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Ting On Chan
Guangdong Key Laboratory for Urbanization and Geo-Simulation, School of Geography and Planning, Sun Yat-sen University, Guangzhou, 510275, China

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Journal article
Published: 12 March 2021 in Energy
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To implement a new mixed approach for electricity energy consumption estimates, this study aimed to estimate country-wide local-scale electricity consumption by combining demographic, remote sensing, and social sensing data. Specifically, England-wide local-scale electricity energy consumption, including domestic and non-domestic ones, was estimated based on population in combination with nighttime light intensity or/and tweet volume. Moreover, to improve the explanatory power of statistical regression models, this study applied a newly developed spatial regression model (i.e., the ‘random effects eigenvector spatial filtering’ model) to the estimation of electricity energy consumption in comparison with conventional spatial regression models used in relevant studies. The spatial regression model used was further compared with machine learning and deep learning models (i.e., random forest and long short-term memory models). The empirical results uncover that: 1) the electricity energy consumption can be best explained by population in combination with both the nighttime light intensity and tweet volume; 2) the domestic electricity energy consumption can be better explained than its non-domestic counterpart; 3) the ‘random effects eigenvector spatial filtering’ models appear to outperform the conventional spatial regression models; and 4) the performance of the ‘random effects eigenvector spatial filtering’ models is similar to that of the random forest models and is lower than that of the long short-term memory models.

ACS Style

Yeran Sun; Shaohua Wang; Xucai Zhang; Ting On Chan; Wenjie Wu. Estimating local-scale domestic electricity energy consumption using demographic, nighttime light imagery and Twitter data. Energy 2021, 226, 120351 .

AMA Style

Yeran Sun, Shaohua Wang, Xucai Zhang, Ting On Chan, Wenjie Wu. Estimating local-scale domestic electricity energy consumption using demographic, nighttime light imagery and Twitter data. Energy. 2021; 226 ():120351.

Chicago/Turabian Style

Yeran Sun; Shaohua Wang; Xucai Zhang; Ting On Chan; Wenjie Wu. 2021. "Estimating local-scale domestic electricity energy consumption using demographic, nighttime light imagery and Twitter data." Energy 226, no. : 120351.

Journal article
Published: 09 February 2021 in Sensors
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Ancient pagodas are usually parts of hot tourist spots in many oriental countries due to their unique historical backgrounds. They are usually polygonal structures comprised by multiple floors, which are separated by eaves. In this paper, we propose a new method to investigate both the rotational and reflectional symmetry of such polygonal pagodas through developing novel geometric models to fit to the 3D point clouds obtained from photogrammetric reconstruction. The geometric model consists of multiple polygonal pyramid/prism models but has a common central axis. The method was verified by four datasets collected by an unmanned aerial vehicle (UAV) and a hand-held digital camera. The results indicate that the models fit accurately to the pagodas’ point clouds. The symmetry was realized by rotating and reflecting the pagodas’ point clouds after a complete leveling of the point cloud was achieved using the estimated central axes. The results show that there are RMSEs of 5.04 cm and 5.20 cm deviated from the perfect (theoretical) rotational and reflectional symmetries, respectively. This concludes that the examined pagodas are highly symmetric, both rotationally and reflectionally. The concept presented in the paper not only work for polygonal pagodas, but it can also be readily transformed and implemented for other applications for other pagoda-like objects such as transmission towers.

ACS Style

Ting Chan; Linyuan Xia; Yimin Chen; Wei Lang; Tingting Chen; Yeran Sun; Jing Wang; Qianxia Li; Ruxu Du. Symmetry Analysis of Oriental Polygonal Pagodas Using 3D Point Clouds for Cultural Heritage. Sensors 2021, 21, 1228 .

AMA Style

Ting Chan, Linyuan Xia, Yimin Chen, Wei Lang, Tingting Chen, Yeran Sun, Jing Wang, Qianxia Li, Ruxu Du. Symmetry Analysis of Oriental Polygonal Pagodas Using 3D Point Clouds for Cultural Heritage. Sensors. 2021; 21 (4):1228.

Chicago/Turabian Style

Ting Chan; Linyuan Xia; Yimin Chen; Wei Lang; Tingting Chen; Yeran Sun; Jing Wang; Qianxia Li; Ruxu Du. 2021. "Symmetry Analysis of Oriental Polygonal Pagodas Using 3D Point Clouds for Cultural Heritage." Sensors 21, no. 4: 1228.

