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International Journal of Remote Sensing Volume 38, 2017 - Issue 20
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Articles

The application of discriminant analysis for mapping cereals and pasture using object-based features

Cheng QiaoCentre for AgroClimate, Geomatics and Earth Observation, Science and Technology Branch, Agriculture and Agri-Food Canada, Ottawa, Ontario, CanadaK1A 0C6Correspondence[email protected]
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Bahram DaneshfarCentre for AgroClimate, Geomatics and Earth Observation, Science and Technology Branch, Agriculture and Agri-Food Canada, Ottawa, Ontario, CanadaK1A 0C6View further author information
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Andrew M. DavidsonCentre for AgroClimate, Geomatics and Earth Observation, Science and Technology Branch, Agriculture and Agri-Food Canada, Ottawa, Ontario, CanadaK1A 0C6ORCID Iconhttp://orcid.org/0000-0003-3784-682XView further author information
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Pages 5546-5568 | Received 12 May 2015, Accepted 23 Apr 2017, Published online: 23 Jun 2017

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Iman Khosravi & Seyed Kazem Alavipanah. (2019) A random forest-based framework for crop mapping using temporal, spectral, textural and polarimetric observations. International Journal of Remote Sensing 40:18, pages 7221-7251.
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Aiym Orynbaikyzy, Ursula Gessner & Christopher Conrad. (2019) Crop type classification using a combination of optical and radar remote sensing data: a review. International Journal of Remote Sensing 40:17, pages 6553-6595.
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Articles from other publishers (2)

Gurwinder Singh, Ganesh Kumar Sethi & Sartajvir Singh. (2021) Survey on Machine Learning and Deep Learning Techniques for Agriculture Land. SN Computer Science 2:6.
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Bester Tawona Mudereri, Timothy Dube, Saliou Niassy, Emily Kimathi, Tobias Landmann, Zeyaur Khan & Elfatih M. Abdel-Rahman. (2020) Is it possible to discern Striga weed (Striga hermonthica) infestation levels in maize agro-ecological systems using in-situ spectroscopy?. International Journal of Applied Earth Observation and Geoinformation 85, pages 102008.
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