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Jen-Yu Han
Department of Civil Engineering, National Taiwan University, Taipei 106, Taiwan

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Short Biography

Jen‑Yu Han received a Ph.D. degree in Civil Engineering from Purdue University, USA and is a Professor at the Civil Engineering Department at National Taiwan University, Taipei, Taiwan. He also serves as the Duty Director at the NRCEE-NTUCE Joint AI Research Center. His research interests include geodetic reference frames, error theory, deformation analysis, lidar systems, and intelligent image sensors.

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Journal article
Published: 08 August 2021 in Applied Sciences
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Due to extreme weather, researchers are constantly putting their focus on prevention and mitigation for the impact of disasters in order to reduce the loss of life and property. The disaster associated with slope failures is among the most challenging ones due to the multiple driving factors and complicated mechanisms between them. In this study, a modern space remote sensing technology, InSAR, was introduced as a direct observable for the slope dynamics. The InSAR-derived displacement fields and other in situ geological and topographical factors were integrated, and their correlations with the landslide susceptibility were analyzed. Moreover, multiple machine learning approaches were applied with a goal to construct an optimal model between these complicated factors and landslide susceptibility. Two case studies were performed in the mountainous areas of Taiwan Island and the model performance was evaluated by a confusion matrix. The numerical results revealed that among different machine learning approaches, the Random Forest model outperformed others, with an average accuracy higher than 80%. More importantly, the inclusion of the InSAR data resulted in an improved model accuracy in all training approaches, which is the first to be reported in all of the scientific literature. In other words, the proposed approach provides a novel integrated technique that enables a highly reliable analysis of the landslide susceptibility so that subsequent management or reinforcement can be better planned.

ACS Style

Yan-Ting Lin; Yi-Keng Chen; Kuo-Hsin Yang; Chuin-Shan Chen; Jen-Yu Han. Integrating InSAR Observables and Multiple Geological Factors for Landslide Susceptibility Assessment. Applied Sciences 2021, 11, 7289 .

AMA Style

Yan-Ting Lin, Yi-Keng Chen, Kuo-Hsin Yang, Chuin-Shan Chen, Jen-Yu Han. Integrating InSAR Observables and Multiple Geological Factors for Landslide Susceptibility Assessment. Applied Sciences. 2021; 11 (16):7289.

Chicago/Turabian Style

Yan-Ting Lin; Yi-Keng Chen; Kuo-Hsin Yang; Chuin-Shan Chen; Jen-Yu Han. 2021. "Integrating InSAR Observables and Multiple Geological Factors for Landslide Susceptibility Assessment." Applied Sciences 11, no. 16: 7289.

Journal article
Published: 12 July 2021 in Survey Review
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Although a dynamic or semi-dynamic datum has been adopted in some countries, it remains a challenge if a long-term stable datum is to be established in a tectonic active area. This study presents an approach to realistically reflect the time dependent behaviors of ground reference points while maintaining the long-term stability of a datum. An adaptive approach coupled with the Euler motion model is proposed for dividing an area into blocks. A least-squares collocation is then applied for modeling the residual velocities in each block. A case study using the data from 375 continuously operated GNSS stations in Taiwan is presented. It is illustrated that the complex surface kinematics in this region can be divided into three blocks. Significant reductions up to 64% of residual velocities were obtained. This shows that a stable datum can be established in a region with active and complicated surface kinematics by implementing the proposed.

ACS Style

Chun-Yun Chou; Jen-Yu Han. Adaptive block modeling of time dependent variations of datum reference points in a tectonically active area. Survey Review 2021, 1 -16.

AMA Style

Chun-Yun Chou, Jen-Yu Han. Adaptive block modeling of time dependent variations of datum reference points in a tectonically active area. Survey Review. 2021; ():1-16.

Chicago/Turabian Style

Chun-Yun Chou; Jen-Yu Han. 2021. "Adaptive block modeling of time dependent variations of datum reference points in a tectonically active area." Survey Review , no. : 1-16.

