Geographic Information Systems Community Research Articles

The Evolution of Public Participation GIS

(1998). The Evolution of Public Participation GIS. Cartography and Geographic Information Systems: Vol. 25, No. 2, pp. 65-66.

Catchment infiltration II: Contributing areas

This study considers two issues of interest to the hydrologic and geographical information systems community. One deals with identifying the spatial distribution of infiltration and runoff contributing areas. The other addresses process modelling within a GIS framework. The study operates on the premise that partitioning of precipitation into runoff or infiltration depends on rainfall intensity and on soil properties. The problem is that neither local rainfall intensity, nor soil properties such as infiltration capacity and macroporosity are known well enough for all points of a catchment and need to be estimated. We infer local intensity from the interpolated distribution of cumulated rain depths over the catchment and record duration at the official met site. Measured values of sorptivity and hydraulic conductivity define infiltration. Negative head infiltration describes macroporosity. To scale‐up measured point values to larger areas and to model infiltration and macropore continuity at a catchment scale we use geostatistical kriging and conditional simulation together with standard GIS techniques of overlay manipulation. Results delineate areas contributing to runoff and infiltration and relate them to macroporosity. By intersecting overlays of precipitation with those of infiltration we create alternate GIS masks targeting specific portions of the watershed as either runoff or infiltration contributing zones. Choice of cell size and time interval define the scales of averaging for the application. Kriged surfaces illustrate the distribution of catchment infiltration, while conditional simulation provides a mechanism to define model uncertainty.

Spatial Data Models for Managing Subsurface Data

Most geographic information system (GIS) software encodes topological relationships between spatial objects, such as neighborhood and inclusion, in node‐line‐polygon tables. However, some applications require semantic relationships that have been difficult to represent in tables. Both the data‐base and GIS communities have documented that data‐base management systems should better support the requirements of spatial data analysis so that engineering applications can extend beyond the planning and management paradigms. Some GISs are incorporating feature‐based characteristics by implementing extensible or object‐oriented data management to meet new needs. Feature‐based systems attempt to add more meaning to data bases that contain natural resource or geographic data. This paper presents the current georelational representation of a system that manages subsurface boring log data for hydrological, geotechnical, and environmental applications. The paper includes an overview of feature‐based GIS and describes ...

Database copyright issues in the European GIS community

The production and dissemination of European geographic information system (GIS) databases are rapidly outpacing the legal structure's ability to protect and regulate the flow of such information. This situation places increased pressure on users, suppliers, and official copyright authorities to adjust the law to accommodate these changes. Database suppliers argue that the present unevenness of the European legal protection setting creates an uncertain and risky environment which is not conducive to investment. In response, the Commission of the European Communities (CEC) has proposed a Directive on the Copyright of Databases to address the concerns of the database industry. This article outlines the current legal structure of the European GIS database industry, critiques the impending CEC Directive, and emphasizes the inevitable need for global consensus on these important issues.

Geographic information systems and spatial analysis

Geographical Information Systems (GIS) are capable of acquiring spatially indexed data from a variety of sources, changing the data into useful formats, storing the data, retrieving and manupulating the data for analysis, and then generating the output required by a given user. Their great strength is based on the ability to handle large, multilayered, heterogenous databases and to query about the existence, location and properties of a wide range of spatial objects in an interactive way. The lack of analytical and modelling functionality is, however, widely recognised as a major deficiency of current systems. There is a wide agreement in both the GIS community and the modelling community that the future success of GIS technology will depend to a large extent on incorporating more powerful analytical and modelling capabilities. This paper discusses some major directions and strategies to increase both the analytical and modelling capabilities and the level of intelligence of geographic information systems.

The Role of Artificial Intelligence in the Integration of Remotely Sensed Data with Geographic Information Systems

Although databases for geographic information systems (GIS) have been developed to manage digital map data, the integration of remotely sensed imagery and other collateral non-map information is rarely performed. For the most part, the use of sophisticated intelligent spatial databases, in which the user can query interactively about map, terrain, or associated imagery, is unknown in the GIS and cartographic community. In standard GIS systems, the ability to formulate complex queries requiring dynamic computation of factual and geometric properties is severely limited, often reflecting its origin as collections of thematic map overlays. Spatial database research requires the integration of ideas and techniques from many disciplines such as computer graphics, computational geometry, database methodology, image analysis, photogrammetry, and artificial intelligence. In this paper we discuss some ideas on how the scope of geographic information systems can be expanded by utilizing techniques from the Al community that may remedy deficiencies in user interfaces, spatial data representation, and its utilization. We draw on ongoing research at Carnegie Mellon University for examples of these techniques in the areas of image/map database and knowledge-based image interpretation.

The National Science Foundation National Center for Geographic Information and Analysis

Abstract The National Science Foundation will soon establish a National Center devoted to geographical research and education based on geographical information systems (GIS). The Center will be located at a university chosen on the basis of competitive proposals that will be evaluated primarily on the quality of their research agendas. The winning institution will be expected to involve government agencies and private firms in Center operations and programmes, and it will be expected to serve the national GIS community. The Center arose from a suggestion made by a member of the GIS research community. A large-scale database initiative and a Foundation commitment to Science and Technology Centers provided an institutional environment hospitable to the Center. There are similarities and differences in the approach taken toward GIS research, policy and applications in the United Kingdom (UK) and in the United States (US). Those similarities and differences offer promising topics for collaborative research on...