Open data in building resilience to recurrent natural hazards in remote mountainous communities of Nepal

Parajuli, B.P., Shakya, P., Khadka, P., Liu, W. ORCID: https://orcid.org/0000-0003-3646-3456, & Pudasaini, U. (2020). Open data in building resilience to recurrent natural hazards in remote mountainous communities of Nepal. DOI:10.5194/egusphere-egu2020-4761. In: European Geosciences Union (EGU) General Assembly 2020, 4-8 May 2020, Vienna, Austria.

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Abstract

The concept of using open data in development planning and resilience building to frequent environmental hazards has gained substantial momentum in recent years. It is helpful in better understanding local capacities and associated risks to develop appropriate risk reduction strategies. Currently, lack of accurate and sufficient data has contributed to increased environmental risks, preventing local planners the opportunity to consider these risks in advance. To fulfil this gap, this study presents an innovative approach of using openly available platforms to map locally available resources and associated risks in two remote communities of Nepal. The study also highlights the possibility of using the combined knowledge of technical persons and citizen scientists to collect geo-spatial data to support proper decision making. We harnessed the power of citizen scientists to collect geo-spatial data by training them on currently available tools and platforms. Also, we equipped these communities with the necessary instruments to collect location based data. Later, these data collected by citizen scientists were uploaded in the online platforms. The collected data are freely accessible to community members, government and humanitarian actors which could be used for development planning and risk reduction. Moreover, the information co-generated by local communities and scientists could be crucial for local government bodies to plan activities related to disaster risk reduction. Through the piloting in two communities of Nepal, we have found that using open data platforms for collecting and analysing location based data has a mutual benefit to researchers and communities. These data could be vital in understanding the local landscape of development, environmental risk and distribution of resources. Furthermore, it enables both researchers and local people to transfer the technical knowledge, collect location specific data and use them in better decision making.

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