ImageCat Inc.

Long Beach, CA, United States

ImageCat Inc.

Long Beach, CA, United States
SEARCH FILTERS
Time filter
Source Type

Graf W.P.,ImageCat Inc. | Seligson H.A.,MMI Engineering Inc.
Earthquake Spectra | Year: 2011

The M7.8 San Andreas earthquake scenario for the ShakeOut exercise subjects more than a million wood-framed buildings to loads beyond their elastic capacity. Residential construction from the boom from the 1960's to 1980's relied heavily upon drywall sheathing and stucco for shear walls - more vulnerable than plywood or the gypsum lath and plaster of older buildings. During this same construction boom, many apartment buildings were built with tuck-under parking, and heavy masonry chimneys were prevalent. Based on HAZUS®MH modeling we describe, more than 30,000 (mostly older) wood buildings could be red-tagged or yellow-tagged in the scenario event. More recent wood-frames, engineered using plywood shear walls, should perform well, evenunder the conditions produced by the San Andreas event considered. Cost-effective retrofit measures exist for some of the weaknesses found in older wood construction, but seismic upgrade of wood-framed buildings with structural wood panels remains expensive and intrusive. © 2011, Earthquake Engineering Research Institute.


Eguchi R.T.,ImageCat Inc.
Natural Hazards | Year: 2013

Disaster experts around the world have continually warned governments and the public about the possibility of "worst-case" natural hazard scenarios and their overwhelming impacts. Yet, planning for the occurrence of these events has fallen far short of need. The large earthquake that occurred off the coast of Sumatra in 2004, which resulted in one of the deadliest tsunamis ever recorded, was a painful reminder that living in some of the most desirable areas of the world does have its risks. We all have enjoyed the fun of restful visits to coastal resort communities all around the world, and we rarely think about earthquakes or tsunamis interfering with this enjoyment. Yet, they take us by surprise. Before these events do occur, there should be adequate education for everyone on what actions are appropriate as well as an effective warning system to trigger the right actions. © 2013 Springer Science+Business Media Dordrecht.


Booth E.,Edmund Booth Consulting Engineer | Saito K.,Cambridge Architectural Research Ltd | Spence R.,Cambridge Architectural Research Ltd | Madabhushi G.,Trumpington Street | Eguchi R.T.,ImageCat Inc.
Earthquake Spectra | Year: 2011

Assessments of damage following the 2010 Haitian earthquake were validated by comparing three datasets. The first, for 107,000 buildings, used vertical aerial images with a 15-25 cm spatial resolution. The second, for 1,241 buildings, used Pictometry images (oblique angle shots with a resolution of about 10 cm taken in four directions by aircraft). The third dataset, for 142 buildings, used ground observations. The ground observations confirmed the tendency of remote sensing to underestimate the proportion of heavily damaged and collapsed buildings, and the difficulty of making remote assessments of moderate or low damage. Bayesian statistics and sample surveys made from Pictometry images and ground observations were used to improve remote damage assessments from vertical images. The possibility of developing standard factors to correct remote assessments is discussed. The field exercise pointed to the need to produce an internationally agreed-upon set of damage definitions, suitable for postdisaster needs assessments as well as for other uses. © 2011, Earthquake Engineering Research Institute.


Rose A.,University of Southern California | Huyck C.K.,ImageCat Inc.
Risk Analysis | Year: 2016

While catastrophe (CAT) modeling of property damage is well developed, modeling of business interruption (BI) lags far behind. One reason is the crude nature of functional relationships in CAT models that translate property damage into BI. Another is that estimating BI losses is more complicated because it depends greatly on public and private decisions during recovery with respect to resilience tactics that dampen losses by using remaining resources more efficiently to maintain business function and to recover more quickly. This article proposes a framework for improving hazard loss estimation for BI insurance needs. Improved data collection that allows for analysis at the level of individual facilities within a company can improve matching the facilities with the effectiveness of individual forms of resilience, such as accessing inventories, relocating operations, and accelerating repair, and can therefore improve estimation accuracy. We then illustrate the difference this can make in a case study example of losses from a hurricane. © 2016 Society for Risk Analysis.


Trademark
ImageCat Inc. | Date: 2013-05-30

Computer software for database management in the field of insurance concerning data quality assessment and insurance exposure factors; Downloadable electronic publication in the nature of magazines, journals, newsletters, articles in the field of insurance data quality assessment and insurance exposure factors. Providing of data for use by the insurance and reinsurance field to model vulnerabilities from disasters; providing of data for modeling and simulating of natural disasters; providing of data for inventorying of insured assets and assessing exposure; and providing of data for assessing damage to buildings and utilities in near real-time following a disaster.


