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Humanitarian OpenStreetMap’s Map4Nepal Project

Forty-six GISCorps volunteers from 10 countries responded to the call for volunteers to the Nepal Earthquake in 2015 and digitized various features on OpenStreetMap shortly after the quake hit. In total volunteers logged over 440  hours.

Volunteers were: S. Suthakaran, C. Hansen, Tom Thompson, M.S. Koo, Bowon Chung, H. Hands, M. Avery, B. Lacabanne, Arindam Majumdar, Cristian Andres Galindo, Muneeb Muzammil, Wanaki Kistabish, Laxman Sharma, S Sundaram, GA, Michael Storey, John Clérin,  Rajesh S Paul, Bianca Hambasan, Maribel Jarrín,  Mukesh Vyas,  Lakshmanan Krishnan, Claudia Blagu, Jomals Mathews John, albhasan,  Jonathan Clayton,  Justin Cole,  Maria Gouveia,,  Esther Bowlin,  Sonal Raisinghani,  DeAnna Hohnhorst,  Paula Hewitt Amram,  Caryn Sobel,  Francesco Petrosino,  Josh Garver,  Alison DeGraff,  Jennifer Lishman Nunn,  Tejpal Kang,  Rossana Padeletti,  Sanjay Kumar,  Rajendra Kumar,  Kevin Hill,  Yoshinori Takahashi,  Festus Olusola,  Michele Jett,  Nyssa Hunt,  Jordan McMillan.

Volunteers assisting with data cleansing in Nepal

The United Nations Office for the Coordination of Humanitarian Affairs (UNOCHA) & ACAPS requested the assistance of volunteers for matching village names in two separate data files; Nepal’s Admin4 boundaries or village names and their corresponding names in Nepal’s comprehensive Census data. The request was sent to the Digital Humanitarian Network (DHN). GISCorps and Statistics Without Borders, both members of DHN, responded to the call.

Dr. Mark Salling, a GISCorps volunteer and longtime member of GISCorps Core Committee along with one of his colleagues Charlie Post used SAS to generate two separate lists. The first included a list of names that exactly matched between the two files and the second one included those that were matched based on similarities in spelling. The second list was then checked by two other volunteers, Adelaide Zumwalt and Shoreh Elhami and several of the records in high priority areas were manually matched using GeoNames.

The resulting files were then joined with the Admin4 GIS layer and a web map identified all the matched and unmatched village names. Members of MapAction team are now examining the partially matched names and will try to locate those names.

In parallel, Statistics without Borders (SWB) has been working on consolidating the Census data which will then be joined with the final and cleansed Admin4/village data layer.

After the census data are linked to the spatial data, it will be used for the ongoing damage and needs assessments. They will provide a vital baseline on which to measure the impacts of the earthquake on the population, and help inform the most appropriate response and recovery solutions – it is really unusual to have such a comprehensive baseline dataset.  Having the rapid support of GISCorps and SWB who were able to interpret and manage these large datasets, and transform them into formats required by the in-country responders was really important.

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