When flooding occurs, people should be evacuated safely to designated shelters along the optimal routes to minimize serious damages on lives and properties. However, in general, only limited information related to evacuation procedures and using a directional arrow to indicate existing shelters is provided on the evacuation map. Moreover, the evacuation routes leading to nearby shelters are not presented effectively to people in an emergency situation. This paper aimed to provide an approach to generate a flood evacuation cartogram based on an actual evacuation. The proposed time–distance cartogram preserves the topological characteristics by minimizing distortion in transforming the evacuation routes. To empirically evaluate its application, we applied the proposed method to Siheung city in Korea. As a result, optimal shelter and evacuation routes were derived by considering significant factors influencing the actual access to the facilities. Moreover, the flood evacuation cartogram provides a more intuitive visualization than classic topographic maps, by relocating shelters and reshaping the routes intended for evacuation. The suggested method is significant as it provides practical flood evacuation information effectively and intuitively, and the generated cartograms as empirical results also provide helpful insights for more efficient evacuation plans.

Since populations in the developing world have been rapidly increasing, accurately determining the population distribution is becoming more critical for many countries. One of the most widely used population density estimation methods is dasymetric mapping. This can be defined as a precise method for areal interpolation between different spatial units. In most applications of dasymetric mapping, land use and land cover data have been considered as ancillary data for the areal disaggregation process. This research presents an alternative dasymetric approach using area specific ancillary data for hilly area population mapping in a GIS environment. Specifically, we propose a Hilly Area Dasymetric Mapping (HDM) technique by combining topographic variables and land use to better disaggregate hilly area population distribution at fine-grain division of ancillary units. Empirical results for Sri Lanka’s highest mountain range show that the combined dasymetric approach estimates hilly area population most accurately because of the significant association that is found to exist between topographic variables and population distribution within this setting. This research is expected to have significant implications for national and regional planning by providing useful information about actual population distributions in environmentally hazardous and sparsely populated areas.

부동산분석(Journal of Real Estate Analysis)