Use of remote sensing-derived variables in developing a forest fire danger forecasting system

dc.contributor.authorChowdhury, Ehsan
dc.contributor.authorHassan, Quazi
dc.date.accessioned2015-03-29T17:39:17Z
dc.date.available2015-03-29T17:39:17Z
dc.date.issued2013-01-26
dc.description.abstractOur aim was to develop a remote sensing-based forest fire danger forecasting system (FFDFS) and its implementation in forecasting 2011 fire season in the Canadian province of Alberta. The FFDFS used Moderate Resolution Imaging Spectroradiometer (MODIS)-derived 8-day composites of surface temperature, normalized multiband drought index, and normalized difference vegetation index as input variables. In order to eliminate the data gaps in the input variables, we propose a gap-filling technique by considering both of the spatial and temporal dimensions. These input variables were calculated during the i period and then integrated to forecast the fire danger conditions into four categories (i.e., very high, high, moderate, and low) during the i ? 1 period. It was observed that 98.19 % of the fire fell under ‘‘very high’’ to ‘‘moderate’’ danger classes. The performance of this system was also demonstrated its ability to forecast the worst fires occurred in Slave Lake and Fort McMurray region during mid-May 2011. For example, 100 and 94.0 % of the fire spots fell under ‘‘very high’’ to ‘‘high’’ danger categories for Slave Lake and Fort McMurray regions, respectively.en_US
dc.identifier.citationChowdhury, E.H.; Hassan, Q.K. 2013. Use of remote sensing-derived variables in developing a forest fire danger forecasting system. Natural Hazards 67, 321-334.en_US
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/10041
dc.identifier.issn1573-0840
dc.identifier.urihttp://hdl.handle.net/1880/50395
dc.language.isoen_USen_US
dc.publisherSpringer Netherlandsen_US
dc.publisher.departmentGeomatics Engineeringen_US
dc.publisher.facultySchulich School of Engineeringen_US
dc.publisher.institutionUniversity of Calgaryen_US
dc.subjectRemote sensingen_US
dc.subjectFire dangeren_US
dc.subjectForecastingen_US
dc.subjectIndicesen_US
dc.titleUse of remote sensing-derived variables in developing a forest fire danger forecasting systemen_US
dc.typejournal article
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