Spatially-Explicit Prediction of Wildfire Burn Probability Using Remotely-Sensed and Ancillary Data-Reference-Cited by-同舟云学术

Spatially-Explicit Prediction of Wildfire Burn Probability Using Remotely-Sensed and Ancillary Data

Published:2020-05-03 Issue:3 Volume:46 Page:313-329
ISSN:0703-8992
Container-title:Canadian Journal of Remote Sensing
language:en
Short-container-title:Canadian Journal of Remote Sensing

Author:

Shang Chen¹,Wulder Michael A.²^ORCID,Coops Nicholas C.¹^ORCID,White Joanne C.²^ORCID,Hermosilla Txomin²^ORCID

Affiliation:

1. Department of Forest Resources Management, Faculty of Forestry, Integrated Remote Sensing Studio, University of British Columbia, 2424 Main Mall, Vancouver, British Columbia, V6T 1Z4, Canada

2. Canadian Forest Service (Pacific Forestry Centre), Natural Resources Canada, 506 West Burnside Road, Victoria, British Columbia, V8Z 1M5, Canada

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/07038992.2020.1788385

Reference97 articles.

1. A comparison of landscape fuel treatment strategies to mitigate wildland fire risk in the urban interface and preserve old forest structure

2. Assessing Wildland Fire Risk Transmission to Communities in Northern Spain

3. Integrating forest fuels and land cover data for improved estimation of fuel consumption and carbon emissions from boreal fires

4. Effect of site preparation on soil properties and vegetation cover, and the growth and survival of white spruce (Picea glauca) seedlings, in Saskatchewan

5. Random forest in remote sensing: A review of applications and future directions

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