A Comparative Analysis of Machine Learning with WorldView-2 Pan-Sharpened Imagery for Tea Crop Mapping

Tea is an important but vulnerable economic crop in East Asia, highly impacted by climate change. This study attempts to interpret tea land use/land cover (LULC) using very high resolution WorldView-2 imagery of central Taiwan with both pixel and object-based approaches. A total of 80 variables deri...

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Detalles Bibliográficos
Autores principales: Chuang, Yung-Chung Matt, Shiu, Yi-Shiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2016
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4883285/
https://www.ncbi.nlm.nih.gov/pubmed/27128915
http://dx.doi.org/10.3390/s16050594

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4883285/
https://www.ncbi.nlm.nih.gov/pubmed/27128915
http://dx.doi.org/10.3390/s16050594

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