used with confidence because simplified data sets may violate domain semantics and may also result in suboptimal model performance. For best modelling results, it is necessary to prioritize domain criteria and constraints during data generalization. Modellers should also be able to automate the generalization techniques and explore the trade-off between model efficiency and model simulation quality for alternative versions of input geographic data at different geographic scales. Based on our long-term research with experts in the analytic element method of groundwater modelling, we developed the multicriteria generalization (MCG) framework as a constraint-based approach to automated geographic data reduction. The MCG framework is based on the spatial multicriteria decision-making paradigm since multiscale data modelling is too complex to be fully automated and should be driven by modellers at each stage. Apart from a detailed discussion of the theoretical aspects of the MCG framework, we discuss two groundwater data modelling experiments that demonstrate how MCG is not just a framework for automated data reduction, but an approach for systematically exploring model performance at multiple geographic scales. Experimental results clearly indicate the benefits of MCG-based data reduction and encourage us to continue expanding the scope of and implement MCG for multiple application domains.  相似文献   

13.
Several application domains require handling spatio‐temporal data. However, traditional Geographic Information Systems (GIS) and database models do not adequately support temporal aspects of spatial data. A crucial issue relates to the choice of the appropriate granularity. Unfortunately, while a formalisation of the concept of temporal granularity has been proposed and widely adopted, no consensus exists on the notion of spatial granularity. In this paper, we address these open problems, by proposing a formal definition of spatial granularity and by designing a spatio‐temporal framework for the management of spatial and temporal information at different granularities. We present a spatio‐temporal extension of the ODMG type system with specific types for defining multigranular spatio‐temporal properties. Granularity conversion functions are introduced to obtain attributes values at different spatial and temporal granularities.  相似文献   

14.
Urban land use information plays an important role in urban management, government policy-making, and population activity monitoring. However, the accurate classification of urban functional zones is challenging due to the complexity of urban systems. Many studies have focused on urban land use classification by considering features that are extracted from either high spatial resolution (HSR) remote sensing images or social media data, but few studies consider both features due to the lack of available models. In our study, we propose a novel scene classification framework to identify dominant urban land use type at the level of traffic analysis zone by integrating probabilistic topic models and support vector machine. A land use word dictionary inside the framework was built by fusing natural–physical features from HSR images and socioeconomic semantic features from multisource social media data. In addition to comparing with manual interpretation data, we designed several experiments to test the land use classification accuracy of our proposed model with different combinations of previously acquired semantic features. The classification results (overall accuracy = 0.865, Kappa = 0.828) demonstrate the effectiveness of our strategy that blends features extracted from multisource geospatial data as semantic features to train the classification model. This method can be applied to help urban planners analyze fine urban structures and monitor urban land use changes, and additional data from multiple sources will be blended into this proposed framework in the future.  相似文献   

15.
The integration of multisource heterogeneous spatial data is one of the major challenges for many spatial data users. To facilitate multisource spatial data integration, many initiatives including federated databases, feature manipulation engines (FMEs), ontology-driven data integration and spatial mediators have been proposed. The major aim of these initiatives is to harmonize data sets and establish interoperability between different data sources.

On the contrary, spatial data integration and interoperability is not a pure technical exercise, and there are other nontechnical issues including institutional, policy, legal and social issues involved. Spatial Data Infrastructure (SDI) framework aims to better address the technical and nontechnical issues and facilitate data integration. The SDIs aim to provide a holistic platform for users to interact with spatial data through technical and nontechnical tools.

This article aims to discuss the complexity of the challenges associated with data integration and propose a tool that facilitates data harmonization through the assessment of multisource spatial data sets against many measures. The measures represent harmonization criteria and are defined based on the requirement of the respective jurisdiction. Information on technical and nontechnical characteristics of spatial data sets is extracted to form metadata and actual data. Then the tool evaluates the characteristics against measures and identifies the items of inconsistency. The tool also proposes available manipulation tools or guidelines to overcome inconsistencies among data sets. The tool can assist practitioners and organizations to avoid the time-consuming and costly process of validating data sets for effective data integration.  相似文献   

