Uncertainty Modeling In Object-Oriented Geographical Information Systems

For the performance of geographic information systems, it has been widely recognized that efficient data structures and algorithms supporting proximity based access to spatial data are a crucial ingredient. Because of that, in the last years, a lot of data structures for storage of multidimensional non-point objects have been proposed in the literature (for an overview see our tutorial introduction in this volume). Almost all of these approaches are made to support queries based on spatial neighborhood of objects, so-called proximity queries. Common examples of such proximity queries are range queries, returning all objects intersecting a given (rectangular) region, or nearest neighbor queries, determining the object nearest to a given point. But a geographic or cartographic information system should also support queries that do not exclusively refer to the spatial neighborhood of objects. For example, different versions of spatial data must be organized such that proximity queries to any version of the data can be answered efficiently. Or, given a set of object classes, a spatial query that involves an arbitrary combination of these classes should also be supported. Because of the growing size of data sets to be handled in geographic information systems, an appropriate data organisation to support such and several other application-specific queries becomes more and more important. In this paper, we will present two approaches for access structures supporting the two types of queries mentioned above. Handling of versioned, spatial data is the topic of Section 2, while Section 3 discusses queries on some classes selected from the set of object classes stored in a geographic information system.

Developing a three-dimensional (3D) data model for Geographic Information Systems (GIS) is an essential and complex issue. 3D modelling in GIS is becoming ever more important for the development of cyber cities and digital earth, which have recently become feasible. A competent 3D model forms an efficient foundation for 3D visualization, query and spatial analysis. As a development of the existing 3D models, this study proposes particular improvements in handling complex 3D objects. We present an object-oriented data model for handling complex 3D objects in GIS. First, the conceptual data model is developed based on the principle of object-oriented (OO) data modelling. This model is designed based on the following three basic geometric elements: node, segment and triangle. Accordingly, the abstract geometric objects are defined: including points, lines, surfaces and volumes. Second, the corresponding 3D logical model is designed based on the defined abstract objects and the relationships between them. Third, a formal representation of the 3D spatial objects is described in detail. Fourth, a prototype 3D GIS is developed based on the proposed 3D data model. Finally, we describe the results of an experimental study to reconstruct 3D objects using this 3D GIS and a comparison with the performance of other 3D data models. The proposed model is able to handle complex objects, such as complex buildings and TV towers, which is an essential functionality for building large-scale cyber cities, such as for Hong Kong. The proposed data model proves to be very efficient, particularly in visualization and rendering. The experimental results show which the data volume of the proposed model is compacted and the visualization speed for 3D objects is improved, compared with the existing models.

Chapter Three - Nature and Aims of Geomorphological Mapping

The most prominent problem of rapid urbanism in Harare is the development of slums and Epworth is a notable example. The quality of planning and decision making in the participatory slum upgrading initiative can be sustainably improved by well managed processes of spatial and socio-economic data collection. More so, existing approaches for slum upgrading are built on the basis of collaborative planning and thus community participation. Geographic Information Systems (GIS) tools and support systems should explicitly consider the needs of professional and non-professional stakeholders in slum upgrading process. This study aimed to develop a customized “GIS based slum upgrading system" that would empower the community to participate in the planning and decision making processes involved in slum upgrading. The study involved developing tools that could be used by lay people, to achieve the same results an expert would. To achieve this, a PostgreSQL/Postgis spatial database integrating the spatial and enumeration data component was developed as the backend with a front end developed using VB.Net. A Map Control tool was imported from Map window 4.7 for displaying and interacting with spatial data. Techniques such as buffering were incorporated in the system to allow users to check for structures within a given distance of a feature. The system also provided a tool that allowed users to select an area and calculate the number of stands that can be obtained after inputting parameters like stand size and type of road. The system provided for tools that calculate statistical values e.g. determining the population as well as the number of households in a selected area. Users could also query for socio-economic data by selecting spatial features. This provided flexibility in terms of the interaction of the users with the data. The system proved that with user oriented GIS system it is possible to develop tools that can be used by lay people especially those in slums to formalize their areas and obtain security of tenure.Keywords: Slum upgrading, Participatory GIS, Security of tenure

