The joining of geospatial datasets is required to utilize the complete set of information available in each of them. There are many open source geospatial datasets available such as GeoNames, Open Street Map, Natural Earth and to get a comprehensive dataset with the union of all available information it is important that such datasets are linked optimally without redundancy or loss of information. Many of the geolocations on digital maps are not classified for importance because of the lack of additional information such as population or administrative level. A way to give an importance scale to the names is by linking the GeoNames to other datasets (OSM, natural earth). OpenStreetMap data provides a limited number of place classifications (such as city, town, village). For the best cartographic results we need classes that are a little more comprehensive about how they rank cities.

Interlinking opensource geo-spatial datasets for optimal utility in ranking / Bhattacharya, D.; Pasquali, P.; Komarkova, J.; Sedlak, P.; Saha, A.; Boccardo, P. (LECTURE NOTES IN GEOINFORMATION AND CARTOGRAPHY). - In: Lecture Notes in Geoinformation and Cartography[s.l] : Springer Berlin Heidelberg, 2015. - ISBN 978-3-319-07925-7. - pp. 159-172 [10.1007/978-3-319-07926-4_13]

Interlinking opensource geo-spatial datasets for optimal utility in ranking

Bhattacharya D.;Boccardo P.
2015

Abstract

The joining of geospatial datasets is required to utilize the complete set of information available in each of them. There are many open source geospatial datasets available such as GeoNames, Open Street Map, Natural Earth and to get a comprehensive dataset with the union of all available information it is important that such datasets are linked optimally without redundancy or loss of information. Many of the geolocations on digital maps are not classified for importance because of the lack of additional information such as population or administrative level. A way to give an importance scale to the names is by linking the GeoNames to other datasets (OSM, natural earth). OpenStreetMap data provides a limited number of place classifications (such as city, town, village). For the best cartographic results we need classes that are a little more comprehensive about how they rank cities.
2015
978-3-319-07925-7
978-3-319-07926-4
Lecture Notes in Geoinformation and Cartography
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2762032
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