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Towards Spatially Explicit Quantification of Pre- and Postfire Fuels and Fuel Consumption from Traditional and Point Cloud Measurements
- Source :
- Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual), Universidade de São Paulo (USP), instacron:USP
- Publication Year :
- 2020
- Publisher :
- Oxford University Press (OUP), 2020.
-
Abstract
- Methods to accurately estimate spatially explicit fuel consumption are needed because consumption relates directly to fire behavior, effects, and smoke emissions. Our objective was to quantify sparkleberry (Vaccinium arboretum Marshall) shrub fuels before and after six experimental prescribed fires at Fort Jackson in South Carolina. We used a novel approach to characterize shrubs non-destructively from three-dimensional (3D) point cloud data collected with a terrestrial laser scanner. The point cloud data were reduced to 0.001 m–3 voxels that were either occupied to indicate fuel presence or empty to indicate fuel absence. The density of occupied voxels was related significantly by a logarithmic function to 3D fuel bulk density samples that were destructively harvested (adjusted R2 = .32, P < .0001). Based on our findings, a survey-grade Global Navigation Satellite System may be necessary to accurately associate 3D point cloud data to 3D fuel bulk density measurements destructively collected in small (submeter) shrub plots. A recommendation for future research is to accurately geolocate and quantify the occupied volume of entire shrubs as 3D objects that can be used to train models to map shrub fuel bulk density from point cloud data binned to occupied 3D voxels.
- Subjects :
- 040101 forestry
010504 meteorology & atmospheric sciences
Ecology
Laser scanning
ved/biology
Ecological Modeling
ved/biology.organism_classification_rank.species
Point cloud
Forestry
04 agricultural and veterinary sciences
TECNOLOGIA LIDAR
computer.software_genre
01 natural sciences
Bulk density
Shrub
Geolocation
Volume (thermodynamics)
Voxel
Fuel efficiency
0401 agriculture, forestry, and fisheries
Environmental science
computer
0105 earth and related environmental sciences
Remote sensing
Subjects
Details
- ISSN :
- 19383738 and 0015749X
- Volume :
- 66
- Database :
- OpenAIRE
- Journal :
- Forest Science
- Accession number :
- edsair.doi.dedup.....2a9ab69713e3d55c370b7c490ffce366
- Full Text :
- https://doi.org/10.1093/forsci/fxz085