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Remote Sens. 2016, 8(12), 1000; doi:10.3390/rs8121000

Tropical Peatland Burn Depth and Combustion Heterogeneity Assessed Using UAV Photogrammetry and Airborne LiDAR

1
Department of Geography, King’s College London, London WC2R 2LS, UK
2
National Centre for Earth Observation (NCEO), Natural Environment Research Council, Leicester LE1 7RH, UK
3
Zoological Society of London, London NW1 4RY, UK
4
Deltares, Boussinesqweg 1, 2629 HV Delft, The Netherlands
5
Zoological Society of London Indonesia, Kota Jambi 36124, Sumatra, Indonesia
*
Author to whom correspondence should be addressed.
Academic Editors: Krishna Prasad Vadrevu, Rama Nemani, Chris Justice, Garik Gutman, Ioannis Gitas and Prasad S. Thenkabail
Received: 4 October 2016 / Revised: 14 November 2016 / Accepted: 29 November 2016 / Published: 6 December 2016
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Abstract

We provide the first assessment of tropical peatland depth of burn (DoB) using structure from motion (SfM) photogrammetry, applied to imagery collected using a low-cost, low-altitude unmanned aerial vehicle (UAV) system operated over a 5.2 ha tropical peatland in Jambi Province on Sumatra, Indonesia. Tropical peat soils are the result of thousands of years of dead biomass accumulation, and when burned are globally significant net sources of carbon emissions. The El Niño year of 2015 saw huge areas of Indonesia affected by tropical peatland fires, more so than any year since 1997. However, the Depth of Burn (DoB) of these 2015 fires has not been assessed, and indeed has only previously been assessed in few tropical peatland burns in Kalimantan. Therefore, DoB remains arguably the largest uncertainty when undertaking fire emissions calculations in these tropical peatland environments. We apply a SfM photogrammetric methodology to map this DoB metric, and also investigate combustion heterogeneity using orthomosaic photography collected using the UAV system. We supplement this information with pre-burn airborne light detection and ranging (LiDAR) data, reducing uncertainty by estimating pre-burn soil height more accurately than from interpolation of adjacent unburned areas alone. Our pre-and post-fire Digital Terrain Models (DTMs) show accuracies of 0.04 and 0.05 m (root-mean-square error, RMSE) respectively, compared to ground-based global navigation satellite system (GNSS) surveys. Our final DoB map of a 5.2 ha degraded peat swamp forest area neighboring Berbak National Park (Sumatra, Indonesia) shows burn depths extending from close to zero to over 1 m, with a mean (±1σ) DoB of 0.23 ± 0.19 m. This lies well within the range found by the few other studies available (on Kalimantan; none are available on Sumatra). Our combustion heterogeneity analysis suggests the deepest burns, which extend to ~1.3 m, occur around tree roots. We use these DoB data within the Intergovernmental Panel on Climate Change (IPCC) default equation for fire emissions to estimate mean carbon emissions as 134 ± 29 t·C∙ha−1 for this peatland fire, which is in an area that had not had a recorded fire previously. This is amongst the highest per unit area fuel consumption anywhere in the world for landscape fires. Our approach provides significant uncertainty reductions in such emissions calculations via the reduction in DoB uncertainty, and by using the UAV SfM approach this is accomplished at a fraction of the cost of airborne LiDAR—albeit over limited sized areas at present. Deploying this approach at locations across Indonesia, sampling a variety of fire-affected landscapes, would provide new and important DoB statistics for producing optimized carbon and greenhouse gas (GHG) emissions estimates from peatland fires. View Full-Text
Keywords: unmanned aerial vehicle (UAV); structure from motion (SfM); light detection and ranging (LiDAR); peat fire; depth of burn (DoB); carbon emissions; Indonesia; reducing emissions from deforestation and forest degradation (REDD+) unmanned aerial vehicle (UAV); structure from motion (SfM); light detection and ranging (LiDAR); peat fire; depth of burn (DoB); carbon emissions; Indonesia; reducing emissions from deforestation and forest degradation (REDD+)
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Simpson, J.E.; Wooster, M.J.; Smith, T.E.L.; Trivedi, M.; Vernimmen, R.R.E.; Dedi, R.; Shakti, M.; Dinata, Y. Tropical Peatland Burn Depth and Combustion Heterogeneity Assessed Using UAV Photogrammetry and Airborne LiDAR. Remote Sens. 2016, 8, 1000.

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