Implementing Random Forest Algorithm in GEE: Separation and Transferability on Built-Up Area in Central Java, Indonesia

Implementing Random Forest Algorithm in GEE: Separation and Transferability on Built-Up Area in Central Java, Indonesia

Measuring the status of achievement of the SDGs is the task and concern of many countries in the world, including Indonesia. Indicators for achieving the SDGs enclose three main pillars, namely environmental, economic, and social. The updated land use/land cover information is needed for environment...

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Bibliographic Details
Main Authors: Aninda W. Rudiastuti, Yustisi Lumban-Gaol, Florence E. S. Silalahi, Yosef Prihanto, Widodo S. Pranowo
Format: Article
Language:English
Published: Politeknik Negeri Padang 2022-03-01
Series:JOIV: International Journal on Informatics Visualization
Subjects:
random forest
machine learning
google earth engine (gee)
settlement
sentinel
land use/land cover (lulc).
Online Access:https://joiv.org/index.php/joiv/article/view/873

Internet

https://joiv.org/index.php/joiv/article/view/873

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