Fusion of sensor data, knowledge sources and algorithms for extraction and classification of topographic objects

baltsavias, emmanuel p.

Bibliographic data

Monograph

Persistent identifier:: 856473650

Author:: Baltsavias, Emmanuel P.

Title:: Fusion of sensor data, knowledge sources and algorithms for extraction and classification of topographic objects

Sub title:: Joint ISPRS/EARSeL Workshop ; 3 - 4 June 1999, Valladolid, Spain

Scope:: III, 209 Seiten

Year of publication:: 1999

Place of publication:: Coventry

Publisher of the original:: RICS Books

Identifier (digital):: 856473650

Illustration:: Illustrationen, Diagramme, Karten

Language:: English

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

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:: Monograph

Collection:: Earth sciences

Chapter

Title:: TECHNICAL SESSION 6 INTEGRATION OF IMAGE ANALYSIS AND GIS

Document type:: Monograph

Structure type:: Chapter

Chapter

Title:: INVESTIGATION OF SYNERGY EFFECTS BETWEEN SATELLITE IMAGERY AND DIGITAL TOPOGRAPHIC DATABASES BY USING INTEGRATED KNOWLEDGE PROCESSING. Dietmar Kunz

Document type:: Monograph

Structure type:: Chapter

International Archives of Photogrammetry and Remote Sensing, Vol. 32, Part 7-4-3 W6, Valladolid, Spain, 3-4 June, 1999 144 INVESTIGATION OF SYNERGY EFFECTS BETWEEN SATELLITE IMAGERY AND DIGITAL TOPOGRAPHIC DATABASES BY USING INTEGRATED KNOWLEDGE PROCESSING Dietmar Kunz Institute of Photogrammetry and Remote Sensing, University of Karlsruhe, Englerstr. 7, D-76128 Karlsruhe, Germany kunz@ipf.uni-karlsruhe.de KEYWORDS: Image Analysis, ATKIS-DLM 200, Symbolic Scene Description, Disjoint Topographic Objects, Semantic Classification, Semantic Network ABSTRACT The aim of this approach is to obtain an improved and automated satellite image analysis with regard to the determination of landuse classes by means of specific knowledge, which is represented in digital topographic databases. Because of the relatively poor geometric resolution of common satellite sensors (e.g. Landsat TM with 30 m) this project concentrates on main area-based landuse classes like ’settlement’, forest’, ’water’ or ’agriculture’. By using integrated knowledge processing (data fusion) in feature extraction, building of disjoint geometric objects and a classification process, the resulting semantic scene description is more accurate than with classical methods of satellite image analysis. The pixel-oriented satellite image and the vector-oriented topographic database are two different sources of knowledge. Both present a description of the same scene, but from different perspectives. For the comparison of the two different knowledge bases, it is necessary to introduce methods on higher symbolic level. The results of feature extraction supply this symbolic description of the satellite image, while the topographic database is already on this higher level. By means of an intersection of both geometric scene descriptions from segmentation and topographic database, we obtain a new unambiguous scene description with disjoint objects. The classification process is performed in a semantic network, which is able to process general and specific knowledge about the topographic and disjoint objects. The use of a semantic network for satellite image analysis is new. After the classification, disjoint objects with the same semantic meaning and a common border are merged. The result is a complete semantic description of the scene. Experiences with the represented knowledge based analysis process confirm the efficiency of this concept by a better separability of object classes. The determination of a good valuation function of spectral as well as non-spectral features in the decision process that is performed in the semantic network has however proved to be a very complex and time consuming task. 1. INTRODUCTION The main emphasis of this paper is placed on the investigation and use of synergy effects between satellite image analysis and digital topographic database. Since several years many countries all over the world have been building-up digital topographic databases for planning, modelling and visualization purposes. In Germany, the surveying administration has designed and created the topographic database ATKIS (Authoritative Topographic Cartographic Information System) (AdV, 1989). ATKIS is divided into three different landscape models DLM25, DLM200 and DLM1000, which contain mainly the objects of the official topographical maps at scales 1:25,000, 1:200,000 and 1:1,000,000 respectively. For updating such a given topographic database, the detail of image information should be higher. Because of common satellite sensors with resolution of approximately 10m to 30m, this project concentrates on the DLM200 map information. The use of such topographic databases can support and improve the satellite image analysis, not only for a knowledge based feature extraction, but also in the following process of semantic modelling of the topographic objects contained in the scene. Fig. 1. Flowchart of the analysis process. real world digital database satellite image ATKIS

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