Original article
Published: 05 February 2021 in Journal of Geodesy
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Despite the high complexity of the real world, linear regression still plays an important role in estimating parameters to model a physical relationship between at least two variables. The precision of the estimated parameters, which can usually be considered as an indicator of the solution quality, is conventionally obtained from the inverse of the normal equations matrix for which intensive computation is required when the number of observations is large. In addition, the impacts of the distribution of the observations on parameter precision are rarely reported in the literature. In this paper, we propose a new methodology to model the distribution of observations for linear regression in order to predict the parameter precision prior to actual data collection and performing the regression. The precision analysis can be readily performed given a hypothesized data distribution. The methodology has been verified with several simulated and real datasets. The results show that the empirical and model-predicted precisions match very well, with discrepancies of up to 6% and 3.4% for simulated and real datasets, respectively. Simulations demonstrate that these differences are simply due to finite sample size. In addition, simulation also demonstrates the relative insensitivity of the method to noise in the independent regression variables that causes deviations from the data distribution function. The proposed methodology allows straightforward prediction of the parameter precision based on the distribution of the observations related to their numerical limits and geometry, which greatly simplify design procedures for various experimental setups commonly involved in geodetic surveying such as LiDAR data collection.

ACS Style

D. D. Lichti; T. O. Chan; D. Belton. Linear regression with an observation distribution model. Journal of Geodesy 2021, 95, 1 -14.

AMA Style

D. D. Lichti, T. O. Chan, D. Belton. Linear regression with an observation distribution model. Journal of Geodesy. 2021; 95 (2):1-14.

Chicago/Turabian Style

D. D. Lichti; T. O. Chan; D. Belton. 2021. "Linear regression with an observation distribution model." Journal of Geodesy 95, no. 2: 1-14.

Journal article
Published: 27 January 2021 in ISPRS International Journal of Geo-Information
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COVID-19 containment policies are not only curbing the spread of COVID-19 but also changing human behavior. According to the routine activity theory, owing to lockdown, the closure of entertainment sites (e.g., pubs and bars), an increase in stay-at-home time, and an increase in police patrols are likely to influence chance of committing a crime. In this study, we aimed to further examine the spatial association of COVID-19 infection rate and crime rate. Particularly, we empirically validated the speculation that increase in COVID-19 cases is likely to reduce crime rate. In the empirical study, we investigated whether and how COVID-19 infection rate is spatially associated with crime rate in London. As the spatial data used are mainly areal data, we adopted a spatial regression mode (i.e., the “random effects eigenvector spatial filtering model”) to investigate the spatial associations after controlling for the socioeconomic factors. More specifically, we investigated the associations for all the four crime categories in three consequent months (March, April, and May of 2020). The empirical results indicate that 1) crime rates of the four categories have no statistically significant associations with COVID-19 infection rate in March; 2) violence-against-the-person rate has no statistically significant association with COVID-19 infection rate; and 3) robbery rate, burglary rate, and theft and handling rate have a statistically significant and negative association with COVID-19 infection rate in both April and May.

ACS Style

Yeran Sun; Ying Huang; Ke Yuan; Ting Chan; Yu Wang. Spatial Patterns of COVID-19 Incidence in Relation to Crime Rate Across London. ISPRS International Journal of Geo-Information 2021, 10, 53 .

AMA Style

Yeran Sun, Ying Huang, Ke Yuan, Ting Chan, Yu Wang. Spatial Patterns of COVID-19 Incidence in Relation to Crime Rate Across London. ISPRS International Journal of Geo-Information. 2021; 10 (2):53.

Chicago/Turabian Style

Yeran Sun; Ying Huang; Ke Yuan; Ting Chan; Yu Wang. 2021. "Spatial Patterns of COVID-19 Incidence in Relation to Crime Rate Across London." ISPRS International Journal of Geo-Information 10, no. 2: 53.

