• Korean Journal of Remote Sensing
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• v.36 no.1
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• pp.15-27
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• 2020

Accurate knowledge of land use/land cover (LULC) features and their relative changes over upon the time are essential for sustainable urban management. Urban sprawl growth has been always also a worldwide concern that needs to carefully monitor particularly in a developing country where unplanned building constriction has been expanding at a high rate. Recently, remotely sensed imageries with a very high spatial/spectral resolution and state of the art machine learning approaches sent the urban classification and growth monitoring to a higher level. In this research, we classified the Quickbird satellite imagery by object-based image analysis of Dempster-Shafer (OBIA-DS) for the years of 2002 and 2015 at Karbala-Iraq. The real LULC changes including, residential sprawl expansion, amongst these years, were identified via change detection procedure. In accordance with extracted features of LULC and detected trend of urban pattern, the future LULC dynamic was simulated by using land transformation model (LTM) in geospatial information system (GIS) platform. Both classification and prediction stages were successfully validated using ground control points (GCPs) through accuracy assessment metric of Kappa coefficient that indicated 0.87 and 0.91 for 2002 and 2015 classification as well as 0.79 for prediction part. Detail results revealed a substantial growth in building over fifteen years that mostly replaced by agriculture and orchard field. The prediction scenario of LULC sprawl development for 2030 revealed a substantial decline in green and agriculture land as well as an extensive increment in build-up area especially at the countryside of the city without following the residential pattern standard. The proposed method helps urban decision-makers to identify the detail temporal-spatial growth pattern of highly populated cities like Karbala. Additionally, the results of this study can be considered as a probable future map in order to design enough future social services and amenities for the local inhabitants.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.2
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• pp.107-116
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• 2012

We investigated the accuracy in three dimensional geo-positioning derived by four high resolution satellite images acquired by two different sensors using the vendor-provided rational polynomial coefficients(RPC) based block adjustment in this research. We used two in-track stereo pairs of GeoEye-1 and WorldView-2 satellite and DGPS surveying data. In this experiment, we analyzed accuracies of RPC block adjustment models of two kinds of homogeneous stereo pairs, four kinds of heterogeneous stereo pairs, three 3 triplet image pairs, and one quadruplet image pair separately. The result shows that the accuracies of the models are nearly same. The accuracy without any GCPs reaches about CEP(90) 2.3m and LEP(90) 2.5m and the accuracy with single GCP is about CEP(90) 0.3m and LEP(90) 0.5m.

• Journal of Korean Society for Geospatial Information Science
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• v.11 no.2 s.25
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• pp.29-37
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• 2003

An approach is described for automatic measuring of GCP's image coordinates from SPOT imagery and focused on the fulfillment an automatic orientation of satellite images. For the orientation of a stereopair of digital images, firstly, GCP(Ground Control Point) should be selected and then the work for measuring of image coordinates correspond to GCPs is required. In this study, we propose the method for extracting the GCP's image coordinates automatically using an image patch for control points and auxiliary points matching. For the evaluation of measurement accuracy, a comparison between points those are extracted manually and automatically by a proposed method have made. Finally, we shows the feasibility of automatic image coordinates measurment by applying in stereo modeling for SPOT images.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.4
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• pp.3-10
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• 2010

In this study, the orbit-based sensor modeling is applied to the digital plotting and the accuracy of digital plotting is analyzed. The KOMPSAT-2 satellite image with orbit-attitude model is used for the analysis. The precise sensor modeling with various combination of parameters is performed for the stereo satellite image. In addition, we analyze the error range of ground control points by applying the result of stereo modeling to digital survey system. According to the result, it is possible to produce digital map using stereo image with a small number of GCPs when the orbit-based sensor modeling for KOMPSAT-2 is applied. This means that it is suitable for the generation of digital map on a scale of 1/5,000 to 1/25,000 considering the resolution of KOMPSAT-2 image.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.2
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• pp.249-260
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• 2009

The georeferencing accuracy of the sensory data acquired by an aerial monitoring system heavily depends on the performance of the GPS/IMU mounted on the system. The employment of a high performance but expensive GPS/IMU unit causes to increase the developmental cost of the overall system. In this study, we simulate the images and GPS/IMU data acquired by an UAV-based aerial monitoring system using an inexpensive integrated GPS/IMU of a MEMS type, and perform the image georeferencing by applying the aerial triangulation to the simulated sensory data without any GCP. The image georeferencing results are then analyzed to assess the accuracy of the estimated exterior orientation parameters of the images and ground points coordinates. The analysis indicates that the RMSEs of the exterior orientation parameters and ground point coordinates is significantly decreased by about 90% in comparison with those resulted from the direct georeferencing without the aerial triangulation. From this study, we confirmed the high possibility to develop a low-cost real-time aerial monitoring system.

