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.

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>

Integrating data from different sensors for damage assessment after a natural disaster in rural areas

2020 ◽  
Author(s):  
Shiran Havivi ◽  
Shimrit Maman ◽  
Stanley R. Rotman ◽  
Dan G. Blumberg
Keyword(s):  
Rural Areas ◽  
Urban Areas ◽  
Damage Assessment ◽  
Urban Environments ◽  
Optical Data ◽  
Rural Settlements ◽  
Damage Level ◽  
Disaster Relief Operations ◽  
Rural Environments ◽  
Damage Mapping

<p>Rapid damage mapping following a disaster event is critical to ensure that the emergency response in the affected area is prompt and efficient. Amongst major disasters, earthquakes are characterized as unpredictable and of high frequency of occurrence. Previous and current studies focus mainly on the mapping of damaged structures in urban areas after an event such as an earthquake disaster. Yet, research focusing on the damage level or its distribution in rural areas is absent. According to the UN, nearly half of the world's population lives in rural areas and is expected to rise. Furthermore, their resources and capabilities for disaster relief operations are limited. Therefore, there is a great importance to assess the damage following a disaster in these areas.</p><p>The primary aim of this study is to characterize and assess the damage (level and extent), temporally and spatially, following an earthquake event, in rural settlements. This will allow producing an algorithm suitable for rural area rapid mapping, which will contribute to our understanding and will provide insights of the damage extent and will allow a better response and access to the affected regions and remote population.</p><p>For this purpose, a damage assessment algorithm that will map the damage in both urban and rural environments is proposed. This algorithm makes use of combining SAR and optical data for rapid damage mapping.</p><p>As a case study we will demonstrate this algorithm using the areas affected by the Sulawesi earthquake and subsequent tsunami event in Indonesia that occurred on 28 September 2018. High-resolution COSMO-SkyMed images pre and post the event, alongside a Sentinel-2 image pre- event are used as inputs.</p><p>The affected areas were analyzed with the SAR data using interferometric SAR (InSAR) coherence map. To overcome the loss of coherence caused by changes in vegetation cover, a vegetation mask was applied by using the NDVI to identify (and remove) vegetated areas from the coherence map. Then, thresholds were determined for the co-event coherence map (≤ 0.5) and the NDVI (≥ 0.4) and the two layers were combined into one. Based on the combined map, a damage assessment map was generated by using GIS spatial statistic tools (Fishnet and Zonal statistics). This map provides a quantitative assessment of the nature and distribution of the damage in rural and urban environments, as well the differences of damage features between them. The preliminary results show that while in urban area many structures were damaged, still in the rural areas the damage is larger, since most of the structures were damaged or even destroyed.</p>

scholarly journals Inventory of uncertainties associated with the process of tsunami damage assessment on buildings (SCHEMA FP6 EC co-funded project)

2011 ◽  
Vol 11 (3) ◽  
pp. 883-893 ◽  
Author(s):  
A. Gardi ◽  
N. Valencia ◽  
R. Guillande ◽  
C. André
Keyword(s):  
Damage Assessment ◽  
Assessment Process ◽  
Stream Velocity ◽  
Damage Functions ◽  
Damage Level ◽  
Digital Terrain ◽  
Funded Project ◽  
Inundation Extent ◽  
Production Errors ◽  
Post Disaster

Abstract. Within the framework of the SCHEMA FP6 EC co-funded project (http://www.schemaproject.org), we have identified the sources of errors/uncertainties that can be introduced at several steps of the damage assessment process, from post-disaster field measures up to hazard and damages maps production. Errors, for instance, are introduced when collecting post-disaster observations owing to different types of instruments/methods, water marks considered, tide correction, etc.: in extreme cases, differences of meters can be found between water heights data published by different teams for the same locations. Much uncertainty comes from difficulties in identifying and characterizing the potential tsunami sources and from numerical modelling. Moreover, the resolution of the employed Digital Terrain Models can noticeably affect the predicted inundation extent. We have also verified that the consistency of the computations on the long term varies sensitively depending on the code, raising the problem of results reliability for emergency management in dangerous coasts exposed to repeated waves. In addition, damage assessment is performed using damage functions linking the mean damage level on buildings with the maximum water elevation measured in the field without considering other tsunami parameters such as stream velocity. Finally, we examined uncertainties introduced in hazard and vulnerability mapping due to cartographic processing.

scholarly journals ASSESSING COMPLEX DAMAGE USING PRE-DISASTER OPTICAL AND POST-DISASTER POLSAR DATA

2019 ◽  
Vol XLII-3/W8 ◽  
pp. 181-185
Author(s):  
M. Jung ◽  
M. Chung ◽  
Y. Kim
Keyword(s):  
Damage Assessment ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Orientation Angle ◽  
Optical Data ◽  
Rescue Operation ◽  
Polarization Orientation ◽  
Sar Data ◽  
Post Disaster

