• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.3
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• pp.78-95
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• 2011

This study has developed various DEMs with different spatial resolutions using many different interpolation methods with the aid of a 1:5,000 digital map. In addition, this study has evaluated the vertical accuracy of various DEMs constructed by check point data obtained from the network RTK GPS survey. The obtained results suggest that a DEM developed from the TIN-based Terrain method performs well in evaluating height restriction of buildings in a flying safety area considering general RMSE values, land-type RMSE values and profile evaluation results, etc. And, it has been found that three meters is the right spatial resolution for a DEM in evaluating height restriction of buildings in a flying safety area. Meanwhile, elevation values obtained by the DEM are not point estimation values but interval estimation values. This can be used to check whether the height of buildings in the vicinity of an airfield violates height limitation values of the area. To check whether the height of buildings measured in interval estimation values violates height limitation values of the area, this study has adopted three steps: 1) high probability of violation, 2) low probability of violation, 3) inconclusiveness about the violation. The obtained results will provide an important basis for developing a GIS related to the evaluation of height restriction of buildings in the vicinity of an airfield. Furthermore, although results are limited to the study area, the vertical accuracy values of the DEM constructed from a two-dimensional digital map may provide useful information to researchers who try to use DEMs.

• Journal of the Korean Geographical Society
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• v.42 no.4
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• pp.488-505
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• 2007

The purposes of this research are twofold; 1) to verify spatial differences of tectonic movement using the spatial distribution of earthquakes, and 2) to infer mechanisms that generate spatial accumulation patterns of earthquakes in the Korean Peninsula. The first part of this sequential paper (Park, 2007) argues that the Korean Peninsula consists of four geostructural regions in which tectonic deformation and consequent geomorphological development patterns are different from each other Since this conclusion has been made by terrain analyses alone, it is necessary to verify this suggestion using other independent geophysical data. Because earthquakes are results of movement and deformation of land masses moving in different directions, the distribution of earthquake epicenters may be used to identify the direction and rates of land mass movement. This paper first analysed the spatial distribution of earthquakes using spatial statistics, and then results were compared with the spatial arrangement of geostructural regions. The spatial distribution of earthquakes in the Korean Peninsula can be summarized as the followings; firstly, the intensity of earthquakes shows only weak spatial dependency, and shows large difference even at adjacent regions. Secondly, the epicenter distribution has a clear spatial accumulation pattern, even though the intensity of earthquake shows a random pattern. Thirdly, the high density area of earthquakes shows a clear 'L' shape, passing through Pyeongannam-do, centered at Pyeongyang, and Hwanghae-do, Seosan and Pohang. The correlation coefficient between the density of earthquakes and distance from geostructral region boundaries is much higher than those between the density of fault lines and distance from tectonic division boundaries. Since fault lines and tectonic divisions in the Korean Peninsula are the results of long-term geological development, there is an apparent scale discrepancy to find significant correlations with earthquakes. This result verifies the research hypothesis that the Korean Peninsula is divided into four geostructral regions in which each has its own moving direction and spatial deformation characteristics. The existence of geostructural regions is also supported by the movement parrerns of land masses estimated from the GPS measurements. This conclusion is expected to provide a new perspective to understand the geomorphological developments and the earthquake occurrences in the Korean Peninsula.

• Journal of the Korean Institute of Landscape Architecture
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• v.45 no.1
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• pp.52-62
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• 2017

Overseas landscape practices have already benefited from the awareness of BIM while landscape-related organizations are encouraging its use and the number of landscape projects using BIM is increasing. However, since BIM has not yet been introduced in the domestic field, this study investigated and analyzed overseas landscape projects and discussed the positive effects and implementation of BIM. For this purpose, landscape projects were selected to show three effects of BIM: improvement of design work efficiency, building of a platform for cooperation, and performance of topography design. These three projects were analyzed across four aspects of implementation methods: landscape information, 3D modeling, interoperability, and visualization uses of BIM. First, in terms of landscape information, a variety of building information was constructed in the form of 3D libraries or 2D CAD format from detailed landscape elements to infrastructure. Second, for 3D modeling, a landscape space including simple terrain and trees was modeled with Revit while elaborate and complex terrain was modeled with Maya, a professional 3D modeling tool. One integrated model was produced by periodically exchanging, reviewing, and finally combining each model from interdisciplinary fields. Third, interoperability of data from different fields was achieved through the unification of file formats, conversion of differing formats, or compliance with information standards. Lastly, visualized 3D models helped coordination among project partners, approval of design, and promotion through public media. Reviewing of the case studies shows that BIM functions as a process to improve work efficiency and interdisciplinary collaboration, rather than simply as a design tool. It has also verified that landscape architects could play an important role in integrated projects using BIM. Just as the introduction of BIM into the architecture, engineering and construction industries saw great benefits and opportunities, BIM should also be introduced to landscape architecture.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.3
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• pp.237-246
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• 2020