Original article
Published: 25 September 2020 in GPS Solutions
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This investigation implements a least-squares methodology to fit a triaxial ellipsoid to a set of three-dimensional Cartesian coordinates obtained from present-day geospatial techniques, materializing the terrestrial frame ITRF2014. To approximate, as much as possible previous research on this topic, the original spatial values of the station coordinates were “reduced” to the surface of the EGM2008 geoid model by introducing a simple and straightforward procedure. The mathematical model adopted in all LS solutions is the standard quadric surface polynomial equation parameterizing a triaxial ellipsoid. Functionally related to these polynomial coefficients are nine geometric parameters: the three ellipsoid semi-axes, its origin location with respect to the current conventional geocentric terrestrial frame, and the three rotations defining its spatial orientation. The final results are compatible with the pioneering work started by Burša in 1970 and, lately, by a recent publication by Panou and colleagues in that incorporates updated geoid models.

ACS Style

Tomás Soler; Jen-Yu Han. Determination of the parameters of the triaxial earth ellipsoid as derived from present-day geospatial techniques. GPS Solutions 2020, 24, 1 -16.

AMA Style

Tomás Soler, Jen-Yu Han. Determination of the parameters of the triaxial earth ellipsoid as derived from present-day geospatial techniques. GPS Solutions. 2020; 24 (4):1-16.

Chicago/Turabian Style

Tomás Soler; Jen-Yu Han. 2020. "Determination of the parameters of the triaxial earth ellipsoid as derived from present-day geospatial techniques." GPS Solutions 24, no. 4: 1-16.

Journal article
Published: 12 June 2020 in Remote Sensing
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Moving object detection and tracking from image sequences has been extensively studied in a variety of fields. Nevertheless, observing geometric attributes and identifying the detected objects for further investigation of moving behavior has drawn less attention. The focus of this study is to determine moving trajectories, object heights, and object recognition using a monocular camera configuration. This paper presents a scheme to conduct moving object recognition with three-dimensional (3D) observation using faster region-based convolutional neural network (Faster R-CNN) with a stationary and rotating Pan Tilt Zoom (PTZ) camera and close-range photogrammetry. The camera motion effects are first eliminated to detect objects that contain actual movement, and a moving object recognition process is employed to recognize the object classes and to facilitate the estimation of their geometric attributes. Thus, this information can further contribute to the investigation of object moving behavior. To evaluate the effectiveness of the proposed scheme quantitatively, first, an experiment with indoor synthetic configuration is conducted, then, outdoor real-life data are used to verify the feasibility based on recall, precision, and F1 index. The experiments have shown promising results and have verified the effectiveness of the proposed method in both laboratory and real environments. The proposed approach calculates the height and speed estimates of the recognized moving objects, including pedestrians and vehicles, and shows promising results with acceptable errors and application potential through existing PTZ camera images at a very low cost.

ACS Style

Tzu-Yi Chuang; Jen-Yu Han; Deng-Jie Jhan; Ming-Der Yang. Geometric Recognition of Moving Objects in Monocular Rotating Imagery Using Faster R-CNN. Remote Sensing 2020, 12, 1 .

AMA Style

Tzu-Yi Chuang, Jen-Yu Han, Deng-Jie Jhan, Ming-Der Yang. Geometric Recognition of Moving Objects in Monocular Rotating Imagery Using Faster R-CNN. Remote Sensing. 2020; 12 (12):1.

Chicago/Turabian Style

Tzu-Yi Chuang; Jen-Yu Han; Deng-Jie Jhan; Ming-Der Yang. 2020. "Geometric Recognition of Moving Objects in Monocular Rotating Imagery Using Faster R-CNN." Remote Sensing 12, no. 12: 1.

Journal article
Published: 01 May 2020 in Journal of Surveying Engineering
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Least-squares (LS) techniques have been a frequent choice advocated by a plethora of engineers for modeling problems requiring a unique solution based on sets of redundant observations perturbed by random noise. In this paper, several versions of LS procedures using the general quadric polynomial equation as the math model are reviewed and applied to a triaxial ellipsoid fitting exercise. The coefficients of this polynomial are then transformed into the nine parameters defining the spatial properties of the ellipsoid: semiaxes, coordinates of the origin, and rotation angles. Finally, a novel methodology requiring eigentheory is introduced to complete the determination of the variance–covariance matrices of these parameters.

