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The Canadian Fire Spread Dataset.
Barber, Quinn E; Jain, Piyush; Whitman, Ellen; Thompson, Dan K; Guindon, Luc; Parks, Sean A; Wang, Xianli; Hethcoat, Matthew G; Parisien, Marc-André.
Affiliation
  • Barber QE; Northern Forestry Centre, Canadian Forest Service, Natural Resources Canada, 5320-122 Street NW, Edmonton, AB, T6H 3S5, Canada. quinn.barber@nrcan-rncan.gc.ca.
  • Jain P; Northern Forestry Centre, Canadian Forest Service, Natural Resources Canada, 5320-122 Street NW, Edmonton, AB, T6H 3S5, Canada.
  • Whitman E; Northern Forestry Centre, Canadian Forest Service, Natural Resources Canada, 5320-122 Street NW, Edmonton, AB, T6H 3S5, Canada.
  • Thompson DK; Great Lakes Forestry Centre, Canadian Forest Service, Natural Resources Canada, 1219 Queen Street, Sault Ste. Marie, ON, P6A 2E5, Canada.
  • Guindon L; Laurentian Forestry Centre, Canadian Forest Service, Natural Resources Canada, 1055 Rue du Peps, P.O. Box 10380, Station Sainte-Foy, Quebec City, QC, G1V 4C7, Canada.
  • Parks SA; USDA Forest Service, Rocky Mountain Research Station, Aldo Leopold Wilderness Research Institute, 790 E. Beckwith Ave., Missoula, MT, United States of America.
  • Wang X; Northern Forestry Centre, Canadian Forest Service, Natural Resources Canada, 5320-122 Street NW, Edmonton, AB, T6H 3S5, Canada.
  • Hethcoat MG; Northern Forestry Centre, Canadian Forest Service, Natural Resources Canada, 5320-122 Street NW, Edmonton, AB, T6H 3S5, Canada.
  • Parisien MA; Northern Forestry Centre, Canadian Forest Service, Natural Resources Canada, 5320-122 Street NW, Edmonton, AB, T6H 3S5, Canada.
Sci Data ; 11(1): 764, 2024 Jul 11.
Article in En | MEDLINE | ID: mdl-38992042
ABSTRACT
Satellite data are effective for mapping wildfires, particularly in remote locations where monitoring is rare. Geolocated fire detections can be used for enhanced fire management and fire modelling through daily fire progression mapping. Here we present the Canadian Fire Spread Dataset (CFSDS), encompassing interpolated progressions for fires >1,000 ha in Canada from 2002-2021, representing the day-of-burning and 50 environmental covariates for every pixel. Day-of-burning was calculated by ordinary kriging of active fire detections from the Moderate Resolution Imaging Spectroradiometer and the Visible Infrared Imaging Radiometer Suite, enabling a substantial improvement in coverage and resolution over existing datasets. Day of burning at each pixel was used to identify environmental conditions of burning such as daily weather, derived weather metrics, topography, and forest fuels characteristics. This dataset can be used in a broad range of research and management applications, such as retrospective analysis of fire spread, as a benchmark dataset for validating statistical or machine-learning models, and for forecasting the effects of climate change on fire activity.

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Sci Data / Scientific data Year: 2024 Document type: Article Affiliation country: Canadá Country of publication: Reino Unido

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Sci Data / Scientific data Year: 2024 Document type: Article Affiliation country: Canadá Country of publication: Reino Unido