Data · dataset · 2021
A Random Forest Algorithm for Learning and Updating Fuel Types for Fire Research
Listed in Borealis and Agri-environmental Research Data Dataverse — shown once because both records carry DOI 10.5683/sp2/n45050
Wildfire drives a tremendous amount of forest and land cover change in the central interior of British Columbia, Canada.
Description
Fuel type maps have been acknowledged as critical references to conduct landscape-level fire simulations as well as fire behavior predictions. Nonetheless, the current thematic maps are not updated on an annual basis and cannot be easily produced at a certain scale and speed.
The objective of this research was to test the hypothesis – that machine learning algorithm can augment the current manual wildfire fuel types identification system and can help to update fuel types on an annual basis, in the meantime the accuracy of the algorithm can meet the standards of The Ministry of Forests, Lands, Natural Resource Operations and Rural Development (BC FLNRO). The random forest algorithm was applied over a 40 000-km² landscape in central interior British Columbia that burned from a megafire in 2017.
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Fuel maps were obtained from the years 2013-2017, with the cross-validation overall accuracy reached 98.57% and the overall accuracy of confusion matrix tested on the validation set reached 92.35%. Various recommendations are given for future research using machine learning algorithms for fuel mapping such as assuring pre-processing procedure follows delicate standards, modifying the machine learning algorithm, and adopting other sources of remotely sensed data.
Links
Where it is published
- Dataverse dataset page borealisdata.ca/dataset.xhtml?persistentId=doi%3A10.5683%2FSP2%2FN45050 ↗
landing page · from borealisdata ca
- DOI doi.org/10.5683/sp2/n45050 ↗
DOI / persistent id · from borealisdata ca
Catalogue records · 1
- Dataverse API borealisdata.ca/api/datasets/:persistentId/?persistentId=doi%3A10.5683%2FSP2%2… ↗
metadata API · from borealisdata ca
Topics
- Stated by source
- Earth and Environmental Sciences · Earth and Environmental Sciences
- From keywords
- Chemistry · Computer Science & AI · Earth & Environmental Science · Earth & Environmental Science · Economics & Finance · Energy · Energy · Engineering · Humanities · Life Sciences · Mathematics & Statistics · Medicine & Health · Ocean & Atmospheric Science · Social Science
- Inferred from text
- Fire ecology 80%
Provenance · 2 source records, 23 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Borealis | doi:10.5683/SP2/N45050 | 13 d ago | JSON v1 |
| Agri-environmental Research Data Dataverse | doi:10.5683/SP2/N45050 | 12 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].anzsrc:field:410205 | enrichment · borealisdata ca | taxonomy-embedding@1.0.0 | title+keywords+description (80%) |
| concepts[field].dataverse_subject:earth-and-environmental-sciences | source · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].dataverse_subject:earth-and-environmental-sciences | source · borealisdata ca | connector:borealisdata_ca@1.0.0 | /subjects |
| concepts[field].local:field:chemistry | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:computer-science-ai | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:earth-environmental | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:earth-environmental | mapping · borealisdata ca | connector:borealisdata_ca@1.0.0 | /subjects |
| concepts[field].local:field:economics-finance | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:energy | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:energy | mapping · borealisdata ca | connector:borealisdata_ca@1.0.0 | /subjects |
| concepts[field].local:field:engineering | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:humanities | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:life-sciences | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:mathematics-statistics | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:medicine-health | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:ocean-atmospheric | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| concepts[field].local:field:social-science | mapping · borealisdata ca dataverse | connector:borealisdata_ca_dataverse@1.0.0 | /subjects |
| created_date | source · borealisdata ca | connector:borealisdata_ca@1.0.0 | |
| description | source · borealisdata ca | connector:borealisdata_ca@1.0.0 | /description |
| publication_date | source · borealisdata ca | connector:borealisdata_ca@1.0.0 | |
| title | source · borealisdata ca | connector:borealisdata_ca@1.0.0 | /name |
| updated_date | source · borealisdata ca | connector:borealisdata_ca@1.0.0 | |
| version_label | source · borealisdata ca | connector:borealisdata_ca@1.0.0 |