A bi-level object-oriented data model together with a user query language called OFQL is designed which can support applications like GIS (geographic information systems). The data model is divided into two layers, the higher-level data model and the lower-level data model. The higher-level data model or the geographic object data model primarily consists of the geographic objects and a set of semantic spatial functions through which the topological relationships of the geographic objects are defined or derived. The lower-level data model or the geometric object data model has geometric objects which are the actual spatial representations of the geographic objects in the higher-level data model. It also has a set of geometric functions that retrieve, manipulate, and compute for geometric objects. The general architecture of a GIS system using this data modeling approach consists of two modules: the query processor and the function implementor. With the OFQL user-interface, the user is able to pose queries of a geographic nature without knowing the details of the spatial representation and computation of the geographic objects.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Part 1 What is a geographic information system?: geographical information systems - an overview, Duane F.Marble geographical information systems - a new frontier, Roger F.Tomlinson a classification of software components commonly used in geographical information systems, Jack Dangermond GIS versus CAD versus DBMS - what are the differences?, David J. Cowen. Part 2 Examples of practical applications: MAGI - a state-level grid cell system, State of Maryland ARC/INFO - a modern GIS, Environmental Systems Research Institute technical description of the DIME system, US Bureau of the Census prinicpal components of the census bureau's TIGER file, Joel Sobel the Tiger system - automating the geographical structure of the United States, Robert W.Marx current and potential uses of geographical information systems - the north American experience, Roger F.Tomlinson an experiment in land-use allocation with a geographical information system, C.Dana Tomlin and Kevin M.Johnston Integration Of Geological Datasets For Gold Exploration In Nova Scotia, G.F.Bonham-Carter, F.P.Agterberg and D.F.Wright modeling community vulnerability to hazardous materials using geographical information systems, Robert B.McMaster representing and applying knowledge about spatial processes in environmental management, J.R.Davis, P.Whingham, and I.W.Grant. Part 3 Operations and problems of building a database: creating large digital files from mapped data, Hugh W.Calkins manual digitizing systems, E.Alan Cameron interaction between the cartographic document and the digitizing process, Donna J.Peuquet and A.Raymond Boyle a review of digital data commonly available and some of the practical problems of entering them into a GIS, Jack Dangermond efficient digitizing through the combination of appropriate hardware and software for error detection and editing, Nicholas R.Chrisman. Part 4 GIS internals - data representation and analysis techniques: spatial data models - a conceptual framework and comprehensive review, Donna J.Peuquet historical data as an explicit component of land information systems, Ric Vrana it makes me so CROSS, David Douglas the accuracy of map overlays - a reassessment, Nicholas R.Chrisman. Part 5 Design and evaluation of GIS: establishing a geographical information system in relation to its use, a process of strategic choices, W.H.Erik DeMan a conceptual model of the manual digitizing process, Duane F.Marble, Jean P.Lauzon and Matthew McGranaghan performance eval and work-load estimation for GIS, Michael Goodchild and Brian R.Rizzo liability for information, Earl F.Epstein and Howard Roitman.

BackgroundThis paper reports on a case study of the use of visualization of geospatial data that is distributed across data sets and requires integration over time and space to aid decision makers. Like many State Highway Agencies (SHAs) in the United States, the Texas Department of Transportation (TxDOT) is organized along the traditional functional lines of planning, design, construction, maintenance, and operations. It has historically relied on experience and longevity of its staff to efficiently and effectively plan its construction and maintenance projects. Although functional boundaries of maintenance and construction are fairly clearly defined, there tends to be some overlap in projects that can be executed by either of the functional groups. The department currently does not have a robust integrated information system for identifying potential planning conflicts between its construction and maintenance projects. This has led to suboptimal use of resources, including overlapping plans for maintenance and mobility enhancement projects.Case descriptionWith over 650 highway projects assigned across two functional groups within the district’s (TxDOT Fort Worth district) boundary, it is a challenging task to assemble a coherent plan for managing these projects over a multi-year planning period that is subject to external stakeholder input as well as shifting funding constraints. Temporal and spatial data needed for integrated planning resides in specialized information systems developed for the needs of individual functional groups. To address this challenge, this district decided to integrate and visualize data from individual information systems in a Geographic Information System (GIS). A GIS-based tool was developed to integrate, visualize, and analyze projects data from multiple information systems.Discussion and evaluationThis paper documents the benefits associated with visualization and integration of projects data in a GIS to address planning challenges facing a typical highway agency. Among the lessons learned are the potential uses of GIS, which include detecting spatially and temporally overlapping projects, supporting integrated planning, and improving communication among functional groups within a state highway agency.ConclusionThe study demonstrates that such spatial-temporal representations of project data can lead to early identification of potential overlaps during the planning phase. In a broader context, such geospatial visualization efforts can also form the basis for eliciting practitioners’ perspectives and knowledge input in the development of spatial decision support systems.

