Change detection for earthquake damage assessment in built-up areas using very high resolution optical and SAR imagery

2010 ◽  
Author(s):  
Dominik Brunner ◽  
Lorenzo Bruzzone ◽  
Guido Lemoine
Keyword(s):  
High Resolution ◽  
Change Detection ◽  
Damage Assessment ◽  
Earthquake Damage ◽  
Sar Imagery ◽  
Very High ◽  
Earthquake Damage Assessment

scholarly journals A fuzzy decision making system for building damage map creation using high resolution satellite imagery

2013 ◽  
Vol 13 (2) ◽  
pp. 455-472 ◽  
Author(s):  
H. Rastiveis ◽  
F. Samadzadegan ◽  
P. Reinartz
Keyword(s):  
High Resolution ◽  
Satellite Imagery ◽  
Damage Assessment ◽  
Fuzzy Inference ◽  
Earthquake Damage ◽  
Fuzzy Decision Making ◽  
Inference System ◽  
High Resolution Satellite Imagery ◽  
Roof Part ◽  
Earthquake Damage Assessment

Abstract. Recent studies have shown high resolution satellite imagery to be a powerful data source for post-earthquake damage assessment of buildings. Manual interpretation of these images, while being a reliable method for finding damaged buildings, is a subjective and time-consuming endeavor, rendering it unviable at times of emergency. The present research, proposes a new state-of-the-art method for automatic damage assessment of buildings using high resolution satellite imagery. In this method, at the first step a set of pre-processing algorithms are performed on the images. Then, extracting a candidate building from both pre- and post-event images, the intact roof part after an earthquake is found. Afterwards, by considering the shape and other structural properties of this roof part with its pre-event condition in a fuzzy inference system, the rate of damage for each candidate building is estimated. The results obtained from evaluation of this algorithm using QuickBird images of the December 2003 Bam, Iran, earthquake prove the ability of this method for post-earthquake damage assessment of buildings.

scholarly journals High-Resolution Early Earthquake Damage Assessment System for Mexico City Based on a Single-Station

2017 ◽  
Vol 56 (1) ◽  
Author(s):  
Mario Ordaz ◽  
Eduardo Reinoso ◽  
Miguel A. Jaimes ◽  
Leonardo Alcántara ◽  
Citlali Pérez
Keyword(s):  
High Resolution ◽  
Mexico City ◽  
Damage Assessment ◽  
Earthquake Damage ◽  
Assessment System ◽  
Peak Ground Velocity ◽  
Population Database ◽  
Emergency Plans ◽  
Single Station ◽  
Earthquake Damage Assessment

A high-resolution early earthquake damage assessment system is presented for Mexico City based on real-time computations of seismic spectral intensities at a reference site. To obtain intensities for the entire Mexico Valley, pre-calculated response spectral ratios at soft sites are used. The estimates of seismic intensities (peak ground acceleration, peak ground velocity and spectral ordinates for selected structural periods), together with intensity-damage relations for buildings, fatalities and water supply network were used to obtain the spatial distribution of expected damage throughout the city. The process takes approximately 10 minutes with no human intervention. Since the available time to carry out all the computations is short, we have built a representative building and population database that concentrates all the information in a square mesh of 400 • 400 m. Results are sent to an Emergency Center and to decision makers to trigger previously set emergency plans and to provide information before emergency plans are in full operation.

Updating GIS Building Inventory Data Using High-Resolution Satellite Images for Earthquake Damage Assessment: Application to Metro Manila, Philippines

2006 ◽  
Vol 22 (1) ◽  
pp. 151-168 ◽  
Author(s):  
Hiroyuki Miura ◽  
Saburoh Midorikawa
Keyword(s):  
High Resolution ◽  
Damage Assessment ◽  
Satellite Images ◽  
Remote Sensing Data ◽  
Earthquake Damage ◽  
Inventory Data ◽  
Building Inventory ◽  
High Resolution Satellite Images ◽  
Metro Manila ◽  
Earthquake Damage Assessment

In order to conduct earthquake damage assessment, a methodology for updating GIS building inventory data in Metro Manila, Philippines, using remote sensing data is proposed. The locations of newly constructed mid- and high-rise buildings are detected from high-resolution satellite images using the image analysis technique, while the number of low-rise buildings is estimated from the built-up areas on a land cover classification map. The building inventory data is updated by incorporating the data on the newly constructed buildings into the existing data. The number of buildings in the updated inventory data shows good agreement with the results of the manual interpretation and a recent survey. A building damage assessment for a scenario earthquake is conducted using the updated inventory data.

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