Mapping invasive alien plant species with very high spatial resolution and multi-date satellite imagery using object-based and machine learning techniques: A comparative study

Fiston Nininahazwea Département de Géomatique appliquée, Université de Sherbrooke, Sherbrooke, Canada;b Centre d’enseignement et de recherche en foresterie (CERFO), Quebec, Canada;c Centre de la science de la biodiversité du Québec, Montréal, CanadaCorrespondence[email protected]
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Jérôme Théaua Département de Géomatique appliquée, Université de Sherbrooke, Sherbrooke, Canada;c Centre de la science de la biodiversité du Québec, Montréal, CanadaView further author information

Genest Marc Antoineb Centre d’enseignement et de recherche en foresterie (CERFO), Quebec, CanadaView further author information

Mathieu Varinb Centre d’enseignement et de recherche en foresterie (CERFO), Quebec, CanadaView further author information

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Mapping invasive alien plant species with very high spatial resolution and multi-date satellite imagery using object-based and machine learning techniques: A comparative study

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Mapping invasive alien plant species with very high spatial resolution and multi-date satellite imagery using object-based and machine learning techniques: A comparative study

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