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Building Instance Classification using Social Media Images

Hoffmann, Eike Jens and Werner, Martin and Zhu, Xiao Xiang (2019) Building Instance Classification using Social Media Images. In: 2019 Joint Urban Remote Sensing Event, JURSE 2019, pp. 1-4. JURSE 2019, 22.-24. Mai 2019, Vannes, France.

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Official URL: http://jurse2019.org/

Abstract

Understanding urbanization and planning for theupcoming changes require detailed knowledge about the placeswhere people live and work. Thus, knowing the usage of buildingsis inevitable to distinguish between residential and commercialplaces. Assessing the usage of buildings from an aerial perspectivealone is challenging and results in unresolveable ambiguities.Ascomplementary data sources, social media images taken fromground level allow access to the building fac ̧ades, as well asongoing social activities around the buildings, which are veryvaluable information while coming to accessing the buildingusages. Towards the fusion of social media images and remotesensing data for this purpose, in this work we present a methodto assess building usages from social media images taken in theirneighborhood. Using a straight forward next neighbor classifierfor mapping images to buildings and pre-trained networks fordimensionality reduction we trained a logistic regression classifierto distinguish between five different building usage classes.Applied to a study area of Los Angeles metropolitan area, USA,we obtain an average precision of 0.67. Hence, we show thatsocial media images can be a valuable additional source to remotesensing data.

Item URL in elib:https://elib.dlr.de/128126/
Document Type:Conference or Workshop Item (Poster)
Title:Building Instance Classification using Social Media Images
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Hoffmann, Eike JensTU Münchenhttps://orcid.org/0000-0001-7702-0403
Werner, MartinDLRUNSPECIFIED
Zhu, Xiao Xiangxiao.zhu (at) dlr.deUNSPECIFIED
Date:2019
Journal or Publication Title:2019 Joint Urban Remote Sensing Event, JURSE 2019
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Page Range:pp. 1-4
Status:Published
Keywords:Building Classification, Social Media, Building Usage, Social Media Image, Complementary Data Source
Event Title:JURSE 2019
Event Location:Vannes, France
Event Type:international Conference
Event Dates:22.-24. Mai 2019
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Vorhaben Geowissenschaftl. Fernerkundungs- und GIS-Verfahren
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > EO Data Science
Deposited By: Hoffmann, Eike Jens
Deposited On:01 Jul 2019 13:13
Last Modified:06 Dec 2019 17:59

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