A rapid assessment of burned areas in Nam Kading National Biodiversity Conservation Area (NBCA), Laos

Severity of natural hazards and related disasters are increasing worldwide. Of the several disasters, forest fires are most common in South/Southeast Asia including Laos. In this study, we use the satellite imagery to detect forest fires in the prior to farming and to quickly estimate the total area of forest burned due to the farmers' land preparation activities Nam Kading national bio-diversity conservation area (NBCA). Pre-fire and post-fire dates were between January and April 2018. Specifically, we used Sentinel-2 data to calculate Differential Normalized Burned Ratio (dNBR) for burned area mapping in Google Earth Engine (GEE). Ground-truth was done at random sites to verify the results. Results suggested burnt areas about 2689 ha inside NBCA and 16,923 ha in the neighboring study area. A total of 500 random points were used to validate the burned area map and the results suggested an overall accuracy of about 97.4%, (98.1% of producer's accuracy, 96.2% of user's accuracy with 0.94 kappa-statistics). Our results highlight the potential of NBR in GEE framework for rapid assessment of burnt areas useful for fire management and mitigation purposes.