c onnecting for a r esilient a merica 1 public- private partnerships: key drivers of disaster supply...

CCONNECTINGONNECTING FOR AFOR A R RESILIENT ESILIENT AAMERICAMERICA 1CCONNECTINGONNECTING FOR AFOR A R RESILIENT ESILIENT AAMERICAMERICA

Public- Private Partnerships: Key Drivers of Disaster Supply

Chains

Dr. Ramesh KolluruDr. Mark Smith

CCONNECTINGONNECTING FOR AFOR A R RESILIENT ESILIENT AAMERICAMERICA 2

Public- Private Collaboration

Partnership

Public SectorPrivate

Businesses

4

Owns 85% of CIKR assets

Drives 98% Supply Chains


Louisiana Business Emergency Operations Center

State Initiative

To support disaster management in Louisiana by developing an accurate understanding of economic impacts to critical

infrastructures and major economic drivers, as well as facilitating the coordination of businesses and volunteer organizations with the

public sector through enhanced resource and information management.

A Partnership Of


Public-Private Partnerships

The NIMSAT Institute establishment of public-private partnerships through the LABEOC seeks to mitigate the risks we face as a nation to the intricate interdependencies between CIKR assets and the public and private sector supply chains that depend on these assets.

•Through the Louisiana BEOC, the State of Louisiana will :– Facilitate communication between public and private sectors– Enable business and industry to identify roadblocks to recovery– Reduce overall economic impacts to Louisiana businesses and

industry– Mobilize government resources

- Ex.- Fuel Supply-Demand Project

*The long term goal would be to create and replicate this model in Louisiana, the Gulf Coast and the Nation.


Current Issues in Public-Private Partnerships

• Can government resources be utilized?

• What types of information are useful and can be shared?

• What are the motivators and roadblocks for such

partnerships?

• Is there a governance structure that all sectors could utilize

in engaging with their counterparts or other stakeholders in

response?

• What is the capability maturity model?

• Modeling, Simulation and Analysis of Operational Capability for

Simple and Complex Events


Challenges & Progress

• Information Sharing Between the Sectors- Government-to-Business Information Sharing- Business-to-Government Information Sharing** The LABEOC has begun to engage these partners in willingness to participate

• Motivators or Roadblocks- Concerns between sectors- LABEOC facilitate these partnerships- Legal policy- Integrated monitoring systems** The LABEOC managers have begun to coordinate and

solve these issues. Since the LABEOC is a neutral party there is a receptiveness .


Challenges & Progress

• Capability Maturity Model

- Complex Emergencies

- Real Time Plans

- Measuring performance between interactions

** LABEOC plans to engage all sectors through a

information hub website to ensure coordinating communications

• Established private sector supply chain models already created- CPFR Model – (Collaborative Planning, Forecasting and Replenishment

**Industry Standard framework in development


Fuel Supply-Demand Project

To enhance Energy sector resiliency through improved information sharing from the “platform to the pump” that enable communications across the energy supply chain to facilitate processing delivery, and distribution, while enhancing the State Energy Profile.

In collaboration with Department of Energy & Louisiana Department of Natural Resources


Current Development

• SmartGrid policy

• Energy Supply-Demand Model

• Evacuation Fuel Plan

• Improved LABEOC measures for monitoring energy sector

• Conduct regional exercises that include the Gulf Coast Region


Fuel Supply Grant

• Transportation/Fuel Demand Model – How much fuel is needed to support an evacuation?

• Behavioral Social Network Model– When will people evacuate? (shadow evacuations?)– Where are they likely to go?

• Fuel Supply System Model– What is the fuel availability at gas stations?

• Results for Decision Support – Can we mobilize adequate emergency fuel, if needed?

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CCONNECTINGONNECTING FOR AFOR A R RESILIENT ESILIENT AAMERICAMERICA11

Private Industry Response to Gustav/Ike

• Public-Private Partnerships– Mobilized business products and services: $23.8

million dollars– Enhanced Situational Awareness: shortages of

fuel

• CIKR Consequence Models– Reported disruptions to operating capacity of 120

petroleum, natural gas, chemical and electricity facilities (CITGO Refinery, Entergy, Henry Hub, LOOP, Port Fourchon, etc.)

