Spatial Database Management System Research Articles

A Proposal to Expand the Community of Users Able to Process Historical Rainfall Data by Means of the Today Available Open Source Libraries

The paper presents a software architecture based on open source technologies, implemented by the authors in an experience of processing spatio-temporal data gathered by rain gauges spread across two regions of central Italy. The interest in the automatic processing of data about precipitation is widespread, however, today only an inner circle of stakeholders can think of taking advantage of the available open source libraries because a strong programming skill is required to use them. It is opinion of the authors that the implemented software architecture is suitable for expanding the community of users able to process “by themselves” historical precipitation data. The centre of the architecture is the technology of the spatial database management systems. They offer full support for the creation and management of a spatial database suitable to store the rainfall data usually spread out in several files. Moreover, they allow adding to such a repository a large set of ad hoc “objects” oriented to carrying out spatio-temporal computations on the precipitation. The stakeholders are only required to familiarize with the database’s objects and invoke their execution. A large part of the paper is devoted to show how the adopted conceptual setting can assist nontechnical users in carrying out personalized computations on rain gauges data. The computing needs posed by the experience described in this paper are common to many other areas of high social impact that involve spatio-temporal data, hence we believe that the implemented framework can be exported to them, keeping unaltered operational effectiveness.

A hybrid risk-aware design method for spatial datacubes handling spatial vague data: implementation and validation

Spatial data warehouses SDWs and spatial OLAP SOLAP are well-known business intelligence BI technologies that aim to support multidimensional and online analysis of huge volumes of data with spatial reference. Spatial vagueness is one of the most neglected imperfections of spatial data. Although several works propose new ad-hoc models for handling spatial vagueness, their implementation in spatial database management systems DBMS and SDW is still in an embryonic state. In this paper, we present a new design method for SOLAP datacubes that allows handling vague spatial data analysis issues. This method relies on a risk management method applied to the potential risks of data misinterpretation and decision makers' tolerance levels to those risks. We also present a tool implementing our method and a validation of the method is done based on the designed datacubes schemas testing.

Design of a standardized geo-database for risk monitoring of potentially polluting marine sites

An increasing availability of geospatial marine data provides an opportunity for hydrographic agencies to contribute to the identification of potentially polluting marine sites (PPMS). This new acronym has been created not only to refer to shipwrecks of modern vessels, but also for other types of marine sites such as dumping areas, pipelines, etc. Independent of the specific type, a PPMS represents a potential source of pollution for the marine environment. Although several type-specific databases are available worldwide (from local to global scale), there is an evident lack of uniformity (e.g., different aims of data collection). A common approach description of these sites at local single-site level may permit aggregation for multi-scale decisions, e.g., for remediation and incident response. To adequately manage these sites, a standardized PPMS geospatial database (GeoDB) application has been designed to collect relevant information suitable for site inventory and geo-spatial analysis. In particular, benefits in structuring the data in conformance with the Universal Hydrographic Data Model (IHO S-100) and encoding using the Geographic Markup Language (GML) are presented. A possible practical storage solution is proposed using a GML-enabled spatial relational database management system. Finally, a Web GIS deployment is illustrated, being the simplest way to communicate to the public the collected information, with the related possibility of using the data as a Web Map Service in almost any GIS, allowing for better development and integration with other available datasets. The adoption of the PPMS GeoDB product specification as part of the IHO S-100 series would represent an innovative and important contribution from the hydrographic community to reduce, or at least better manage, environmental and economic risks related to PPMSs.

A Spatial Database Management System for Urban and Rural Planning

The data management of urban and rural planning is very important and special. It is quite necessary to customize a thematic database system for urban and rural planning. According to their characteristics and classifications, the requirements of this system are firstly analyzed in this paper. With the integration of traditional relation database management system and geographical information system, an extendable data model for this thematic database is proposed. In this model, Client/Server architecture is adopted, Oracle is extended to store both attribute data and spatial data, and spatial database engine is utilized to access the spatial data in Oracle. At the client side, some functional modules such as data import and export, browse and display, query and retrieval, update and maintain, and security management are designed and developed. Finally, a case study of the thematic database system is applied. It is concluded that the customized spatial database management system for urban and rural planning is not only able to unify and store all types of data, but also able to improve the efficiency and visualization.

