Sentinel-2 Satellite Imagery for Urban Land Cover Classification by Optimized Random Forest Classifier

Land cover classification is able to reflect the potential natural and social process in urban development, providing vital information to stakeholders. Recent solutions on land cover classification are generally addressed by remotely sensed imagery and supervised classification methods. However, a...

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Detalles Bibliográficos

Principais autores:	Tianxiang Zhang, Jinya Su, Zhiyong Xu, Yulin Luo, Jiangyun Li
Formato:	Artigo
Idioma:	Inglês
Publicado:	MDPI AG 2021-01-01
Series:	Applied Sciences
Assuntos:	Sentinel-2 satellite random forest bayesian optimization hyperparameter tuning urban management land cover classification
Acceso en liña:	https://www.mdpi.com/2076-3417/11/2/543
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