In this thesis, concepts for developing Spatial Data Infrastructures with an emphasis on visualizing 3D landscape and city models in distributed environments are discussed. Spatial Data Infrastructures are important for public authorities in order to perform tasks on a daily basis, and serve as research topic in geo-informatics. Joint initiatives at national and international level exist for harmonizing procedures and technologies. Interoperability is an important aspect in this context - as enabling technology for sharing, distributing, and connecting geospatial data and services. The Open Geospatial Consortium is the main driver for developing international standards in this sector and includes government agencies, universities and private companies in a consensus process. &#13;\n3D city models are becoming increasingly popular not only in desktop Virtual Reality applications but also for being used in professional purposes by public authorities. Spatial Data Infrastructures focus so far on the storage and exchange of 3D building and elevation data. For efficient streaming and visualization of spatial 3D data in distributed network environments such as the internet, concepts from the area of real time 3D Computer Graphics must be applied and combined with Geographic Information Systems (GIS). For example, scene graph data structures are commonly used for creating complex and dynamic 3D environments for computer games and Virtual Reality applications, but have not been introduced in GIS so far. &#13;\nIn this thesis, several aspects of how to create interoperable and service-based environments for 3D spatial data are addressed. These aspects are covered by publications in journals and conference proceedings. The introductory chapter provides a logic succession from geometrical operations for processing raw data, to data integration patterns, to system designs of single components, to service interface descriptions and workflows, and finally to an architecture of a complete distributed service network.&#13;\nDigital Elevation Models are very important in 3D geo-visualization systems. Data structures, methods and processes are described for making them available in service based infrastructures. A specific mesh reduction method is used for generating lower levels of detail from very large point data sets. An integration technique is presented that allows the combination with 2D GIS data such as roads and land use areas. This approach allows using another optimization technique that greatly improves the usability for immersive 3D applications such as pedestrian navigation: flattening road and water surfaces. It is a geometric operation, which uses data structures and algorithms found in numerical simulation software implementing Finite Element Methods. &#13;\n3D Routing is presented as a typical application scenario for detailed 3D city models. Specific problems such as bridges, overpasses and multilevel networks are addressed and possible solutions described. The integration of routing capabilities in service infrastructures can be accomplished with standards of the Open Geospatial Consortium. An additional service is described for creating 3D networks and for generating 3D routes on the fly. Visualization of indoor routes requires different representation techniques.&#13;\nAs server interface for providing access to all 3D data, the Web 3D Service has been used and further developed. Integrating and handling scene graph data is described in order to create rich virtual environments. Coordinate transformations of scene graphs are described in detail, which is an important aspect for ensuring interoperability between systems using different spatial reference systems. The Web 3D Service plays a central part in nearly all experiments that have been carried out. It does not only provide the means for interactive web-visualizations, but also for performing further analyses, accessing detailed feature information, and for automatic content discovery.&#13;\nOpenStreetMap and other worldwide available datasets are used for developing a complete architecture demonstrating the scalability of 3D Spatial Data Infrastructures. Its suitability for creating 3D city models is analyzed, according to requirements set by international standards. A full virtual globe system has been developed based on OpenStreetMap including data processing, database storage, web streaming and a visualization client.&#13;\nResults are discussed and compared to similar approaches within geo-informatics research, clarifying in which application scenarios and under which requirements the approaches in this thesis can be applied.&#13;\n