ACS Style

Tomás Soler; J.-Y. Han; C. J. Huang. Estimating Variance–Covariance Matrix of the Parameters of a Fitted Triaxial Ellipsoid. Journal of Surveying Engineering 2020, 146, 04020003 .

AMA Style

Tomás Soler, J.-Y. Han, C. J. Huang. Estimating Variance–Covariance Matrix of the Parameters of a Fitted Triaxial Ellipsoid. Journal of Surveying Engineering. 2020; 146 (2):04020003.

Chicago/Turabian Style

Tomás Soler; J.-Y. Han; C. J. Huang. 2020. "Estimating Variance–Covariance Matrix of the Parameters of a Fitted Triaxial Ellipsoid." Journal of Surveying Engineering 146, no. 2: 04020003.

Journal article
Published: 21 February 2020 in Remote Sensing
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Many people use smartphone cameras to record their living environments through captured images, and share aspects of their daily lives on social networks, such as Facebook, Instagram, and Twitter. These platforms provide volunteered geographic information (VGI), which enables the public to know where and when events occur. At the same time, image-based VGI can also indicate environmental changes and disaster conditions, such as flooding ranges and relative water levels. However, little image-based VGI has been applied for the quantification of flooding water levels because of the difficulty of identifying water lines in image-based VGI and linking them to detailed terrain models. In this study, flood detection has been achieved through image-based VGI obtained by smartphone cameras. Digital image processing and a photogrammetric method were presented to determine the water levels. In digital image processing, the random forest classification was applied to simplify ambient complexity and highlight certain aspects of flooding regions, and the HT-Canny method was used to detect the flooding line of the classified image-based VGI. Through the photogrammetric method and a fine-resolution digital elevation model based on the unmanned aerial vehicle mapping technique, the detected flooding lines were employed to determine water levels. Based on the results of image-based VGI experiments, the proposed approach identified water levels during an urban flood event in Taipei City for demonstration. Notably, classified images were produced using random forest supervised classification for a total of three classes with an average overall accuracy of 88.05%. The quantified water levels with a resolution of centimeters (

ACS Style

Yan-Ting Lin; Ming-Der Yang; Jen-Yu Han; Yuan-Fong Su; Jiun-Huei Jang. Quantifying Flood Water Levels Using Image-Based Volunteered Geographic Information. Remote Sensing 2020, 12, 706 .

AMA Style

Yan-Ting Lin, Ming-Der Yang, Jen-Yu Han, Yuan-Fong Su, Jiun-Huei Jang. Quantifying Flood Water Levels Using Image-Based Volunteered Geographic Information. Remote Sensing. 2020; 12 (4):706.

Chicago/Turabian Style

Yan-Ting Lin; Ming-Der Yang; Jen-Yu Han; Yuan-Fong Su; Jiun-Huei Jang. 2020. "Quantifying Flood Water Levels Using Image-Based Volunteered Geographic Information." Remote Sensing 12, no. 4: 706.

Articles
Published: 04 September 2019 in Journal of the Chinese Institute of Engineers
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Geospatial and geometric states of traffic signs are indispensable information for traffic facility maintenance. This study applies a low-cost single camera system to locate and identify traffic signs and reflects their on-site conditions for assisting in maintenance. Referring to official regulations, a traffic sign can be identified and classified based on its color and shape attributes. The poses and states of the sign planes can also be evaluated according to their geometric shape ratios and the discrepancy with respect to traffic sign regulations, in which a least-square consistency check is proposed to ensure assessment reliability and accuracy. Validation with day and nighttime image sequences was performed to verify the effectiveness of the proposed method and the robustness to illumination changes, color deterioration, and motion blur. Considering the promising results, this study can be deemed as an alternative to promote routine maintenance of traffic facilities.

ACS Style

Jen-Yu Han; Tsung-Hsien Juan; Tzu-Yi Chuang. Traffic sign detection and positioning based on monocular camera. Journal of the Chinese Institute of Engineers 2019, 42, 757 -769.

