SDI and crowdsourced spatial information management automation for disaster management

Koswatte, Saman and McDougall, Kevin and Liu, Xiaoye (2014) SDI and crowdsourced spatial information management automation for disaster management. In: FIG Commission 3 Workshop 2014, 4-7 Nov 2014, Bologna, Italy.

Abstract

Modern disaster reporting is becoming increasingly sophisticated with the ready access to social media and user friendly online mapping tools. The general public’s 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, although quality and credibility issues exist. Although Spatial Data Infrastructures (SDIs) have proven to be successful in coping with disaster management activities in the past, delays in providing public mapping portals and feedback have emerged. Within the current limitations, the lack of currency and
incomplete data are prominent in SDIs. Crowd actions in the 2011 Queensland Floods caught the attention of disaster responders. Crowd support and crowd generated spatial data has the potential to speed up disaster management actions and disaster mitigations. Within the study, crowd communications which occurred during the 2011 Queensland floods through 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 Maps streets and Google streets to compare the accuracy of the street and address names provided through the crowd sourced 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: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: No evidence of copyright restrictions preventing deposit.
Faculty / Department / School: Current - Faculty of Health, Engineering and Sciences - School of Civil Engineering and Surveying
Date Deposited: 30 Jan 2015 02:30
Last Modified: 12 Jun 2017 04:44
Uncontrolled Keywords: SDI, crowdsourcing, Ushahidi, Queensland floods, SIM automation
Fields of Research : 08 Information and Computing Sciences > 0806 Information Systems > 080607 Information Engineering and Theory
09 Engineering > 0909 Geomatic Engineering > 090903 Geospatial Information Systems
Socio-Economic Objective: B Economic Development > 89 Information and Communication Services > 8903 Information Services > 890399 Information Services not elsewhere classified
URI: http://eprints.usq.edu.au/id/eprint/26623

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