Mapping crop cover using multi-temporal Landsat 8 OLI imagery

Sonobe, Rei; Yamaya, Yuki; Tani, Hiroshi; Wang, Xiufeng; Kobayashi, Nobuyuki; Mochizuki, Kan-ichiro

Mapping crop cover using multi-temporal Landsat 8 OLI imagery

Sonobe, Rei; Yamaya, Yuki; Tani, Hiroshi et al.

International Journal of Remote Sensing, 2017, 38(15), 4348-4361

Permalink : https://hdl.handle.net/2115/70679

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論文情報

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アクセス権	open access
URI	https://hdl.handle.net/2115/70679
タイトル	Mapping crop cover using multi-temporal Landsat 8 OLI imagery
著者	Sonobe, Rei ; Yamaya, Yuki ; Tani, Hiroshi ; Wang, Xiufeng ; Kobayashi, Nobuyuki ; Mochizuki, Kan-ichiro
e-Rad_Researcher 40755352 著者名 Sonobe, Rei
著者名 Yamaya, Yuki
e-Rad_Researcher 80142701 著者名 Tani, Hiroshi
e-Rad_Researcher 30301873 著者名 Wang, Xiufeng
著者名 Kobayashi, Nobuyuki
著者名 Mochizuki, Kan-ichiro
言語	英語
キーワード	Bayesian optimisation
	crop
	Kauth-Thomas transform
	Landsat-8
	random forests
	vegetation indices
発行日	2017-05-18
出版者	Taylor & Francis
収録物名	International Journal of Remote Sensing
巻(号)	38(15)
ページ	4348-4361
抄録	ABSTRACT: Crop classification maps are useful for estimating amounts of crops harvested, which could help address challenges in food security. Remote-sensing techniques are useful tools for generating crop maps. Optical remote sensing is one of the most attractive options because it offers vegetation indices (VIs) with frequent revisits and has adequate spatial and spectral resolution and some data has been distributed free of charge. However, sufficient consideration has not been given to the potential of VIs calculated from Landsat 8 Operational Land Imager (OLI) data. This article describes the use of Landsat 8 OLI data for the classification of crops in Hokkaido, Japan. In addition to reflectance, VIs calculated from simple formulas that consisted of combinations of two or more reflectance wavebands were evaluated, as well as the six components of the Kauth–Thomas transform. The VIs based on shortwave infrared bands (bands 6 or 7) improved classification accuracy, and using a combination of all derived data from Landsat 8 OLI data resulted in an overall accuracy of 94.5% (allocation disagreement = 4.492 and quantity disagreement = 1.017).
資源タイプ	学術雑誌論文
出版タイプ	Accepted Manuscript
権利情報	This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Remote Sensing on 18 May 2017, available online: http://www.tandfonline.com/doi/abs/10.1080/01431161.2017.1323286.
PISSN	0143-1161
EISSN	1366-5901
関連情報 (isVersionOf)	出版社版DOI https://doi.org/10.1080/01431161.2017.1323286