SDI and crowdsourced spatial information management automation for disaster management

Koswatte, S. and McDougall, K. and Liu, X. (2015) SDI and crowdsourced spatial information management automation for disaster management. Survey Review, 47 (344). pp. 307-315. ISSN 0039-6265

Abstract

Modern disaster reporting is becoming increasingly sophisticated with the ready access to social media and user-friendly online mapping tools. Citizen engagement in location enabled disaster reporting is more obvious, and the availability of crowd generated geospatial data is higher than ever before. Crowd generated geospatial content is current and more diverse than conventional geographic information; however, quality and credibility issues exist. Although spatial data infrastructures (SDIs) have proven to be successful in supporting disaster management activities in the past, delays in providing public mapping portals and gaps in data are common. Crowd support and crowd generated spatial data have the potential to speed up disaster management actions and disaster mitigations. Within the study, crowd communications that occurred during the 2011 Queensland floods through the Australian Broadcasting Corporation's (ABC's) QLD flood crisis map were critically analysed to investigate the readiness of current information sources to support disaster management. The accuracy of the reported event locations were compared to the authoritative Queensland Government street network, Open Street Map's (OSM's) streets and Google streets to compare the accuracy of the street and address names provided through the crowdsourced data. The study reveals that several issues exist regarding the quality of the data provided and the intent of the data provider. Moreover, the results indicate that the direct usage of reported location is problematic and that the semantic processing of the information location along with available spatial data may be required to improve data quality.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: Permanent restriction to paper, in accordance with the copyright policy of the publisher.
Faculty / Department / School: Current - Faculty of Health, Engineering and Sciences - School of Civil Engineering and Surveying
Date Deposited: 22 Apr 2016 04:31
Last Modified: 19 Sep 2017 02:24
Uncontrolled Keywords: SDI, crowdsourcing, Ushahidi, QLD floods, SIM automation
Fields of Research : 09 Engineering > 0909 Geomatic Engineering > 090903 Geospatial Information Systems
Socio-Economic Objective: E Expanding Knowledge > 97 Expanding Knowledge > 970108 Expanding Knowledge in the Information and Computing Sciences
Identification Number or DOI: 10.1179/1752270615Y.0000000008
URI: http://eprints.usq.edu.au/id/eprint/28404

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