<div class="csl-bib-body">
<div class="csl-entry">Gao, S. (2023). Explainable AI for Urban Land Cover Classification Using Mobile Application Traffic Data. In <i>Proceedings of the 18th International Conference on Location Based Services</i> (pp. 82–86). https://doi.org/10.34726/5739</div>
</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/194764
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dc.identifier.uri
https://doi.org/10.34726/5739
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dc.description.abstract
This research explores the use of mobile application traffic data to interpret urban land cover classification using explainable machine learning methods. The experiments using a high-resolution mobile service traffic data in Paris, France show that the hourly downlink traffic of Microsoft Office, Netflix, and Uber together with the XGBoost model can accurately classify land cover types and the SHAP values help interpret instance-level feature importance and their spatial patterns.
en
dc.language.iso
en
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dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
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dc.subject
Explainable GeoAI
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dc.subject
LBS
en
dc.subject
Location Big Data
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dc.title
Explainable AI for Urban Land Cover Classification Using Mobile Application Traffic Data
en
dc.type
Inproceedings
en
dc.type
Konferenzbeitrag
de
dc.rights.license
Creative Commons Namensnennung 4.0 International
de
dc.rights.license
Creative Commons Attribution 4.0 International
en
dc.identifier.doi
10.34726/5739
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dc.contributor.affiliation
University of Wisconsin–Madison, United States of America (the)
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dc.relation.doi
10.34726/5400
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dc.description.startpage
82
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dc.description.endpage
86
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dc.rights.holder
Authors
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dc.type.category
Full-Paper Contribution
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tuw.booktitle
Proceedings of the 18th International Conference on Location Based Services
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tuw.relation.ispartof
10.34726/5400
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tuw.researchTopic.id
I5
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tuw.researchTopic.name
Visual Computing and Human-Centered Technology
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tuw.researchTopic.value
100
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tuw.publication.orgunit
E000 - Technische Universität Wien
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dc.description.numberOfPages
5
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dc.rights.identifier
CC BY 4.0
de
dc.rights.identifier
CC BY 4.0
en
tuw.event.name
18th International Conference on Location Based Services (LBS 2023)
en
tuw.event.startdate
20-11-2023
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tuw.event.enddate
22-11-2023
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tuw.event.online
On Site
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tuw.event.type
Event for scientific audience
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tuw.event.place
Ghent
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tuw.event.country
BE
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tuw.event.presenter
Gao, Song
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item.fulltext
with Fulltext
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item.grantfulltext
open
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item.languageiso639-1
en
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item.mimetype
application/pdf
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item.openairetype
conference paper
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item.cerifentitytype
Publications
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item.openaccessfulltext
Open Access
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item.openairecristype
http://purl.org/coar/resource_type/c_5794
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crisitem.author.dept
University of Wisconsin–Madison, United States of America (the)