Journal article
Published: 06 January 2021 in Sustainability
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Urban vibrancy contributes towards a successful city and high-quality life for people as one of its vital elements. Therefore, the association between service facilities and vibrancy is crucial for urban managers to understand and improve city construction. Moreover, the rapid development of information and communications technology (ICT) allows researchers to easily and quickly collect a large volume of real-time data generated by people in daily life. In this study, against the background of emerging multi-source big data, we utilized Tencent location data as a proxy for 24-h vibrancy and adopted point-of-interest (POI) data to represent service facilities. An analysis framework integrated with ordinary least squares (OLS) and geographically and temporally weighted regression (GTWR) models is proposed to explore the spatiotemporal relationships between urban vibrancy and POI-based variables. Empirical results show that (1) spatiotemporal variations exist in the impact of service facilities on urban vibrancy across Guangzhou, China; and (2) GTWR models exhibit a higher degree of explanatory capacity on vibrancy than the OLS models. In addition, our results can assist urban planners to understand spatiotemporal patterns of urban vibrancy in a refined resolution, and to optimize the resource allocation and functional configuration of the city.

ACS Style

Xucai Zhang; Yeran Sun; Ting Chan; Ying Huang; AnYao Zheng; Zhang Liu. Exploring Impact of Surrounding Service Facilities on Urban Vibrancy Using Tencent Location-Aware Data: A Case of Guangzhou. Sustainability 2021, 13, 444 .

AMA Style

Xucai Zhang, Yeran Sun, Ting Chan, Ying Huang, AnYao Zheng, Zhang Liu. Exploring Impact of Surrounding Service Facilities on Urban Vibrancy Using Tencent Location-Aware Data: A Case of Guangzhou. Sustainability. 2021; 13 (2):444.

Chicago/Turabian Style

Xucai Zhang; Yeran Sun; Ting Chan; Ying Huang; AnYao Zheng; Zhang Liu. 2021. "Exploring Impact of Surrounding Service Facilities on Urban Vibrancy Using Tencent Location-Aware Data: A Case of Guangzhou." Sustainability 13, no. 2: 444.

Journal article
Published: 30 December 2020 in Sensors
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In global navigation satellite system (GNSS)-based positioning and applications, multipath is by far the most obstinate impact. To overcome paradoxical issues faced by current processing approaches for multipath, this paper employs an intrinsic method to identify and mitigate multipath based on empirical mode decomposition (EMD) and Hilbert–Huang transform (HHT). Frequency spectrum and power spectrum are comprehensively employed to identify and extract multipath from complex data series composed by combined GNSS observations. To systematically inspect the multipath from both code range and carrier phase, typical kinds of combinations of the GNSS observations including the code minus phase (CMP), differential correction (DC), and double differential (DD) carrier phase are selected for the suggested intrinsic approach to recognize and mitigate multipath under typical positioning modes. Compared with other current processing algorithms, the proposed methodology can deal with multipath under normal positioning modes without recourse to the conditions that satellite orbits are accurately repeated and surrounding environments of observing sites remain intact. The method can adaptively extract and eliminate multipath from solely the GNSS observations using intrinsic decomposition mechanism. From theoretical discussions and validating tests, it is found that both code and carrier phase multipath can be identified and distinguished from ionospheric delay and other impacts using the EMD based techniques. The resultant positioning accuracy is therefore improved to an obvious extent after the removal of the multipath. Overall, the proposed method can form an extensive and sound technical frame to enhance localization accuracy under typical GNSS positioning modes and harsh multipath environments.

ACS Style

Qianxia Li; Linyuan Xia; Ting On Chan; Jingchao Xia; Jijun Geng; Hongyu Zhu; Yuezhen Cai. Intrinsic Identification and Mitigation of Multipath for Enhanced GNSS Positioning. Sensors 2020, 21, 188 .

AMA Style

Qianxia Li, Linyuan Xia, Ting On Chan, Jingchao Xia, Jijun Geng, Hongyu Zhu, Yuezhen Cai. Intrinsic Identification and Mitigation of Multipath for Enhanced GNSS Positioning. Sensors. 2020; 21 (1):188.

Chicago/Turabian Style

Qianxia Li; Linyuan Xia; Ting On Chan; Jingchao Xia; Jijun Geng; Hongyu Zhu; Yuezhen Cai. 2020. "Intrinsic Identification and Mitigation of Multipath for Enhanced GNSS Positioning." Sensors 21, no. 1: 188.

