E3S Web Conf.
Volume 125, 2019The 4th International Conference on Energy, Environment, Epidemiology and Information System (ICENIS 2019)
|Number of page(s)||7|
|Section||Culture and Environment Development in Coastal Community|
|Published online||28 October 2019|
An Evaluation of Tsunami Hazard Modeling in Gunungkidul Coastal Area using UAV Photogrammetry and GIS. Case Study: Drini Coastal Area
1 Dept. of Environmental Geography, Faculty of Geography, Universitas Gadjah MadaYogyakarta, Indonesia
2 Dept. of Geographic Information Science, Faculty of Geography, Universitas Gadjah Mada, Yogyakarta, Indonesia
3 Master Program in Planning and Management of Coastal Area and Watershed, Universitas Gadjah Mada, Yogyakarta, Indonesia
* Corresponding author: email@example.com
In recent years, Tourism activities in Gunungkidul Coastal Area rapidly increased. A large number of tourists visiting the coast considered as elements at risk that are exposed to tsunami hazards. Disaster infrastructures provided by the government e.g. hazard maps, evacuation routes, and locations for assembly points are inadequate. The tsunami inundation models provided by the government are based on national topographic maps (RBI), resulting in inaccurate models. DEM generation using UAV Photogrammetry produces high spatial resolution data that results in more accurate tsunami inundation model. The results of the model using UAV photogrammetry are also capable of producing several inundation scenarios and determine the safe areas that can be used for temporary evacuation sites. The use of UAV photogrammetry for tsunami inundation models provides many advantages including low cost and accurate model results. Evaluation of hazard maps and assembly points using UAV Photogrammetry modeling lead to more effective and less time-consuming on the evacuation process.
Key words: Unmanned Aerial Vehicle / Hazard / Tsunami / Loss Estimation
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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