– Economic impact to Oil & Gas industry: $7.6B - $8.3B


Future Research Areas

• LABEOC has begun research on partnerships

• Ability to integrate systems and plans between

sectors

• State Emergency Center communication

• Facilitation on all levels (legal issues, monitoring,

planning, etc.)

• Possible merging of operational systems

• Regional cooperation

• Energy sector and Fuel Supply- Demand project


CCONNECTINGONNECTING FOR AFOR A R RESILIENT ESILIENT AAMERICAMERICA

Public- Private Partnerships: Key Drivers of Disaster Supply

Chains

Dr. Ramesh KolluruDr. Mark Smith

Ronald T. EguchiPaul AmyxCharles K. HuyckImageCat, Inc.

www.virtualdisasterviewer.com

DHS – S&T Workshop on Emergency Management: Incident, Resource, and Supply Chain Management

5-6, November 2009, UCI, Irvine, CA

Presentation Outline

• The Problem• VDV interface for damage assessment • Outreach• Future activities• Summary

There is a post-disaster need…… for expert analysis to provide rapid and accurate commentary after significant

events… to harness the skills of experts from a wide variety of industries, affiliations, and

locations… for a central repository for experts’ interpretations to improve dissemination

and discussion of data from current and past disasters

After major disasters, it is not always feasible to deploy field teams due to damage and/or access restrictions

Multiple field deployments can result in duplication of effort and costs

Data is not shared from multiple field teams

KoreaJapan

Philippines

Hong Kong

Beijing

Tibetan Plateau

Shanghai

Wenchuan Earthquake

Chengdu

2008 Wenchuan Earthquake

Details (known):May 12, 2008, 2:28pm (Local time)Magnitude: 7.9 (USGS)Location: 30.986°N, 103.364°E Depth: 19kmFault length: approx. 250km

Details (unknown):Number of ? dead (missing)

? injured? buildings

collapsed ? buildings damaged ? homeless ? evacuated ? people affected ? Economic loss

Damage Estimates:69,200 dead (20,000 missing)374,200 injured5.4 million buildings collapsed21 million buildings damaged5 million homeless15 million evacuated46 million people affectedEconomic loss US$80 billion?UNDMT Situation Report No. 8, 14 June 2008

VDV Interface for Damage Assessment

• The login procedure• Accepting an assignment• Scope of evaluation• The notion of a damage scale based on

remote-sensed images• Damage assessment procedure• Results from 2008 Sichuan, China

earthquake

Figure 1. Virtual Disaster Viewer homepage

Virtual Earth navigation

controls

Virtual Earth base data

and imagery

Details of project sponsors and participating organizations

Pre- and post-disaster

satellite imagery

Derived layers

Field data

Legend for expert interpretation results

Major sponsors and affiliations

www.virtualdisasterviewer.com

Grid Cells for Analysis

Remote sensing damage scale

Damage level Description Example pre - earthquakeExample post -

earthquake

RSE - 0 Indistinguishable

a) Pre disaster shows building, post-disaster is homogenous cleared area with no evidence of debris, suggesting demolition prior to earthquake. b) Partially built building; (under construction site at the time of the earthquake). c) Building is under cloud cover, or is otherwise obscured by another imagery artefact.

RSE - 1Non / Slight

a) No damage seen within image. Pre- and post-event images same shape, size, colour (.b) Slight damage (i.e. tiles from roof small amount of debris)c) Equated to EMS98 level 1 or 2

RSE - 2 Extensive

a) Extensive damage seen. b) Possible changes include: Change in building footprint shape. Roof collapsed. Heterogeneous roof colour/texture Substantial rubble. c) New builds that are extensively damagedd) Equated to EMS98 level 3 or 4

RSE - 3 Collapse

a) Building collapsedb) Copious rubble evidentc) New build which is completely collapsedd) Equated to EMS98 level 5.