AMA Style

Jen-Yu Han, Tsung-Hsien Juan, Tzu-Yi Chuang. Traffic sign detection and positioning based on monocular camera. Journal of the Chinese Institute of Engineers. 2019; 42 (8):757-769.

Chicago/Turabian Style

Jen-Yu Han; Tsung-Hsien Juan; Tzu-Yi Chuang. 2019. "Traffic sign detection and positioning based on monocular camera." Journal of the Chinese Institute of Engineers 42, no. 8: 757-769.

Journal article
Published: 20 June 2019 in Automation in Construction
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Pavement performance is a critical factor toward riding comfort experience and drastically affect traffic management and the safety of road users. Since road quality declines over time and current periodic inspection on a vast road network is laborious and costly to the authority. This paper proposes a participatory system to conduct pavement performance monitoring of a country-wide road network based on crowdsourcing spatiotemporal data. By conducting cloud computing of a statistical grading mechanism with respect to the vertical and lateral acceleration behavior, the perception of riding comfort, which has a high correlation with pavement quality, can be reflected faithfully based on the spatiotemporal data acquired from a smartphone-driven progressive web application. Moreover, a deep learning technique is leveraged to identify road anomalies from the on-site images for a cross-check mechanism, which ensures the reliability of the monitoring pavement conditions and facilitates the automation level of road anomaly labeling and documenting. The proposed pavement performance monitoring was validated by the road network of Taipei city, Taiwan, which rendered promising results with an accuracy up to 98% and a false positive rate smaller than 1.3% showing the practicality and adaptability in a complex road network.

ACS Style

Tzu-Yi Chuang; Nei-Hao Perng; Jen-Yu Han. Pavement performance monitoring and anomaly recognition based on crowdsourcing spatiotemporal data. Automation in Construction 2019, 106, 102882 .

AMA Style

Tzu-Yi Chuang, Nei-Hao Perng, Jen-Yu Han. Pavement performance monitoring and anomaly recognition based on crowdsourcing spatiotemporal data. Automation in Construction. 2019; 106 ():102882.

Chicago/Turabian Style

Tzu-Yi Chuang; Nei-Hao Perng; Jen-Yu Han. 2019. "Pavement performance monitoring and anomaly recognition based on crowdsourcing spatiotemporal data." Automation in Construction 106, no. : 102882.

Journal article
Published: 01 October 2018 in Measurement
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ACS Style

Yan-Ting Lin; Yi Chun Lin; Jen-Yu Han. Automatic water-level detection using single-camera images with varied poses. Measurement 2018, 127, 167 -174.

AMA Style

Yan-Ting Lin, Yi Chun Lin, Jen-Yu Han. Automatic water-level detection using single-camera images with varied poses. Measurement. 2018; 127 ():167-174.

Chicago/Turabian Style

Yan-Ting Lin; Yi Chun Lin; Jen-Yu Han. 2018. "Automatic water-level detection using single-camera images with varied poses." Measurement 127, no. : 167-174.

Journal article
Published: 11 April 2018 in Journal of Hydroinformatics
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Bed topography in river bends is highly non-uniform as a result of the spiral motion of fluid and sediment transports related to channel curvature. To grasp a full understanding of geomorphology and hydrology in natural river bends, detailed bed topography data are necessary, but are usually not of high enough quality and so require further interpolation for sophisticated studies. In this paper, an algorithm is proposed that is particularly suited to bathymetry interpolation in rivers with apparent bends. The thalweg and the two banks are used as geographical features to ensure that a concave cross-sectional bed-form can be found in bend geometry, while linear interpolations are conducted in the in accordance with secondary and main stream currents, respectively. In comparison with conventional spatial interpolation methods, the proposed algorithm is validated to ensure better performance in generating smooth and accurate bed topography in channel bends, which results in better predictions of river stage by 2D hydrodynamic simulation in practical field tests.

ACS Style

Yan Ting Lin; Wei-Bo Chen; Yuan-Fong Su; Jen-Yu Han; Jiun-Huei Jang. Improving river stage forecast by bed reconstruction in sinuous bends. Journal of Hydroinformatics 2018, 20, 960 -974.