Journal article
Published: 20 October 2020 in Sustainability
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Public availability of geo-coded or geo-referenced road collisions (crashes) makes it possible to perform geovisualisation and spatio-temporal analysis of road collisions across a city. This study aims to detect spatio-temporal clusters of road collisions across Greater London between 2010 and 2014. We implemented a fast Bayesian model-based cluster detection method with no covariates and after adjusting for potential covariates respectively. As empirical evidence on the association of street connectivity measures and the occurrence of road collisions had been found, we selected street connectivity measures as the potential covariates in our cluster detection. Results of the most significant cluster and the second most significant cluster during five consecutive years are located around the central areas. Moreover, after adjusting the covariates, the most significant cluster moves from the central areas of London to its peripheral areas, while the second most significant cluster remains unchanged. Additionally, one potential covariate used in this study, length-based road density, exhibits a positive association with the number of road collisions; meanwhile count-based intersection density displays a negative association. Although the covariates (i.e., road density and intersection density) exhibit potential impact on the clusters of road collisions, they are unlikely to contribute to the majority of clusters. Furthermore, the method of fast Bayesian model-based cluster detection is developed to discover spatio-temporal clusters of serious injury collisions. Most of the areas at risk of serious injury collisions overlay those at risk of road collisions. Although not being identified as areas at risk of road collisions, some districts, e.g., City of London, are regarded as areas at risk of serious injury collisions.

ACS Style

Yeran Sun; Yu Wang; Ke Yuan; Ting Chan; Ying Huang. Discovering Spatio-Temporal Clusters of Road Collisions Using the Method of Fast Bayesian Model-Based Cluster Detection. Sustainability 2020, 12, 8681 .

AMA Style

Yeran Sun, Yu Wang, Ke Yuan, Ting Chan, Ying Huang. Discovering Spatio-Temporal Clusters of Road Collisions Using the Method of Fast Bayesian Model-Based Cluster Detection. Sustainability. 2020; 12 (20):8681.

Chicago/Turabian Style

Yeran Sun; Yu Wang; Ke Yuan; Ting Chan; Ying Huang. 2020. "Discovering Spatio-Temporal Clusters of Road Collisions Using the Method of Fast Bayesian Model-Based Cluster Detection." Sustainability 12, no. 20: 8681.

Journal article
Published: 11 October 2020 in ISPRS International Journal of Geo-Information
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To examine to what extent spatial inequalities in childhood obesity are attributable to spatial inequalities in socioeconomic characteristics across a country, we aimed to investigate the spatial associations of socioeconomic characteristics and childhood obesity. We first explored spatial patterns of childhood obesity prevalence, and subsequently investigated the spatial associations of socioeconomic factors and childhood obesity prevalence across England by selecting and estimating appropriate spatial regression models. As the data used are geospatial data, we used two newly developed specifications of spatial regression models to investigate the spatial association of socioeconomic factors and childhood obesity prevalence. As a result, among the two newly developed specifications of spatial regression models, the fast random effects specification of eigenvector spatial filtering (FRES-ESF) model appears to outperform the matrix exponential spatial specification of spatial autoregressive (MESS-SAR) model. Empirical results indicate that positive spatial dependence is found to exist in childhood obesity prevalence across England; and that socioeconomic factors are significantly associated with childhood obesity prevalence across England. In England, children living in areas with lower socioeconomic status are at higher risk of obesity. This study suggests effectively reducing spatial inequalities in socioeconomic status will plays a vital role in mitigating spatial inequalities in childhood obesity prevalence.

ACS Style

Yeran Sun; Xuke Hu; Ying Huang; Ting On Chan. Spatial Patterns of Childhood Obesity Prevalence in Relation to Socioeconomic Factors across England. ISPRS International Journal of Geo-Information 2020, 9, 599 .

AMA Style

Yeran Sun, Xuke Hu, Ying Huang, Ting On Chan. Spatial Patterns of Childhood Obesity Prevalence in Relation to Socioeconomic Factors across England. ISPRS International Journal of Geo-Information. 2020; 9 (10):599.

Chicago/Turabian Style

Yeran Sun; Xuke Hu; Ying Huang; Ting On Chan. 2020. "Spatial Patterns of Childhood Obesity Prevalence in Relation to Socioeconomic Factors across England." ISPRS International Journal of Geo-Information 9, no. 10: 599.