16.
修文群 《地理研究》2006,25(5):939-948
当前急剧增长的网络犯罪行为与有限警力、人工监控之间的结构性矛盾日益突出,针对网络犯罪的广泛性、隐蔽性、超时空性等特点,迫切需要开发应用先进技术手段,建立“网络犯罪空间管理系统”,使打击网络犯罪从突发事件、被动应对走向重点监控、主动预防。从当前公安网监部门实际需求出发,以地理信息系统为核心,结合网络搜索、IP追踪技术,建立“网络犯罪空间数据库”,进行相关空间数据挖掘,探索网络犯罪要素的空间结构、空间行为及其与环境间互动关系,以制定打击防范的对策方案。  相似文献   

17.
A Monte Carlo approach is used to evaluate the uncertainty caused by incorporating Post Office Box (PO Box) addresses in point‐cluster detection for an environmental‐health study. Placing PO Box addresses at the centroids of postcode polygons in conventional geocoding can introduce significant error into a cluster analysis of the point data generated from them. In the restricted Monte Carlo method I presented in this paper, an address that cannot be matched to a precise location is assigned a random location within the smallest polygon believed to contain that address. These random locations are then combined with the locations of precisely matched addresses, and the resulting dataset is used for performing cluster analysis. After repeating this randomization‐and‐analysis process many times, one can use the variance in the calculated cluster evaluation statistics to estimate the uncertainty caused by the addresses that cannot be precisely matched. This method maximizes the use of the available spatial information, while also providing a quantitative estimate of the uncertainty in that utilization. The method is applied to lung‐cancer data from Grafton County, New Hampshire, USA, in which the PO Box addresses account for more than half of the address dataset. The results show that less than 50% of the detected cluster area can be considered to have high certainty.  相似文献   

18.
ABSTRACT

Air pollution has become a serious environmental problem causing severe consequences in our ecology, climate, health, and urban development. Effective and efficient monitoring and mitigation of air pollution require a comprehensive understanding of the air pollution process through a reliable database carrying important information about the spatiotemporal variations of air pollutant concentrations at various spatial and temporal scales. Traditional analysis suffers from the severe insufficiency of data collected by only a few stations. In this study, we propose a rigorous framework for the integration of air pollutant concentration data coming from the ground-based stations, which are spatially sparse but temporally dense, and mobile sensors, which are spatially dense but temporally sparse. Based on the integrated database which is relatively dense in space and time, we then estimate air pollutant concentrations for given location and time by applying a two-step local regression model to the data. This study advances the frontier of basic research in air pollution monitoring via the integration of station and mobile sensors and sets up the stage for further research on other spatiotemporal problems involving multi-source and multi-scale information.  相似文献   

19.
面向对象整体GIS数据模型的设计与实现   总被引：18，自引：4，他引：18  
本文在前期GIS概念数据模型研究的基础上 ,提出了面向对象整体GIS数据模型 ,并针对整体GIS软件的实现在系统数据组织、存储结构与访问机制方面进行了较为深入的探讨 ,Deskpro最后简单介绍了基于整体GIS数据模型的商品化软件———SuperMapDeskpro的实现情况  相似文献   

20.
There has been a resurgence of interest in time geography studies due to emerging spatiotemporal big data in urban environments. However, the rapid increase in the volume, diversity, and intensity of spatiotemporal data poses a significant challenge with respect to the representation and computation of time geographic entities and relations in road networks. To address this challenge, a spatiotemporal data model is proposed in this article. The proposed spatiotemporal data model is based on a compressed linear reference (CLR) technique to transform network time geographic entities in three-dimensional (3D) (x, y, t) space to two-dimensional (2D) CLR space. Using the proposed spatiotemporal data model, network time geographic entities can be stored and managed in classical spatial databases. Efficient spatial operations and index structures can be directly utilized to implement spatiotemporal operations and queries for network time geographic entities in CLR space. To validate the proposed spatiotemporal data model, a prototype system is developed using existing 2D GIS techniques. A case study is performed using large-scale datasets of space-time paths and prisms. The case study indicates that the proposed spatiotemporal data model is effective and efficient for storing, managing, and querying large-scale datasets of network time geographic entities.  相似文献   

设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号