Next Article in Journal
Investigation of Spectral Band Requirements for Improving Retrievals of Phytoplankton Functional Types
Next Article in Special Issue
Development of a Multi-Spatial Resolution Approach to the Surveillance of Active Fire Lines Using Himawari-8
Previous Article in Journal
Interannual Variability in Dry Mixed-Grass Prairie Yield: A Comparison of MODIS, SPOT, and Field Measurements
Previous Article in Special Issue
Post-Fire Changes in Forest Biomass Retrieved by Airborne LiDAR in Amazonia
Article Menu
Issue 10 (October) cover image

Export Article

Open AccessArticle

Separability Analysis of Sentinel-2A Multi-Spectral Instrument (MSI) Data for Burned Area Discrimination

Geospatial Sciences Center of Excellence, South Dakota State University, Brookings, SD 57007, USA
Department of Natural Resources and Society, College of Natural Resources, University of Idaho, Moscow, ID 83844, USA
NERC National Centre for Earth Observation (NCEO), UCL Geography, Gower Street, London WC1E 6BT, UK
Department of Geography, University College London, Gower Street, London WC1E 6BT, UK
Author to whom correspondence should be addressed.
Academic Editors: Diofantos Hadjimitsis, Ioannis Gitas, Luigi Boschetti, Kyriacos Themistocleous, Clement Atzberger and Prasad S. Thenkabail
Remote Sens. 2016, 8(10), 873;
Received: 12 July 2016 / Revised: 17 October 2016 / Accepted: 18 October 2016 / Published: 22 October 2016
PDF [10220 KB, uploaded 22 October 2016]


Biomass burning is a global phenomenon and systematic burned area mapping is of increasing importance for science and applications. With high spatial resolution and novelty in band design, the recently launched Sentinel-2A satellite provides a new opportunity for moderate spatial resolution burned area mapping. This study examines the performance of the Sentinel-2A Multi Spectral Instrument (MSI) bands and derived spectral indices to differentiate between unburned and burned areas. For this purpose, five pairs of pre-fire and post-fire top of atmosphere (TOA reflectance) and atmospherically corrected (surface reflectance) images were studied. The pixel values of locations that were unburned in the first image and burned in the second image, as well as the values of locations that were unburned in both images which served as a control, were compared and the discrimination of individual bands and spectral indices were evaluated using parametric (transformed divergence) and non-parametric (decision tree) approaches. Based on the results, the most suitable MSI bands to detect burned areas are the 20 m near-infrared, short wave infrared and red-edge bands, while the performance of the spectral indices varied with location. The atmospheric correction only significantly influenced the separability of the visible wavelength bands. The results provide insights that are useful for developing Sentinel-2 burned area mapping algorithms. View Full-Text
Keywords: Sentinel-2; fire; burned area; separability analysis Sentinel-2; fire; burned area; separability analysis

Graphical abstract

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).

Share & Cite This Article

MDPI and ACS Style

Huang, H.; Roy, D.P.; Boschetti, L.; Zhang, H.K.; Yan, L.; Kumar, S.S.; Gomez-Dans, J.; Li, J. Separability Analysis of Sentinel-2A Multi-Spectral Instrument (MSI) Data for Burned Area Discrimination. Remote Sens. 2016, 8, 873.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top