Spatial planning documents contain information about the principles and rights of land use in different zones of a local authority. They are the basis for administrative decision making in support of sustainable development. In Poland these documents are published on the Web according to a prescribed non-extendable XML schema, designed for optimum presentation to humans in HTML web pages. There is no document standard, and limited functionality exists for adding references to external resources. The text in these documents is discoverable and searchable by general-purpose web search engines, but the semantics of the content cannot be discovered or queried. The spatial information in these documents is geographically referenced but not machine-readable. Major manual efforts are required to integrate such heterogeneous spatial planning documents from various local authorities for analysis, scenario planning and decision support. This article presents results of an implementation using machine-readable semantic metadata to identify relationships among regulations in the text, spatial objects in the drawings and links to external resources. A spatial planning ontology was used to annotate different sections of spatial planning documents with semantic metadata in the Resource Description Framework in Attributes (RDFa). The semantic interpretation of the content, links between document elements and links to external resources were embedded in XHTML pages. An example and use case from the spatial planning domain in Poland is presented to evaluate its efficiency and applicability. The solution enables the automated integration of spatial planning documents from multiple local authorities to assist decision makers with understanding and interpreting spatial planning information. The approach is equally applicable to legal documents from other countries and domains, such as cultural heritage and environmental management.

This paper presents some results of a project aimed at combining the expertise of a human cartographer with software tools to automate the generalization of topographic maps of urban areas from 1:10,000 to 1:50,000 scale. A hybrid system has been created for such generalization, utilizing the MGE Map Generalizer in batch mode to perform the actual map transformations, and a rule based system for controlling the process. A fine level of control was achieved by performing the generalization in small steps working on individual map elements. The maps processed this way are not 100% correct; there are always a number of map elements incorrectly generalized. This is due to some specific features found in local areas, which require special treatment. Such special cases are classified either as exceptions or conflicts and approaches to deal with them are discussed.

GRASS (Geographic Resources Analysis Support System) is a widely used open source desktop GIS system. Its architecture is modular – each of its functions (or a group of functions) is implemented as separate program module running in the common GRASS environment. WPS (Web Processing Service) is the web services specification developed by OGC (Open Geospatial Consortium) for sharing processing abilities over the network according to the SOA (Service Oriented Architecture) paradigm. The specification provides the definitions of the service interface, but does not describe any specific processing functionality offered by the service nor the way of its implementation. This part is left to the WPS service providers who can build their own processing algorithms behind the service interface and offer them to the service clients through the Execute operation. This opens an opportunity to incorporate the GRASS functionality in the service design; especially that modular architecture of GRASS is highly suitable for this task. The number of WPS server implementations with a GRASS as a processing backend is rather small. One of the examples is PyWPS. This paper describes another implementation of WPS (an extendable software framework) with GRASS modules used as processing engines. The implementation described conforms to the OGC WPS version 1.0 specification. The language of implementation is C# language. The IIS (Internet Information Server) and .NET framework are technologies this implementation is based on. The system works in the Windows environment. The connectivity platform between WPS service and GRASS modules is scripting system. The prototype installation offers only few spatial analyses, like: shadowing, morphometric parameters calculation, raster calculator etc. However, it is very easy to extend it with new functions.

Service-oriented architecture (SOA) is a concept of services, architecture and infrastructure that is being widely adopted in a geospatial information domain. It provides foundation for searching, obtaining and viewing spatial information in a distributed environment. The key actors on the scene are service providers and service consumers interacting remotely trough the Internet via HTTP protocol. However, because of open nature and features (such as service bus, service composition, and service virtualization) SOA adoption requires radical changes in the way the information resources are being developed and managed. The needs of setting up a new set of security requirements becomes substantial. Numerous studies on the security subject have been conducted in the IT domain. They resulted with security standards propositions which vary in degree of completion and commercialization, and even occasionally compete. The deficiencies in the open standards definitions are sometimes covered by the proprietary solutions implemented by the security software vendors, but they are related to the vendor technology and distributed on a commercial bases. Regarding geospatial information the research on securing data and services has not been finalized yet. Most recent spatial data infrastructure implementations follows the SOA paradigm and open standards defined by the OGC, ISO and INSPIRE. These standards include specification of GeoDRM architecture (digital rights management) and GeoREL (rights expression language, ISO/CD 19149) for geographic information. The article touches the problem of securing geospatial data and web services focusing on architecture of authorization services based on open standards and technologies. A special attention was given to the access protection to the OGC Web Mapping Services layers and other OGC Web Services. As a result some architecture scenarios were introduced and discussed together with the uniform supervised access mechanism to the functionality of the system components. Some security issues and solutions were discussed that have come about as a result of web services and their related technologies use and are compliant to the GeoRM requirements.

This work presents a new approach to the satellite image classification process. An artificial neural network has been applied for the identification of urban areas mapped in satellite images. The results presented here are based on images obtained from the Landsat satellite using the Thematic Mapper scanner and a land cover map produced under the CORINE Program. The evaluation of the results has been conducted using a point-to-point comparison with a topographic map. The test areas include the metropolitan areas of Warsaw and Cracow.