Remote Sensing for Earthquake Scale (RSE) Damage Scale Descriptions

Assigning Damage Level

Pre

Post

Results

BUILDING

DAMAGE

Results

LANDSLIDE

EXTENT

Initial funding from EPSRC (UK), EERI, MCEER (USA) Tool developed by ImageCat Currently being developed for inclusion in EEFIT

missions to Indonesia & South Pacific 84 expert volunteers from 8 countries

• Conferences & Workshops• Wired Magazine article: April 2009• Imaging Notes Magazine article:

Fall 2009

• Flagship project for Community Remote Sensing theme: IEEE International Geoscience & Remote Sensing Symposium (IGARSS) 2010

• Sumatra & Samoa currently being developed• Validation of expert analysis & assessing

experts’ skills – “superusers”• Extend functionality may include

– Video field blogs & text summaries of professional findings

– Greater use of commenting facilities– Develop analytical tools for automatic

interpretation of results

• VDV developed to fill technological need for a post-disaster data portal

• Multiple functions developed according to needs of field teams on per-event basis

• Currently broadening VDV’s outreach for future funding and data partnerships

• A growing community of expert users and contributors are realizing VDV’s potential

Presented: 11/05/09 http://teamcore.usc.edu

Agent-based Evacuation Modeling:Simulating the Los Angeles International Airport

Milind Tambe, Jason Tsai, Matthew E. Taylor, Shira Epstein, Andrew Ogden, Prakhar Garg

University of Southern California

Gal Kaminka, Natalie Fridman

Bar Ilan University

Emma Bowring

University of the Pacific

Presented: 11/05/09 Jason Tsaihttp://teamcore.usc.edu

Emergency evacuationTraining and policy decisions are difficult

Scenario: Evacuation of an airport terminal after an event

Ideal: Conduct live exercises Personnel can see what actually happens

Policy-makers can try different rules

Issue: Live exercises are difficult Requires the terminal to be shut down

Requires realistic response of hundreds of people

Unethical to instill real fear/anxiety in people


Evacuation simulationSimulations provide an answer

Proposal: Simulation replaces live exercises Evaluate different policies

Decision-making training for officer

Visual conditioning for officers

We propose to build an agent-based model with realistic human behavior and compelling visualization


Our approachWe focus on unaddressed issues unique to the domain

BDI-style architecture Standard architecture style for agents

Social Comparison Theory mechanics General theory of how agents impact each other

Transition to emergency Model the transition from normal to emergency behavior

Massive software visualization Movie-quality people seen at eye-level


Previous work: TeamcoreWe have worked in simulations in the past

DEFACTO system Training / coordination tool for fire

department incident commanders

Robocup Rescue Search and rescue simulation

Helicopter team simulations Helicopter attack strategy simulation


Previous work: Academic Evac. SimulationWealth of work in evacuation simulations

BDI-style architecture Agent interactivity without underlying social theory

Social Psychology simulations Apply theories limited to very specific activities

Physics-based simulations Individual behaviors are generalized

We propose to use a general psychological model that can model both ‘normal’ and ‘emergency’ behavior


Previous work: Architectural planningArchitectural simulations provide a high-level view

Metrics are high-level (e.g., time to clear a building)

Lacks validated realism in individual behaviorLegion software


Previous work: CinemaCinema simulations focus on dramatic effect and believability

Metrics involve believability, director’s desires, etc.

Lacks validated realism in individual behavior

Massive software


CollaborationsWe have established key collaborations

Los Angeles Airport Police and TSA First step will be to develop a simulation of Terminal 1

Massive software

USC School of Cinematic Arts

Cross-institutional team Expertise in crowd simulation, disaster response simulation, and Social

Comparison Theory


Challenges

Computational speed Hundreds of agents with complex decision mechanisms

Parameters / Calibration Data for calibration is sensitive information

Techniques for analyzing the data are imperfect

Validation Scientific validation

Expert user buy-in

[email protected]://teamcore.usc.edu

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