Journal article
Published: 21 September 2020 in International Journal of Disaster Risk Reduction
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The failure of transmission towers often causes widespread blackouts and results in electrical shock to people and animals via water bodies especially in areas prone to river floods and storm surges. To ensure safety operation of the power networks, the structural health of transmission towers should be maintained and investigated under the potential of flood hazards. We propose a comprehensive risk assessment framework for the transmission towers affected by the pluvial flood, based on the geometry of the tower and the terrain. The geometry is first obtained from 3D point clouds derived from airborne Light Detection And Ranging (LiDAR). The framework consists of a series of new point cloud segmentation and fitting algorithms, designed to accurately estimate the inclination angles of the transmission towers. In addition, the framework includes an existing flood risk index (Topographic Control Index, TCI) and a new risk index for the transmission towers (Transmission Tower Risk Index, TTRI) which reflects the risk for tower damages under the pluvial flooding. The framework is applied to Hengman, situated on Pearl River estuary, Southern China. Based on our results, high TTRI were shown to be often associated with high flooding risk. This coincides with our hypothesis that the floods weaken foundation settlements and thus trigger tower inclinations. The TTRI and TCI analyses reveal that 8 towers out of ∼60 in total are with low-risk (13.8%); 2 with medium-risk (3.5%) and 1 tower is at high-risk. The total area affected by the risk tower is ∼2.7 km2, accounting for 5.5% of the study area. The results suggested that the proposed framework is implementable and reliable. The resultant analysis can help decision makers to pinpoint the affected transmission towers along with the peripheral affected areas for precaution.

ACS Style

Mingwei Chen; Ting On Chan; Xianwei Wang; Ming Luo; Yi Lin; Huabing Huang; Yeran Sun; Ge Cui; Ying Huang. A risk analysis framework for transmission towers under potential pluvial flood - LiDAR survey and geometric modelling. International Journal of Disaster Risk Reduction 2020, 50, 101862 .

AMA Style

Mingwei Chen, Ting On Chan, Xianwei Wang, Ming Luo, Yi Lin, Huabing Huang, Yeran Sun, Ge Cui, Ying Huang. A risk analysis framework for transmission towers under potential pluvial flood - LiDAR survey and geometric modelling. International Journal of Disaster Risk Reduction. 2020; 50 ():101862.

Chicago/Turabian Style

Mingwei Chen; Ting On Chan; Xianwei Wang; Ming Luo; Yi Lin; Huabing Huang; Yeran Sun; Ge Cui; Ying Huang. 2020. "A risk analysis framework for transmission towers under potential pluvial flood - LiDAR survey and geometric modelling." International Journal of Disaster Risk Reduction 50, no. : 101862.

Journal article
Published: 10 September 2020 in Sustainability
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Air pollution can have adverse impacts on both the physical health and mental health of people. Increasing air pollution levels are likely to increase suicide rates, although the causal mechanisms underlying the relationship between pollution exposure and suicidal behaviour are not well understood. In this study, we aimed to further examine the spatial association of air pollution and suicidal behaviour. Specifically, we investigated whether or how PM2.5 levels are spatially associated with the adult suicide rates at the district level across London. As the data used are geospatial data, we used two newly developed specifications of spatial regression models to investigate the spatial association of PM2.5 levels and suicide. The empirical results show that PM2.5 levels are spatially associated with the suicide rates across London. The two models show that PM2.5 levels have a positive association with adult suicide rates over space. An area with a high percentage of White people or a low median household income is likely to suffer from a high suicide rate.

ACS Style

Yeran Sun; Ting Chan; Jing Xie; Xuan Sun; Ying Huang. Examining Spatial Association of Air Pollution and Suicide Rate Using Spatial Regression Models. Sustainability 2020, 12, 7444 .

AMA Style

Yeran Sun, Ting Chan, Jing Xie, Xuan Sun, Ying Huang. Examining Spatial Association of Air Pollution and Suicide Rate Using Spatial Regression Models. Sustainability. 2020; 12 (18):7444.

Chicago/Turabian Style

Yeran Sun; Ting Chan; Jing Xie; Xuan Sun; Ying Huang. 2020. "Examining Spatial Association of Air Pollution and Suicide Rate Using Spatial Regression Models." Sustainability 12, no. 18: 7444.

