ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., I-2, 195-202, 2012
https://doi.org/10.5194/isprsannals-I-2-195-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
13 Jul 2012
A New Models for Emergency Evacuation under the Disaster Condition
L. Tang, X. Yang, F. Huang, H. Xu, and Q. Li State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, 430079, P. R. China
Keywords: Emergency evacuation, Multi-level emergency evacuation model, Spatial point matching, The K routs, Car assignment, Emergency evacuation platform Abstract. People must face many disasters every day, which cause losses in property and human lives. It is significant how to establish the emergency evacuation model and for high density population in large areas according to the actual situation of their emergency evacuation. This paper put forward a Multi-levels Emergency Evacuation Model (MEE) based on the collective evacuation for high density of population in large areas under the earthquake condition in China, which firstly find the best ways from the multi-gathering points(Origins) in the disaster area to multi-settling points(Destinations )in the safe area based on the road impedance such as the traffic, road speed limit and pavement damage to weight the evacuation ability of road network, and secondly determine the evacuation auto numbers on the every routes which is at the target to deliver all the evacuating people from the Origins to Destinations in the shortest time. The experiment area is Dezhou city in Shandong province of China, and an emergency evacuation platform was put up according to the multilevel emergency evacuation model using Google map API and C# as development platform, and the result show us that MEE is promised to be a new methods for emergency evacuation.
Conference paper (PDF, 1642 KB)


Citation: Tang, L., Yang, X., Huang, F., Xu, H., and Li, Q.: A New Models for Emergency Evacuation under the Disaster Condition, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., I-2, 195-202, https://doi.org/10.5194/isprsannals-I-2-195-2012, 2012.

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