Recently, as high resolution satellites data have been serviced, frequent DSM (Digital Surface Model) generation over urban areas has been possible. In addition, it is possible to detect changes using a high-resolution DSM at building level such that various methods of building change detection using DSM have been studied. In order to detect building changes using DSM, we need to generate a DSM using a stereo satellite image. The change detection method using D-DSM (Differential DSM) uses the elevation difference between two DSMs of different dates. The D-DSM method has difficulty in applying a precise vertical threshold, because between the two DSMs may have elevation errors. In this study, we focus on the urban structure change detection using D-nDSM (Differential nDSM) based on nDSM (Normalized DSM) that expresses only the height of the structures or buildings without terrain elevation. In addition, we attempted to reduce noise using a morphological filtering. Also, in order to improve the roadside buildings extraction precision, we exploited the urban road network extraction from nDSM. Experiments were conducted for high-resolution stereo satellite images of two periods. The experimental results were compared for D-DSM, D-nDSM, and D-nDSM with road extraction methods. The D-DSM method showed the accuracy of about 30% to 55% depending on the vertical threshold and the D-nDSM approaches achieved 59% and 77.9% without and with the morphological filtering, respectively. Finally, the D-nDSM with the road extraction method showed 87.2% of change detection accuracy.

• Korean Journal of Remote Sensing
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• v.27 no.4
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• pp.481-494
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• 2011

Investigation of the $CO_2$ exchange between biosphere and atmosphere at regional, continental, and global scales can be directed to combining remote sensing with carbon cycle process to estimate vegetation productivity. NASA Earth Observing System (EOS) currently produces a regular global estimate of gross primary productivity (GPP) and annual net primary productivity (NPP) of the entire terrestrial earth surface at 1 km spatial resolution. While the MODIS GPP algorithm uses meteorological data provided by the NASA Data Assimilation Office (DAO), the sub-pixel heterogeneity or complex terrain are generally reflected due to coarse spatial resolutions of the DAO data (a resolution of $1{\circ}\;{\times}\;1.25{\circ}$). In this study, we estimated inputs retrieved from MODIS products of the AQUA and TERRA satellites with 5 km spatial resolution for the purpose of finer GPP and/or NPP determinations. The derivatives included temperature, VPD, and solar radiation. Seven AmeriFlux data located in the Corn Belt region were obtained to use for evaluation of the input data from MODIS. MODIS-derived air temperature values showed a good agreement with ground-based observations. The mean error (ME) and coefficient of correlation (R) ranged from $-0.9^{\circ}C$ to $+5.2^{\circ}C$ and from 0.83 to 0.98, respectively. VPD somewhat coarsely agreed with tower observations (ME = -183.8 Pa ~ +382.1 Pa; R = 0.51 ~ 0.92). While MODIS-derived shortwave radiation showed a good correlation with observations, it was slightly overestimated (ME = -0.4 MJ $day^{-1}$ ~ +7.9 MJ $day^{-1}$; R = 0.67 ~ 0.97). Our results indicate that the use of inputs derived MODIS atmosphere and land products can provide a useful tool for estimating crop GPP.

• Korean Journal of Heritage: History & Science
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• v.56 no.4
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• pp.54-70
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• 2023

Surveys and studies on cultural assets using LiDAR measurement are already active overseas. Recently, awareness of the advantages and availability of LiDAR measurement has increased in Korea, and cases of using it for surveys of cultural assets are gradually increasing. However, it is usually restricted to surveys of mountain fortresses and is not actively used for surveys of ancient tombs yet. Therefore, this study intends to emphasize the need to secure fundamental data from LiDAR measurement for the era from the Three Kingdoms to Unified Silla in which recovery, maintenance, etc., in addition to the actual surveys, are unfulfilled due to the sites being mainly distributed in mountainous areas. For this, LiDAR measurement was executed for the area of Jangsan Ancient Tombs and Chunghyo-dong Ancient Tombs in Seoak-dong, Gyeongju, to review the distribution and geographical conditions of ancient tombs. As a result, in the Jangsan Ancient Tombs, in which a precision archaeological (measurement) survey was already executed, detailed geographic information and distribution conditions could be additionally identified, which could not be known only with the layout indicated by the topographic map of the existing report. Also, in the Chunghyo-dong Ancient Tombs, in which an additional survey was not conducted after 10 tombs were found during the Japanese colonial period, the location of the ancient tombs initially excavated was accurately identified, and the status and additional information was acquired, such as on the conditions of ancient tombs not surveyed. Such information may also be used as fundamental data for the preservation and maintenance of future ancient tombs in addition to the survey and study of the ancient tombs themselves. LiDAR measurement is most effective for identifying the condition of ancient tombs in mountainous areas where observation is difficult or access is limited due to the forest zone. It may be executed before on-site surveys, such as archaeological surveys, to secure data with high availability as prior surveys or pre-surveys. Therefore, it is necessary to secure fundamental data from LiDAR measurement in future surveys of ancient tombs and to establish a survey and maintenance/utilization plan based on this. To establish survey/study and preservation/maintenance measures for ancient tombs located in mountainous areas, a precision archaeological survey is currently executed to draw up a distribution chart of ancient tombs. If LiDAR measurement data is secured before this and used, a more effective and accurate distribution chart can be drawn up, and the actual conditions can be identified. Also, most omissions or errors in information can be prevented in on-site surveys of large regions. Therefore, it is necessary to accumulate fundamental data by actively using LiDAR measurement in future surveys of ancient tombs.

