IGARSS 2010 - 2010 IEEE International Geoscience and Remote Sensing Symposium - July 25 - 30, 2010 - Honolulu, Hawaii, USA

Community Remote Sensing: Virtual Disaster Viewer


A web-based tool for rapid, distributed community-based imagery analysis to assist response to natural disasters.


ImageCat, in association with Earthquake Engineering Research Institute (EERI) and the Earthquake Engineering Field Investigation Team (EEFIT).


The Virtual Disaster Viewer (VDV) was initially developed by an international consortium of earthquake experts from Europe and USA, following the 2008 Sichuan, China Earthquake. The groundbreaking 'social networking'-style disaster monitoring tool is based on community remote sensing principles and offers remote support to response and recovery efforts by enabling distributed users to remotely conduct online damage assessments. Customised within days after a disaster, VDV integrates all common genres of geospatial data for a holistic perspective on the unfolding scene, and it provides a forum for sharing experiences and intelligence as it is gathered.

VDV uses Microsoft Bing functionality, and incorporates high-resolution pre- and post-event imagery overlaid with GIS datasets relevant to the disaster event. To date, VDV has been used by EERI and EEFIT as a tool for planning and prioritising post-disaster field deployments, as well as providing simultaneous support to their teams once in the field, allowing instant upload of geo-referenced video, photographs and observations that are immediately viewable by colleagues back at base, together with the general public at large. Once published in VDV, an interactive, online repository for a multitude of data becomes instantly accessible to hundreds of remote experts globally, creating a virtual disaster scene where professional users can provide their opinions on the unfolding event at a time where there may be access restrictions or difficulties in reaching isolated communities. Damage assessment responsibilities can be distributed to a network of practised volunteers, cataloguing buildings, bridges and roads that have been damaged or destroyed, mapping areas devastated by landslides, and monitoring governmental and NGO relief efforts as tents and temporary camps are set-up. Comments and professional damage assessments using the field photos and video are stored in VDV providing an interactive social environment for an expert global community to provide independent knowledge that accumulates into an overall understanding of the disaster event that can guide response and recovery activities.

Thus far, VDV has been customised for the 2008 Sichuan Earthquake, the 2009 L’Aquila, Italy Earthquake, and is being used as a historical library for geo-referenced data collected in the aftermath of Hurricane Charley, USA (2004) and Izmit, Turkey Earthquake (1999). Still in its beta stage, VDV has been developed through limited research funding, and has grown organically based on user requirements and previous experiences of field teams and disaster experts. It has shown tremendous potential as a community remote-sensing tool, with nearly 100 volunteer experts from 3 continents participating in damage assessment following the China Earthquake. Funding is currently being sought to further develop and publicise VDV, to allow a greater outreach to imagery and field data providers, expert volunteers, as well as enabling the collation of data from historic events for future research projects. A Web 2.0 portal has finally been created where it is needed most.


To be posted when available.


Project LeadBeverley Adams (bja@imagecatinc.com)
Project Websitehttp://www.virtualdisasterviewer.com


Distributed analysis uses the community to rapidly extract knowledge from raw remote sensing data. With VDV, imagery of disaster regions such as earthquakes can be rapidly communicated via the internet to a large network of analysts. These may include known experts, pre-qualified volunteers, or perhaps even anyone who is accessing the internet and is knowledgeable about the affected area. The tool segregates the analysis by grid area to distribute the task and provides a variety of functions to assess the situation and rapidly inform decision-makers of needed actions. The use of community speeds up time-critical tasks that might otherwise take centralized organizations hours or days to complete.

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