Crop classification using spectral indices derived from Sentinel-2A imagery

Crop classification using spectral indices derived from Sentinel-2A imagery

Optical remote sensing is one of the most attractive options for generating crop cover maps because it enables computation of vegetation indices, which are useful for assessing the condition of vegetation. The Sentinel-2A Multispectral Instrument (MSI), which is a multispectral sensor with 13 bands...

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Bibliographic Details
Main Authors:	Nobuyuki Kobayashi, Hiroshi Tani, Xiufeng Wang, Rei Sonobe
Format:	Article
Language:	English
Published:	Taylor & Francis Group 2020-01-01
Series:	Journal of Information and Telecommunication
Subjects:	crop random forests spectral indices sentinel-2a variable selection
Online Access:	http://dx.doi.org/10.1080/24751839.2019.1694765

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