Spatial Network Databases

2009 ◽  
pp. 307-315 ◽  
Author(s):  
Michael Vassilakopoulos
Keyword(s):  
Information Systems ◽  
Spatial Data ◽  
Computer Aided Design ◽  
Geographical Information Systems ◽  
Large Scale ◽  
Spatial Databases ◽  
Query Language ◽  
Geographical Information ◽  
Data Types ◽  
Large Scale Integration

A Spatial Database is a database that offers spatial data types, a query language with spatial predicates, spatial indexing techniques, and efficient processing of spatial queries. All these fields have attracted the focus of researchers over the past 25 years. The main reason for studying spatial databases has been applications that emerged during this period, such as Geographical Information Systems, Computer-Aided Design, Very Large Scale Integration design, Multimedia Information Systems, and so forth. In parallel, the field of temporal databases, databases that deal with the management of timevarying data, attracted the research community since numerous database applications (i.e., Banking, Personnel Management, Transportation Scheduling) involve the notion of time.

Spatial and Spatiotemporal Data Types as a Foundation for Representing Space-Time Data in GIS

2017 ◽  
pp. 1-28 ◽  
Author(s):  
Markus Schneider
Keyword(s):  
Spatial Data ◽  
Geographical Information Systems ◽  
Moving Objects ◽  
Spatial Databases ◽  
Query Languages ◽  
Geographical Information ◽  
Spatiotemporal Data ◽  
Data Types ◽  
Time Data ◽  
Use Of Data

A data type comprises a set of homogeneous values together with a collection of operations defined on them. This chapter emphasizes the importance of crisp spatial data types, fuzzy spatial data types, and spatiotemporal data types for representing static, vague, and time-varying geometries in Geographical Information Systems (GIS). These data types provide a fundamental abstraction for modeling the geometric structure of crisp spatial, fuzzy spatial, and moving objects in space and time as well as their relationships, properties, and operations. The goal of this chapter is to provide an overview and description of these data types and their operations that have been proposed in research and can be found in GIS, spatial databases, moving objects databases, and other spatial software tools. The use of data types, operations, and predicates will be illustrated by their embedding into query languages.

Consistency in Spatial Databases

2005 ◽  
pp. 93-98 ◽  
Author(s):  
M. Andrea Rodríguez-Tastets
Keyword(s):  
Spatial Data ◽  
Computer Aided Design ◽  
Large Scale ◽  
Spatial Databases ◽  
Data Sets ◽  
Navigation Systems ◽  
Large Scale Integration ◽  
Spatial Data Sets ◽  
Scale Integration ◽  
Aided Design

During the past several years, traditional databases have been enhanced to include spatially referenced data. Spatial database management (SDBM) systems aim at providing models for the efficient manipulation of data related to space. Such type of manipulation is useful for any type of applications based on large spatial data sets, such as computer-aided design (CAD), very large scale integration (VLSI), robotics, navigation systems, and image processing.

Query Processing in Spatial Databases

2009 ◽  
pp. 269-278
Author(s):  
Antonio Corral ◽  
Michael Vassilakopoulos
Keyword(s):  
Information Systems ◽  
Query Processing ◽  
Spatial Data ◽  
Spatial Databases ◽  
Spatial Database ◽  
Database System ◽  
Data Types ◽  
Spatial Data Models ◽  
Large Scale Integration ◽  
Efficient Query Processing

Spatial data management has been an active area of intensive research for more than two decades. In order to support spatial objects in a database system several important issues must be taken into account such as: spatial data models, indexing mechanisms and efficient query processing. A spatial database system (SDBS) is a database system that offers spatial data types in its data model and query language and supports spatial data types in its implementation, providing at least spatial indexing and efficient spatial query processing (Güting, 1994). The main reason that has caused the active study of spatial database management systems (SDBMS) comes from the needs of the existing applications such as geographical information systems (GIS), computer-aided design (CAD), very large scale integration design (VLSI), multimedia information systems (MIS), data warehousing, multi-criteria decision making, location-based services, etc.

scholarly journals Using Social Media Data to Map Mortar Shells Falling in Damascus, Syria

2021 ◽  
Vol 27 (2) ◽  
pp. 233-240
Author(s):  
Mohamad Hasan
Keyword(s):  
Social Media ◽  
Information Systems ◽  
Spatial Data ◽  
Geographical Information Systems ◽  
Hot Spot ◽  
Geographical Information ◽  
Data Types ◽  
Social Phenomena ◽  
Social Media Data ◽  
Media Data