Towards integration of 3D legal and physical objects in cadastral data models

Digital 3D cadastres are often envisaged as the visualisation of 3D property rights (legal objects) and to some extent, their physical counterparts (physical objects) such as buildings and utility networks on, above and under the surface. They facilitate registration and management of 3D properties and reduction of boundary disputes. They also enable a wide variety of applications that in turn identify detailed and integrated 3D legal and physical objects for property management and city space management (3D land use management).Efficient delivery and implementation of these applications require many elements to support a digital 3D cadastre, such as existing 3D property registration laws, appropriate 3D data acquisition methods, 3D spatial database management systems, and functional 3D visualisation platforms. In addition, an appropriate 3D cadastral data model can also play a key role to ensure successful development of the 3D cadastre.A 3D cadastral data model needs to reflect the complexity and interrelations of 3D legal objects and their physical counterparts. Many jurisdictions have defined their own cadastral data models for legal purposes and have neglected the third dimension, integration of physical counterparts and semantic aspects.To address these problems, this paper aims to investigate why existing cadastral data models do not facilitate effective representation and analysis of 3D data, integration of 3D legal objects with their physical counterparts, and semantics. Then, a 3D cadastral data model (3DCDM) is proposed as a solution to improve the current cadastral data models. The data model is developed based on the ISO standards. UML modelling language is used to specify the data model. The results of this research can be used by cadastral data modellers to improve existing or develop new cadastral data models to support the requirements of 3D cadastres.

Landslide susceptibility zonation in Greece

The objective of this study is to perform a preliminary national-scale assessment of the landslide susceptibility in Greece using a landslide inventory derived from historical archives. The effects of controlling factors on landslide susceptibility combined with multivariate statistics have been evaluated using GIS aided mapping techniques. Thousand six hundred thirty-five landslide occurrences, mainly earth slides obtained from Public Authorities archives, covering a long time period were recorded and digitally stored using a spatial relational database management system. Ten landslide predisposing factors (predictors) were identified, while digital thematic maps on the spatial distribution of those factors were generated. The correlation between the landslide locations and predictor classes was analyzed by using the Landslide Relative Frequency. R-mode factor analysis was applied to study the interrelations between predictors (independent variables) while weighting coefficients were determined. Landslide susceptibility was derived from an algorithm which modeled the influence of predictors, and a susceptibility map was compiled. The landslide susceptibility map was verified using a data set of 375 new landslide locations. It is the first comprehensive attempt to illustrate the landslide susceptibility in the total country based on the interpretation of historical data only.

New Database Architecture for Smart Query Handler of Spatial Database

A spatial database system is a database system with additional capabilities for handling spatial data. It also supports spatial data types in its implementation, providing spatial indexing and efficient algorithms for spatial join. The retrieval of data values from a spatial database involves searching through the huge repository of data, involving huge cost. Thus query optimization on spatial database takes more time as compared to RDBMS. The current state of art shows that during the execution of a query in a spatial database management system (SDBMS), the query optimizer creates all possible query evaluation plans. All plans are equivalent in term of their final output but vary in their execution cost, the amount of time to run. Once the data is retrieved the query and its plans are deleted from memory to free the space for future usage. This is repeated for the next query even if the query is already executed. This leads to increased storage overhead and execution time. In this paper, a new database architecture is proposed, which uses a buffer based query optimization technique for faster data retrieval.

Modelling and mapping third dimension in a spatial database

In this paper, an overview of phases for modelling and mapping third dimension of spatial objects in a database is presented based on a selected spatial database management system (DBMS). These phases include (1) defining a spatial reference system for representing three-dimensional (3D) objects with real-world coordinates, (2) geometric modelling of 3D objects in the database, (3) 3D spatial indexing for fast accessing/querying the 3D data, 3D spatial queries and representation of 3D data. Then, a case study is performed to assess needs, possibilities and potential limitations of 3D data modelling in the spatial database.

A Survey on Clustering Algorithms for Data in Spatial Database Management Systems

A Survey on Clustering Algorithms for Data in Spatial Database Management Systems

Applicability of Geo-spatial Processing Open Sources to Geographic Object-based Image Analysis (GEOBIA)

At present, GEOBIA (Geographic Object-based Image Analysis), heir of OBIA (Object-based Image Analysis), is regarded as an important methodology by object-oriented paradigm for remote sensing, dealing with geo-objects related to image segmentation and classification in the different view point of pixel-based processing. This also helps to directly link to GIS applications. Thus, GEOBIA software is on the booming. The main theme of this study is to look into the applicability of geo-spatial processing open source to GEOBIA. However, there is no few fully featured open source for GEOBIA which needs complicated schemes and algorithms, till It was carried out to implement a preliminary system for GEOBIA running an integrated and user-oriented environment. This work was performed by using various open sources such as OTB or PostgreSQL/PostGIS. Some points are different from the widely-used proprietary GEOBIA software. In this system, geo-objects are not file-based ones, but tightly linked with GIS layers in spatial database management system. The mean shift algorithm with parameters associated with spatial similarities or homogeneities is used for image segmentation. For classification process in this work, tree-based model of hierarchical network composing parent and child nodes is implemented by attribute join in the semi-automatic mode, unlike traditional image-based classification. Of course, this integrated GEOBIA system is on the progressing stage, and further works are necessary. It is expected that this approach helps to develop and to extend new applications such as urban mapping or change detection linked to GIS data sets using GEOBIA.

