Proceedings of the Symposium on Global and Environmental Monitoring: Proceedings of the Symposium on Global and Environmental Monitoring

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Persistent identifier:: 856665355

Title:: Proceedings of the Symposium on Global and Environmental Monitoring

Sub title:: techniques and impacts ; September 17 - 21, 1990, Victoria Conference Centre, Victoria, British Columbia, Canada

Year of publication:: 1990

Place of publication:: Victoria, BC

Publisher of the original:: [Verlag nicht ermittelbar]

Identifier (digital):: 856665355

Language:: English

Document type:: Multivolume work

Volume

Persistent identifier:: 856669164

Title:: Proceedings of the Symposium on Global and Environmental Monitoring

Sub title:: techniques and impacts; September 17 - 21, 1990, Victoria Conference Centre, Victoria, British Columbia, Canada

Scope:: XIV, 912 Seiten

Year of publication:: 1990

Place of publication:: Victoria, BC

Publisher of the original:: [Verlag nicht ermittelbar]

Identifier (digital):: 856669164

Illustration:: Illustrationen, Diagramme, Karten

Signature of the source:: ZS 312(28,7,1)

Language:: English

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Editor:: International Society for Photogrammetry and Remote Sensing, Commission of Photographic and Remote Sensing Data

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2016

Document type:: Volume

Collection:: Earth sciences

Chapter

Title:: [WA-1 KNOWLEDGE-BASED TECHNIQUES/ SYSTEMS FOR DATA FUSION]

Document type:: Multivolume work

Structure type:: Chapter

Chapter

Title:: MODEL-BASED ASSISTANCE FOR ANALYZING REMOTE SENSOR DATA. Wolf-Fritz Riekert, Thomas Ruwwe, Günther Hess

Document type:: Multivolume work

Structure type:: Chapter

Raster Image Data: satellite data scanned aerial photographs Expert Knowledge: concepts end methods from remote sensing, geo-science and Image processing Known Geographic Information: spetiai data factual data Figure 1: Remote sensing as a knowledge-based analysis task X DEVELOPING AN EXPERT SYSTEM TO ASSIST REMOTE SENSING TASKS Instead of developing new data processing methods in remote sensing, the RESEDA project is exploring exi sting operational methods in state-of-the-art remote sen sing projects. Our objectives are to embed these methods into a consistent theoretical framework and to represent them in a knowledge base on a computer system. To this end, we are developing an intelligent advisory system, called the RESEDA Assistant, which makes use of this software knowledge base in order to assist the user in efficiently performing remote sensing tasks. The main purpose of the RESEDA Assistant is to plan the sequence of computations necessary for a given analysis. For that purpose, the user specifies the available data and the desired data. The available data may include sensor data and some additional geographic information repre sented in a resident database or to be entered by the user. From these specifications, the RESEDA Assistant com putes a set of processing plans, that is, sequences of computations. These computations may consist of ima ge-processing operators, statistical evaluations, or mani pulations of spatial data. In the first stage of the RESEDA project, the computed processing plans will be printed out by a prototype system called the RESEDA Advisor and will have to be executed explicitly by the user. The final system, the RESEDA Assistant, will display a set of alternative processing plans as a menu. After selecting one of the menu items, the respective processing plan will be executed automatically by a plan interpreter. In this context, automatic execution means that the appropriate data processing programs are called with correct argu ments in correct sequence; the programs being called may nonetheless run in interactive mode and require intervention by the user, such as digitizing training areas for a supervised classification. Serving as a knowledge- based interface to traditional analysis software, the RESEDA Assistant resembles to the Analyst Advisor developed at the CCRS in Ottawa (Goodenough, 1987) that interfaces the LDIAS data processing system. However, the con cepts of these systems differ, since RESEDA focuses rather on the methodological knowledge of a remote sensing expert than on the facilities offered by a given data analysis system. The global control strategy of the RESEDA expert sy stem is backward chaining. That is, the system first asks for the desired information. The desired information may be described by its format (e.g., image, map, or factual data), its accuracy (i.e., qualitative or quantitative results required), and the subject of interest (i.e., which target classes or target attributes are to be recognized). The system tries to activate processing models that are able to compute the desired information from other data. If this data is not present, the system recursively tries to activate processing models for computing the data. The process stops when the system tries to determine data items that are explicitly labeled as so-called primary data. In this case, the user is asked whether the primary data in question is available. If the user says no, the system tracks back and tries to activate different processing models. The advantage of the backward-chaining strategy is that the user is asked for available data only if this is effecti vely necessary. An alternate design idea, which is not to ask for the available data at all, was rejected, since it would have required the implementation of a complete data management system. This was found not to be feasible because of the great number of foreign data sources that can be made available on demand, such as remote sensing data, geographic databases, raster-scan ned maps, or even printed maps to be digitized manually by the user.

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