First AGILE-Conference (ASSOCIATION OF GEOGRAPHIC INFORMATION LABORATORIES IN EUROPE),  23.-25.-April 1998, ITC, Enschede (NL), ITC-Publications.

GIS- or environmental analysis tasks are specific to individual Information Communities (ICs) and related to their spatial questions and problems to solve. The accomplishing GIS-tasks exist in a variety of complexity. These tasks can be solved through well defined GIS- Operations. The user’s demands are metadata driven process and operation design. For this, a conceptual framework and generic design of analytical GIS-Operators have to be built up. To fulfil all requirements of spatial analysis, the simultaneous and combinational processing of vector and raster data is needed. For reaching this approach, a zoom-in towards the functionality of hybrid analysis is needed.

All spatial data analysis systems, including image processing and GIS, offer a large amount of algorithms and analytical operations to solve spatial problems. For non-experts, this variety as well as the complexity of operations, mostly technical in nature, often impede fast digital solutions. Necessary system decisions, different data formats, data structures, and data models as well as the lack of compatibility are additional drawbacks to theme of GIS for different spatially related tasks. What is needed is a broad technical toolbox that is capable of supplying full functionality for a wide range of complex spatial problems. Consequently there are strong demands to design operators closer to the user’s needs, but still of universal nature. That requires independence from any Information Community and its specific applications.

During the design of each analysis task, these operations have to be modelled in a data independent manner. This means, the operations have to be designed at a high level of abstraction as universal analytical GIS-Operators. At this level, the operators are independent of any data catalogue, data type or data structure.

At task level which manages the operation due to the application, the operators only work with metadata where the end-user is responsible for the conceptual task. The operation is defined by the input data and task with the underlying functionality. Both are selected from catalogues and their metadata: The input data is chosen from a data catalogue, the functionality is selected from an operation library and its metadata.

The results are data in a data catalogue, attached with new metadata and the results, descriptions and characteristics of the operation.

Based on this conceptual, technology independent modelling of an operator, a mapping to the technological tools is needed. For that, requirements of interoperability in geoprocessing have to be fulfilled. The generic design of the operator’s functionality should be able to process any kind of geographic data types (point, line, area, nodes, edges, meshes, grid, tin, raster ...).

Especially for the integration and combination of vector and raster technology (e.g. for the integration of GIS and remote sensing), there is an increasing need for hybrid analysis. This paper represents an approach to design and structure such universal and generic operators.

An overview is shown in figure 1: An operator needs input, and its results are the output. Input, the operator itself and the output consist of data and metadata, all concerning geometry and semantics (chapter 2). A zoom-in to the architecture of such an operator is focused in chapter 3, where the different levels of abstraction are classified as management, controlling and processing. In chapter 4 specifications of different components as user interface, plausibility check as well as data types and algorithms are described. The descriptive and cognitive control of the operations is made upon the metadata for input, output and the operator. The relationships and mapping between them have to be known (see chapter 5). The increasing need of hybrid analysis asks for hybrid functionality. The basic principles for that are shown in chapter 6.

The design of Analysis-Operators in GIS predominantly concerns their structure and behaviour. A universal analytical GIS- operator is characterised by its functionality. It is able to analyse the input data to choose the appropriate algorithm. As a result, new output data are generated. A High-Level- Operator has to be metadata driven. For selecting data and functionality, only metadata will be used. The following survey describes the concept of operators and their input and output data. Their relationships are also shown in figure 2.

The functionality of a GIS-Analysis-Operator can be modelled by the following three categories: geometric converter, semantic translator and metadata processor. Each category concerns different kind of data.

The controlling of the operator includes the preconditions that are derived from the input data and the chosen operation with its implemented algorithms. For the output, the postconditions include the requirements of the output data. The operation has to be protocolled including the lineage and other metadata.

