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Designing a spatial planning support system for rapid building damage survey after an earthquake: the case of Bogotá D.C., Colombia

Contreras Mojica, Diana 2009. Designing a spatial planning support system for rapid building damage survey after an earthquake: the case of Bogotá D.C., Colombia. MScD Thesis, Faculty of Geo-Information Science and Earth Observation (ITC) - University of Twente.

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Ten years ago, in January 1999, an earthquake with a magnitude of 6.2 on the Richter scale and with a depth of 10 km had shaken an estimated area of 1.360 square km in the Eje Cafetero, Tolima and Valle del Cauca departments in Colombia. Another, strong aftershock of magnitude 5.8 on Richter scale was registered, followed by others with reducing intensity sometimes producing more damage than the first tremor. Eventually, there were 985 casualties in addition to the 4.517 injuries in a period of 3 days. It was the first time that a building damage survey was carried out in Colombia, in spite that it was an important step and seen as a major improvement from previous disasters in Colombia, some logistic problems were witnessed. These included houses being visited twice or more because of errors in the allocation of the inspectors; delays to have the information collected, due to the lack of trained people and people to type the information, besides absence of standard procedure criteria to assess the damage in the buildings, etc. Bogotá D.C. (Colombia), is located on a medium hazard seismic zone, and it has not experienced any strong earthquake since 1928. Taking this into account, the Major has allocated funds in seismic hazard research, loss estimation scenarios and preparedness. Taking into account the risk condition, the data available and the preparedness level, the importance to design a Spatial Planning Support System-SPSS to support the building damage survey after an earthquake became visible and evident. The model in the present research is built on by three sub-models aiming to estimate the number of trained people required, their allocation, the ways to manage and map the information before, during and after an earthquake. The model assumes that the inspection area is the residential area in a pre-defined range of damage, and according to this output the model allows to estimate the number of parcels to inspect for every seismic scenario. The combination of the number of parcels to inspect, the inspections times per parcel, the operational times and the control ranges will be addressed by the first model. To allocate the trained people, five methods with different levels of accuracy in their results were applied: Average number of parcels or blocks, Euclidean allocation, multiple-ring-buffer, network analysis (service area), and route allocation. All the information about trained people and zone allocation, besides all the information required to respond in an emergency must be collected, updated and shared in order to have indicators in the right time to all the activities that imply the disaster management. The results show wide ranges of values that can be utilized in the preparedness or in the response phase according to the budget and the availability of trained people. The allocation methods can be used according to the data that every city has, but the highest level of accuracy come from the route allocation method. The data must be available, updated and accessible to all the entities involved in the emergency response task, before, during and after the earthquake, due to these reasons the research recommends the use and implementation of a Spatial Data Infrastructure - SDI to manage the information.

Item Type: Thesis (MScD)
Date Type: Published Online
Status: Unpublished
Schools: Earth and Environmental Sciences
Subjects: G Geography. Anthropology. Recreation > G Geography (General)
G Geography. Anthropology. Recreation > GE Environmental Sciences
Funders: Faculty of Geo-Information Science and Earth Observation (ITC) - University of Twente
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Date of First Compliant Deposit: 5 August 2021
Last Modified: 05 Aug 2021 09:11

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