Geographic Information System (GIS) is a technology that deals with location to support better representations and decision making. It has a long tradition in several planning areas, such as urbanism, environment, riskiness, transportation, archeology or tourism. In academics context higher education has followed that evolution. Despite of their potentialities in education, GIS technologies at the elementary and secondary have been underused. Empowering graduates to learn with GIS and to manipulate spatial data can effectively facilitate the teaching of critical thinking. Likewise it has been recognized that GIS tools can be incorporated as an interdisciplinary pedagogical tool. Nevertheless more practical examples on how GIS tools can enhance teaching and learning process, namely to promote interdisciplinary approaches. The proposed paper presents some results obtained from the project “Each thing in its place: the science in time and space”. This project results from the effort of three professors of Geography, History and Natural Sciences in the context of Didactics of World Knowledge curricular unit to enhance interdisciplinarity through Geographic Information Technologies (GIT). Implemented during the last three years this action-research project developed the research practice using GIS to create an interdisciplinary attitude in the future primary education teachers. More than teaching GIS the authors were focused on teaching with GIS to create an integrated vision where spatial data representation linked the space, the time and natural sciences. Accumulated experience reveals that those technologies can motivate students to learn and facilitating teacher’s interdisciplinary work.

Spatial big data architecture: From Data Warehouses and Data Lakes to the LakeHouse

Abstract: This book presents a comprehensive and interdisciplinary framework for advancing spatial big data analytics by integrating distributed computing technologies with modern Geographic Information Systems (GIS). It addresses the growing complexity and scale of geospatial data characterized by high volume, velocity, and spatial-temporal heterogeneity. The core objective is to equip researchers, analysts, and practitioners with scalable methodologies that harness the combined power of the Hadoop ecosystem and ArcGIS platforms for processing, modeling, and visualizing large-scale spatial datasets. The analytical framework developed in this work builds on foundational spatial concepts—such as topology, projections, and spatial autocorrelation—and extends into advanced topics including spatial machine learning, geostatistics, real-time sensor stream analytics, and spatial-temporal modeling. Methodologies encompass the use of HDFS, MapReduce, GeoSpark, and SpatialHadoop for distributed processing, combined with ArcGIS tools for spatial modeling, scripting (ArcPy), and high-resolution visualization. Empirical case studies drawn from environmental monitoring, urban planning, disaster response, and precision agriculture illustrate end-to-end pipelines that emphasize reproducibility, ethical data handling, and decision-oriented visualization. The key contribution of this volume lies in bridging computational infrastructure with geospatial reasoning, offering a scalable, interoperable, and ethically informed approach to modern spatial data science. Keywords spatial big data, geospatial analytics, Hadoop, ArcGIS, spatial machine learning, spatial-temporal modeling, GIS, MapReduce, GeoSpark, SpatialHadoop, ArcPy, distributed computing, geostatistics, spatial data visualization, real-time stream analytics, spatial data science, geoinformatics, environmental monitoring, urban analytics, data-intensive GIS

Spatial data is data or information that contains a geographical component. Its representation is considered to be increasingly important in decision-making and it is therefore necessary to guarantee access to spatial data in an easy, intuitive and fast way. The main problems of Geographic Information Systems (GIS) are the large amount of information and performance of relational databases (RDBMS) in storage and in unstructured spatial data queries. This problem is significant, since the efficiency of accessing large amounts of spatial data over the Web today is important for conducting on-demand and real-time queries. This work presents a solution to improve efficiency in accessing large amounts of spatial data through the Web, by standardizing spatial data formats. This proposal, called Web GIS, uses the NoSQL MongoDB database engine and provides the spatial data in GeoJSON via a REST API. The results show that MongoDB has substantial advantages over relational databases in storing and querying large amounts of unstructured spatial data, since it supports the storage of data with different structures and also by the efficiency of its spatial operators.