<p><strong>Abstract.</strong> Combining pre-disaster optical and post-disaster synthetic aperture radar (SAR) data is regarded as desirable for timely damage assessment, which is essential for the prompt rescue operation. Due to the extreme differences between the two data, however, this combination has not been practically used in the previous research. In this paper, a method to assess the various types of damage caused by disasters using the desirable data combination, particularly pre-disaster very high resolution optical data and post-disaster polarimetric SAR data. The proposed method is a rule-based classification, and uses diverse components derived from the two data such as normalized difference vegetation index, polarization orientation angle, SPAN, and entropy. The proposed method was applied to the case study of the 2011 tsunami in Japan. The experimental results demonstrated the potential of the proposed method to assesses the types of tsunami-induced damage in urban and vegetated areas. The achievement in this paper is expected to facilitate efficient and fast disaster-induced complex damage assessment.</p>

scholarly journals Geographies of Doing Nothing–Internal Displacement and Practices of Post-Disaster Recovery in Urban Areas of the Kathmandu Valley, Nepal

2021 ◽  
Vol 10 (3) ◽  
pp. 110
Author(s):  
Alexandra Titz
Keyword(s):  
Urban Areas ◽  
Evidence Base ◽  
Internal Displacement ◽  
Kathmandu Valley ◽  
Reconstruction Process ◽  
Internally Displaced ◽  
Secondary Displacement ◽  
Displaced People ◽  
Durable Solutions ◽  
Post Disaster

Disaster-related internal displacement is on the rise in many countries and is increasingly becoming an urban phenomenon. For many people, as in the case of the earthquake disaster 2015 in Nepal, protracted or multiple disaster displacements are a lived reality. While the drivers of displacement are relatively well understood, significant uncertainties remain regarding the factors that trigger prolonged or secondary displacement and impede ending of displacement or achieving durable solutions. The purpose of this article is to illustrate and theorise the discourse of reconstruction and return that shapes experiences, strategies, and policies in order to gain a better understanding of the obstacles to pursuing durable solutions that are still shaping the reality of life for urban internally displaced people (IDPs) in Kathmandu Valley. I use the concepts of ‘fields of practice’ and ‘disaster justice’ to provide insights into the theorisation of the links between social inequality, structural forms of governance, and the reconstruction process itself. Findings demonstrate that the application of these concepts has great potential to expand our understanding of ‘realities of life’ and practices of IDPs, and thus contribute to a more differentiated evidence base for the development and implementation of appropriate disaster risk reduction policies and practices.

scholarly journals Building Damage Detection Using U-Net with Attention Mechanism from Pre- and Post-Disaster Remote Sensing Datasets

2021 ◽  
Vol 13 (5) ◽  
pp. 905
Author(s):  
Chuyi Wu ◽  
Feng Zhang ◽  
Junshi Xia ◽  
Yichen Xu ◽  
Guoqing Li ◽  
...  
Keyword(s):  
Damage Assessment ◽  
Large Scale ◽  
Binary Classification ◽  
Open Data ◽  
Building Damage ◽  
Attention Mechanism ◽  
Large Scale Dataset ◽  
Data Program ◽  
The Impact ◽  
Post Disaster

The building damage status is vital to plan rescue and reconstruction after a disaster and is also hard to detect and judge its level. Most existing studies focus on binary classification, and the attention of the model is distracted. In this study, we proposed a Siamese neural network that can localize and classify damaged buildings at one time. The main parts of this network are a variety of attention U-Nets using different backbones. The attention mechanism enables the network to pay more attention to the effective features and channels, so as to reduce the impact of useless features. We train them using the xBD dataset, which is a large-scale dataset for the advancement of building damage assessment, and compare their result balanced F (F1) scores. The score demonstrates that the performance of SEresNeXt with an attention mechanism gives the best performance, with the F1 score reaching 0.787. To improve the accuracy, we fused the results and got the best overall F1 score of 0.792. To verify the transferability and robustness of the model, we selected the dataset on the Maxar Open Data Program of two recent disasters to investigate the performance. By visual comparison, the results show that our model is robust and transferable.

scholarly journals Environmental Risk Assessment of Vehicle Exhaust Particles on Aquatic Organisms of Different Trophic Levels

Toxics ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 261
Author(s):  
Konstantin Pikula ◽  
Mariya Tretyakova ◽  
Alexander Zakharenko ◽  
Seyed Ali Johari ◽  
Sergey Ugay ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Sea Urchin ◽  
Urban Areas ◽  
Aquatic Organisms ◽  
Artemia Salina ◽  
Trophic Levels ◽  
Submicron Particles ◽  
Vehicle Exhaust ◽  
Exhaust Particles ◽  
The Difference

