Volume XLII-2/W7
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W7, 871-874, 2017
https://doi.org/10.5194/isprs-archives-XLII-2-W7-871-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W7, 871-874, 2017
https://doi.org/10.5194/isprs-archives-XLII-2-W7-871-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.

  13 Sep 2017

13 Sep 2017

ASSESSMENTS OF SENTINEL-2 VEGETATION RED-EDGE SPECTRAL BANDS FOR IMPROVING LAND COVER CLASSIFICATION

S. Qiu, B. He, C. Yin, and Z. Liao S. Qiu et al.
  • University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, China

Keywords: Classification, Sentinel-2, Multi spectral instrument, Vegetation red-edge, Land cover

Abstract. The Multi Spectral Instrument (MSI) onboard Sentinel-2 can record the information in Vegetation Red-Edge (VRE) spectral domains. In this study, the performance of the VRE bands on improving land cover classification was evaluated based on a Sentinel-2A MSI image in East Texas, USA. Two classification scenarios were designed by excluding and including the VRE bands. A Random Forest (RF) classifier was used to generate land cover maps and evaluate the contributions of different spectral bands. The combination of VRE bands increased the overall classification accuracy by 1.40 %, which was statistically significant. Both confusion matrices and land cover maps indicated that the most beneficial increase was from vegetation-related land cover types, especially agriculture. Comparison of the relative importance of each band showed that the most beneficial VRE bands were Band 5 and Band 6. These results demonstrated the value of VRE bands for land cover classification.