Landsat-8 vs. Sentinel-2: examining the added value of sentinel-2's red-edge bands to land-use and land-cover mapping in Burkina Faso

• Published in: GIScience and remote sensing Vol. 55; no. 3; pp. 331 - 354
• Main Authors: Forkuor, Gerald, Dimobe, Kangbeni, Serme, Idriss, Tondoh, Jerome Ebagnerin
• Format: Journal Article
• Language: English
• Published: Taylor & Francis 04.05.2018; Taylor & Francis Group
• Subjects: Burkina Faso; land use and land cover maps; Landsat; Landsat-8; random forest; red edge; remote sensing; Sentinel-2; stochastic gradient boosting; support vector machines; Burkina Faso
• ISSN: 1548-1603; 1943-7226; 1943-7226
• DOI: 10.1080/15481603.2017.1370169

The availability of freely available moderate-to-high spatial resolution (10-30 m) satellite imagery received a major boost with the recent launch of the Sentinel-2 sensor by the European Space Agency. Together with Landsat, these sensors provide the scientific community with a wide range of spatial, spectral, and temporal properties. This study compared and explored the synergistic use of Landsat-8 and Sentinel-2 data in mapping land use and land cover (LULC) in rural Burkina Faso. Specifically, contribution of the red-edge bands of Sentinel-2 in improving LULC mapping was examined. Three machine-learning algorithms - random forest, stochastic gradient boosting, and support vector machines - were employed to classify different data configurations. Classification of all Sentinel-2 bands as well as Sentinel-2 bands common to Landsat-8 produced an overall accuracy, that is 5% and 4% better than Landsat-8. The combination of Landsat-8 and Sentinel-2 red-edge bands resulted in a 4% accuracy improvement over that of Landsat-8. It was found that classification of the Sentinel-2 red-edge bands alone produced better and comparable results to Landsat-8 and the other Sentinel-2 bands, respectively. Results of this study demonstrate the added value of the Sentinel-2 red-edge bands and encourage multi-sensoral approaches to LULC mapping in West Africa.