• Korean Journal of Remote Sensing
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• v.40 no.4
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• pp.351-361
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• 2024

Satellite imagery contains various elements such as clouds, cloud shadows, and terrain shadows. Accurately identifying and eliminating these factors that complicate satellite image analysis is essential for maintaining the reliability of remote sensing imagery. For this reason, satellites such as Landsat-8, Sentinel-2, and Compact Advanced Satellite 500-1 (CAS500-1) provide Usable Data Masks(UDMs)with images as part of their Analysis Ready Data (ARD) product. Precise detection of clouds and their shadows is crucial for the accurate construction of these UDMs. Existing cloud and their shadow detection methods are categorized into threshold-based methods and Artificial Intelligence (AI)-based methods. Recently, AI-based methods, particularly deep learning networks, have been preferred due to their advantage in handling large datasets. This study aims to analyze the applicability of constructing UDMs for high-resolution satellite images through deep learning-based cloud and their shadow detection using open-source datasets. To validate the performance of the deep learning network, we compared the detection results generated by the network with pre-existing UDMs from Landsat-8, Sentinel-2, and CAS500-1 satellite images. The results demonstrated that high accuracy in the detection outcomes produced by the deep learning network. Additionally, we applied the network to detect cloud and their shadow in KOMPSAT-3/3A images, which do not provide UDMs. The experiment confirmed that the deep learning network effectively detected cloud and their shadow in high-resolution satellite images. Through this, we could demonstrate the applicability that UDM data for high-resolution satellite imagery can be constructed using the deep learning network.

• Journal of Korean Society of Transportation
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• v.19 no.4
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• pp.35-47
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• 2001

Traffic represents one of the largest sources of primary air pollutants in urban area. As a consequence. numerous abatement strategies are being pursued to decrease the ambient concentration of pollutants. A characteristic of most of the these strategies is a requirement for accurate data on both the quantity and spatial distribution of emissions to air in the form of an atmospheric emission inventory database. In the case of traffic pollution, such an inventory must be compiled using activity statistics and emission factors for vehicle types. The majority of inventories are compiled using passive data from either surveys or transportation models and by their very nature tend to be out-of-date by the time they are compiled. The study of current trends are towards integrating urban traffic control systems and assessments of the environmental effects of motor vehicles. In this study, a methodology of motor vehicle emission calculation by using real-time traffic data was studied. A methodology for estimating emissions of CO at a test area in Seoul. Traffic data, which are required on a street-by-street basis, is obtained from induction loops of traffic control system. It was calculated speed-related mass of CO emission from traffic tail pipe of data from traffic system, and parameters are considered, volume, composition, average velocity, link length. And, the result was compared with that of a method of emission calculation by VKT(Vehicle Kilometer Travelled) of vehicles of category.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.4
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• pp.363-373
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• 2020

During last decades numerous studies generating orthoimage have been carried out. Traditional methods require exterior orientation parameters of aerial images and precise 3D object modeling data and DTM (Digital Terrain Model) to detect and recover occlusion areas. Furthermore, it is challenging task to automate the complicated process. In this paper, we proposed a new concept of true orthoimage generation using DL (Deep Learning). DL is rapidly used in wide range of fields. In particular, GAN (Generative Adversarial Network) is one of the DL models for various tasks in imaging processing and computer vision. The generator tries to produce results similar to the real images, while discriminator judges fake and real images until the results are satisfied. Such mutually adversarial mechanism improves quality of the results. Experiments were performed using GAN-based Pix2Pix model by utilizing IR (Infrared) orthoimages, intensity from LiDAR data provided by the German Society for Photogrammetry, Remote Sensing and Geoinformation (DGPF) through the ISPRS (International Society for Photogrammetry and Remote Sensing). Two approaches were implemented: (1) One-step training with intensity data and high resolution orthoimages, (2) Recursive training with intensity data and color-coded low resolution intensity images for progressive enhancement of the results. Two methods provided similar quality based on FID (Fréchet Inception Distance) measures. However, if quality of the input data is close to the target image, better results could be obtained by increasing epoch. This paper is an early experimental study for feasibility of DL-based true orthoimage generation and further improvement would be necessary.

• Journal of Navigation and Port Research
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• v.37 no.1
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• pp.71-77
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• 2013

Most of the maritime accidents are the crash that occurred by complex coastal terrain, increased maritime traffic and frequent weather changes. Therefore, transportation safety is exactly determined using accurate environmental informations, but if informations are inaccurate or insufficient, accident risk can be increased. Therefore, ship need the system that can accurately generate transportation safety information. This paper proposes the transportation safety system and performance evaluation in the real environment. The proposed system includes database of environment informations and navigation algorithm using PPP method to estimate the accurate ship position. Therefore, this system can accurately calculate distance or freeboard between ship with other factors. Futhermore, when weather is deteriorated, crew can sail with database based 3-D monitoring module in the transportation safety system. To verify the function and performance, data of Kyungin ARA waterway and ferry is used to evaluation.