Relative space-based GIS data model to analyze the group dynamics of moving objects

Spatial indexing technology is widely used in Geographic Information Systems (GIS) and spatial databases. As a data retrieval technology, spatial indexing is becoming increasingly important in the big-data age. The purpose of this study is to propose a unified indexing strategy for the mixed data of a future marine GIS. First, data organisation of the system is described. Second, the display condition of each type of data is introduced. These conditions are the basis for the construction of a unified indexing structure. Third, a unified indexing structure for mixed data is presented. The construction process and the search method of the indexing structure are described. Finally, we implement the indexing strategy in our system “Automotive Intelligent Chart Three-dimensional Electronic Chart Display and Information Systems” (AIC 3D ECDIS). Our strategy can provide fast and integrated data retrieval. The spatial indexing strategy we propose breaks through the limitation of data types in our system. It can also be applied in other GIS systems. With the advent of the big-data age, mixed data indexing will become more and more important.

Identifying the (Hot Spots) for traffic accidents in Erbil City A study of the problems of the Urban Environment

Abstract. Research in geographic information science has not yet found clear answers to the questions of what geographic information is about or what a geographic information system (GIS) contains. This lack of consensus makes it especially challenging to teach and learn GIS. Existing pedagogical approaches either focus on the representational level of data (e.g., “raster and vector”) or are too generic (e.g., “geo-referenced information”). This characterization of GIS and its content is difficult for learners to transfer and apply broadly. As instructors, we approach the challenge of teaching GIS from a conceptual basis. We describe our process to develop a set of core concepts of spatial information, which we use to redesign an undergraduate-level introductory GIS course. Our intervention focuses instruction on the kinds of questions that geographic information enables before training students to produce workflows and answers through system commands. The course redesign complements and informs ongoing research on core concepts of spatial information. Our results demonstrate that GIS courses can deliver more than software training, indicating both theoretical gains and didactic challenges.

Geographic Information Science (GIScience or GISci) — using the synergy of global positioning systems (GPS), remote sensing, spatial analysis and statistics, and geographic information systems (GIS) — provides a powerful set of tools and intellectual approaches to address environmental change. Since the advent of satellite remote sensing of Earth resources in the 1970s, new and innovative ways have been developed to map, measure, monitor, model, and provide decision support for the ongoing changes on our planetary surface. Healthy green vegetation has a unique spectral reflectance response due to absorption in the visible red portion of the spectrum and strong reflectance in the near infrared. Indexes derived from combinations of satellite digital data have been documented to provide good indicators of the amount and geographic coverage of green vegetation. Thus, GIScience methods can be very helpful in spatial reasoning and scientific visualization of the success of agroforestry programs designed to combat desertification. Change detection or monitoring of the success of establishing green vegetation can be accomplished in a geographic information system using multiple dates of satellite imagery or aerial photography. In addition, when information about the state of the vegetation cover is combined with other digital data types, such as soils, access to water, transportation routes, the location of human settlements, and/or natural vegetation cover, then strategic decisions regarding development of the Great Green Wall can be made.

Geographical Information Systems (GIS) provide a powerful tool to transportation planners and engineers for a variety of analytical tasks. However, even with the advent of PC-based GIS systems and strong state and federal support, transportation planners and engineers in small and medium-sized communities face many constraints in finding the resources to pay for a GIS and in the development of a data base that can be used for practical applications. The Lane Council of Governments (LCOG) has been a leader in the design, implementation and management of Geographic Information Systems (GIS) for almost three decades. The root of this successful implementation of GIS lies in the formation of multi-jurisdictional (cities, county, utilities, MPO), multi-application (transportation, natural resources, public works, assessment and taxation, land use planning) approach (termed the Common Mapping Project) and development of a Cooperative Project Agreement which has provided for sustained development of a parcel-level data base. This approach has allowed LCOG's transportation planners to have access to a very rich database. For example, the GIS provides land use and demographic inputs to the system model and overlay analyses incorporating the transportation system (both supply and demand characteristics), natural resources (soils, topography, hydrology, etc.) and other public works features (sanitary, storm sewers, utility lines, etc.). In addition, this approach has allowed LCOG to focus its transportation planning resources on the transportation system as other agencies have provided the resources for development and maintenance of other parts of the database. The 30-year history provides evidence of success of the approach. Without this cooperative, long-term approach, it is doubtful the GIS would be available to transportation planners in the Eugene-Springfield area. Certainly, we would not have the rich database that has resulted from this integrated approach. This paper/presentation will describe the approach taken by agencies in the Eugene-Springfield area in the development of its GIS, the benefits of this approach to transportation planning in a medium-sized area, and the key lessons learned over the years.

