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

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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Bibliographic Details
Main Authors: Sri Yulianto Joko Prasetyo, Kristoko Dwi Hartomo, Mila Chrismawati Paseleng
Format: Article
Language:English
Published: PeerJ Inc. 2021-05-01
Series:PeerJ Computer Science
Subjects:
Vegetation indices
Machine learning
Remote sensing
Aridity
Online Access:https://peerj.com/articles/cs-415.pdf

Internet

https://peerj.com/articles/cs-415.pdf

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