Geographic information systems (GISs) as a technology have been studied and reported extensively and, not unexpectedly, in the field of geography. The various ways of capturing spatial data, arranging attribute data into appropriate database structures, and making the resulting large data sets efficient to store and query have been extensively researched and reported (Densham, 1991). However, the geographic research community has only recently noted the need to study how GISs are used as decision tools, especially with regard to how such decision making might be related to a decision maker’s cognitive style (Mennecke, Crossland, et al., 2000). As an example, the University Consortium for Geographic Information Science called for research examining how geographic knowledge is acquired through different media and by users with different levels of experience and training (University Consortium for Geographic Information Science, 1996). Researchers in the fields of decision sciences and information systems have more recently begun to make contributions in the area of decision making with GISs. When a GIS is employed as a decision support system, in these studies the resultant system is often referred to as a spatial decision support system, or SDSS (see Crossland, 1992; Crossland, Perkins, et al., 1995; Mennecke et al., 2000). A geographic information system in its simplest form is a marriage of accurately scaled digital maps with a database. The digital maps comprise spatially referenced details such as natural elements (lakes, rivers, topographic elevation contours, etc.), manmade objects (buildings, roads, pipelines, etc.), and political boundaries (city limits, state and county lines, international boundaries, etc.). These natural elements are typically referenced, with varying degrees of precision, to latitude/longitude coordinates on the earth’s surface. It must be noted here that the degree of precision and, more importantly, differences in degrees of precision for the various elements are the subjects of much research and user consternation in applications of GISs to solving problems. The database, in turn, catalogs information about the various spatial elements (e.g., the names of rivers, names of buildings, building owner, operator of a pipeline, etc.). These descriptive entries in the database are often referred to as attributes of the various spatial elements. A GIS may be paired with the global positioning system (GPS), from which real-time, satellite-derived location information may be derived, as provided by an appropriate GPS receiver.

In recent years, applications aimed at exploring and analyzing spatial data have emerged, powered by the increasing need of software that integrates Geographic Information Systems (GIS) and On-Line Analytical Processing (OLAP). These applications have been called SOLAP (Spatial OLAP). In previous work, the authors have introduced Piet, a system based on a formal data model that integrates in a single framework GIS, OLAP (On-Line Analytical Processing), and Moving Object data. Real-world problems are inherently spatio-temporal. Thus, in this paper we present a data model that extends Piet, allowing tracking the history of spatial data in the GIS layers. We present a formal study of the two typical ways of introducing time into Piet: timestamping the thematic layers in the GIS, and timestamping the spatial objects in each layer. We denote these strategies snapshot-based and timestamp-based representations, respectively, following well-known terminology borrowed from temporal databases. We present and discuss the formal model for both alternatives. Based on the timestamp-based representation, we introduce a formal First-Order spatio-temporal query language, which we denote $\mathcal{L}_t,$ able to express spatio-temporal queries over GIS, OLAP, and trajectory data. Finally, we discuss implementation issues, the update operators that must be supported by the model, and sketch a temporal extension to Piet-QL, the SQL-like query language that supports Piet.

Geographic information systems (GIS) are becoming more usual due to the improved performance of computer systems. GIS applications are being developed using the three-tier software architecture traditionally used for general-purpose information systems. Even though this architecture is suitable for GIS applications, the special nature and exclusive characteristics of geographic information pose special functional requirements on the architecture in terms of conceptual and logical models, data structures, access methods, analysis techniques, or visualization procedures. In this paper, we propose a generic architecture for GIS that provides support for the special nature of geographic information and conforms with the specifications proposed by the ISO/TC 211 and the OGC. Our strategy to achieve this goal consists of two steps: (i) we analyze the special characteristics of GIS with respect to traditional information systems, (ii) and we adapt the traditional three-tier architecture for information systems to take into account the special characteristics of GIS. Finally, we have tried to apply the architecture that we propose in the development of a complete and complex real-life GIS application using commercial tools in the analysis, design and implementation. We describe this application, and we use it to describe the limitations of current commercial GIS development tools by analyzing the differences in the architecture of the resulting system with respect to our proposal.