1. Ronald T. Eguchi Paul Amyx Charles K. Huyck ImageCat, Inc. www.virtualdisasterviewer.com DHS – S&T Workshop on Emergency Management: Incident, Resource, and Supply Chain Management 5-6, November 2009, UCI, Irvine, CA

2. Presentation Outline The Problem VDV interface for damage assessment Outreach Future activities Summary

3. 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

4. Korea Japan 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: 19km Fault 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 injured 5.4 million buildings collapsed 21 million buildings damaged 5 million homeless 15 million evacuated 46 million people affected Economic loss US$80 billion? UNDMT Situation Report No. 8, 14 June 2008

5. 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

6. 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

9. Grid Cells for Analysis

13. Remote sensing damage scale Damage level Description Example pre - earthquake Example 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 - 1 Non / 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 damaged d) Equated to EMS98 level 3 or 4 RSE - 3 Collapse a) Building collapsed b) Copious rubble evident c) New build which is completely collapsed d) Equated to EMS98 level 5. Remote Sensing for Earthquake Scale (RSE) Damage Scale Descriptions

14. Assigning Damage Level Pre Post

15. Results BUILDING DAMAGE

16. Results LANDSLIDE EXTENT

17. 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

18. 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

19. 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

20. 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