• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.2
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• pp.69-77
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• 2022

The 3D spatial model is an analysis framework for solving urban problems and is used in various fields such as urban planning, environment, land and housing management, and disaster simulation. The utilization of drones that can capture 3D images in a short time at a low cost is increasing for the construction of 3D spatial model. In terms of building a virtual city and utilizing simulation modules, high location accuracy of aerial survey and precision of 3D spatial model function as important factors, so a method to increase the accuracy has been proposed. This study analyzed location accuracy of aerial survey and precision of 3D spatial model by each condition of aerial survey for urban areas where buildings are densely located. We selected Daerim 2-dong, Yeongdeungpo-gu, Seoul as a target area and applied shooting angle, shooting altitude, and overlap rate as conditions for the aerial survey. In this study, we calculated the location accuracy of aerial survey by analyzing the difference between an actual survey value of CPs and a predicted value of 3D spatial Model. Also, We calculated the precision of 3D spatial Model by analyzing the difference between the position of Point cloud and the 3D spatial Model (3D Mesh). As a result of this study, the location accuracy tended to be high at a relatively high rate of overlap, but the higher the rate of overlap, the lower the precision of 3D spatial model and the higher the shooting angle, the higher precision. Also, there was no significant relationship with precision. In terms of baseline-height ratio, the precision tended to be improved as the baseline-height ratio increased.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.2
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• pp.1-11
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• 2023

This study intended to develop a technique for quantitatively and 3-dimensionally predicting the potential failure zone and impulse that may occur when trees are fall down. The main outcomes of this study are as follows. First, this study established the potential failure zone and impulse calculation formula in order to quantitatively calculate the risks generated when trees are fallen down. When estimating the potential failure zone, the calculation was performed by magnifying the height of trees by 1.5 times, reflecting the likelihood of trees falling down and slipping. With regard to the slope of a tree, the range of 360° centered on the root collar was set in the case of trees that grow upright and the range of 180° from the inclined direction was set in the case of trees that grow inclined. The angular momentum was calculated by reflecting the rotational motion from the root collar when the trees fell down, and the impulse was calculated by converting it into the linear momentum. Second, the program to calculate a potential failure zone and impulse was developed using Rhino3D and Grasshopper. This study created the 3-dimensional models of the shapes for topography, buildings, and trees using the Rhino3D, thereby connecting them to Grasshopper to construct the spatial information. The algorithm was programmed using the calculation formula in the stage of risk calculation. This calculation considered the information on the trees' growth such as the height, inclination, and weight of trees and the surrounding environment including adjacent trees, damage targets, and analysis ranges. In the stage of risk inquiry, the calculation results were visualized into a three-dimensional model by summarizing them. For instance, the risk degrees were classified into various colors to efficiently determine the dangerous trees and dangerous areas.