• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.1
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• pp.152-161
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• 2017

Making precise 3D maps using Mobile Mapping System (MMS) sensors are essential for the development of self-driving cars. This paper conducts research on the extraction of 3D objects around the roads using the point cloud acquired by the MMS Light Detection and Ranging (LiDAR) sensor through the following steps. First, the digital surface model (DSM) is generated using MMS LiDAR data, and then the slope map is generated from the DSM. Next, the 3D objects around the roads are identified using the slope information. Finally, 97% of the 3D objects around the roads are extracted using the morphological filtering technique. This research contributes a plan for the application of automated driving technology by extracting the 3D objects around the roads using spatial information data acquired by the MMS sensor.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.3
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• pp.397-406
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• 2022

Recently, research and development to revitalize smart construction are being actively carried out. Accordingly, 3D mapping technology that digitizes construction site is drawing attention. To create a 3D digital map for construction site a point cloud generation method based on LiDAR(Light detection and ranging) using MMS(Mobile mapping system) is mainly used. The purpose of this study is to analyze the accuracy of MMS LiDAR-based point cloud data. As a result, accuracy of MMS point cloud data was analyzed as dx = 0.048m, dy = 0.018m, dz = 0.045m on average. In future studies, accuracy comparison of point cloud data produced via UAV(Unmanned aerial vegicle) photogrammetry and MMS LiDAR should be studied.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.1
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• pp.1-11
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• 2018

Mapping accurate spatial information is important for constructing three-dimensional (3D) spatial models and managing artificial facilities, and, especially, mapping road centerlines is necessary for constructing accurate road maps. This research developed a semi-automatic methodology for mapping road centerlines using the MMS(Mobile Mapping System) LiDAR(Light Detection And Ranging) point cloud as follows. First, the intensity image was generated from the given MMS LiDAR data through the interpolation method. Next, the line segments were extracted from the intensity image through the edge detection technique. Finally, the road centerline segments were manually selected among the extracted line segments. The statistical results showed that the generated road centerlines had 0.065 m overall accuracy but had some errors in the areas near road signs.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.6_2
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• pp.1145-1153
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• 2023

This study presents the development of pointcloud data integration technology in construction sites via drone photogrammetry and MMS LiDAR. The integration of pointcloud data from drones and MMS technology can provide precise and accurate 3D digital maps of construction sites, which can benefit the development of smart construction and BIM. The advantages of using both drones and MMS technology for pointcloud data acquisition in construction sites are discussed, along with the limitations and challenges of using drone photogrammetry and MMS LiDAR for pointcloud data integration. The results of this study can contribute to the advancement of pointcloud data integration technology in construction sites and improve the efficiency and accuracy of construction projects.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.2
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• pp.183-189
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• 2019

Researches utilizing the fourth industrial revolution technology are being conducted as a breakthrough for improving the earthworker productivity. In order to make the earthwork site smarter, it is necessary to digitize the construction site topography at first. For this purpose, photogrammetry using drones and LiDAR on MMS have been recently used. The purpose of this study is to analyze the accuracy of LiDAR by installation angles for verifying the application of MMS in the construction site. As a result of comparing the coordinates measured by the total station and the LiDAR, a small error of about 1-2 centimeters was shown. It is confirmed that MMS could be well applied to the earthwork site. In addition, there was no significant difference in the accuracy of the acquired coordinates according to the installation angle of the LiDAR, but the shape of the point clouds was different. The larger the installation angle, the better the shape of the site terrain is measured.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.11
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• pp.13-18
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• 2019

The DEM(Digital Elevation Model) is a three-dimensional spatial information that stores the height of the terrain as a numerical value. This means the elevation of the terrain not including the vegetation and the artifacts. The DEM is used in various fields, such as 3D visualization of the terrain, slope, and incense analysis, and calculation of the quantity of construction work. Recently, many studies related to the construction of 3D geospatial information have been conducted, but research related to DEM generation is insufficient. Therefore, in this study, a DEM was constructed using a MMS (Mobile Mapping System), UAV image, and UAV LiDAR (Light Detection And Ranging), and the accuracy evaluation of each result was performed. As a result, the accuracy of the DEM generated by MMS and UAV LiDAR was within ± 4.1cm, and the accuracy of the DEM using the UAV image was ± 8.5cm. The characteristics of MMS, UAV image, and UAV LiDAR are presented through a comparison of data processing and results. The DEM construction using MMS and UAV can be applied to various fields, such as an analysis and visualization of the terrain, collection of basic data for construction work, and service using spatial information. Moreover, the efficiency of the related work can be improved greatly.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.6
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• pp.453-464
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• 2019