An Object-Oriented Modeling and Implementation of Spatio-Temporal Knowledge Discovery System

Spatiotemporal databases deal with changes to spatial objects with time. The Spatiotemporal knowledge discovery process involves the integration of such database systems with data warehousing, data mining and online-analytical processing technologies. The applications in this domain will process spatial, temporal and attribute data elements and use spatio-temporal relationships among these elements. These applications deal with the evolution of spatial objects and changes in their topological relationships, associations along with time. These advanced database applications require storing, management and processing of complex spatiotemporal data. In this paper we consider the classification and modeling requirements for spatiotemporal applications, System modeling, preprocessing spatiotemporal data, discovering spatiotemporal topological relationships and extension of apriori algorithm for mining spatiotemporal frequent predicates. The design of an appropriate system that can capture spatiotemporal features of datasets is discussed. Prototype implementation of the system is carried out on top of open source object relational spatial database management system called postgresql and postgis. The algorithms are experimented on historical cadastral datasets which are created using OpenJump. The results that are visualized using OpenJump software are presented.

Research and Application on Technology of Integration and Processing of Multi-Source and Multi-Scale Spatial Data (IPMMSD)

this paper’s goal is to make fuse, manipulation, management, maintenance and service of spatial data to an organic integrity by IPMMSD, to digitalize model of geo-spatial data, also to bring an software platform for abundant spatial data’s management, to provide users an intelligent platform for getting spatial information rapidly, and also to make an basic software for spatial dynamic and quantitative analysis. On the support of spatial database management system to realize integration of multi-scale, multiresolution, multi-type, multi-time digital map, image and property data, and manage these data by concentrative or distributive way, to make abundant isolated information into share data resource.

The generic annular bucket histogram for estimating the selectivity of spatial selection and spatial join

Selectivity estimation is crucial for query optimizers choosing an optimal spatial execution plan in a spatial database management system. This paper presents an Annular Bucket spatial histogram (AB histogram) that can estimate the selectivity in finer spatial selection and spatial join operations even when the spatial query has more operators or more joins. The AB histogram is represented as a set of bucket-range, bucket-count value pairs. The bucket-range often covers an annular region like a single-cell-sized photo frame. The bucket-count is the number of objects whose Minimum Bounding Rectangles (MBRs) fall between outer rectangle and inner rectangle of the bucket-range. Assuming that all MBRs in each a bucket distribute evenly, for every bucket, we can obtain serial probabilities that satisfy a certain spatial selection or join conditions from the operations’ semantics and the spatial relations between every bucket-range and query ranges. Thus, according to some probability theories, spatial selection or join selectivity can be estimated by the every bucket-count and its probabilities. This paper also shows a way to generate an updated AB histogram from an original AB histogram and those probabilities. Our tests show that the AB histogram not only supports the selectivity estimation of spatial selection or spatial join with “disjoint”, “intersect”, “within”, “contains”, and “overlap” operators but also provides an approach to generate a reliable updated histogram whose spatial distribution is close to the distribution of actual query result.

Pengembangan SIG berbasis Web Sebagai Decission Support System (DSS) untuk Manajemen Jaringan Jalan di Kabupaten Aceh Timur

This research aims to develop a web-based GIS that can be used as a decision support system in managing the road network in East Aceh district. In this case, MySQL is used as a spatial database management system and Scalable Vector Graphics (SVG) is used as the technology to visualize spatial data in web programming. Therefore, it is expected can make geo-database application that can be distributed widely to related user. Stages of development of the system used in this study refers to the waterfall model. The order of execution of the study is divided into five stages include: early stage research, web GIS design stage, the stage of data collection, web GIS development phase and implementation phase. Data used in this study include primary and secondary data. Primary data consists of spatial and attribute data of road network (lines) and bridges (points) taken through surveys with Global Positioning System (GPS). Secondary data used include base maps derived from maps of the Rupa Bumi Indonesia (RBI) 1:25.000 scale area of East Aceh Regency. The unit of analysis used was the Locational referencing system that is defining a road network using the “node” and “section”. The results of this study showed that implementation of the SVG generated by PHP is able to produce a superior display vector and dynamic so it is easy to analyze. These capabilities combined with MySQL capabilities in spatial analysis and queries on RDBMS database is able to produce applications that are capable of supporting the activities of decision-making in the management of roads and bridges.

