Handling spatio-temporal uncertainties of geo-objects for dynamic update of GIS databases from multisource data

Ryosuke Shibasaki

doi:10.1117/12.182835

17 August 1994 Handling spatio-temporal uncertainties of geo-objects for dynamic update of GIS databases from multisource data

Ryosuke Shibasaki

Author Affiliations +

Proceedings Volume 2357, ISPRS Commission III Symposium: Spatial Information from Digital Photogrammetry and Computer Vision; (1994) https://doi.org/10.1117/12.182835
Event: Spatial Information from Digital Photogrammetry and Computer Vision: ISPRS Commission III Symposium, 1994, Munich, Germany

Abstract

As more GISs are used in many institutions and fields, the importance of keeping GIS database current is keenly recognized. To fulfill the requirement, a concept of dynamic update of GIS databases using a wide variety of data from multiple sources is proposed and a methodological framework is proposed to realize it. At first, a model to represent geo-objects with spatio- temporal uncertainties is proposed. The model can serve as a basis to handle geo-objects with different levels of spatio-temporal uncertainties especially in integrating data from multiple sources. Secondly, a method is proposed to estimate or reconstruct the status of relatively static geo-objects which only emerge and extinguish using observational data from multiple sources. Further extension of the method is required to estimate the status of more dynamic geo-objects. To merge geometric data with different levels of uncertainties, a method to estimate the `most probable' position of a line feature with a statistically sound basis is proposed. It is necessary to validate the effectiveness of this methodological framework using actual data of an urban object such as houses or structures.

Citation Download Citation

Ryosuke Shibasaki "Handling spatio-temporal uncertainties of geo-objects for dynamic update of GIS databases from multisource data", Proc. SPIE 2357, ISPRS Commission III Symposium: Spatial Information from Digital Photogrammetry and Computer Vision, (17 August 1994); https://doi.org/10.1117/12.182835

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