Abstract
Earthquakes are one of the most devastating natural disasters, causing serious and severe damage to human life and property. This chapter aims to provide a systematic and comprehensive review of satellite-based earthquake damage assessment using multi-temporal remote sensing images. Change detection methods compare remote sensing images acquired at different times to discover the changes in the land cover, but the images typically have different properties, such as different spatial resolution, type of sensors and the incidence angle. Filtering-based methods are very successful in extracting contextual information from an image by removing redundant spatial details and preserving the geometric characteristics of the objects in the region of interest. The chapter focuses on the general view of the use of synthetic aperture radar images for earthquake studies, including tectonics to damage-level identification. To identify an earthquake-induced damage level at the building scale, it is necessary to use a very high-resolution image.
| Original language | English |
|---|---|
| Title of host publication | Change Detection and Image Time Series Analysis 2 |
| Subtitle of host publication | Supervised Methods |
| Publisher | wiley |
| Pages | 155-221 |
| Number of pages | 67 |
| ISBN (Electronic) | 9781119882299 |
| ISBN (Print) | 9781789450576 |
| DOIs | |
| Publication status | Published - 3 Dec 2021 |
Bibliographical note
Publisher Copyright:© ISTE Ltd 2021. All rights reserved.
Keywords
- Damage-level identification
- Earthquake-induced damage
- Filtering-based methods
- High-resolution image
- Multi-temporal remote sensing
- Satellite-based earthquake damage assessment
- Synthetic aperture radar images
