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Towards the Use of Crowdsourced Volunteered Meteorological Data for Forest Fire Monitoring

Authors:
Sagi Dalyot
Shay Sosko

Keywords: VGI; crowdsourcing; geosensor netowrk; densification; forest fires.

Abstract:
Static geosensor networks equipped with variety of sensors are used for collecting and transmitting physical data from their surrounding environment. These geosensor networks are used for monitoring potential disaster areas for early warning systems. Weather stations are an example of such static geosensor networks used for the collection of meteorological data, as temperature, humidity, pressure, wind direction and speed, used, for example, as input data for forest fire prediction and behavior systems. Nevertheless, static geosensor networks show some limitations, in terms of insufficient coverage, low density, nondynamical, limited power source and budget constraints. In recent years, the use of crowdsourced Volunteered Geographic Information (VGI) has emerged as a working methodology for retrieving real-time data in disaster areas; thus, allowing real-time and continuous aggregation of data and production of information. Using VGI methodologies, having the capacity of collecting dynamic real-time data can reduce deficiencies related to the use of static geosensor networks. This study is aimed at proving the feasibility of using VGI data as a reliable data source for reducing weather geosensor network limitations along with estimating the reliability and accuracy of crowdsourced data. This is done by analyzing the observations made by smartphones to prove their capacity. An example is presented to emphasize the potential of using crowdsourced VGI to densify and enhance static geosensor networks.

Pages: 127 to 132

Copyright: Copyright (c) IARIA, 2015

Publication date: February 22, 2015

Published in: conference

ISSN: 2308-393X

ISBN: 978-1-61208-383-4

Location: Lisbon, Portugal

Dates: from February 22, 2015 to February 27, 2015