AMA Style

Yan Ting Lin, Wei-Bo Chen, Yuan-Fong Su, Jen-Yu Han, Jiun-Huei Jang. Improving river stage forecast by bed reconstruction in sinuous bends. Journal of Hydroinformatics. 2018; 20 (4):960-974.

Chicago/Turabian Style

Yan Ting Lin; Wei-Bo Chen; Yuan-Fong Su; Jen-Yu Han; Jiun-Huei Jang. 2018. "Improving river stage forecast by bed reconstruction in sinuous bends." Journal of Hydroinformatics 20, no. 4: 960-974.

Journal article
Published: 01 November 2017 in Journal of Surveying Engineering
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New insights about the concept of local accuracies are elaborated in this article. Recently found evidence supports the mathematical rigor of equations previously published in this journal as a unique alternative to rigorously estimate local accuracies. A mathematical algorithm to compute the averaged local accuracies at a point using the full network statistics of a preselected cluster of surrounding points is introduced. The relationship between eigenvalues and eigenvectors of error ellipsoids among different local frames is also addressed.

ACS Style

Tomás Soler; Jen-Yu Han. Rigorous Estimation of Local Accuracies Revisited. Journal of Surveying Engineering 2017, 143, 06017002 .

AMA Style

Tomás Soler, Jen-Yu Han. Rigorous Estimation of Local Accuracies Revisited. Journal of Surveying Engineering. 2017; 143 (4):06017002.

Chicago/Turabian Style

Tomás Soler; Jen-Yu Han. 2017. "Rigorous Estimation of Local Accuracies Revisited." Journal of Surveying Engineering 143, no. 4: 06017002.

Conference paper
Published: 01 July 2017 in Proceedings of the 34th International Symposium on Automation and Robotics in Construction (ISARC)
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ACS Style

Nei-Hao Perng; Bo-Sheng Bai; Po-Han Chen; Jen-Yu Han; Ming-Yi Jiang; Jyun-Hao Huang; Cheng-Wei Su; Po-Yuan Chen. Automatic Generation of 3D Models from UAV-Captured Image Data for Immersive VR Applications. Proceedings of the 34th International Symposium on Automation and Robotics in Construction (ISARC) 2017, 812 -815.

AMA Style

Nei-Hao Perng, Bo-Sheng Bai, Po-Han Chen, Jen-Yu Han, Ming-Yi Jiang, Jyun-Hao Huang, Cheng-Wei Su, Po-Yuan Chen. Automatic Generation of 3D Models from UAV-Captured Image Data for Immersive VR Applications. Proceedings of the 34th International Symposium on Automation and Robotics in Construction (ISARC). 2017; ():812-815.

Chicago/Turabian Style

Nei-Hao Perng; Bo-Sheng Bai; Po-Han Chen; Jen-Yu Han; Ming-Yi Jiang; Jyun-Hao Huang; Cheng-Wei Su; Po-Yuan Chen. 2017. "Automatic Generation of 3D Models from UAV-Captured Image Data for Immersive VR Applications." Proceedings of the 34th International Symposium on Automation and Robotics in Construction (ISARC) , no. : 812-815.

Journal article
Published: 26 February 2016 in GPS Solutions
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ACS Style

Tomás Soler; Jen-Yu Han. On rotation of frames and physical vectors: an exercise based on plate tectonics theory. GPS Solutions 2016, 21, 345 -361.

AMA Style

Tomás Soler, Jen-Yu Han. On rotation of frames and physical vectors: an exercise based on plate tectonics theory. GPS Solutions. 2016; 21 (2):345-361.

Chicago/Turabian Style

Tomás Soler; Jen-Yu Han. 2016. "On rotation of frames and physical vectors: an exercise based on plate tectonics theory." GPS Solutions 21, no. 2: 345-361.

Journal article
Published: 01 February 2016 in Journal of Surveying Engineering
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ACS Style

Tomás Soler; Jen-Yu Han; Neil D. Weston. Variance–Covariance Matrix of Transformed GPS Positions: Case Study for the NAD 83 Geodetic Datum. Journal of Surveying Engineering 2016, 142, 04015004 .