Trademark
ImageCat Inc. | Date: 2013-05-15

Computer software for assessing global disaster risk, including exposure data quality assessment and scoring for disaster risk management in the field of insurance and reinsurance; Downloadable electronic publications in the nature of magazines, journals, articles and newsletters in the field of global risk and disaster management. Disaster risk assessment, namely, provision of business exposure information data for vulnerability modelling, natural disaster modelling and simulation, asset/exposure inventorying, near real time post-disaster building and utility damage assessment for the insurance and reinsurance field; business risk management for the insurance and reinsurance field. Financial loss and claims assessments of damages after a disaster, for the insurance field; providing information concerning financial assessment of damages after a disaster; financial assessment of risk; all the aforesaid provided to the insurance market. Scientific and technological services provided to the insurance and reinsurance industries, namely, scientific research and analysis; surveys, namely, scientific surveying, seismic data surveying, field surveying undertaken to gather data to model natural disaster risk; design and development of computer software for these purpose.


Grant
Agency: NSF | Branch: Standard Grant | Program: | Phase: | Award Amount: 40.65K | Year: 2010

This Grant for Rapid Response Research (RAPID) seeks to understand the relationship between physical damage in disasters and socio-economic disruption at the community-scale. In this study, the community scale refers to neighborhoods or similar spatial units that comprise an urban area. Our central research question is: To what extent can the extent of building damage predict the severity of disruption to the communities social fabric and economic function? Is there a linear relationship between damage rate and disruption? Or are there thresholds of damage beyond which disasters become catastrophes? How does the relationship between damage and disruption change over time in the initial response and restoration periods? Post-earthquake Haiti experienced an extensive range of damage and disruption across the urban landscape, thus providing a rare opportunity to investigate these questions within the context of a single disaster event.

Fieldwork will focus on gathering two types of information: 1) damage data to ground-truth available remote satellite information on building damage, and 2) data on socio-economic disruption at the community scale. Gathering the damage data is time-sensitive because the field information must be temporally consistent with the remote sensing images. Gathering the disruption data is time-sensitive because the information will be based on field interviews that seek to elicit judgments and recollections about conditions in the immediate aftermath and first few months of the disaster. These data must be gathered quickly, in order to capture the perishable recollections and situational observations that rapidly fade from memory.

This research will be undertaken using three complementary approaches: 1) automated, semi-automated and visually-based analysis of high resolution satellite and aerial remote sensing imagery; 2) acquisition and expert interpretation of street-view GPS referenced photographs and video using the VIEWS field data collection system; and 3) interviews with NGOs involved in community-scale relief, response and recovery within Haiti (supplemented with secondary data). Data collection will focus on 8-12 selected Haitian communities that collectively represent a broad range of earthquake damage severity.

The study extends the research teams current work on methods for measuring community disruption and recovery following Hurricanes Charley and Katrina, by testing U.S. methods in the context of Haiti. It also draws on the research teams experience with remote sensing-based damage assessment for the Haiti earthquake (through the GEO-CAN initiative) by extending the nationwide work to the community scale.

In addition to the datasets on damage and disruption to be developed, a primary outcome of the research will be analysis of the relationship between damage and disruption over space and time in the Haitian case. We envision that the outputs of this research will take the form of a report documenting our findings about disruption and the restoration of basic needs in the selected Haitian communities. Remote sensing and in-field survey results will also be documented and displayed through online media including the Virtual Disaster Viewer.


Grant
Agency: NSF | Branch: Standard Grant | Program: | Phase: | Award Amount: 49.57K | Year: 2015

The April 2015 Nepal earthquake has resulted in a large number of local, national and international damage data collection efforts. Many organizations involved have a long history of responding to natural disasters and do so with a mandate from the national government or other recognized organization. There are other efforts that have emerged for the Nepal event that are not as coordinated, resulting in confusion to a variety of end-users as to the veracity, technical rigor, or openness of the data. This Rapid Response Research (RAPID) project aims to take a view on the damage datasets generated since the earthquake and assess the impact of each dataset in terms of the objectives and eventual end-use. This information will feed the development of data quality benchmarking criteria that can be used by any data collection effort following disaster events. The eventual impact is to reduce the uncertainty in future datasets and support the end-user to better understand the purpose, pedigree and appropriateness of the data for their specific use case.

