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Mapping from Space – Ontology Based Map Production Using Satellite Imageries : Volume Xl-1/W3, Issue 1 (25/09/2013)

By Asefpour Vakilian, A.

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Book Id: WPLBN0004014518
Format Type: PDF Article :
File Size: Pages 6
Reproduction Date: 2015

Title: Mapping from Space – Ontology Based Map Production Using Satellite Imageries : Volume Xl-1/W3, Issue 1 (25/09/2013)  
Author: Asefpour Vakilian, A.
Volume: Vol. XL-1/W3, Issue 1
Language: English
Subject: Science, Isprs, International
Collections: Periodicals: Journal and Magazine Collection, Copernicus Publications
Publication Date:
Publisher: Copernicus Publications, Göttingen, Germany
Member Page: Copernicus Publications


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Vakilian, A. A., & Momeni, M. (2013). Mapping from Space – Ontology Based Map Production Using Satellite Imageries : Volume Xl-1/W3, Issue 1 (25/09/2013). Retrieved from

Description: Department of Surveying, Faculty of Engineering, University of Isfahan, Hezar Jarib Street, Isfahan, Iran. Determination of the maximum ability for feature extraction from satellite imageries based on ontology procedure using cartographic feature determination is the main objective of this research. Therefore, a special ontology has been developed to extract maximum volume of information available in different high resolution satellite imageries and compare them to the map information layers required in each specific scale due to unified specification for surveying and mapping. ontology seeks to provide an explicit and comprehensive classification of entities in all sphere of being. This study proposes a new method for automatic maximum map feature extraction and reconstruction of high resolution satellite images. For example, in order to extract building blocks to produce 1 : 5000 scale and smaller maps, the road networks located around the building blocks should be determined. Thus, a new building index has been developed based on concepts obtained from ontology. Building blocks have been extracted with completeness about 83 %. Then, road networks have been extracted and reconstructed to create a uniform network with less discontinuity on it. In this case, building blocks have been extracted with proper performance and the false positive value from confusion matrix was reduced by about 7 %. Results showed that vegetation cover and water features have been extracted completely (100 %) and about 71 % of limits have been extracted. Also, the proposed method in this article had the ability to produce a map with largest scale possible from any multi spectral high resolution satellite imagery equal to or smaller than 1 : 5000.



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