A Hybrid Convolutional Neural Network and Random Forest for Burned Area Identification with Optical and Synthetic Aperture Radar (SAR) Data

A Hybrid Convolutional Neural Network and Random Forest for Burned Area Identification with Optical and Synthetic Aperture Radar (SAR) Data

Forest and land fires are disasters that greatly impact various sectors. Burned area identification is needed to control forest and land fires. Remote sensing is used as common technology for rapid burned area identification. However, there are not many studies related to the combination of optical...

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Bibliographic Details
Main Authors: Dodi Sudiana, Anugrah Indah Lestari, Indra Riyanto, Mia Rizkinia, Rahmat Arief, Anton Satria Prabuwono, Josaphat Tetuko Sri Sumantyo
Format: Article
Language:English
Published: MDPI AG 2023-01-01
Series:Remote Sensing
Subjects:
remote sensing
burned area
convolutional neural network (CNN)
random forest (RF)
synthetic aperture radar (SAR)
Sentinel-1
Online Access:https://www.mdpi.com/2072-4292/15/3/728

Internet

https://www.mdpi.com/2072-4292/15/3/728

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