Mapping Fine-Scale Crown Scorch in 3D with Remotely Piloted Aircraft Systems

Christopher J. Moran; Valentijn Hoff; Russell A. Parsons; Lloyd P. Queen; Carl A. Seielstad

doi:10.3390/fire5030059

Mapping Fine-Scale Crown Scorch in 3D with Remotely Piloted Aircraft Systems

Christopher J. Moran, Valentijn Hoff, Russell A. Parsons, Lloyd P. Queen, Carl A. Seielstad

W. A. Franke College of Forestry and Conservation

Research output: Contribution to journal › Article › peer-review

7 Scopus citations

Abstract

Remotely piloted aircraft systems (RPAS) are providing fresh perspectives for the remote sensing of fire. One opportunity is mapping tree crown scorch following fires, which can support science and management. This proof-of-concept shows that crown scorch is distinguishable from uninjured canopy in point clouds derived from low-cost RGB and calibrated RGB-NIR cameras at fine resolutions (centimeter level). The Normalized Difference Vegetation Index (NDVI) provided the most discriminatory spectral data, but a low-cost RGB camera provided useful data as well. Scorch heights from the point cloud closely matched field measurements with a mean absolute error of 0.52 m (n = 29). Voxelization of the point cloud, using a simple threshold NDVI classification as an example, provides a suitable dataset worthy of application and further research. Field-measured scorch heights also showed a relationship to RPAS-thermal-camera-derived fire radiative energy density (FRED) estimates with a Spearman rank correlation of 0.43, but there are many issues still to resolve before robust inference is possible. Mapping fine-scale scorch in 3D with RPAS and SfM photogrammetry is a viable, low-cost option that can support related science and management.

Original language	English
Article number	59
Journal	Fire
Volume	5
Issue number	3
DOIs	https://doi.org/10.3390/fire5030059
State	Published - Jun 2022

Funding

This research was funded by the Strategic Environmental Research and Development Program (SERDP), grant number RC20-1025. Funding also provided by the USDA Western Wildland Environmental Threat Assessment Center and the National Center for Landscape Fire Analysis at the University of Montana. Acknowledgments: We thank all those involved in the prescribed burn who are too numerous to list and Sarah Flanary who assisted with initial data collection and plot layout. Three anonymous reviewers’ comments significantly improved the final manuscript. Funding: This research was funded by the Strategic Environmental Research and Development Program (SERDP), grant number RC20-1025. Funding also provided by the USDA Western Wildland Environmental Threat Assessment Center and the National Center for Landscape Fire Analysis at the University of Montana.

Funder number
RC20-1025

Keywords

UAS
UAV
drones
fire effects
photogrammetry
prescribed fire
vegetation mapping

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10.3390/fire5030059

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title = "Mapping Fine-Scale Crown Scorch in 3D with Remotely Piloted Aircraft Systems",

abstract = "Remotely piloted aircraft systems (RPAS) are providing fresh perspectives for the remote sensing of fire. One opportunity is mapping tree crown scorch following fires, which can support science and management. This proof-of-concept shows that crown scorch is distinguishable from uninjured canopy in point clouds derived from low-cost RGB and calibrated RGB-NIR cameras at fine resolutions (centimeter level). The Normalized Difference Vegetation Index (NDVI) provided the most discriminatory spectral data, but a low-cost RGB camera provided useful data as well. Scorch heights from the point cloud closely matched field measurements with a mean absolute error of 0.52 m (n = 29). Voxelization of the point cloud, using a simple threshold NDVI classification as an example, provides a suitable dataset worthy of application and further research. Field-measured scorch heights also showed a relationship to RPAS-thermal-camera-derived fire radiative energy density (FRED) estimates with a Spearman rank correlation of 0.43, but there are many issues still to resolve before robust inference is possible. Mapping fine-scale scorch in 3D with RPAS and SfM photogrammetry is a viable, low-cost option that can support related science and management.",

keywords = "UAS, UAV, drones, fire effects, photogrammetry, prescribed fire, vegetation mapping",

author = "Moran, \{Christopher J.\} and Valentijn Hoff and Parsons, \{Russell A.\} and Queen, \{Lloyd P.\} and Seielstad, \{Carl A.\}",

note = "Publisher Copyright: {\textcopyright} 2022 by the authors. Licensee MDPI, Basel, Switzerland.",

year = "2022",

month = jun,

doi = "10.3390/fire5030059",

language = "English",

volume = "5",

journal = "Fire",

issn = "2571-6255",

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T1 - Mapping Fine-Scale Crown Scorch in 3D with Remotely Piloted Aircraft Systems

AU - Moran, Christopher J.

AU - Hoff, Valentijn

AU - Parsons, Russell A.

AU - Queen, Lloyd P.

AU - Seielstad, Carl A.

PY - 2022/6

Y1 - 2022/6

N2 - Remotely piloted aircraft systems (RPAS) are providing fresh perspectives for the remote sensing of fire. One opportunity is mapping tree crown scorch following fires, which can support science and management. This proof-of-concept shows that crown scorch is distinguishable from uninjured canopy in point clouds derived from low-cost RGB and calibrated RGB-NIR cameras at fine resolutions (centimeter level). The Normalized Difference Vegetation Index (NDVI) provided the most discriminatory spectral data, but a low-cost RGB camera provided useful data as well. Scorch heights from the point cloud closely matched field measurements with a mean absolute error of 0.52 m (n = 29). Voxelization of the point cloud, using a simple threshold NDVI classification as an example, provides a suitable dataset worthy of application and further research. Field-measured scorch heights also showed a relationship to RPAS-thermal-camera-derived fire radiative energy density (FRED) estimates with a Spearman rank correlation of 0.43, but there are many issues still to resolve before robust inference is possible. Mapping fine-scale scorch in 3D with RPAS and SfM photogrammetry is a viable, low-cost option that can support related science and management.

AB - Remotely piloted aircraft systems (RPAS) are providing fresh perspectives for the remote sensing of fire. One opportunity is mapping tree crown scorch following fires, which can support science and management. This proof-of-concept shows that crown scorch is distinguishable from uninjured canopy in point clouds derived from low-cost RGB and calibrated RGB-NIR cameras at fine resolutions (centimeter level). The Normalized Difference Vegetation Index (NDVI) provided the most discriminatory spectral data, but a low-cost RGB camera provided useful data as well. Scorch heights from the point cloud closely matched field measurements with a mean absolute error of 0.52 m (n = 29). Voxelization of the point cloud, using a simple threshold NDVI classification as an example, provides a suitable dataset worthy of application and further research. Field-measured scorch heights also showed a relationship to RPAS-thermal-camera-derived fire radiative energy density (FRED) estimates with a Spearman rank correlation of 0.43, but there are many issues still to resolve before robust inference is possible. Mapping fine-scale scorch in 3D with RPAS and SfM photogrammetry is a viable, low-cost option that can support related science and management.

KW - UAS

KW - UAV

KW - drones

KW - fire effects

KW - photogrammetry

KW - prescribed fire

KW - vegetation mapping

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JO - Fire

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ER -

Mapping Fine-Scale Crown Scorch in 3D with Remotely Piloted Aircraft Systems

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