AMA Style

Tomás Soler, Jen-Yu Han, Neil D. Weston. Variance–Covariance Matrix of Transformed GPS Positions: Case Study for the NAD 83 Geodetic Datum. Journal of Surveying Engineering. 2016; 142 (1):04015004.

Chicago/Turabian Style

Tomás Soler; Jen-Yu Han; Neil D. Weston. 2016. "Variance–Covariance Matrix of Transformed GPS Positions: Case Study for the NAD 83 Geodetic Datum." Journal of Surveying Engineering 142, no. 1: 04015004.

Journal article
Published: 01 February 2016 in Journal of Surveying Engineering
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Road profile extraction and analysis are essential tasks in transportation asset management. Current approaches use vehicle-borne laser sensors in order to precisely measure the variations in elevation along a specific route. However, a complicated sensor mechanism, such as in the mobile light detection and ranging (LiDAR) system, is involved and the resulting quality is compromised owing to multiple factors. In this study, an image-based approach for extracting road profiles is proposed. It requires only a single camera sensor and a low-cost laser module and is capable of collecting road profiles along both the longitudinal and transverse directions. A detailed methodology is first presented in this paper, followed by a simulation evaluation and a case study. The case study illustrates that the quality of the extracted profiles based on the proposed approach achieves millimeter accuracy. Consequently, an accurate and cost-efficient road profile analysis becomes possible when the proposed approach is implemented.

ACS Style

Jen-Yu Han; Aichin Chen; Yan Ting Lin; Jen-Yu Han M.Asce. Image-Based Approach for Road Profile Analyses. Journal of Surveying Engineering 2016, 142, 06015003 .

AMA Style

Jen-Yu Han, Aichin Chen, Yan Ting Lin, Jen-Yu Han M.Asce. Image-Based Approach for Road Profile Analyses. Journal of Surveying Engineering. 2016; 142 (1):06015003.

Chicago/Turabian Style

Jen-Yu Han; Aichin Chen; Yan Ting Lin; Jen-Yu Han M.Asce. 2016. "Image-Based Approach for Road Profile Analyses." Journal of Surveying Engineering 142, no. 1: 06015003.

Journal article
Published: 01 October 2015 in Automation in Construction
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ACS Style

Jenny Guo; Meng-Ju Tsai; Jen-Yu Han. Automatic reconstruction of road surface features by using terrestrial mobile lidar. Automation in Construction 2015, 58, 165 -175.

AMA Style

Jenny Guo, Meng-Ju Tsai, Jen-Yu Han. Automatic reconstruction of road surface features by using terrestrial mobile lidar. Automation in Construction. 2015; 58 ():165-175.

Chicago/Turabian Style

Jenny Guo; Meng-Ju Tsai; Jen-Yu Han. 2015. "Automatic reconstruction of road surface features by using terrestrial mobile lidar." Automation in Construction 58, no. : 165-175.

Journal article
Published: 28 April 2015 in Acta Geodaetica et Geophysica
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The global navigation satellite system (GNSS) positioning solution relies greatly on the satellite configuration visible at a specific receiver location. As a consequence, satellite visibility analysis considering the surrounding terrain obstruction, becomes a key step when the GNSS positioning quality is to be evaluated. Current satellite visibility analysis requires high-resolution digital surface model (DSM) data and is thus a pricey and time-consuming task. In this study, an image-based approach for the satellite visibility analysis is proposed. Terrain obstructions are first identified from photo images, using image-processing techniques. The maximal obstruction angle at each direction is then determined, based on photogrammetric principles. According to the results from a case study, this novel approach provides a satellite visibility analysis solution comparable to that of the current DSM approaches, but with significantly improved computational efficiency. Consequently, a highly efficient and low-cost satellite visibility analysis becomes possible when the proposed approach is implemented.

ACS Style

Jen-Yu Han; Tsung-Hsien Juan. Image-based approach for satellite visibility analysis in critical environments. Acta Geodaetica et Geophysica 2015, 51, 113 -123.

AMA Style

Jen-Yu Han, Tsung-Hsien Juan. Image-based approach for satellite visibility analysis in critical environments. Acta Geodaetica et Geophysica. 2015; 51 (1):113-123.

