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.

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.

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.

Including the spatial dimension: using geographical information systems in hydrology

1996 ◽  
Vol 20 (2) ◽  
pp. 159-177 ◽  
Author(s):  
R.A. McDonnell
Keyword(s):  
Information Systems ◽  
Spatial Data ◽  
Geographical Information Systems ◽  
Spatial Dimension ◽  
Geographical Information ◽  
Gis Technology ◽  
Gis Data ◽  
Spatial Data Models ◽  
The Many ◽  
Hydrological Applications

Developments in geographical information systems (GIS) technology have coincided with moves within hydrology to a more explicit accounting of space through distributed rather than lumped or topological representations. GIS support these spatial data models and provide integrating, measuring and analytical capabilities which have been used in many hydrological applications ranging from inventory and assessment studies through to process modelling. The many examples in the article illustrate how the technology has supported moves away from averaged value representations for catchments towards a greater inclusion of spatial variations in hydrological studies. While the potential of these systems is gradually being realized, there are still various issues, both technical and methodological, which at present limit their use. As new data sources become available, GIS data structures become more flexible and open, and, as the understanding of scale variations in processes improves, the possibilities for using the technology in hydrological research will expand.

scholarly journals Grounded Design and GIScience - A framework for informing the design of geographical information systems and spatial data infrastructures

2019 ◽  
Author(s):  
Alexander Kmoch ◽  
Evelyn Uuemaa ◽  
Hermann Klug
Keyword(s):  
Information Systems ◽  
Spatial Data ◽  
Geographical Information Systems ◽  
Information Science ◽  
Design Science ◽  
Environmental Data ◽  
Geographical Information ◽  
Data Infrastructure ◽  
Development Framework ◽  
Grounded Design

Geographical Information Science (GIScience), also Geographical Information Science and Systems, is a multi-faceted research discipline and comprises a wide variety of topics. Investigation into data management and interoperability of geographical data and environmental data sets for scientific analysis, visualisation and modelling is an important driver of the Information Science aspect of GIScience, that underpins comprehensive Geographical Information Systems (GIS) and Spatial Data Infrastructure (SDI) research and development. In this article we present the 'Grounded Design' method, a fusion of Design Science Research (DSR) and Grounded Theory (GT), and how they can act as guiding principles to link GIScience, Computer Science and Earth Sciences into a converging GI systems development framework. We explain how this bottom-up research framework can yield holistic and integrated perspectives when designing GIS and SDI systems and software. This would allow GIScience academics, GIS and SDI practitioners alike to reliably draw from interdisciplinary knowledge to consistently design and innovate GI systems.

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