The technical implementation of the described conceptual design of analysis operations asks for concrete solutions. Therefor the operator is divided into three levels of abstraction. The design is a top-down concept because of its user- oriented and user-friendly approach. At high level, concerning the management , the operator works with metadata only. It is this level which the user is faced with. At mid level, the control of the operations, including the handling of the data types and the metadata, is performed. At low level, the algorithms are processed and protocolled.

The universality of an operator is displayed at the highest level of abstraction because of its design which is independent of data structure and data schema. The interactions between the levels directly concern neighbour levels because of their hierarchy. The core of such a universal operator is at the control level. The performance of the operator is carried out at the processing level.

Based upon the operator design described above, the specification of a generic high level spatial analysis operator is necessary to create instances of an operator class "high level-operators". An instance of that class could be any high level operator, e.g. buffer, overlay, shortest path. At the current state of development the specification introduced in this section does not claim to be complete or formal in mathematical terms. It rather serves as a more detailed description of components in order to approach to a formal specification. It is the attempt to outline the general conditions necessary to create high level operators. Therefore it has to be regarded as a step towards the realisation of operator design.

The variety of instances of high level operators, design and specification comprises different aspects. The data structure independence of the management level has to be implemented through a data type driven polymorphism at the control level. Due to the polymorphism a high level operator is able to execute different algorithms or sequences of algorithms at the processing level.

In addition, cognitive and semantic aspects can not be neglected in operator design. Yet the structure of data plays a central role in the building process of high level operators concerning different parts of the specification.

The user interface specifies what kind of interaction can take place between the user and the operator. User interaction includes any form of communication between the user and the operator, such as:

Plausibility control of an operator should be able to determine whether an operation proves to be meaningful or not. Representation of this advanced form of semantics has to be one level above the creation of the correct data type management. It comprises several aspects.

Assumed that spatial data are organised in data types, it has to be exactly specified which data types can be processed by an operator and which data types will be produced by the operator after processing. Data types distinguish between different representations of geometry within spatial data.

Polymorphism stands for different algorithms related to different data types of the same high level operator. Program structures are created at the control level by decisions made according to data types, user parametrisation and semantic specifications. To include conditions have to be fulfilled:

At processing level standard software development guidelines have to be regarded. It is planned to choose an object-oriented approach with certain advantages related to the described operator design.

Optional is an extension of high level operators towards the restricted and/or expanded use in certain information communities. That would require:

Metadata is used to manage all operators at the highest level of abstraction. At the interface or management level, only metadata control user interaction. Explicit and implicit metadata are analysed to control the operator at mid level. The metadata have different meanings at the three levels as described in chapter ??.

In the following, the processing of metadata for high level-GIS-operators is divided into two parts: metadata of spatial data and metadata of the operator.

The metadata describe the data at a high level of abstraction in a data catalogue with its related information. The information is the link to the database and to its data schema in which all other information is stored implicitly.

The operator metadata control their spatial analysis process. They map and process the metadata of input and output and protocol the operation and the lineage.

Hybrid analysis is part of polymorph implementation of GIS-analysis-operations. Hybrid analysis is needed for the integration of GIS and remote sensing, for terrain analysis (DTM’s in raster format with overlay of vector data) etc.

As input data, we have raster and vector data which have to interact correctly. The result of a hybrid analysis are new raster data, vector data or both of them.

Some examples of hybrid analysis functionality

The complexity of the hybrid functionality may be shown by the following survey:

The full range of spatial analysis may be reached with operations that interact with raster and vector data without the need of conversion. The requirements of hybrid analysis are divided in geometric interaction, semantic analysis and metadata processing.

The concept of universal analytical GIS-Operators independent of Information Communities has been outlined and specified. Universality in this context includes a domain independence as well as the aim to work with data . This can only be achieved by metadata driven user interaction.

To generate the aspired data structure independence of universal operators, hybrid analysis techniques have to be integrated. Due to a currently increasing demand for the integration of remote sensing and GIS, hybrid analysis gains significance. Our future work will focus on a detailed specification of hybrid analysis operations and its prototypical implementation.