• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• 제36권2호
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• pp.67-74
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• 2018

This study has proposed a methodology to detect suspicious facilities that occupy national and public land by using the cadastral and digital maps. First, we constructed a spatial database of national & public land based on the cadastral maps by linking its management ledger. Using the PNU (Parcel Number) code as a key field, the data managed by different institutions are integrated into a single spatial information DB (database) and then, the use or nonuse state of each parcel is confirmed on the cadastral map. Next, we explored the suspicious facilities that existed in the unused parcel by utilizing the digital topographical map. Then, the proposed methodology was applied for various regions and tested its feasibility. Through this study, it will be possible to improve the utilization of digital maps and to manage the national and public land efficiently and economically.

• IEMEK Journal of Embedded Systems and Applications
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• 제15권5호
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• pp.215-225
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• 2020

Light detection and ranging (LiDAR) sensors detect the distance of the surrounding environment and objects. Conventional LiDAR sensors require a certain amount of a power because they detect objects by transmitting lasers at a regular interval depending on a constant resolution. The constant power consumption from operating multiple LiDAR sensors is detrimental to autonomous and electric vehicles using battery power. In this paper, we propose two algorithms that improve the inefficient power consumption during the constant operation of LiDAR sensors. LiDAR sensors with algorithms efficiently reduce the power consumption in two ways: (a) controlling the resolution to vary the laser transmission period (T_P) of a laser diode (LD) depending on the vehicle's speed and (b) reducing the static power consumption using a sleep mode depending on the surrounding environment. A proposed LiDAR sensor with a resolution control algorithm reduces the power consumption of the LD by 6.92% to 32.43% depending on the vehicle's speed, compared to the maximum number of laser transmissions (N_x·max). The sleep mode with a surrounding environment-sensing algorithm reduces the power consumption by 61.09%. The proposed LiDAR sensor has a risk factor for 4-cycles that does not detect objects in the sleep mode, but we consider it to be negligible because it immediately switches to an active mode when a change in surrounding conditions occurs. The proposed LiDAR sensor was tested on a commercial processor chip with the algorithm controlling the resolution according to the vehicle's speed and the surrounding environment.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• 제34권5호
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• pp.479-493
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• 2016

LiDAR(Light Detection and Ranging) data acquired from ALS(Airborne Laser Scanner) has been intensively utilized to reconstruct object models. Especially, researches for 3D modeling from LiDAR data have been performed to establish high quality spatial information such as precise 3D city models and true orthoimages efficiently. To reconstruct object models from irregularly distributed LiDAR point clouds, sensor calibration, noise removal, filtering to separate objects from ground surfaces are required as pre-processing. Classification and segmentation based on geometric homogeneity of the features, grouping and representation of the segmented surfaces, topological analysis of the surface patches for modeling, and accuracy assessment are accompanied by modeling procedure. While many modeling methods are based on the segmentation process, this paper proposed to extract key points directly for building modeling without segmentation. The method was applied to simulated and real data sets with various roof shapes. The results demonstrate feasibility of the proposed method through the accuracy analysis.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• 제36권5호
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• pp.395-401
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• 2018

Recently, most of mobile devices are equipped with GNSS (Global Navigation Satellite System). When the GNSS signal is available, it is easy to obtain position information. However, GNSS is not suitable solution for indoor localization, since the signals are normally not reachable inside buildings. A wide varieties of technology have been developed as a solution for indoor localization such as Wi-Fi, beacons, and inertial sensor. With the increased sensor combinations in mobile devices, mobile devices also became feasible to provide a solution, which based on PDR (Pedestrian Dead Reckoning) method. In this study, we utilized the combination of three sensors equipped in mobile devices including accelerometer, digital compass, and gyroscope and applied three representative PDR methods. The proposed methods are done in three stages; step detection, step length estimation, and heading determination and the final indoor localization result was evaluated with terrestrial LiDAR (Light Detection And Ranging) data obtained in the same test site. By using terrestrial LiDAR data as reference ground truth for PDR in two differently designed experiments, the inaccuracy of PDR methods that could not be found by existing evaluation method could be revealed. The firstexperiment included extreme direction change and combined with similar pace size. Second experiment included smooth direction change and irregular step length. In using existing evaluation method which only checks traveled distance, The results of two experiments showed the mean percentage error of traveled distance estimation resulted from three different algorithms ranging from 0.028 % to 2.825% in the first experiment and 0.035% to 2.282% in second experiment, which makes it to be seen accurately estimated. However, by using the evaluation method utilizing terrestrial LiDAR data, the performance of PDR methods emerged to be inaccurate. In the firstexperiment, the RMSEs (Root Mean Square Errors) of x direction and y direction were 0.48 m and 0.41 m with combination of the best available algorithm. However, the RMSEs of x direction and y direction were 1.29 m and 3.13 m in the second experiment. The new evaluation result reveals that the PDR methods were not effective enough to find out exact pedestrian position information opposed to the result from existing evaluation method.

