Mapping the Distribution of Coffee Plantations from Multi-Resolution, Multi-Temporal, and Multi-Sensor Data Using a Random Forest Algorithm

Mapping the Distribution of Coffee Plantations from Multi-Resolution, Multi-Temporal, and Multi-Sensor Data Using a Random Forest Algorithm

Indonesia is the world’s fourth largest coffee producer. Coffee plantations cover 1.2 million ha of the country with a production of 500 kg/ha. However, information regarding the distribution of coffee plantations in Indonesia is limited. This study aimed to assess the accuracy of classification mod...

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Bibliographic Details
Main Authors: Anggun Tridawati, Ketut Wikantika, Tri Muji Susantoro, Agung Budi Harto, Soni Darmawan, Lissa Fajri Yayusman, Mochamad Firman Ghazali
Format: Article
Language:English
Published: MDPI AG 2020-12-01
Series:Remote Sensing
Subjects:
random forest algorithm
tree
multi-temporal
multi-resolution
Online Access:https://www.mdpi.com/2072-4292/12/23/3933

Internet

https://www.mdpi.com/2072-4292/12/23/3933

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