Recently, as the demand for 3D geospatial information increases, the importance of rapid and accurate data construction has increased. Although many studies have been conducted to register UAV (Unmanned Aerial Vehicle) imagery based on LiDAR (Light Detection and Ranging) data, which is capable of precise 3D data construction, studies using LiDAR data embedded in MMS (Mobile Mapping System) are insufficient. Therefore, this study compared and analyzed 9 matching algorithms based on feature points for registering reflectance image converted from LiDAR point cloud intensity data acquired from MMS with image data from UAV. Our results indicated that when the SIFT (Scale Invariant Feature Transform) algorithm was applied, it was able to stable secure a high matching accuracy, and it was confirmed that sufficient conjugate points were extracted even in various road environments. For the registration accuracy analysis, the SIFT algorithm was able to secure the accuracy at about 10 pixels except the case when the overlapping area is low and the same pattern is repeated. This is a reasonable result considering that the distortion of the UAV altitude is included at the time of UAV image capturing. Therefore, the results of this study are expected to be used as a basic research for 3D registration of LiDAR point cloud intensity data and UAV imagery.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.2
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• pp.75-84
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• 2018

The purpose of this study is that the low-cost mobile mapping system using INS (Inertial Navigation System) based on MEMS (Micro Electro Mechanical System) could decipher the interpretation of road facility with the accuracy of x, y 0.546m plane error. Even though the MMS (Mobile Mapping System) technology as a new measurement technology has been used vividly to set up geographic information by some world leading surveying equipment manufacturers, the domestic technology is still in its beginning stage. Several domestic institutes and companies tried to catch up the leading technology but they just produced prototypes which needs more stabilization. Through this thesis, we developed low-cost mobile mapping system installed with INS based on MEMS after time synchronizing sensors for MMS such as LiDAR (Light Detection And Ranging), CCD (Charge Coupled Device), GPS/INS (Global Positioning System / Inertial Navigation System) and DMI (Distance Measurement Instrument).

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.3
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• pp.99-106
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• 2019

Technology that cannot be excluded from 4th industry is self-driving sector. The self-driving sector can be seen as a key set of technologies in the fourth industry, especially in the DB sector is getting more and more popular as a business. The DB, which was previously produced and managed in two dimensions, is now evolving into three dimensions. Among the data obtained by Mobile Mapping System () to produce the HD MAP necessary for self-driving, Point Cloud, which is LiDAR data, is used as a DB because it contains accurate location information. However, at present, it is not widely used as a base data for 3D modeling in addition to HD MAP production. In this study, MMS Point Cloud was used to extract facilities around the road and to overlay the location to expand the usability of Point Cloud. Building utility poles and communication poles DB from Point Cloud and comparing road name address base and location, it is believed that the accuracy of the location of the facility DB extracted from Point Cloud is also higher than the basic road name address of the road, It is necessary to study the expansion of the facility field sufficiently.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.507-513
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• 2021

GPR (Ground Penetrating RADAR) is a sensor that inspects the pavement state of roads, sinkholes, and underground pipes. It is widely used in road management. MMS (Mobile Mapping System) creates a detailed and accurate road map of the road surface and its surroundings. If both types of data are built in the same area, it is efficient to construct both ground and underground spatial information at the same time. In addition, since it is possible to grasp the road and important facilities around the road, the location of underground pipelines, etc. without special technology, an intuitive understanding of the site is also possible, which is a useful tool in managing the road or facilities. However, overseas equipment to which this latest technology is applied is expensive and does not fit the domestic situation. LiDAR (Light Detection And Raging) and GNSS/INS (Global Navigation Satellite System / Inertial Navigation System) were synchronized in order to replace overseas developed equipment and to secure original technology to develop domestic equipment in the future, and GPR data was also synchronized to the same GNSS/INS. We developed software that performs georeferencing using the location and attitude information from GNSS/INS at the time of acquiring synchronized GPR data. The experiments were conducted on the road site by dividing the open sky and the non-open sky. The road and surrounding facilities on the ground could be easily checked through the 3D point cloud data acquired through LiDAR. Georeferenced GPR data could also be viewed with a 3D viewer along with point cloud data, and the location of underground facilities could be easily and quickly confirmed through GPR data.