Vehicle emission particles (VEPs) represent a significant part of air pollution in urban areas. However, the toxicity of this category of particles in different aquatic organisms is still unexplored. This work aimed to extend the understanding of the toxicity of the vehicle exhaust particles in two species of marine diatomic microalgae, the planktonic crustacean Artemia salina, and the sea urchin Strongylocentrotus intermedius. These aquatic species were applied for the first time in the risk assessment of VEPs. Our results demonstrated that the samples obtained from diesel-powered vehicles completely prevented egg fertilization of the sea urchin S. intermedius and caused pronounced membrane depolarization in the cells of both tested microalgae species at concentrations between 10 and 100 mg/L. The sample with the highest proportion of submicron particles and the highest content of polycyclic aromatic hydrocarbons (PAHs) had the highest growth rate inhibition in both microalgae species and caused high toxicity to the crustacean. The toxicity level of the other samples varied among the species. We can conclude that metal content and the difference in the concentrations of PAHs by itself did not directly reflect the toxic level of VEPs, but the combination of both a high number of submicron particles and high PAH concentrations had the highest toxic effect on all the tested species.

scholarly journals A Study of the Understated Violence Within Social Contexts Against Adolescent Girls

2017 ◽  
Vol 8 (2) ◽  
pp. 29-41
Author(s):  
Shivangi Nigam ◽  
Niranjana Soperna
Keyword(s):  
Adolescent Girls ◽  
Rural Areas ◽  
Urban Areas ◽  
Social Issues ◽  
Well Being ◽  
Structured Interview ◽  
Social Contexts ◽  
The Social ◽  
The Difference ◽  
The Individual

Violence against women is linked to their disadvantaged position in the society. It is rooted in unequal power relationships between men and women in society and is a global problem which is not limited to a specific group of women in society. An adolescent girl’s life is often accustomed to the likelihood of violence, and acts of violence exert additional power over girls because the stigma of violence often attaches more to a girl than to the  perpetrator. The experience of violence is distressing at the individual emotional and physical level. The field of research and programmes for adolescent girls has traditionally focused on sexuality, reproductive health, and behaviour, neglecting the broader social issues that underpin adolescent girls’ human rights, overall development, health, and well-being. This paper is an endeavour to address the understated or disguised form of violence which the adolescent girls experience within the social contexts. The parameters exposed under this research had been ignored to a large extent when it comes to studying the dimension of violence under the social domain. Hence, the researchers attempted to explore this camouflaged form of violence and discovered some specific parameters such as: Diminished Self Worth and Esteem, Verbal Abuse, Menstruation Taboo and Social Rigidity, Negligence of Medical and Health Facilities and Complexion- A Prime Parameter for Judging Beauty. The study was conducted in the districts of Haryana (India) where personal interviews were taken from both urban and rural adolescent girls (aged 13 to 19 years) based on  a structured interview schedule. The results revealed that the adolescent girls, both in urban as well as rural areas were quite affected with the above mentioned issues. In urban areas, however, due to the higher literacy rate, which resulted in more rational thinking, the magnitude was comparatively smaller, but the difference was still negligible.  

scholarly journals Observed decreases in on-road CO<sub>2</sub> concentrations in Beijing during COVID-19 restrictions

2021 ◽  
Vol 21 (6) ◽  
pp. 4599-4614
Author(s):  
Di Liu ◽  
Wanqi Sun ◽  
Ning Zeng ◽  
Pengfei Han ◽  
Bo Yao ◽  
...  
Keyword(s):  
Urban Areas ◽  
Low Cost ◽  
Working Hours ◽  
Weather Conditions ◽  
Co2 Concentration ◽  
Mobile Platforms ◽  
Local Standard ◽  
Transportation Emissions ◽  
Enhancement Method ◽  
The Difference

Abstract. To prevent the spread of the COVID-19 epidemic, restrictions such as “lockdowns” were conducted globally, which led to a significant reduction in fossil fuel emissions, especially in urban areas. However, CO2 concentrations in urban areas are affected by many factors, such as weather, biological sinks and background CO2 fluctuations. Thus, it is difficult to directly observe the CO2 reductions from sparse ground observations. Here, we focus on urban ground transportation emissions, which were dramatically affected by the restrictions, to determine the reduction signals. We conducted six series of on-road CO2 observations in Beijing using mobile platforms before (BC), during (DC) and after (AC) the implementation of COVID-19 restrictions. To reduce the impacts of weather conditions and background fluctuations, we analyze vehicle trips with the most similar weather conditions possible and calculated the enhancement metric, which is the difference between the on-road CO2 concentration and the “urban background” CO2 concentration measured at the tower of the Institute of Atmospheric Physics (IAP), Chinese Academy of Sciences. The results showed that the DC CO2 enhancement was decreased by 41 (±1.3) parts per million (ppm) and 26 (±6.2) ppm compared to those for the BC and AC trips, respectively. Detailed analysis showed that, during COVID-19 restrictions, there was no difference between weekdays and weekends during working hours (09:00–17:00 local standard time; LST). The enhancements during rush hours (07:00–09:00 and 17:00–20:00 LST) were almost twice those during working hours, indicating that emissions during rush hours were much higher. For DC and BC, the enhancement reductions during rush hours were much larger than those during working hours. Our findings showed a clear CO2 concentration decrease during COVID-19 restrictions, which is consistent with the CO2 emissions reductions due to the pandemic. The enhancement method used in this study is an effective method to reduce the impacts of weather and background fluctuations. Low-cost sensors, which are inexpensive and convenient, could play an important role in further on-road and other urban observations.

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