Georeferencing Oblique Aerial Wildfire Photographs: An Untapped Source of Fire Behaviour Data”
| dc.contributor.author | Hart, Henry | |
| dc.contributor.author | Perrakis, Daniel D. B. | |
| dc.contributor.author | Taylor, Stephen W. | |
| dc.contributor.author | Bone, Christopher | |
| dc.contributor.author | Bozzini, Claudio | |
| dc.date.accessioned | 2021-11-01T17:51:44Z | |
| dc.date.available | 2021-11-01T17:51:44Z | |
| dc.date.copyright | 2021 | en_US |
| dc.date.issued | 2021 | |
| dc.description | The authors wish to thank the BC Provincial Air Tanker Centre for the archive of aerial wildfire images and Patrick Day at GeoBC/FLNRORD for the LiDAR and Orthoimage access. Thanks are also extended to Chris Stockdale and Claudio Bozzini for hosting a MPT training course in Edmonton, AB, Canada and for their continued support regarding MPT troubleshooting. Finally, we would like to thank the three anonymous reviewers whose comments improved the manuscript as well as Rick Lanoville for his passion and original ideas on wildfire image analysis. | en_US |
| dc.description.abstract | In this study, we investigate a novel application of the photogrammetric monoplotting technique for assessing wildfires. We demonstrate the use of the software program WSL Monoplotting Tool (MPT) to georeference operational oblique aerial wildfire photographs taken during airtanker response in the early stages of fire growth. We located the position of the fire front in georeferenced pairs of photos from five fires taken 31–118 min apart, and calculated the head fire spread distance and head fire rate of spread (HROS). Our example photos were taken 0.7 to 4.7 km from fire fronts, with camera angles of incidence from –19 to –50 [degrees] to image centre. Using high quality images with detailed landscape features, it is possible to identify fire front positions with high precision; in our example data, the mean 3D error was 0.533 m and the maximum 3D error for individual fire runs was less than 3 m. This resulted in a maximum HROS error due to monoplotting of only ~0.5%. We then compared HROS estimates with predictions from the Canadian Fire Behavior Prediction System, with differences mainly attributed to model error or uncertainty in weather and fuel inputs. This method can be used to obtain observations to validate fire spread models or create new empirical relationships where databases of such wildfire photos exist. Our initial work suggests that monophotogrammetry can provide reproducible estimates of fire front position, spread distance and rate of spread with high accuracy, and could potentially be used to characterize other fire features such as flame and smoke plume dimensions and spotting. | en_US |
| dc.description.reviewstatus | Reviewed | en_US |
| dc.description.scholarlevel | Faculty | en_US |
| dc.description.sponsorship | This research was funded by the Natural Resources Canada-Canadian Forest Service’s Emergency Management System program as a grant under Account 51574-58300. | en_US |
| dc.identifier.citation | Hart, H., Perrakis, D. D. B., Taylor, S. W., Bone, C., & Bozzini, C. (2021). Georeferencing oblique aerial wildfire photographs: An untapped source of fire behaviour data. fire, 4(81), 1-19. https://doi.org/10.3390/fire4040081 | en_US |
| dc.identifier.uri | https://doi.org/10.3390/fire4040081 | |
| dc.identifier.uri | http://hdl.handle.net/1828/13473 | |
| dc.language.iso | en | en_US |
| dc.publisher | fire | en_US |
| dc.subject | wildfire modelling | |
| dc.subject | fire behaviour | |
| dc.subject | rate of spread | |
| dc.subject | remote sensing | |
| dc.subject | monophotogrammetry | |
| dc.subject | WSL monoplotting tool | |
| dc.subject | georeferencing | |
| dc.subject | oblique aerial wildfire photography | |
| dc.subject.department | Department of Geography | |
| dc.title | Georeferencing Oblique Aerial Wildfire Photographs: An Untapped Source of Fire Behaviour Data” | en_US |
| dc.type | Article | en_US |