The paper analyzes the use of social media data in geographical information systems to map the areas most affected by mortar shells in the capital of Syria, Damascus, by using geocoded and parsed social media data in geographical information systems. This paper describes a created algorithm to collecting and store data from social media sites. For the data store both a NoSQL database to save JSON format document and an RDBMS is used to save other spatial data types. A python script was written to collect the data in social media based on certain keywords related to the search. A geocoding algorithm to locate social media posts that normalize, standardize and tokenize the text was developed. The result of the developed diagram provided a year by year from 2013 to 2018 maps for mortar shell falling locations in Damascus. These layers give an overview for the changing of the numbers of mortar shells falls or in hot spot analysis for the city. Finally, social media data can prove to be useful when creating maps for dynamic social phenomena, for example, mortar shells’ location falling in Damascus, Syria. Moreover, social media data provide easy, massive, and timestamped data which makes these phenomena easier to study.

scholarly journals External-Memory Algorithms for Processing Line Segments in Geographic Information Systems

1996 ◽  
Vol 3 (12) ◽  
Author(s):  
Lars Arge ◽  
Darren E. Vengroff ◽  
Jeffery S. Vitter
Keyword(s):  
Information Systems ◽  
Spatial Data ◽  
Line Segment ◽  
Geographical Information Systems ◽  
Large Scale ◽  
Geographical Information ◽  
External Memory ◽  
External Memory Algorithms ◽  
Line Segments ◽  
Line Segment Intersection

In the design of algorithms for large-scale applications it is essential to consider the problem of minimizing I/O communication. Geographical information systems (GIS) are good examples of such large-scale applications as they frequently handle huge amounts of spatial data. In this paper we develop efficient new external-memory algorithms for a number of important problems involving line segments in the plane, including trapezoid decomposition, batched planar point location, triangulation, red-blue line segment intersection reporting, and general line segment intersection reporting. In GIS systems, the first three problems are useful for rendering and modeling, and the latter two are frequently used for overlaying maps and extracting information<br />from them.

scholarly journals Digital spatial data as support for river basin management: The case of Sotla river basin

Spatium ◽  
2013 ◽  
pp. 59-67
Author(s):  
Klemen Prah ◽  
Andrej Lisec ◽  
Anka Lisec
Keyword(s):  
Information Systems ◽  
River Basin ◽  
Spatial Data ◽  
Geographical Information Systems ◽  
River Basin Management ◽  
Geographical Information ◽  
Basin Management ◽  
Alternative Evaluation ◽  
Policy Alternatives ◽  
Social Environmental

Many real-world spatially related problems, including river-basin planning and management, give rise to geographical information system based decision making, since the performance of spatial policy alternatives were traditionally and are still often represented by thematic maps. Advanced technologies and approaches, such as geographical information systems (GIS), offer a unique opportunity to tackle spatial problems traditionally associated with more efficient and effective data collection, analysis, and alternative evaluation. This paper discusses the advantages and challenges of the use of digital spatial data and geographical information systems in river basis management. Spatial data on social, environmental and other spatial conditions for the study area of 451.77 km2, the Slovenian part of the Sotla river basin, are used to study the GIS capabilities of supporting spatial decisions in the framework of river basin management.

scholarly journals COMPLEMENTARITY OF HISTORIC BUILDING INFORMATION MODELLING AND GEOGRAPHIC INFORMATION SYSTEMS

2016 ◽  
Vol XLI-B5 ◽  
pp. 437-443 ◽  
Author(s):  
X. Yang ◽  
M. Koehl ◽  
P. Grussenmeyer ◽  
H. Macher
Keyword(s):  
Information Systems ◽  
Spatial Data ◽  
Geographical Information Systems ◽  
Point Clouds ◽  
3D Models ◽  
Geographical Information ◽  
Building Information Modelling ◽  
Historic Building ◽  
Information Modelling ◽  
Building Information

In this paper, we discuss the potential of integrating both semantically rich models from Building Information Modelling (BIM) and Geographical Information Systems (GIS) to build the detailed 3D historic model. BIM contributes to the creation of a digital representation having all physical and functional building characteristics in several dimensions, as e.g. XYZ (3D), time and non-architectural information that are necessary for construction and management of buildings. GIS has potential in handling and managing spatial data especially exploring spatial relationships and is widely used in urban modelling. However, when considering heritage modelling, the specificity of irregular historical components makes it problematic to create the enriched model according to its complex architectural elements obtained from point clouds. Therefore, some open issues limiting the historic building 3D modelling will be discussed in this paper: how to deal with the complex elements composing historic buildings in BIM and GIS environment, how to build the enriched historic model, and why to construct different levels of details? By solving these problems, conceptualization, documentation and analysis of enriched Historic Building Information Modelling are developed and compared to traditional 3D models aimed primarily for visualization.

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