scholarly journals Earthquake/Tsunami Damage Assessment for Urban Areas Using Post-Event PolSAR Data

2018 ◽  
Vol 10 (7) ◽  
pp. 1088 ◽  
Author(s):  
Yaqi Ji ◽  
Josaphat Sri Sumantyo ◽  
Ming Chua ◽  
Mirza Waqar
Keyword(s):  
Urban Areas ◽  
Damage Assessment ◽  
Tsunami Damage

Damage assessment mapping of rural environments; integration of SAR and Optical data

2021 ◽  
Author(s):  
Shiran Havivi ◽  
Stanley R. Rotman ◽  
Dan G. Blumberg ◽  
Shimrit Maman
Keyword(s):  
Natural Disaster ◽  
Rural Areas ◽  
Urban Areas ◽  
Damage Assessment ◽  
Vegetation Index ◽  
Urban Environments ◽  
Optical Data ◽  
Damage Level ◽  
Rural Environments ◽  
Rural And Urban

<p>The damage caused by a natural disaster in rural areas differs in nature, extent, landscape and in structure, from the damage in urban environments. Previous and current studies focus mainly on mapping damaged structures in urban areas after catastrophe events such as an earthquake or tsunami. Yet, research focusing on the damage level or its distribution in rural areas is absent. In order to apply an emergency response and for effective disaster management, it is necessary to understand and characterize the nature of the damage in each different environment. </p><p>Havivi et al. (2018), published a damage assessment algorithm that makes use of SAR images combined with optical data, for rapid mapping and compiling a damage assessment map following a natural disaster. The affected areas are analyzed using interferometric SAR (InSAR) coherence. To overcome the loss of coherence caused by changes in vegetation, optical images are used to produce a mask by computing the Normalized Difference Vegetation Index (NDVI) and removing the vegetated area from the scene. Due to the differences in geomorphological settings and landuse\landcover between rural and urban settlements, the above algorithm is modified and adjusted by inserting the Modified Normalized Difference Water Index (MNDWI) to better suit rural environments and their unique response after a disaster. MNDWI is used for detection, identification and extraction of waterbodies (such as irrigation canals, streams, rivers, lakes, etc.), allowing their removal which causes lack of coherence at the post stage of the event. Furthermore, it is used as an indicator for highlighting prone regions that might be severely affected pre disaster event. Thresholds are determined for the co-event coherence map (≤ 0.5), the NDVI (≥ 0.4) and the MNDWI (≥ 0), and the three layers are combined into one. Based on the combined map, a damage assessment map is generated. </p><p>As a case study, this algorithm was applied to the areas affected by multi-hazard event, following the Sulawesi earthquake and subsequent tsunami in Palu, Indonesia, which occurred on September 28th, 2018. High-resolution COSMO-SkyMed images pre and post the event, alongside a Sentinel-2 image pre- event are used as inputs. The output damage assessment map provides a quantitative assessment and spatial distribution of the damage in both the rural and urban environments. The results highlight the applicability of the algorithm for a variety of disaster events and sensors. In addition, the results enhance the contribution of the water component to the analysis pre and post the event in rural areas. Thus, while in urban regions the spatial extent of the damage will occur in its proximity to the coastline or the fault, rural regions, even in significant distance will experience extensive damage due secondary hazards as liquefaction processes.     </p>

scholarly journals Methodology for the damage assessment of vehicles exposed to flooding in urban areas

2018 ◽  
Vol 12 (3) ◽  
pp. e12475 ◽  
Author(s):  
Eduardo Martínez-Gomariz ◽  
Manuel Gómez ◽  
Beniamino Russo ◽  
Pablo Sánchez ◽  
Josep-Anton Montes
Keyword(s):  
Urban Areas ◽  
Damage Assessment

scholarly journals Comparison of Pre-Event VHR Optical Data and Post-Event PolSAR Data to Investigate Damage Caused by the 2011 Japan Tsunami in Built-Up Areas

2018 ◽  
Vol 10 (11) ◽  
pp. 1804 ◽  
Author(s):  
Minyoung Jung ◽  
Junho Yeom ◽  
Yongil Kim
Keyword(s):  
Urban Areas ◽  
Damage Assessment ◽  
Optical Data ◽  
Alos Palsar ◽  
Physical Relationship ◽  
Level Indicator ◽  
Damage Level ◽  
2011 Japan Tsunami ◽  
The Difference ◽  
Post Disaster