Network data structures were one of the earliest representations in geographic information systems (GIS), and network analysis remains one of the most significant and persistent research and application areas in geographic information science (GIScience). Network analysis has a strong theoretical basis in the mathematical disciplines of graph theory and topology, and it is the topological relationships inherent in networks that led to revolutionary advances in GIS data structures. Networks can represent an alternative datum for geo-location in the context of linear referencing and support a set of tools for graphical display known as dynamic segmentation. Many network location problems are among the most difficult to solve in terms of their combinatorial complexity and, therefore, provide both a challenge and an opportunity for GIScience researchers. Because elements of network analysis appear in a wide range of academic disciplines—from physics, to sociology, to neurobiology—there are ample opportunities for interdisciplinary investigations of emerging research topics.

Spatial Data Grid allows for solving larger problems and executing applications that traditional Web GIS (Geographic Information System) can not handle efficiently. In Spatial Data Grid, all functions of GIS are encapsulated as stateful Web Services. The purpose of this paper is to design and implement a new mechanism to organize miscellaneous Vector Map Services, built on GT4 (Globus Toolkit 4), and based on WSRF (Web Services Resource Framework). In this paper, we demonstrate the general procedure to build a Grid Vector Map Service (spatial query, buffer analysis, overlay analysis, etc) based on GT4. We design and implement two kinds of Vector Map Services: Domain Service and Node Service, which can be chosen by users after they log in the Grid Portal correctly. Finally, we present some experimental results and draw some conclusions. The new mechanism allows more flexible usage of available resources in the Grid and is expected to decrease the efforts needed to configure and maintain nodes in the Grid, and it buffers some frequently accessed information in resources, in this way, access times of GIS Server will be sharply decreased and query time will be reduced.

The space–place dichotomy has long been discussed in geography, psychology, philosophy, and more recently in geographic information science. The attempts to integrate vague notions of place into geographic information systems (GIS) constitute the foundations of the place‐based GIS stream of research, but the rationale and methods for operationalizing place differ considerably in the literature. We present a literature review in an attempt to identify and discuss the distinct yet overlapping frameworks that aim to bridge the gap between space, place, and GIS. The review shows that most studies designed knowledge‐based models in the urban context based on concepts drawn from human geography. Using mixed methods, we synthesize the findings, thus encouraging future research in building new conceptual and methodological models that are able to expand and solidify the scope of place‐based GIS.

Adaptive indexing allows for the progressive and simultaneous query-driven exploration and indexing of memoryresident data, starting as soon as they become available without upfront indexing. This technique has been so far applied to onedimensional and multidimensional data, as well as to objects with spatial extent arising in geographic information systems. However, existing spatial adaptive indexing methods cater to static data made available in an one-off manner. To date, no spatial adaptive indexing method can ingest data updates interleaved with data exploration. In this paper we introduce GLIDE, a novel method that intertwines the adaptive indexing and incremental updating of a spatial-object data set. GLIDE builds a hierarchical spatial index incrementally in response to queries and also ingests updates judiciously into it. We examine several design choices and settle for a variant that combines gradual self-driven top-down insertions with query-driven indexing operations. In an extensive experimental comparison, we show that GLIDE achieves a lower cumulative cost than upfront-indexing methods and adaptiveindexing baselines.

