Data Mining - Concepts and Techniques.

The GIS software sector has developed rapidly over the last ten years. Open Source GIS applications are gaining relevant market shares in academia, business, and public administration. In this paper, we illustrate the history and features of a key Open Source GIS, the Geographical Resources Analysis Support System (GRASS). GRASS has been under development for more than 28 years, has strong ties into academia, and its review mechanisms led to the integration of well tested and documented algorithms into a joint GIS suite which has been used regularly for environmental modelling. The development is community-based with developers distributed globally. Through the use of an online source code repository, mailing lists and a Wiki, users and developers communicate in order to review existing code and develop new methods. In this paper, we provide a functionality overview of the more than 400 modules available in the latest stable GRASS software release. This new release runs natively on common operating systems (MS-Windows, GNU/Linux, Mac OSX), giving basic and advanced functionality to casual and expert users. In the second part, we review selected publications with a focus on environmental modelling to illustrate the wealth of use cases for this open and free GIS.

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GRASS GIS: A multi-purpose open source GIS

Implementation: How Great Expectations in Washington Are Dashed in Oakland; Or Why It's Amazing That Federal Programs Work at All . By Jeffrey L. Pressman and Aaron B. Wildavsky. (Berkeley: University of California Press, 1973. Pp. xviii, 182. $7.50.)

CityGML is the international standard of the Open Geospatial Consortium (OGC) for the representation and exchange of 3D city models It defines the three-dimensional geometry, topology, semantics and appearance of the most relevant topographic objects in urban or regional contexts These definitions are provided in different, well-defined Levels-of-Detail (multiresolution model) The focus of CityGML is on the semantical aspects of 3D city models, its structures, taxonomies and aggregations, allowing users to employ virtual 3D city models for advanced analysis and visualization tasks in a variety of application domains such as urban planning, indoor/outdoor pedestrian navigation, environmental simulations, cultural heritage, or facility management This is in contrast to purely geometrical/graphical models such as KML, VRML, or X3D, which do not provide sufficient semantics CityGML is based on the Geography Markup Language (GML), which provides a standardized geometry model Due to this model and its well-defined semantics and structures, CityGML facilitates interoperable data exchange in the context of geo web services and spatial data infrastructures Since its standardization in 2008, CityGML has become used on a worldwide scale: tools from notable companies in the geospatial field provide CityGML interfaces Many applications and projects use this standard CityGML is also having a strong impact on science: numerous approaches use CityGML, particularly its semantics, for disaster management, emergency responses, or energy-related applications as well as for visualizations, or they contribute to CityGML, improving its consistency and validity, or use CityGML, particularly its different Levels-of-Detail, as a source or target for generalizations This paper gives an overview of CityGML, its underlying concepts, its Levels-of-Detail, how to extend it, its applications, its likely future development, and the role it plays in scientific research Furthermore, its relationship to other standards from the fields of computer graphics and computer-aided architectural design and to the prospective INSPIRE model are discussed, as well as the impact CityGML has and is having on the software industry, on applications of 3D city models, and on science generally

CityGML – Interoperable semantic 3D city models

The emergence of geoportals and their role in spatial data infrastructures

The European geoportal––one step towards the establishment of a European Spatial Data Infrastructure

In this paper we study the feasibility of using services offered by a Spatial Data Infrastructure as a basis for distributed service oriented geoprocessing. By developing a prototype we demonstrate that a Spatial Data Infrastructure facilitates rapid development of applications that solve typical problems for an existing risk management application. The prototype provides users with a distributed application that enables the assessment of fire damage areas based on land cover data in a given area. The services involved in the application include: Web Feature Services, Web Map Services, a Gazetteer Service, a Catalogue Service, and Geoprocessing Services. We present the architecture of the application and describe details about implementation-specific issues. We conclude that current OGC specifications provide a sound basis for developing service oriented architectures for geographic applications; however, in particular for geoprocessing applications, we question the

Designing Service Architectures for Distributed Geoprocessing: Challenges and Future Directions

The synthesis of spatial data from the various sources available on the Web is a major challenge for current applications based on Web-based information retrieval and spatial decision-making. This article addresses spatial data fusion, with particular emphasis on its application in Spatial Data Infrastructures SDIs. Possibilities for the integration of SDI and Semantic Web developments in the context of spatial data fusion are reviewed with a focus on the harmonized description and usage of feature relations. Specifically, potential applications of Linked Data principles are discussed in detail. On this basis, a classification and a decomposition of fusion processes in a service-oriented environment are proposed. A prototype implementation demonstrates the feasibility and usability of the approach using Open Geospatial Consortium OGC and Semantic Web standards.

https://www.tandfonline.com/doi/pdf/10.1080/13658816.2015.1084420

Spatial data fusion in Spatial Data Infrastructures using Linked Data

This article describes the conception and implementation of a web platform which uses special charts and maps for climate monitoring and analysis. At first it gives an overview of related web appli...

https://www.tandfonline.com/doi/pdf/10.1080/17538947.2020.1829112

ClimateCharts.net – an interactive climate analysis web platform

This paper is offered as a contribution to the Workshop on Cross-learning between Spatial Data Infrastructures, and Information Infrastructures, Enschede, 31 March-1 April, 2005. Its purpose is to consider some of the key challenges we see for the development of Spatial Data Infrastructures (SDIs) in the short and medium term. Although much attention has been given recently to the initiative of the European Commission aimed at developing an Infrastructure for Spatial Information in Europe (INSPIRE) we deliberately have chosen not to focus specifically on the requirements of this initiative but to consider the broader research questions raised by the development of SDIs. Many of the questions raised by the paper are likely to be relevant also to Information Infrastructure research and to other domains-specific infrastructures, and these synergies will hopefully emerge form the discussion at the Workshop. The paper is organised in two main sections considering technical challenges, and socio-economic impacts respectively. The paper does not claim to be exhaustive in the research needs, and many important areas such as ethical considerations, privacy, and security are not addressed here even though they are clearly of major importance for the future development of SDIs, and related infrastructures.

Lars Bernard

Papers

The European geoportal––one step towards the establishment of a European Spatial Data Infrastructure

Designing Service Architectures for Distributed Geoprocessing: Challenges and Future Directions

Spatial data fusion in Spatial Data Infrastructures using Linked Data

ClimateCharts.net – an interactive climate analysis web platform

SDI - From Spatial Data Infrastructure to Service Driven Infrastructure