Remote Sensing | |
Development of a New Daily-Scale Forest Fire Danger Forecasting System Using Remote Sensing Data | |
Ehsan H. Chowdhury2  Quazi K. Hassan1  Ioannis Gitas2  | |
[1] Department of Geomatics Engineering, Schulich School of Engineering, University of Calgary, 2500 University Dr NW, Calgary, AB T2N 1N4, Canada; E-Mail | |
关键词: fire spot; normalized multiband drought index; normalized difference vegetation index; operational perspective; precipitable water; surface temperature; | |
DOI : 10.3390/rs70302431 | |
来源: mdpi | |
【 摘 要 】
Forest fires are a critical natural disturbance in most of the forested ecosystems around the globe, including the Canadian boreal forest where fires are recurrent. Here, our goal was to develop a new daily-scale forest fire danger forecasting system (FFDFS) using remote sensing data and implement it over the northern part of Canadian province of Alberta during 2009–2011 fire seasons. The daily-scale FFDFS was comprised of Moderate Resolution Imaging Spectroradiometer (MODIS)-derived four-input variables,
【 授权许可】
CC BY
© 2015 by the authors; licensee MDPI, Basel, Switzerland.
【 预 览 】
Files | Size | Format | View |
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RO202003190015925ZK.pdf | 5445KB | download |