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Instantaneous Pre-Fire Biomass and Fuel Load Measurements from Multi-Spectral UAS Mapping in Southern African Savannas

1
Department of Earth Sciences, Faculty of Science, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
2
Charles Darwin University, P.O. Box 40146, Casuarina, Darwin NT 0811, Australia
3
Department of Forest Engineering, Faculty of Agronomy and Forest Engineering, Universidade Eduardo Mondlane, Avenida Julius Nyerere, Street. nr. 3453, Maputo, Mozambique
4
Wildlife Conservation Society Mozambique, Orlando Mendes Street, no.163, Sommerschield, Maputo, Mozambique
*
Author to whom correspondence should be addressed.
Received: 11 November 2020 / Revised: 22 December 2020 / Accepted: 5 January 2021 / Published: 14 January 2021
Landscape fires are substantial sources of (greenhouse) gases and aerosols. Fires in savanna landscapes represent more than half of global fire carbon emissions. Quantifying emissions from fires relies on accurate burned area, fuel load and burning efficiency data. Of these, fuel load remains the source of the largest uncertainty. In this study, we used high spatial resolution images from an Unmanned Aircraft System (UAS) mounted multispectral camera, in combination with meteorological data from the ERA-5 land dataset, to model instantaneous pre-fire above-ground biomass. We constrained our model with ground measurements taken in two locations in savanna-dominated regions in Southern Africa, one low-rainfall region (660 mm year1) in the North-West District (Ngamiland), Botswana, and one high-rainfall region (940 mm year1) in Niassa Province (northern Mozambique). We found that for fine surface fuel classes (live grass and dead plant litter), the model was able to reproduce measured Above-Ground Biomass (AGB) (R2 of 0.91 and 0.77 for live grass and total fine fuel, respectively) across both low and high rainfall areas. The model was less successful in representing other classes, e.g., woody debris, but in the regions considered, these are less relevant to biomass burning and make smaller contributions to total AGB. View Full-Text
Keywords: burning; biomass burning; fuel load; savanna fire; drone; UAS; remote sensing burning; biomass burning; fuel load; savanna fire; drone; UAS; remote sensing
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MDPI and ACS Style

Eames, T.; Russell-Smith, J.; Yates, C.; Edwards, A.; Vernooij, R.; Ribeiro, N.; Steinbruch, F.; van der Werf, G.R. Instantaneous Pre-Fire Biomass and Fuel Load Measurements from Multi-Spectral UAS Mapping in Southern African Savannas. Fire 2021, 4, 2. https://0-doi-org.brum.beds.ac.uk/10.3390/fire4010002

AMA Style

Eames T, Russell-Smith J, Yates C, Edwards A, Vernooij R, Ribeiro N, Steinbruch F, van der Werf GR. Instantaneous Pre-Fire Biomass and Fuel Load Measurements from Multi-Spectral UAS Mapping in Southern African Savannas. Fire. 2021; 4(1):2. https://0-doi-org.brum.beds.ac.uk/10.3390/fire4010002

Chicago/Turabian Style

Eames, Tom, Jeremy Russell-Smith, Cameron Yates, Andrew Edwards, Roland Vernooij, Natasha Ribeiro, Franziska Steinbruch, and Guido R. van der Werf 2021. "Instantaneous Pre-Fire Biomass and Fuel Load Measurements from Multi-Spectral UAS Mapping in Southern African Savannas" Fire 4, no. 1: 2. https://0-doi-org.brum.beds.ac.uk/10.3390/fire4010002

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