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Krishna Murthy, Y. V. N.; Raju, P. L. N.; Srivastav, S. K.; Kumar, P.; Mitra, D.; Karnatak, H.; Saran, S.; Pandey, K.; Oberai, K.; Shiva Reddy, K.; Gupta, K.; Swamy, M.; Deshmukh, A.; Dadhwal, V. K.; Bothale, V.; Diwakar, P. G.; Ravikumar, M. V.; Leisely, A.; Arulraj, M.; Kumar, S.; Rao, S. S.; Singh Rawat, R.; Pathak, D. M.; Dutt, V.; Negi, D.; Singh, J.; Shukla, K. K.; Tomar, A.; Ahmed, N.; Singh, B. ... view all 32 authors View less authors (2014)
Languages: English
Types: Article
Subjects:
Uttarakhand State of India suffered a widespread devastation in June 2013 due to floods caused by excessive rain in the upper reaches of the Himalaya, glacial lake outburst flood (GLOF) and landslides. Restoration process in this mountainous State calls for scientifically sound planning so that the vulnerabilities and risks to such natural hazards are minimised and developmental processes are sustainable in long run. Towards this, an understanding of the patterns and major controls of damage of the recent disaster is a key requirement which can be achieved only if the primary data on locations and types of damage along with other local site conditions are available. Considering widespread damage, tough nature of terrain and the need for collecting the primary data on damage in shortest possible time, crowdsourcing approach was considered to be the most viable solution. Accordingly, a multiinstitutional initiative called "Map the Neighbourhood in Uttarakhand" (MANU) was conceptualised with the main objective of collecting primary data on damage through participation of local people (mainly students) using state-of-art tools and technologies of data collection and a mechanism to integrate the same with Bhuvan geo-portal (www.bhuvan.nrsc.gov.in) in near real-time. Geospatial analysis of crowd-sourced points with different themes has been carried out subsequently for providing inputs to restoration planning and for future developmental activities. The present paper highlights the capacity building aspect in enabling the data collection process using crowdsourcing technology.
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