scholarly journals Development of Building Inventory Data for Earthquake Damage Assessment in Tacna, Peru Using Satellite Imagery

2016 ◽  
Vol 16 (3) ◽  
pp. 3_137-3_146 ◽  
Author(s):  
Kentaro SUZUKI ◽  
Wen LIU ◽  
Masashi MATSUOKA ◽  
Fumio YAMAZAKI
Keyword(s):  
Satellite Imagery ◽  
Damage Assessment ◽  
Earthquake Damage ◽  
Inventory Data ◽  
Building Inventory ◽  
Earthquake Damage Assessment

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.

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.

The September 7, 2017 Tehuantepec, Mexico, earthquake: Damage assessment in masonry structures for housing

2021 ◽  
Vol 56 ◽  
pp. 102123
Author(s):  
Eber Alberto Godínez-Domínguez ◽  
Arturo Tena-Colunga ◽  
Luis Eduardo Pérez-Rocha ◽  
Hans Israel Archundia-Aranda ◽  
Alonso Gómez-Bernal ◽  
...  
Keyword(s):  
Damage Assessment ◽  
Earthquake Damage ◽  
Masonry Structures ◽  
Mexico Earthquake ◽  
Earthquake Damage Assessment

scholarly journals Crowdsourcing earthquake damage assessment using remote sensing imagery

2012 ◽  
Vol 54 (6) ◽  
Author(s):  
Luke Barrington ◽  
Shubharoop Ghosh ◽  
Marjorie Greene ◽  
Shay Har-Noy ◽  
Jay Berger ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Damage Assessment ◽  
Earthquake Damage ◽  
Remote Sensing Imagery ◽  
Earthquake Damage Assessment
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