DISASTER RECOVERY THROUGH PREDICTION OF SAFE ROUTE USING DEM LEVELS
DOI:
https://doi.org/10.22159/ajpcr.2017.v10s1.19539Keywords:
Digital elevation model, Disaster, Elevation levels, Environmental Systems Research Institute, Geographic information system, Threshold valueAbstract
When a disaster occurs, the normal commutation routes are disrupted. People get stuck at these disaster points and would be in trouble, hence people in those areas find it difficult to communicate and evacuation route to safe area is unknown. The aim of the paper is to predict safe routes to reach the refuge point from the disaster point. The prototype was developed using Arc geographic information system runtime SDK for Java Application and APIs in Eclipse. The system was developed with digital elevation model layer, and route layer for India basemap focused to Tamil Nadu. The safe route is found based on the elevation values of the area from the disaster point to a safe point. The developed system could be used by the relief providers to reach the disaster point and rescue victims.
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Cetateanu A, Luca BA, Popescu AA, Page A, Cooper A, Jones A. A novel methodology for identifying environmental exposures using GPS data. Int J Geogr Inf Sci 2016;30(10):1944-60.
Khawaldah HA. A prediction of future land use/land cover in Amman area using GIS-based markov model and remote sensing. J Geogr Inf Syst 2016;8(3):412-27.
Roy S, Sarker S. Integration of remote sensing data and GIS tools for accurate mapping of flooded area of Kurigram, Bangladesh. J Geogr Inf Syst 2016;8(2):184-92.
Puente RR, Cortés ML. Graph-reduction algorithm for finding shortest path in geographic information systems. IEEE Latin Am Trans 2012;10(6):2201-8.
Odum PO, Adeoye NO, Abubakar EO, Idoko MA. Comparative geospatial planning model for location specific†intervention and continuous improvement strategy. J Geogr Inf Syst 2016;8(3):329-37.
Poursaber MR, Ariki Y. Integrated GIS, remote sensing and survey data for damage assessment of buildings in tsunami event, Ishinomaki city, Japan. J Geogr Inf Syst 2016;8(2):260-81.
Pogácsás R. ArcGIS scripting generating unique hydrogeological maps. J GeoPython 2016;1(1):1-24.
Pandian P, Kalidasan S. On hypergraph assignment problems. Int J Pharm Technol 2016;8(3):16335-43.
Jayashree J, Vijayashree J. Technical aids for outdoor assistive navigation for visually impaired people. Int J Pharm Technol 2016;8(3):16344-51.
Forkuo EK. Flood hazard mapping using aster image data with GIS. Int J Geomatics Geosci 2011;1(4):1-19.
Sanyal J, Lu XX. Application of remote sensing in flood management with special reference to monsoon Asia: A review. Nat Hazard 2004;33(2):283-301.
Skelton S, Panda S. Geo-Spatial Technology Use to Model Flooding Potential in Chestatee River Watershed. Proceedings of Georgia Water Resources Conference, University of Georgia; 2009. p. 27-9.
Singh AK, Sharma AK. GIS and a remote sensing based approach for urban flood-plain mapping for the tapi catchment, India. J Hydrol Sci 2009;331:389-94.
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