Chicago/Turabian Style

Jen-Yu Han; Tsung-Hsien Juan. 2015. "Image-based approach for satellite visibility analysis in critical environments." Acta Geodaetica et Geophysica 51, no. 1: 113-123.

Journal article
Published: 16 March 2015 in Journal of the Chinese Institute of Engineers
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ACS Style

Jenny Guo; Jen-Yu Han. Quality assessment for strain field determination based on the NISLT approach. Journal of the Chinese Institute of Engineers 2015, 38, 1 -10.

AMA Style

Jenny Guo, Jen-Yu Han. Quality assessment for strain field determination based on the NISLT approach. Journal of the Chinese Institute of Engineers. 2015; 38 (6):1-10.

Chicago/Turabian Style

Jenny Guo; Jen-Yu Han. 2015. "Quality assessment for strain field determination based on the NISLT approach." Journal of the Chinese Institute of Engineers 38, no. 6: 1-10.

Articles
Published: 22 December 2014 in Journal of the Chinese Institute of Engineers
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Mapping road surface features, such as manholes, traffic markings, and cracks, is an essential task for transportation facility management. Although, these features can be rapidly surveyed using the latest mobile mapping techniques, a sophisticated sensor system with a complicated post-processing procedure is usually required. In this study, an efficient framework for modeling road surface features is proposed using a single camera system installed on a moving platform. First, the road surface images along a route of interest are acquired and potential objects are identified based on their shapes and recorded spectra in the images. Then, the contour pixels of the identified objects are extracted by the Canny edge detection technique. Finally, the 3D coordinates of the detected features in object space are obtained by integrating the profile-image technique and the instantaneous exterior orientation parameters of the platform. Based on the numerical results from a case study, it has been demonstrated that a fully automatic and reliable extraction of road surface features can be easily achieved by implementing the proposed approach. Consequently, the modeling of road surface features, which essentially contributes to the management of transportation facilities, can be executed in a cost-efficient manner.

ACS Style

Jen-Yu Han; Jun-Yun Chou; Meng-Ju Tsai. Mapping road surface features using single-camera images acquired by a mobile mapping system. Journal of the Chinese Institute of Engineers 2014, 38, 486 -493.

AMA Style

Jen-Yu Han, Jun-Yun Chou, Meng-Ju Tsai. Mapping road surface features using single-camera images acquired by a mobile mapping system. Journal of the Chinese Institute of Engineers. 2014; 38 (4):486-493.

Chicago/Turabian Style

Jen-Yu Han; Jun-Yun Chou; Meng-Ju Tsai. 2014. "Mapping road surface features using single-camera images acquired by a mobile mapping system." Journal of the Chinese Institute of Engineers 38, no. 4: 486-493.

Review
Published: 25 June 2014 in Smart Structures and Systems
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ACS Style

Peter Liu; Albert Chen; Yin-Nan Huang; Jen-Yu Han; Jihn-Sung Lai; Shih-Chung Kang; Tzong-Hann Wu; Ming-Chang Wen; Meng-Han Tsai. A review of rotorcraft Unmanned Aerial Vehicle (UAV) developments and applications in civil engineering. Smart Structures and Systems 2014, 13, 1065 -1094.

AMA Style

Peter Liu, Albert Chen, Yin-Nan Huang, Jen-Yu Han, Jihn-Sung Lai, Shih-Chung Kang, Tzong-Hann Wu, Ming-Chang Wen, Meng-Han Tsai. A review of rotorcraft Unmanned Aerial Vehicle (UAV) developments and applications in civil engineering. Smart Structures and Systems. 2014; 13 (6):1065-1094.

Chicago/Turabian Style

Peter Liu; Albert Chen; Yin-Nan Huang; Jen-Yu Han; Jihn-Sung Lai; Shih-Chung Kang; Tzong-Hann Wu; Ming-Chang Wen; Meng-Han Tsai. 2014. "A review of rotorcraft Unmanned Aerial Vehicle (UAV) developments and applications in civil engineering." Smart Structures and Systems 13, no. 6: 1065-1094.