Segmentation quality evaluation for large scale mapping purposes in Flanders, Belgium
In Flanders the large scale reference database called GRB, takes care of the layout, exchange and management of large scale geographic information with respect to, amongst others, roads, buildings and parcels. As Flanders is extremely urbanized (average population density of about 450 inhabitants per square kilometer), the large scale maps need to be highly accurate. Currently, accuracies at the centimeter level are guaranteed due to topographic field measurements aided by standard photogrammetry based on analogue aerial photographs. In order to speed up the GRB production and to ensure large... Mehr ...
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Dokumenttyp: | conference |
Erscheinungsdatum: | 2010 |
Verlag/Hrsg.: |
Copernicus Gesellschaft
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Schlagwörter: | Science General / Image segmentation / segmentation evaluation / segmentation quality / large scale mapping |
Sprache: | Englisch |
Permalink: | https://search.fid-benelux.de/Record/base-27379766 |
Datenquelle: | BASE; Originalkatalog |
Powered By: | BASE |
Link(s) : | https://biblio.ugent.be/publication/1220278 |
In Flanders the large scale reference database called GRB, takes care of the layout, exchange and management of large scale geographic information with respect to, amongst others, roads, buildings and parcels. As Flanders is extremely urbanized (average population density of about 450 inhabitants per square kilometer), the large scale maps need to be highly accurate. Currently, accuracies at the centimeter level are guaranteed due to topographic field measurements aided by standard photogrammetry based on analogue aerial photographs. In order to speed up the GRB production and to ensure large scale map products at the long term, it is essential to automate this labour-intensive, but highly accurate production process. Segmentation of very high resolution digital images could be an alternative approach for maintaining and updating the Flemish GRB as long as high accuracy segmentation results are obtained. Based on DMC images (8 cm ground resolution) and several reference buildings, a comprehensive sensitivity analysis is performed testing different segmentation parameter settings in order to gain insight into their impact on segmentation accuracy. The segmentation quality is evaluated using similarity measures focusing on aspects of presence, shape and positional accuracy where emphasis is placed on interpretability of the measures with respect to operational conditions put on the reference data. The end user should be able to read the measures and link this to the return-on-investment he will gain by using a given segmentation process on his data.