How to achieve consistency for 3D city models

Consistency is a crucial prerequisite for a large number of relevant applications of 3D city models, which have become more and more important in GIS. Users need efficient and reliable consistency checking tools in order to be able to assess the suitability of spatial data for their applications. In this paper we provide the theoretical foundations for such tools by defining an axiomatic characterization of 3D city models. These axioms are effective and efficiently supported by recent spatial database management systems and methods of Computational Geometry or Computer Graphics. They are equivalent to the topological concept of the 3D city model presented in this paper, thereby guaranteeing the reliability of the method. Hence, each error is detected by the axioms, and each violation of the axioms is in fact an error. This property, which is proven formally, is not guaranteed by existing approaches. The efficiency of the method stems from its locality: in most cases, consistency checks can safely be restricted to single components, which are defined topologically. We show how a 3D city model can be decomposed into such components which are either topologically equivalent to a disk, a sphere, or a torus, enabling the modeling of the terrain, of buildings and other constructions, and of bridges and tunnels, which are handles from a mathematical point of view. This enables a modular design of the axioms by defining axioms for each topological component and for the aggregation of the components. Finally, a sound, consistent concept for aggregating features, i.e. semantical objects like buildings or rooms, to complex features is presented.

An Integrated Photogrammetric and Spatial Database Management System for Producing Fully Structured Data Using Aerial and Remote Sensing Images

3D spatial data acquired from aerial and remote sensing images by photogrammetric techniques is one of the most accurate and economic data sources for GIS, map production, and spatial data updating. However, there are still many problems concerning storage, structuring and appropriate management of spatial data obtained using these techniques. According to the capabilities of spatial database management systems (SDBMSs); direct integration of photogrammetric and spatial database management systems can save time and cost of producing and updating digital maps. This integration is accomplished by replacing digital maps with a single spatial database. Applying spatial databases overcomes the problem of managing spatial and attributes data in a coupled approach. This management approach is one of the main problems in GISs for using map products of photogrammetric workstations. Also by the means of these integrated systems, providing structured spatial data, based on OGC (Open GIS Consortium) standards and topological relations between different feature classes, is possible at the time of feature digitizing process. In this paper, the integration of photogrammetric systems and SDBMSs is evaluated. Then, different levels of integration are described. Finally design, implementation and test of a software package called Integrated Photogrammetric and Oracle Spatial Systems (IPOSS) is presented.

부분 맵 업데이트 지원 내비게이션을 위한 모바일 공간 DBMS 개발 및 성능 평가

모바일 단말에서의 맵 데이터 활용 서비스는 내비게이션, 위치기반서비스 등 그 활용 범위가 다양해지고 있다. 이러한 모바일 단말에서 저장/관리되는 맵 데이터의 크기는 갈수록 커져 수 GB에 이른다. 기존 내비게이션 시스템의 경우, 리소스 제약으로 인해 모바일 단말의 성능을 최대로 활용하기 위하여 맵 데이터를 읽기 최적화된 물리적인 저장형식(PSF: Physical Storage Format)으로 저장 관리하고 있다. 즉, 맵 데이터가 변경된 경우 변경된 부분만의 업데이트가 불가능하여 전체 데이터를 업데이트해야 하는 단점이 있다. 일반적으로 2 GB 데이터를 모바일 단말의 플래시메모리에 기록하는 시간은 수십 분이 소요된다. 따라서 본 연구에서는 이러한 기존의 내비게이션용 맵 데이터의 부분 업데이트가 불가능한 점을 해결하고자 모바일 공간 DBMS을 개발하였다. 그리고, 모바일 공간 DBMS에서의 내비게이션 서비스의 성능을 보장하기 위한 기법을 제시하고 실험을 통하여 이를 검증하였다. The service handling the map data in the mobile device including navigation, LBS, Telematics, and etc., becomes various. The size of map data which is stored and managed in the mobile device is growing and reaches in several GB. The conventional navigation system has used the read-only PSF (physical storage format) in order to enhance the performance of system by maximum in the mobile device which has limited resources. So though a little part of the map data is changed the whole data must be updated. In general, it takes several ten minutes to write the 2 GB map data to a flash memory of mobile device. Therefore, we have developed the mobile spatial DBMS (database management system) to solve the problem which is that the partial map data couldn't be updated in the conventional navigation system. And we suggest the policy to guarantee the performance of the navigation system which is implemented using the spatial mobile DBMS and verify this by experiment.