• Journal of Korean Society of Forest Science
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• 제94권6호
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• pp.431-440
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• 2005

Location, height and clear-length of individual tree can be measured directly by LiDAR Remote Sensing, and dbh(diameter at breast height) can be estimated indirectly by tree height measured by LiDAR. In addition, stand volume and stand biomass are computed from estimated growth factors. In this study, each estimated growth factor was compared to the field measurements to validate accuracy. The coefficient of determination of total tree heights was 0.66 for total trees, 0.68 for Pinus koraiensis, 0.66 for Larix leptolepis and 0.60 for Quercus spp. The coefficient of determination of clear-length was 0.79 for total trees, 0.73 for Pinus koraiensis, 0.79 for Larix leptolepis, 0.68 for Quercus spp. The coefficient of determination of dbh predicted was 0.73 for Pinus koraiensis, 0.73 for Larix leptolepis and 0.85 for Quercus spp. Moreover The coefficient of determination of basal area was 0.82 for Pinus koraiensis, 0.92 for Larix leptolepis and 0.95 for Quercus spp. Biomass per ha computed by growth factor using LiDAR was 40,306 dm/ha for Pinus koraiensis, 94,150 tdm/ha for Larix leptolepis and 94,481 tdm/ha for Quercus spp. by species.

• Korean Journal of Remote Sensing
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• 제28권5호
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• pp.573-586
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• 2012

Point clouds acquired by a LIDAR(Light Detection And Ranging, also LADAR) system often contain erroneous points called outliers seeming not to be on physical surfaces, which should be carefully detected and eliminated before further processing for applications. Particularly in case of LIDAR systems employing with a Gieger-mode array detector (GmFPA) of high sensitivity, the outlier ratio is significantly high, which makes existing algorithms often fail to detect the outliers from such a data set. In this paper, we propose a method to discriminate outliers from a point cloud with high outlier ratio acquired by a GmFPA LIDAR system. The underlying assumption of this method is that a meaningful targe surface occupy at least two adjacent pixels and the ranges from these pixels are similar. We applied the proposed method to simulated LIDAR data of different point density and outlier ratio and analyzed the performance according to different thresholds and data properties. Consequently, we found that the outlier detection probabilities are about 99% in most cases. We also confirmed that the proposed method is robust to data properties and less sensitive to the thresholds. The method will be effectively utilized for on-line realtime processing and post-processing of GmFPA LIDAR data.

• Toxicological Research
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• 제27권2호
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• pp.125-131
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• 2011

Through the present study, we produced a monoclonal antibody against aflatoxin B1 (AFB1) using AFB1-carboxymethoxylamine BSA conjugates. One clone showing high binding ability was selected and it was applied to develop a direct competitive ELISA system. The epitope densities of AFB1-CMO against BSA and KLH were about 1 : 6 and 1 : 545, respectively. The monoclonal antibody (mAb) from cloned hybridoma cell was the IgG1 subclass with ${\lambda}$-type light chains. The $IC_{50}s$ of the monoclonal antibody developed for AFB1, AFB2, AFG1 and AFG2 were 4.36, 7.22, 6.61 and 29.41 ng/ml, respectively, based on the AFB1-KLH coated ELISA system and 15.28, 26.62, 32.75 and 56.67 ng/ml, respectively, based on the mAb coated ELISA. Cross-relativities of mAb to AFB1 for AFB2, AFG1 and AFG2 were 60.47, 65.97 and 14.83% in the AFB1-KLH coated ELISA, and 59.41, 46.66 and 26.97% in the mAb coated ELISA, respectively. Quantitative calculations for AFB1 from the AFB1-Ab ELISA and AFB1-Ag ELISA ranged from 0.25 to 25 ng/ml ($R^2$ > 0.99) and from 1 to 100 ng/ml ($R^2$ > 0.99), respectively. The intra- and inter-assay precision CVs were < 10% in both ELISA assay, representing good reproducibility of developed assay. Recoveries ranged from 79.18 to 91.27%, CVs ranged from 3.21 to 7.97% after spiking AFB1 at concentrations ranging from 5 to 50 ng/ml and following by extraction with 70% methanol solution in the Ab-coated ELISA. In conclusion, we produced a group specific mAb against aflatoxins and developed two direct competitive ELISAs for the detection of AFB1 in feeds based on a monoclonal antibody developed.

