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. 2020 May 27;15(5):e0232962.
doi: 10.1371/journal.pone.0232962. eCollection 2020.

Exploring the utility of Sentinel-2 MSI and Landsat 8 OLI in burned area mapping for a heterogenous savannah landscape

Fiona Ngadze  1 , Kudzai Shaun Mpakairi  2 , Blessing Kavhu  3 , Henry Ndaimani  2 , Monalisa Shingirayi Maremba  1
Affiliations

Exploring the utility of Sentinel-2 MSI and Landsat 8 OLI in burned area mapping for a heterogenous savannah landscape

Fiona Ngadze et al. PLoS One. .

Abstract

When wildfires are controlled, they are integral to the existence of savannah ecosystems and play an intrinsic role in maintaining their structure and function. Ample studies on wildfire detection and severity mapping are available but what remains a challenge is the accurate mapping of burnt areas in heterogenous landscapes. In this study, we tested which spectral bands contributed most to burnt area detection when using Sentinel-2 and Landsat 8 multispectral sensors in two study sites. Post-fire Sentinel 2A and Landsat 8 images were classified using the Random Forest (RF) classifier. We found out that, the NIR, Red, Red-edge and Blue spectral bands contributed most to burned area detection when using Landsat 8 and Sentinel 2A. We found out that, Landsat 8 had a higher classification accuracy (OA = 0.92, Kappa = 0.85 and TSS = 0.84)) in study site 1 as compared to Sentinel-2 (OA = 0.86, Kappa = 0.74 and TSS = 0.76). In study site 2, Sentinel-2 had a slightly higher classification accuracy (OA = 0.89, Kappa = 0.67 and TSS = 0.64) which was comparable to that of Landsat 8 (OA = 0.85, Kappa = 0.50 and TSS = 0.41). Our study adds rudimentary knowledge on the most reliable sensor allowing reliable estimation of burnt areas and improved post-fire ecological evaluations on ecosystem damage and carbon emission.

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Conflict of interest statement

Fiona Ngadze and Monalisa Maremba are employed at Allied Systems. However, Allied Systems did not participate or influence this research and their involvement with Allied Systems does not alter our adherence to PLOS ONE policies on sharing data and materials.

Figures

Fig 1
Fig 1. Location of the two sites used for this study.
The study sites, (a) site 1 and (b) site 2, are overlaid on a composite image from Sentinel-2A imagery. The imagery was freely downloaded from http://earthexplorer.usgs.gov. The imagery is an RGB image with red = red band, green = water vapor band and blue = near infrared band. The burnt areas are the dark purple areas.
Fig 2
Fig 2
Classification accuracy for Sentinel -2A and Landsat 8 OLI in (a) study site 1 and (b) study site 2 using the overall accuracy (OA), Cohen’s Kappa (Kappa) and True Skill Statistics (TSS).
Fig 3
Fig 3
Burned (red) areas classified using the random forest algorithm with Sentinel-2 (a and c) and Landsat 8 imagery (b and d). The burnt areas are overlaid on Sentinel-2 natural color imagery. The black outline shows the field measured burned area. The imagery was freely downloaded from http://earthexplorer.usgs.gov.
Fig 4
Fig 4
The contribution of each spectral band to burn area mapping with Sentinel -2A and Landsat 8 OLI in (a) study site 1 and (b) study site 2.
See this image and copyright information in PMC

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Grants and funding

This research received no external funding. Allied System provided support in the form of salaries for Fiona Ngadze and Monalisa Maremba, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section.