Spatial Data Management and Analysis System for Flood Hazard Mitigation of Poyang Lake Watershed, China

Flood hazard Prevention and mitigation of Poyang Lake watershed is an emergent environmental problem because Poyang Lake watershed is one of the regions exposed most frequently to flood hazard in China. In order to meet the need of disaster reduction decision making of Poyang Lake watershed, Spatial Data Management and Analysis System of China Land Territory (not include islands in South Sea of China)for Flood Hazard Mitigation(short for SMAS-FHM) has been established making use of the methodology of spatial database technology based on Oracle9i&ArcSDE9. This paper, probes into designing and implementation of multi-resources and scales massive spatial database management system about flood hazard, and integral management between hazard thematic data and spatial data. Especially, a bitmap index adapted to primal TM/ETM+ image has been put forwards and realized to accelerate data search in the spatial database, which is turned out to be efficient and effective. Based on carrying out experiment, this paper has been also researched the key issues, including massive spatial data and flood hazard thematic data organization and storage, spatial index creating, spatial data searching, and flood hazard analysis models realizing and their effective organizing, such as flooding areas computing, 3-dimension flooding simulation, refuge location selection, refugee evacuation path analysis and relief material dispensing. Finally, important applications of SMAS-FHM in flood hazard mitigation have been also discussed for Poyang Lake watershed.

논 블록킹 검색연산을 위한 R-tree 기반의 동시성 제어 기법

본 논문에서는 검색 위주의 공간 데이터베이스 시스템을 위한 R-tree 기반의 동시성 제어 기법을 제안한다. 기존의 제안된 기법들은 검색연산이 갱신연산과 동시에 수행되는 것을 막기 위해 노드에 공유 락이나 래치를 획득함으로써 갱신연산으로 인한 검색연산의 블록킹을 막을 수 없다는 문제를 가지고 있으며, 또한 R-tree같은 다차원 색인의 경우 갱신연산의 락 획득은 여러 노드에 걸쳐 일어날 수 있으며, 노드 분할과 같은 경우 오랜 시간동안 락을 획득하고 있을 수도 있기 때문에 검색연산은 장시간 블록킹이 되어야 하는 문제를 갖는다. 따라서 본 논문에서는 이러한 문제를 해결하기 위하여 노드의 엔트리들을 링크드 리스트로 연결하는 방법을 사용하여 노드에 엔트리를 삽입하고 있는 중에도 락이나 래치를 획득하지 않고 검색연산을 할 수 있는 링크드 리스트 기반의 동시성 제어 기법과, 노드 분할이 진행 중에 있는 노드에도 검색연산이 락이나 래치를 획득하지 않고 노드를 탐색할 수 있는 버전 기반의 동시성 제어 기법을 제안한다. In this paper, we propose a concurrency control algorithm based on R-tree for spatial database management system. The previous proposed algorithms can't prevent problem that search operation is to be blocking during update operations. In case of multidimensional indexes like R-tree, locking of update operations may be locked to several nodes, and splitting of nodes have to lock a splitting node for a long time. Therefore search operations have to waiting a long time until update operations unlock. In this paper we propose new algorithms for lock-free search operation. First, we develop a new technique using a linked-list technique on the node. The linked-list enable lock-free search when search operations search a node. Next, we propose a new technique using a version technique. The version technique enable lock-free search on the node that update operations is to be splitting.

Spatial Data Mining: Database Primitives, Algorithms and Efficient DBMS Support

Spatial data mining algorithms heavily depend on the efficient processing of neighborhood relations since the neighbors of many objects have to be investigated in a single run of a typical algorithm. Therefore, providing general concepts for neighborhood relations as well as an efficient implementation of these concepts will allow a tight integration of spatial data mining algorithms with a spatial database management system. This will speed up both, the development and the execution of spatial data mining algorithms. In this paper, we define neighborhood graphs and paths and a small set of database primitives for their manipulation. We show that typical spatial data mining algorithms are well supported by the proposed basic operations. For finding significant spatial patterns, only certain classes of paths “leading away” from a starting object are relevant. We discuss filters allowing only such neighborhood paths which will significantly reduce the search space for spatial data mining algorithms. Furthermore, we introduce neighborhood indices to speed up the processing of our database primitives. We implemented the database primitives on top of a commercial spatial database management system. The effectiveness and efficiency of the proposed approach was evaluated by using an analytical cost model and an extensive experimental study on a geographic database.