• Journal of Information Processing Systems
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• 제14권6호
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• pp.1445-1456
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• 2018

Environment perception and three-dimensional (3D) reconstruction tasks are used to provide unmanned ground vehicle (UGV) with driving awareness interfaces. The speed of obstacle segmentation and surrounding terrain reconstruction crucially influences decision making in UGVs. To increase the processing speed of environment information analysis, we develop a CPU-GPU hybrid system of automatic environment perception and 3D terrain reconstruction based on the integration of multiple sensors. The system consists of three functional modules, namely, multi-sensor data collection and pre-processing, environment perception, and 3D reconstruction. To integrate individual datasets collected from different sensors, the pre-processing function registers the sensed LiDAR (light detection and ranging) point clouds, video sequences, and motion information into a global terrain model after filtering redundant and noise data according to the redundancy removal principle. In the environment perception module, the registered discrete points are clustered into ground surface and individual objects by using a ground segmentation method and a connected component labeling algorithm. The estimated ground surface and non-ground objects indicate the terrain to be traversed and obstacles in the environment, thus creating driving awareness. The 3D reconstruction module calibrates the projection matrix between the mounted LiDAR and cameras to map the local point clouds onto the captured video images. Texture meshes and color particle models are used to reconstruct the ground surface and objects of the 3D terrain model, respectively. To accelerate the proposed system, we apply the GPU parallel computation method to implement the applied computer graphics and image processing algorithms in parallel.

• Korean Journal of Agricultural Science
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• 제49권3호
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• pp.483-493
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• 2022

It is important to improve the efficiency of plant breeding and crop yield to fulfill increasing food demands. In plant phenotyping studies, the capability to correlate morphological traits such as plant height, stem diameter, leaf length, leaf width, leaf angle and size of panicle of the plants has an important role. However, manual phenotyping of plants is prone to human errors and is labor intensive and time-consuming. Hence, it is important to develop techniques that measure plant phenotypic traits accurately and rapidly. The aim of this study was to determine the feasibility of point cloud data based on a 3D light detection and ranging (LiDAR) system for plant phenotyping. The obtained results were then verified through manually acquired data from the sorghum samples. This study measured the plant height, plant crown diameter and the panicle height and diameter. The R² of each trait was 0.83, 0.94, 0.90, and 0.90, and the root mean square error (RMSE) was 6.8 cm, 1.82 cm, 5.7 mm, and 7.8 mm, respectively. The results showed good correlation between the point cloud data and manually acquired data for plant phenotyping. The results indicate that the 3D LiDAR system has potential to measure the phenotypes of sorghum in a rapid and accurate way.

• Coupled systems mechanics
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• 제11권6호
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• pp.505-524
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• 2022

Floods represent extreme hydrological phenomena that affect populations, environment, social, political, and ecological systems. After the catastrophic floods that have hit Europe and the World in recent decades, the flood problem has become more current. At the EU level, a legal framework has been put in place with the entry into force of Directive 2007/60/EC on Flood Risk Assessment and Management (Flood Directive). Two years after the entry into force of the Floods Directive, Bosnia and Herzegovina (B&H), has adopted a Regulation on the types and content of water protection plans, which takes key steps and activities under the Floods Directive. The "Methodology for developing flood hazard and risk maps" (Methodology) was developed for the territory of Bosnia and Herzegovina, following the methodology used in the majority of EU member states, but with certain modifications to the country's characteristics. Accordingly, activities for the preparation of the Preliminary Flood Risk Assessment for each river basin district were completed in 2015 for the territory of Bosnia and Herzegovina. Activities on the production of hazard maps and flood risk maps are in progress. The results of probable climate change impact model forecasts should be included in the preparation of the Flood Risk Management Plans, which is the subsequent phase of implementing the Flood Directive. By the foregoing, the paper will give an example of the development of the hydrodynamic model of the Zujevina River, as well as the development of hazard and risk maps. Hazard and risk maps have been prepared for medium probability floods of 1/100 as well as for high probability floods of 1/20. The results of LiDAR (Light Detection and Ranging) recording were used to create a digital terrain model (DMR). It was noticed that there are big differences between the flood maps obtained by recording LiDAR techniques in relation to the previous flood maps obtained using georeferenced topographic maps. Particular attention is given to explaining the Methodology applied in Bosnia and Herzegovina.