Please use this identifier to cite or link to this item:
https://doi.org/10.21256/zhaw-4030Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Indermühle, Selina | - |
| dc.contributor.author | Laube, Patrick | - |
| dc.contributor.author | Geilhausen, Martin | - |
| dc.contributor.author | Zwicker, Thomas | - |
| dc.date.accessioned | 2018-10-16T16:27:20Z | - |
| dc.date.available | 2018-10-16T16:27:20Z | - |
| dc.date.issued | 2014 | - |
| dc.identifier.uri | https://digitalcollection.zhaw.ch/handle/11475/11876 | - |
| dc.description.abstract | Modern urban planning considers various socio-economic issues and hence requires fine-grained, potentially sensitive spatial data, raising the disclosure dilemma: Whilst it is imperative to aggregate fine-grained sensitive records large enough to avoid disclosure, aggregation blurs the information, potentially hindering insights about spatially explicit relationships. MASC is an aggregation algorithm for sensitive data, balancing five aggregation criteria. | de_CH |
| dc.language.iso | en | de_CH |
| dc.publisher | ZHAW Zürcher Hochschule für Angewandte Wissenschaften | de_CH |
| dc.rights | Licence according to publishing contract | de_CH |
| dc.subject | Cartographic generalization | de_CH |
| dc.subject | Census data | de_CH |
| dc.subject.ddc | 711: Raumplanung (Städtebau) | de_CH |
| dc.title | Multi-criteria aggregation for sensistive parcel-based census data | de_CH |
| dc.type | Konferenz: Poster | de_CH |
| dcterms.type | Text | de_CH |
| zhaw.departement | Life Sciences und Facility Management | de_CH |
| zhaw.organisationalunit | Institut für Umwelt und Natürliche Ressourcen (IUNR) | de_CH |
| dc.identifier.doi | 10.21256/zhaw-4030 | - |
| zhaw.conference.details | 8th International Conference on Geographic Information Science, Vienna, Austria, 24-26 September 2014 | de_CH |
| zhaw.funding.eu | No | de_CH |
| zhaw.originated.zhaw | Yes | de_CH |
| zhaw.publication.status | publishedVersion | de_CH |
| zhaw.publication.review | Peer review (Abstract) | de_CH |
| zhaw.webfeed | Geoinformatik | de_CH |
| zhaw.funding.zhaw | modularCity | de_CH |
| Appears in collections: | Publikationen Life Sciences und Facility Management | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| laup_GIScience14_poster.pdf | 2.48 MB | Adobe PDF |  View/Open |
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Indermühle, S., Laube, P., Geilhausen, M., & Zwicker, T. (2014). Multi-criteria aggregation for sensistive parcel-based census data. 8th International Conference on Geographic Information Science, Vienna, Austria, 24-26 September 2014. https://doi.org/10.21256/zhaw-4030
Indermühle, S. et al. (2014) ‘Multi-criteria aggregation for sensistive parcel-based census data’, in 8th International Conference on Geographic Information Science, Vienna, Austria, 24-26 September 2014. ZHAW Zürcher Hochschule für Angewandte Wissenschaften. Available at: https://doi.org/10.21256/zhaw-4030.
S. Indermühle, P. Laube, M. Geilhausen, and T. Zwicker, “Multi-criteria aggregation for sensistive parcel-based census data,” in 8th International Conference on Geographic Information Science, Vienna, Austria, 24-26 September 2014, 2014. doi: 10.21256/zhaw-4030.
INDERMÜHLE, Selina, Patrick LAUBE, Martin GEILHAUSEN und Thomas ZWICKER, 2014. Multi-criteria aggregation for sensistive parcel-based census data. In: 8th International Conference on Geographic Information Science, Vienna, Austria, 24-26 September 2014. Conference poster. ZHAW Zürcher Hochschule für Angewandte Wissenschaften. 2014
Indermühle, Selina, Patrick Laube, Martin Geilhausen, and Thomas Zwicker. 2014. “Multi-Criteria Aggregation for Sensistive Parcel-Based Census Data.” Conference poster. In 8th International Conference on Geographic Information Science, Vienna, Austria, 24-26 September 2014. ZHAW Zürcher Hochschule für Angewandte Wissenschaften. https://doi.org/10.21256/zhaw-4030.
Indermühle, Selina, et al. “Multi-Criteria Aggregation for Sensistive Parcel-Based Census Data.” 8th International Conference on Geographic Information Science, Vienna, Austria, 24-26 September 2014, ZHAW Zürcher Hochschule für Angewandte Wissenschaften, 2014, https://doi.org/10.21256/zhaw-4030.
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