SAR and LIDAR Datasets for Building Damage Evaluation Based on Support Vector Machine and Random Forest Algorithms—A Case Study of Kumamoto Earthquake, Japan

SAR and LIDAR Datasets for Building Damage Evaluation Based on Support Vector Machine and Random Forest Algorithms—A Case Study of Kumamoto Earthquake, Japan

The evaluation of buildings damage following disasters from natural hazards is a crucial step in determining the extent of the damage and measuring renovation needs. In this study, a combination of the synthetic aperture radar (SAR) and light detection and ranging (LIDAR) data before and after the e...

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Bibliographic Details
Main Authors: Masoud Hajeb, Sadra Karimzadeh, Masashi Matsuoka
Format: Article
Language:English
Published: MDPI AG 2020-12-01
Series:Applied Sciences
Subjects:
damage assessment
airborne SAR
LIDAR
Kumamoto
earthquake
Online Access:https://www.mdpi.com/2076-3417/10/24/8932

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