RELIEF 11-01 Camp Roberts Report (November 2010)

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Dr. Linton Wells II, John Crowley

From 8-12 November 2010, RELIEF convened its sixth session of field experiments for humanitarian information management and crisis mapping at Camp Roberts in Paso Robles, CA. The RELIEF experiments occurred within a partnership of the National Defense University’s Center for Technology and National Security Policy and the Naval Postgraduate School.

RELIEF 11-01 focused on problems stemming from operations in Haiti, the US Gulf Oil Spill, and Afghanistan/Pakistan. It attempted to solve three problems common to both domestic and international response operations:

1. How to integrate imagery collected and/or processed by multiple communities. During each operation in 2010, both commercial and government satellites collected imagery, making much of the data available under open licenses for use by multiple stakeholders, including state and local agencies, academic institutions, and non-governmental organizations (NGOs) and private volunteer organizations (PVOs) such as OpenStreetMap and Crisis Mappers. However, there existed no single place to index these various data sets, let alone store the processed imagery in formats that enabled any stakeholder to quickly mashup and analyze data as multiple layers.

2. How to make citizen-generated map data available for editing and/or correction by federal officials and UN field staff. In Haiti, OpenStreetMap created the best map of the post-disaster situation, tracing roads and building footprints for most of the country in a matter of days. This dataset quickly became the standard used across the operation. However, traditional GIS tools (such as ESRI ArcGIS) could not read or write in the data format of OpenStreetMap, making it difficult to reconcile changes made in one platform with edits made in another.

3. How to reduce the delay between data collection and its integration into the information systems being used to make decisions. While data collection and assessment teams collected reams of paper forms, this data often sat in piles for long periods before being entered into data systems used for decision making. This problem was particularly an issue with georeferenced data collected about the locations of critical infrastructure, including hospitals, schools, and cholera treatment clinics in Haiti. It is also an issue for citizen-generated data that requires translation.

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