Next Article in Journal
Improving the Imaging Quality of Ghost Imaging Lidar via Sparsity Constraint by Time-Resolved Technique
Next Article in Special Issue
Preliminary Comparison of Sentinel-2 and Landsat 8 Imagery for a Combined Use
Previous Article in Journal
Evaluating the Potential of PROBA-V Satellite Image Time Series for Improving LC Classification in Semi-Arid African Landscapes
Previous Article in Special Issue
Data Service Platform for Sentinel-2 Surface Reflectance and Value-Added Products: System Use and Examples
Article Menu

Export Article

Open AccessArticle
Remote Sens. 2016, 8(12), 986; doi:10.3390/rs8120986

The Potential of Sentinel Satellites for Burnt Area Mapping and Monitoring in the Congo Basin Forests

1
Bio-Economy Unit, Sustainable Resources Directorate, Joint Research Centre (JRC), European Commission, Via E. Fermi, 2749, TP 261, Ispra VA 21027, Italy
2
Water and Marine Resources Unit, Sustainable Resources Directorate, Joint Research Centre (JRC), European Commission, Via E. Fermi, 2749, TP 120, Ispra VA 21027, Italy
3
Centre de coopération internationale en recherche agronomique pour le développement (CIRAD), UPR 105 Forêts et Sociétés, F-34398 Montpellier Cedex 5, France
4
Center for International Forestry Research (CIFOR), United Nations Avenue, Gigiri, P.O. Box 30677-00100, Nairobi 00601, Kenya
*
Authors to whom correspondence should be addressed.
Academic Editors: Clement Atzberger, Ioannis Gitas and Prasad S. Thenkabail
Received: 31 August 2016 / Revised: 18 November 2016 / Accepted: 21 November 2016 / Published: 30 November 2016
View Full-Text   |   Download PDF [33013 KB, uploaded 30 November 2016]   |  

Abstract

In this study, the recently launched Sentinel-2 (S2) optical satellite and the active radar Sentinel-1 (S1) satellite supported by active fire data from the MODIS sensor were used to detect and monitor forest fires in the Congo Basin. In the context of a very strong El Niño event, an unprecedented outbreak of fires was observed during the first months of 2016 in open forests formations in the north of the Republic of Congo. The anomalies of the recent fires and meteorological situation compared to historical data show the severity of the drought. Burnt areas mapped by the S1 SAR and S2 Multi Spectral Instrument (MSI) sensors highlight that the fires occurred mainly in Marantaceae forests, characterized by open tree canopy cover and an extensive tall herbaceous layer. The maps show that the origin of the fires correlates with accessibility to the forest, suggesting an anthropogenic origin. The combined use of the two independent and fundamentally different satellite systems of S2 and S1 captured an extent of 36,000 ha of burnt areas, with each sensor compensating for the weakness (cloud perturbations for S2, and sensitivity to ground moisture for S1) of the other. View Full-Text
Keywords: Sentinel-2; Sentinel-1; tropical rainforests; fires; burnt areas; Republic of Congo; logging roads Sentinel-2; Sentinel-1; tropical rainforests; fires; burnt areas; Republic of Congo; logging roads
Figures

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).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Verhegghen, A.; Eva, H.; Ceccherini, G.; Achard, F.; Gond, V.; Gourlet-Fleury, S.; Cerutti, P.O. The Potential of Sentinel Satellites for Burnt Area Mapping and Monitoring in the Congo Basin Forests. Remote Sens. 2016, 8, 986.

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

1

Comments

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