Web GIS is becoming the developing hotpot for GIS With the development of Internet technology .Geographical Information System (GIS) is an information system which stores analyzes and visually express spatial data . WebGIS can Provide not only simple text and data , but also graphics and images to more and more people. WebGIS is the outcome of Internet development and information sharing . However, many traditional GIS software adopts file-based data organization, which only publishes GIS data less. The technology of publishing mass vector and image database would be restricted . It is necessary to take the proper syncretizing among such technologies as Web, software engineering, programming languages, database and GIS functions into account and consider how to provide a simple and convenient application mode to client. In This paper the author first discuss the model about the data-memory, organizing and the data publishing, then research the design model and the realize model of the Web GIS based on J2EE. Analyse the work principle , merit , demerit and the realizing method of the constitutes of Web GIS, i.e. the structure of three layers.

Nowadays, medical information is increasingly used many hospitals around the world. Then, the need of sharing information from different sources is an obvious consequence from such proliferation of systems. Unfortunately, integrating medical information is not a trivial issue, because data and knowledge exchange among users of medical information systems present many challenges. We must deal with the heterogeneity problem, which increase complexity of integration approaches. This paper provides the advantageous environment for information interoperability and interoperation, and according to the willingness of users to share information. The main difference between the system prototype with the new methodology and the traditional Geographic Information System (GIS) is prototype system implies the Knowledge Engineering methodology and extends the reasoning function with the logic method.

It has been over 15 years since the concept of Virtual Geographic Environments (VGEs) was formally proposed (Lin and Gong 2001). Although the thinking about VGEs never stops since it was born, and the continued development of VGEs has brought about significant achievements resulting from this concept (e.g., Goodchild 2009; Gong et al. 2010; Konecny 2011; Lu 2011; Priestnall et al. 2012; Lin et al. 2013a, b, 2015) as well as related technologies and implementations (e.g., Xu et al. 2011, 2013; Chen et al. 2012, 2013a, b; Zhang et al. 2015a, b; Zhu et al. 2015), there are still some misunderstandings about this ‘new’ branch of Geoscience. Questions generally are related to two concepts: the first concerns the differences between VGEs and game-like virtual worlds, similar virtual communities and cities, and digital earth; the second asks how VGEs can contribute to geographic research beyond traditional Geographic Information Systems (GIS) and Maps (Aydi et al. 2013; Tung et al. 2013). The answer to the first question may be found in the term ‘geographic environment’ which refers not only to the natural surface of the earth, space, or a place, but also involves the social behaviors that interact with natural factors; it is the sphere of direct interaction between nature and society (Kalesnik 1979). An important feature of geographic environments is that they change continuously with time. Although some objects in geographic environments have relatively stable shapes (such as a rock or soils), many exist in constantly changing forms (such as vegetation, air and water), and human beings (both in groups or individual) are active throughout their ‘lives’. Given this definition, to build a virtual mirror that can reflect the real geographic environment, only considering the physical part would result only in a one-sided perspective. Moreover, dynamic geographic phenomena and processes require careful attention, a fact often overlooked by traditional systems. Thus, an ideal virtual environment

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.

Developing a Geographic Information System (GIS) for Mapping and Analysing Fossil Deposits at Swartkrans, Gauteng Province, South Africa

Spatial Data Grid allows for solving larger problems and executing applications that traditional Web GIS (Geographic Information System) can not handle efficiently. The purpose of this paper is to design and implement a new mechanism to organize miscellaneous Vector Map Services, built on GT 4 (Globus Toolkit 4), and based on WSRF (Web Services Resource Framework). In this paper, we illustrate the architecture of the Domain Vector Map Service and then some experimental results are brought forth. In addition, a new method to buffer the geospatial information based on WSRF is amplified. The new mechanism allows more flexible usage of available resources in the Grid and is expected to decrease the efforts needed to configure and maintain nodes in Spatial Data Grid, and it buffers some frequently accessed information in resources, in this way, access times of GIS Server will be sharply decreased and query time will be reduced.