Full text: Proceedings of the Symposium on Global and Environmental Monitoring (Pt. 1)

152 
- On the knowledge-engineering level, we are conti 
nuously integrating new knowledge from remote 
sensing, geo-science, and image-processing into the 
existing framework of the RESEDA knowledge base. 
It is mainly here that experiences from the applica 
tion level are integrated. A surveying engineer, a 
specialist in remote sensing, is working .on this 
knowledge-acquisition task. 
- On the implementation level we are augmenting the 
representational framework for the RESEDA know 
ledge base and extending the inference and data 
processing subsystem. This work is guided by requi 
rements formulated at the knowledge-engineering 
level. Two software engineers are permanently en 
gaged in these tasks of expert system-design and 
programming. 
Our research aims at an expert system to simplify the use 
of remote sensing techniques for non-expert users. To 
achieve this task we need to elicit the knowledge behind 
these techniques to gain better insight into the concepts 
and models available to a remote sensing expert. Beyond 
building the RESEDA expert system and its knowledge 
base, the research being done in RESEDA also contribu 
tes to the development and refinement of a scientific 
theory of remote sensing. 
References 
B. G. Buchanan and E. H. Shortliffe (eds.), 1984. Rule- 
Based Expert Systems: The MYCIN Experiments of the 
Stanford Heuristic Programming Project. Addison-Wes- 
ley, Reading, MA. 
J. Desachy, 1989. ICARE: An Expert System for Auto 
matic Mapping from Satellite Imagery. In: L.F. Pau 
(ed.), Mapping and Spatial Modeling for Navigation. 
Springer-Verlag. 
J. Gordon and E. Shortliffe, 1985. A Method for Mana 
ging Evidential Reasoning in a Hierarchical Hypotheses 
Space. AI Journal 26: 323-357. 
D.G. Goodenough et al., 1987. An Expert System for 
Remote Sensing. IEEE Transactions on Geoscience and 
Remote Sensing, GE-25 (3): 349-359. 
L. L. F. Jansen, 1990. GIS Supported Land Cover Clas 
sification of Satellite Images. Proceedings of the EGIS’90 
conference, Amsterdam. 
T.M. Lillesand, Ralph W. Kiefer, 1987. Remote Sensing 
and Image Interpretation. John Wiley & Sons. 
D.M. McKeown, Jr., 1987. The Role of Artificial Intel 
ligence in the Integration of Remotely Sensed Data with 
Geographic Information Systems. IEEE Transactions on 
Geoscience and Remote Sensing, GE-25 (3): 330-347. 
H. Middelkoop et al., 1989. Knowledge Engineering for 
Image Interpretation and Classification: a Trial Run. ITC 
Journal 1989-1, Enschede. 
W.-F. Riekert, 1990. The RESEDA Project - A Knowled 
ge Based Approach to Extracting Environmental Infor 
mation from Remote Sensor Data. In: V. Cantoni et al. 
(cds.), Progress in Image Analysis and Processing; Pro 
ceedings of the 5th International Conference on Image 
Processing and Analysis. World Scientific.
	        
Waiting...

Note to user

Dear user,

In response to current developments in the web technology used by the Goobi viewer, the software no longer supports your browser.

Please use one of the following browsers to display this page correctly.

Thank you.