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Band selection in Sentinel-2 satellite for agriculture applications

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conference contribution
posted on 2017-07-07, 11:10 authored by Tianxiang Zhang, Jinya Su, Cunjia LiuCunjia Liu, Wen-Hua ChenWen-Hua Chen, Hui Liu, Guohai Liu
Various indices are used for assessing vegetation and soil properties in satellite remote sensing applications. Some indices, such as NDVI and NDWI, are defined based on the sensitivity and significance of specific bands. Nowadays, remote sensing capability with a good number of bands and high spatial resolution is available. Instead of classification based on indices, this paper explores direct classification using selected bands. Recently launched Sentinel-2A is adopted as a case study. Three methods are compared, where the first approach utilizes traditional indices and the latter two approaches adopt specific bands (Red, NIR, and SWIR) and full bands of on-board sensors, respectively. It is shown that a better classification performance can be achieved by directly using the three selected bands compared with the one using indices, while the use of all 13 bands can further improve the performance. Therefore, it is recommended the new approach can be applied for Sentinel-2A image analysis and other wide applications.

Funding

This work was supported by Newton Fund UK-China Agri-Tech Network Plus which is managed by Rothamsted Research on behalf of Science and Technology Facilities Council (STFC). Tianxiang Zhang would also like to thank Chinese Scholarship Council (CSC) for supporting his study in the U.K.

History

School

  • Aeronautical, Automotive, Chemical and Materials Engineering

Department

  • Aeronautical and Automotive Engineering

Published in

23rd International Conference on Automation & Computing

Citation

ZHANG, T. ... et al, 2017. Band selection in Sentinel-2 satellite for agriculture applications. 2017 23rd International Conference on Automation & Computing (ICAC), Huddersfield, UK, 7th-8th September 2017.

Publisher

© IEEE

Version

  • AM (Accepted Manuscript)

Acceptance date

2017-06-15

Publication date

2017

Notes

Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

ISBN

9780701702601

Language

  • en

Location

Huddersfield,

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