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Remote Sensing of Wildfire Using a Small Unmanned Aerial System: Post-Fire Mapping, Vegetation Recovery and Damage Analysis in Grand Bay, Mississippi/Alabama, USA

1
Geosystems Research Institute, Mississippi State University, Mississippi State, MS 39762, USA
2
Grand Bay National Estuarine Research Reserve, Moss Point, MS, 39562, USA
*
Author to whom correspondence should be addressed.
Drones 2019, 3(2), 43; https://doi.org/10.3390/drones3020043
Received: 4 April 2019 / Revised: 6 May 2019 / Accepted: 7 May 2019 / Published: 9 May 2019
Wildfires can be beneficial for native vegetation. However, wildfires can impact property values, human safety, and ecosystem function. Resource managers require safe, easy to use, timely, and cost-effective methods for quantifying wildfire damage and regeneration. In this work, we demonstrate an approach using an unmanned aerial system (UAS) equipped with a MicaSense RedEdge multispectral sensor to classify and estimate wildfire damage in a coastal marsh. We collected approximately 7.2 km2 of five-band multispectral imagery after a wildfire event in February 2016, which was used to create a photogrammetry-based digital surface model (DSM) and orthomosaic for object-based classification analysis. Airborne light detection and ranging data were used to validate the accuracy of the DSM. Four-band airborne imagery from pre- and post-fire were used to estimate pre-fire health, post-fire damage, and track the vegetation recovery process. Immediate and long-term post-fire classifications, area, and volume of burned regions were produced to track the revegetation progress. The UAS-based classification produced from normalized difference vegetation index and DSM was compared to the Landsat-based Burned Area Reflectance Classification. Experimental results show the potential of using UAS and the presented approach compared to satellite-based mapping in terms of classification accuracies, turnaround time, and spatial and temporal resolutions. View Full-Text
Keywords: wildfire; damage assessment; vegetation recovery wildfire; damage assessment; vegetation recovery
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MDPI and ACS Style

Samiappan, S.; Hathcock, L.; Turnage, G.; McCraine, C.; Pitchford, J.; Moorhead, R. Remote Sensing of Wildfire Using a Small Unmanned Aerial System: Post-Fire Mapping, Vegetation Recovery and Damage Analysis in Grand Bay, Mississippi/Alabama, USA. Drones 2019, 3, 43. https://doi.org/10.3390/drones3020043

AMA Style

Samiappan S, Hathcock L, Turnage G, McCraine C, Pitchford J, Moorhead R. Remote Sensing of Wildfire Using a Small Unmanned Aerial System: Post-Fire Mapping, Vegetation Recovery and Damage Analysis in Grand Bay, Mississippi/Alabama, USA. Drones. 2019; 3(2):43. https://doi.org/10.3390/drones3020043

Chicago/Turabian Style

Samiappan, Sathishkumar; Hathcock, Lee; Turnage, Gray; McCraine, Cary; Pitchford, Jonathan; Moorhead, Robert. 2019. "Remote Sensing of Wildfire Using a Small Unmanned Aerial System: Post-Fire Mapping, Vegetation Recovery and Damage Analysis in Grand Bay, Mississippi/Alabama, USA" Drones 3, no. 2: 43. https://doi.org/10.3390/drones3020043

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