Development of a method for calculating overground-openness and underground-openness with high precision based on the digital elevation model data

Tomohiro Andoh; Hiroaki Sakamoto; Toshikazu Samura; Katsumi Tadamura

doi:10.1117/12.2590845

13 March 2021 Development of a method for calculating overground-openness and underground-openness with high precision based on the digital elevation model data

Tomohiro Andoh, Hiroaki Sakamoto, Toshikazu Samura, Katsumi Tadamura

Author Affiliations +

Proceedings Volume 11766, International Workshop on Advanced Imaging Technology (IWAIT) 2021; 117662Z (2021) https://doi.org/10.1117/12.2590845
Event: International Workshop on Advanced Imaging Technology 2021 (IWAIT 2021), 2021, Online Only

Abstract

Predicting the occurrence of a natural disaster with high accuracy and providing an evacuation warning at the appropriate level are important for reducing any casualties. In the case of a landslide, for example, the behavior of rainwater after falling on the ground needs to be estimated. This estimation requires information on not only the local ground slope but also topographic features such as ridges and valleys. To obtain the latter, a method was previously proposed for using digital elevation model (DEM) data to obtain the overground and underground openness of an area. However, this method is not suitable for high-precision DEM data because it does not allow for dense sampling. To address this problem, this paper proposes a method for calculating the openness that uses a computer graphics technique to reflect the features of high-precision DEM data. The proposed method was applied to both simple-shape artificial terrain data and actual DEM data, and its usefulness was confirmed.

Citation Download Citation

Tomohiro Andoh, Hiroaki Sakamoto, Toshikazu Samura, and Katsumi Tadamura "Development of a method for calculating overground-openness and underground-openness with high precision based on the digital elevation model data", Proc. SPIE 11766, International Workshop on Advanced Imaging Technology (IWAIT) 2021, 117662Z (13 March 2021); https://doi.org/10.1117/12.2590845

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