• Korean Journal of Remote Sensing
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• v.30 no.5
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• pp.617-625
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• 2014

The Rational Function Model has been used as a replacement sensor model in most commercial photogrammetric systems due to its capability of maintaining the accuracy of the physical sensor models. Although satellite images with rational polynomial coefficients have been used to determine three-dimensional position, it has limitations in the accuracy for large scale topographic mapping. In this study, high resolution stereo satellite images, QuickBird-2, were used to investigate how much the three-dimensional position accuracy was affected by the No. of ground control points, polynomial order, and distribution of GCPs. As the results, we can confirm that these experiments satisfy the accuracy requirements for horizontal and height position of 1:25,000 map scale.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.533-540
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• 2021

High-resolution satellite images have high potential to acquire geospatial information over inaccessible areas such as Antarctica. Reference data are often required to increase the positional accuracy of the satellite data but the data are not available in many inland areas in Antarctica. Therefore this paper presents a multi-image RPCs (Rational Polynomial Coefficients) sensor modeling without any ground controls or reference data. Conjugate points between multi-images are extracted and used for the multi-image sensor modeling. The experiment was carried out for Kompsat-3A and showed that the significant accuracy increase was not observed but the approach has potential to suppress the maximum errors, especially the vertical errors.

• The Journal of Korean Academy of Orthopedic Manual Physical Therapy
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• v.29 no.1
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• pp.81-93
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• 2023

Purpose: The current case study focuses on identifying the effects of manual therapy and home self-therapeutic exercise including on mouth opening and pain relief in patients with continuous neck pain with myofascial temporomandibular disorders (TMDs) accompanied by headache induced by masticatory myalgia Subjects: The study participant was a 27-year-old woman who was treated a year ago for pain related to TMDs accompanied by a headache. Methods: Manual therapy of the cervical spine with upper cervical spine posterior-to-anterior mobilization (C1~C2), upper cervical spine flexion mobilization (C0~C2), upper cervical spine lateral flexion mobilization (C0~C1), upper cervical spine thrust manual therapy (C1~C2) and manual therapy of the temporomandibular joint and muscles with transverse medial accessory temporomandibular joint mobilization, manual therapies for the temporal, the masseter, and medial pterygoid muscles were performed twice a week for about 30 minutes for 4 weeks. This protocol included 3 sessions in total. The home self-therapeutic exercise was to be performed two to three times a day. Results: The values more improved MMO increased to 41.4 mm, left masseter muscle PPT to 2.9 kgf/cm², right masseter muscle PPT to 3.1 kgf/cm², KHIT-6 to 46 points, neck pain intensity (by NRS) to 2 points, headache frequency to per weeks, cervical kyphotic angle to -8.06%, and GCPS to grade 1 (low-intensity pain without pain-related disorder). Conclusion: Manual therapy and home self-therapeutic exercise can be helpful for mouth opening and pain relief in patients with myofascial TMDs accompanied by secondary headaches induced by masticatory myalgia.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.6D
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• pp.771-779
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• 2009

Digital topographical maps used for GIS DB are mainly produced by the traditional way of analogue aerial photogrammetry. Therefore, analogue photos are only available for digital mapping after preprocessing such as film developing, printing and scanning. However, digital aerial camera is able to get digital image directly without preprocessing and thus the performance and efficiency of photogrammetry are extremely increased. This study aims to investigate geometric stability of digital aerial frame camera DMC (Digital Modular Camera). In order to verify the geometric stability of digital aerial camera DMC, some different block conditions with and without cross strips, GPS/INS data and variation of GCPs are introduced in the block adjustment. The accuracy results of every block condition were compared each other by computation of residuals of exterior orientation (EO) parameters. Results of study shows that the geometric stability of the block adjustment with cross strips is increased about 30% against without cross strips. The accuracy of EO parameters of block adjustment with cross strips is also increased about 2cm for X-coordinate, 3cm for Y-coordinate, 3cm for Z-coordinate, and 6" for omega, 4" for phi and 3" for kappa.

• Korean Journal of Remote Sensing
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• v.40 no.4
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• pp.387-396
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• 2024

Most very high-resolution (VHR) satellite images provide rational polynomial coefficients (RPC) data to facilitate the transformation between ground coordinates and image coordinates. However, initial RPC often contains geometric errors, necessitating correction through matching with ground control points (GCPs). A GCP chip is a small image patch extracted from an orthorectified image together with height information of the center point, which can be directly used for geometric correction. Many studies have focused on area-based matching methods to accurately align GCP chips with VHR satellite images. In cases with seasonal differences or changed areas, edge-based algorithms are often used for matching due to the difficulty of relying solely on pixel values. However, traditional edge extraction algorithms,such as canny edge detectors, require appropriate threshold settings tailored to the spectral characteristics of satellite images. Therefore, this study utilizes deep learning-based edge information that is insensitive to the regional characteristics of satellite images for matching. Specifically,we use a pretrained pixel difference network (PiDiNet) to generate the edge maps for both satellite images and GCP chips. These edge maps are then used as input for normalized cross-correlation (NCC) and relative edge cross-correlation (RECC) to identify the peak points with the highest correlation between the two edge maps. To remove mismatched pairs and thus obtain the bias-compensated RPC, we iteratively apply the data snooping. Finally, we compare the results qualitatively and quantitatively with those obtained from traditional NCC and RECC methods. The PiDiNet network approach achieved high matching accuracy with root mean square error (RMSE) values ranging from 0.3 to 0.9 pixels. However, the PiDiNet-generated edges were thicker compared to those from the canny method, leading to slightly lower registration accuracy in some images. Nevertheless, PiDiNet consistently produced characteristic edge information, allowing for successful matching even in challenging regions. This study demonstrates that improving the robustness of edge-based registration methods can facilitate effective registration across diverse regions.