The project will collect data from a number of sources and bring together a database of damage data for Nepal. In-country interviews with data suppliers and end-users will help the understanding of the impact of each dataset. Finally, criteria of best-practice will be generated to help inform users understand and compare data in future events. With evermore increasing technical capabilities for data collection, advancement of data processing, storage and online sharing, it is clear that the demand for open standards and interoperability is increasing. Therefore, it is crucial that data quality measures are clear and accessible to help openly compare data and reduce uncertainty to avoid unintended misuse of damage datasets.


Grant
Agency: NSF | Branch: Standard Grant | Program: | Phase: | Award Amount: 42.02K | Year: 2011

This Grant for Rapid Response Research (RAPID) project seeks to understand the relationship between urban development patterns and the extent of physical damage caused by widespread tsunami run up. The 11 March 2011 Tohoku, Japan earthquake caused significant damage all along the northeastern coast of Japan. In order to understand how the built environment can affect the performance of communities in a tsunami, the project will study at least nine communities in the Miyagi/Chiba/Ibaraki Prefectures ¨C areas ranging from minor to moderate damage to complete devastation. The central research question is: Can the urban topology of a community mitigate the effects of a tsunami by isolating the more damaging surge effects to a few well designed and well placed buildings, thus limiting damage to protected buildings to just rising water effects. The main objectives of this study are: 1) to perform field studies to collect perishable data on coastal community performance following the Tohoku earthquake, 2) to develop an understanding of the data landscape in post earthquake Japan, and 3) to develop a preliminary understanding of the role that urban development patterns played in either mitigating or exacerbating tsunami induced impacts.

This project will gather new information to systematically and comprehensively assess the effect that urban development patterns have in mitigating or exacerbating the effects of tsunamis. Such information would complement current studies that focus only on the performance of individual structures, i.e., not on the performance of communities. This information can also provide an important reference point for any future studies on long term recovery in Japan by documenting the initial damage states of representative communities along the coast of Japan. In addition to data collection, this project will explore new methods of performing rapid damage assessment using distributed visual analytics and crowd sourcing, and high resolution aerial and satellite imagery; these methods can be vital in situations where immediate field access is not possible or damage is widespread (as was the case in the Tohoku earthquake). Furthermore, the knowledge gained in this study will help to inform future tsunami loss modeling activities by introducing community based parameters that can either enhance or exacerbate the direct effects of an earthquake. The results of this study will also enforce the notion that resilience should be viewed at a community level in order to minimize the socioeconomic impacts of large disasters. The knowledge gained from this study will help to improve regional preparedness plans for many coastal areas, including the west coast of the United States, which also experienced significant damage in the Tohoku earthquake.


Grant
Agency: NSF | Branch: Standard Grant | Program: | Phase: | Award Amount: 50.00K | Year: 2015

Water is a critical resource and a lifeline service to communities worldwide; the generation, treatment, distribution and maintenance of water workflows is typically managed by local governments and water districts. Recent events such as water supply disruptions caused by Hurricane Sandy in 2012 and the looming California drought crisis clearly indicate societys dependence on critical lifeline services such as water and the far-reaching impacts that its disruption can cause. Over the years, these critical infrastructures have become more complex and often more vulnerable to failures. The ability to view water workflows as a community wide cyber-physical system (CPS) with multiple levels of observation/control and diverse players (suppliers, distributors, consumers) presents new possibilities. Designing robust water systems involves a clear understanding of the structure, components and operation of this CPS system and how community infrastructure dynamics (e.g. varying demands, small/large disruptions) impact lifeline service availabilities and how service level decisions impact infrastructure control.

The proposal emphasizes a new approach to exploring engineering systems that will result in substantial advances in the understanding of lifeline systems and approaches to make them adaptive and resilient. Building resilience into urban lifelines raises a number of monumental challenges including identifying the aspects of systems that can be observed/sensed and adapted and to developing general principles that can guide adaptation. The key idea is to develop methodologies to understand operational performance and resilience issues for real-world community water infrastructures and explore solutions to problems in cyberspace before instantiating them into a physical infrastructure. The effort includes: 1) Developing a flexible modeling framework that captures system needs at multiple levels of temporal and spatial abstraction; 2) Developing real-time algorithms supporting resilience; 3) Designing adaptations for water systems using a data-driven approach; and 4) Demonstrating the important broader impact of the research on critical water system infrastructure at the Global City Technology Challenge and the longer term impact on infrastructure for a resilient control framework.

Loading ImageCat Inc. collaborators
Loading ImageCat Inc. collaborators