Combining pre-disaster optical and post-disaster synthetic aperture radar (SAR) satellite data is essential for the timely damage investigation because the availability of data in a disaster area is usually limited. This article proposes a novel method to assess damage in urban areas by analyzing combined pre-disaster very high resolution (VHR) optical data and post-disaster polarimetric SAR (PolSAR) data, which has rarely been used in previous research because the two data have extremely different characteristics. To overcome these differences and effectively compare VHR optical data and PolSAR data, a technique to simulate polarization orientation angles (POAs) in built-up areas was developed using building orientations extracted from VHR optical data. The POA is an intrinsic parameter of PolSAR data and has a physical relationship with building orientation. A damage level indicator was also proposed, based on the consideration of diminished homogeneity of POA values by damaged buildings. The indicator is the difference between directional dispersions of the pre and post-disaster POA values. Damage assessment in urban areas was conducted by using the indicator calculated with the simulated pre-disaster POAs from VHR optical data and the derived post-disaster PolSAR POAs. The proposed method was validated on the case study of the 2011 tsunami in Japan using pre-disaster KOMPSAT-2 data and post-disaster ALOS/PALSAR-1 data. The experimental results demonstrated that the proposed method accurately simulated the POAs with a root mean square error (RMSE) value of 2.761° and successfully measured the level of damage in built-up areas. The proposed method can facilitate efficient and fast damage assessment in built-up areas by comparing pre-disaster VHR optical data and post-disaster PolSAR data.

Using Social Media and Satellite Data for Damage Assessment in Urban Areas During Emergencies

2016 ◽  
pp. 443-457 ◽  
Author(s):  
Guido Cervone ◽  
Emily Schnebele ◽  
Nigel Waters ◽  
Martina Moccaldi ◽  
Rosa Sicignano
Keyword(s):  
Social Media ◽  
Satellite Data ◽  
Urban Areas ◽  
Damage Assessment

scholarly journals Advanced DInSAR analysis for building damage assessment in large urban areas: an application to the city of Roma, Italy

2015 ◽  
Author(s):  
Peppe J. V. D'Aranno ◽  
Maria Marsella ◽  
Silvia Scifoni ◽  
Marianna Scutti ◽  
Alberico Sonnessa ◽  
...  
Keyword(s):  
Urban Areas ◽  
Damage Assessment ◽  
Building Damage ◽  
The City

A REVIEW OF TSUNAMI DAMAGE ASSESSMENT METHODS AND BUILDING PERFORMANCE IN THAILAND

2013 ◽  
Vol 07 (05) ◽  
pp. 1350036 ◽  
Author(s):  
ANAWAT SUPPASRI ◽  
SHUNICHI KOSHIMURA ◽  
FUMIHIKO IMAMURA ◽  
ANAT RUANGRASSAMEE ◽  
PIYAWAT FOYTONG
Keyword(s):  
Indian Ocean ◽  
Damage Assessment ◽  
Fragility Curves ◽  
Assessment Methods ◽  
Indian Ocean Tsunami ◽  
Building Performance ◽  
Inundation Depth ◽  
Tsunami Damage ◽  
Damage Data ◽  
Damage Criteria

Although the 2004 Indian Ocean tsunami occurred several years ago and all the building repair and infrastructure reconstruction needed in Thailand to repair the damage caused by the tsunami are complete, there is still a need for damage assessment methods that can be used in future tsunami damage assessments in Thailand and that can possibly be applied to other countries. This study summarizes three methods for assessing tsunami damage, "tsunami damage criteria," "tsunami damage ratios" and "tsunami fragility curves," based on damage data from the 2004 Indian Ocean tsunami in Thailand, and these methods are compared using other tsunami events. Using the data from a field survey of damaged buildings, tsunami damage criteria were summarized for each degree of damage as a function of inundation depth for different building types. Tsunami damage ratios were summarized using building damage data obtained from surveys in the field and reconstruction cost estimates provided by the Thai government. The fragility curves developed were validated based on building performance data obtained from full-scale experiments on buildings and columns. Despite differences in the tsunami characteristics (inundation depth, current velocity and hydrodynamic force), the damage probabilities were nearly the same. The summarized methods might be useful for future tsunami damage assessments and loss estimation in Thailand and serve as guidelines for tsunami damage assessment in other countries.

Tsunami damage assessment: a case study in Car Nicobar Island, India

2007 ◽  
Vol 28 (13-14) ◽  
pp. 2937-2959 ◽  
Author(s):  
A. Kumar ◽  
R. K. Chingkhei ◽  
Th. Dolendro
Keyword(s):  
Damage Assessment ◽  
Nicobar Island ◽  
Tsunami Damage
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