Arif Cagdas Aydinoglu, Elif Demir, & Serpil Ates. (2011). Designing a harmonized geo-data model for Disaster Management. In E. Portela L. S. M.A. Santos (Ed.), 8th International Conference on Information Systems for Crisis Response and Management: From Early-Warning Systems to Preparedness and Training, ISCRAM 2011. Lisbon: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: There are problems for managing and sharing geo-data effectively in Turkey. The key to resolving these problems is to develop a harmonized geo-data model. General features of this model are based on ISO/TC211 standards, INSPIRE Data Specifications, and expectations of Turkey National GIS actions. The generic conceptual model components were defined to harmonize geo-data and to produce data specifications. In order to enable semantic interoperability, application schemas were designed for data themes such as administrative unit, address, cadastre/building, hydrographic, topography, geodesy, transportation, and land cover/use. The model, as base and the domain geo-data model, is a starting point to create sector models in different thematic areas. Disaster Management Geo-data Model model was developed as an extension of base geo-data model to manage geo-data collaborate on disaster management activities. This model includes existing geo-data special for disaster management activities and dynamic data collecting during disaster.
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Suthep Chutiratanaphun, Rungsaridh Boonsin, Parida Kuneepong, & Julalux Suttirod. (2005). Land use / land cover change by tsunami 2004 in Thailand: A case study at phi phi Island, Krabi Province and Ban Num Kem Village, Pang Nga Province. In B. C. B. Van de Walle (Ed.), Proceedings of ISCRAM 2005 – 2nd International Conference on Information Systems for Crisis Response and Management (pp. 301–303). Brussels: Royal Flemish Academy of Belgium.
Abstract: Aerial photo interpretation were utilized for monitoring land cover changes with emphasis on tsunami ravaged coastal regions in Phi Phi Island, Krabi Province and Ban Num Kem, Bang Muang, Pang Nga Province areas in the southern peninsula Thailand. All of the images acquired after the Dec 26/2004 tsunami hit, were analyzed and results were compared to image taken before to address the tsunami-affected communities' details. Results of interpretation show different land cover changes in different areas due to the former land cover/land use. It was also showed that aerial photo interpretation data are capable of identification on devastated areas with a high level of accuracy at scale of 1:25, 000. Special attention is given to a few examples of Ban Num Kem village in Takuepa District, Pang Nga Province and Phi Phi Island, Krabi Province.
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Sérgio Freire, & Christoph Aubrecht. (2011). Assessing spatio-temporal population exposure to tsunami hazard in the Lisbon Metropolitan Area. In E. Portela L. S. M.A. Santos (Ed.), 8th International Conference on Information Systems for Crisis Response and Management: From Early-Warning Systems to Preparedness and Training, ISCRAM 2011. Lisbon: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: The coastal region of Lisbon, Portugal, is potentially subject to tsunami hazard. Mapping and assessing tsunami risk requires giving adequate consideration to the population exposure. In the present work we model and map the spatio-temporal distribution of population in the daily cycle and analyze it with a tsunami hazard map to better assess tsunami risk in the Lisbon Metropolitan Area. New high-resolution daytime and nighttime population distribution surfaces are developed using 'intelligent dasymetric mapping' to combine best-available census data and statistics with land use and land cover data. Mobility statistics are considered for mapping daytime distribution. Finally, the population distribution maps are combined with the Tsunami Inundation Susceptibility map to assess potential human exposure to tsunami in daytime and nighttime periods. Results show that a significant amount of population is potentially at risk, and its numbers increase from nighttime to daytime, especially in the zones of high susceptibility.
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Simon Mulwa Mutie, Banci Mati, Hussein Gadain, & Patrick Home. (2005). Land cover change effects on flow regime of mara river. In B. C. B. Van de Walle (Ed.), Proceedings of ISCRAM 2005 – 2nd International Conference on Information Systems for Crisis Response and Management (pp. 237–246). Brussels: Royal Flemish Academy of Belgium.
Abstract: The transboundary Mara River across Kenya and Tanzania and draining in to Lake Victoria has undergone major anthropogenic changes affecting its land cover over the past 50 years. However, these changes have not been quantified in a manner to allow wider scale understanding of the causative factors, their effects and show hot spots that required immediate intervention. To address these issues, a study of the land use/land cover change was done based on interpretation of digital LANDSAT TM and ETM images of 1986 and 2000 respectively with Idrisi Kilimanjaro software. In a separate addition, analyses of hydrological factors was done which involved comparing monthly mean flow hydrographs to assess changes in flow characteristics of the Mara river immediately after the basin forests. The results obtained showed 2.3 % deforestation, 0.7% reforestation, 20.9% of the basin was opened up for agriculture and 7.5% changed to wetlands. Hydrological investigations showed that river flow regimes have changed, with sharp increases in peaks, attenuation of the river hydrographs and reduction in base flows, factors that could not be linked to changes in rainfall amounts and characteristics but related to modifications of the land surface induced by artificial influences of the man in the basin.
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