Satellite imagery and machine learning for identification of aridity risk in central Java Indonesia

This study aims to develop a software framework for predicting aridity using vegetation indices (VI) from LANDSAT 8 OLI images. VI data are predicted using machine learning (ml): Random Forest (RF) and Correlation and Regression Trees (CART). Comparison of prediction using Artificial Neural Network...

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Detalles Bibliográficos
Autores principales: Prasetyo, Sri Yulianto Joko, Hartomo, Kristoko Dwi, Paseleng, Mila Chrismawati
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2021
Materias:
Artificial Intelligence
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8157165/
https://www.ncbi.nlm.nih.gov/pubmed/34084916
http://dx.doi.org/10.7717/peerj-cs.415

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8157165/
https://www.ncbi.nlm.nih.gov/pubmed/34084916
http://dx.doi.org/10.7717/peerj-cs.415

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