Journal article
Published: 16 August 2020 in Sensors
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Pipe elbow joints exist in almost every piping system supporting many important applications such as clean water supply. However, spatial information of the elbow joints is rarely extracted and analyzed from observations such as point cloud data obtained from laser scanning due to lack of a complete geometric model that can be applied to different types of joints. In this paper, we proposed a novel geometric model and several model adaptions for typical elbow joints including the 90° and 45° types, which facilitates the use of 3D point clouds of the elbow joints collected from laser scanning. The model comprises translational, rotational, and dimensional parameters, which can be used not only for monitoring the joints’ geometry but also other applications such as point cloud registrations. Both simulated and real datasets were used to verify the model, and two applications derived from the proposed model (point cloud registration and mounting bracket detection) were shown. The results of the geometric fitting of the simulated datasets suggest that the model can accurately recover the geometry of the joint with very low translational (0.3 mm) and rotational (0.064°) errors when ±0.02 m random errors were introduced to coordinates of a simulated 90° joint (with diameter equal to 0.2 m). The fitting of the real datasets suggests that the accuracy of the diameter estimate reaches 97.2%. The joint-based registration accuracy reaches sub-decimeter and sub-degree levels for the translational and rotational parameters, respectively.

ACS Style

Ting On Chan; Linyuan Xia; Derek D. Lichti; Yeran Sun; Jun Wang; Tao Jiang; Qianxia Li. Geometric Modelling for 3D Point Clouds of Elbow Joints in Piping Systems. Sensors 2020, 20, 4594 .

AMA Style

Ting On Chan, Linyuan Xia, Derek D. Lichti, Yeran Sun, Jun Wang, Tao Jiang, Qianxia Li. Geometric Modelling for 3D Point Clouds of Elbow Joints in Piping Systems. Sensors. 2020; 20 (16):4594.

Chicago/Turabian Style

Ting On Chan; Linyuan Xia; Derek D. Lichti; Yeran Sun; Jun Wang; Tao Jiang; Qianxia Li. 2020. "Geometric Modelling for 3D Point Clouds of Elbow Joints in Piping Systems." Sensors 20, no. 16: 4594.

Articles
Published: 12 April 2020 in International Journal of Remote Sensing
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Urban villages (UVs) are commonly found in many Asian cities. These villages contain many closely packed buildings constructed decades ago without proper urban planning. There is a need for those buildings to be identified and put into statistics. In this paper, we present a segmentation framework that invokes multiple machine learning techniques and point cloud/image processing algorithms to segment individual closely packed buildings from large urban scenes. The presented framework consists of two major segmentation processes. The framework first filters out the non-ground objects from the point cloud, then it classified them by using the Random Forest classifier to isolate buildings from the entire scene. After that, the building point clouds will be segmented based on several building attribute analysis methods. This is followed by using the Random Sample Consensus (RANSAC) plane filtering method to expand the space between two closely packed buildings, so that the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) clustering technique can be used to more accurately segment each individual building from the closely packed building areas. Two airborne Light Detection and Ranging (LiDAR) datasets collected in two different cities with some typical closely packed buildings were used to verify the proposed framework. The results show that the framework can effectively identify the closely packed buildings with unified structures from large airborne LiDAR datasets. The overall segmentation accuracy reaches 84% for the two datasets. The proposed framework can serve as a basis for analysis and segmentation of closely packed buildings with a more complicated structure.

ACS Style

Xinsheng Wang; Ting On Chan; Kai Liu; Jun Pan; Ming Luo; Wenkai Li; Chunzhu Wei. A robust segmentation framework for closely packed buildings from airborne LiDAR point clouds. International Journal of Remote Sensing 2020, 41, 5147 -5165.

AMA Style

Xinsheng Wang, Ting On Chan, Kai Liu, Jun Pan, Ming Luo, Wenkai Li, Chunzhu Wei. A robust segmentation framework for closely packed buildings from airborne LiDAR point clouds. International Journal of Remote Sensing. 2020; 41 (14):5147-5165.

Chicago/Turabian Style

Xinsheng Wang; Ting On Chan; Kai Liu; Jun Pan; Ming Luo; Wenkai Li; Chunzhu Wei. 2020. "A robust segmentation framework for closely packed buildings from airborne LiDAR point clouds." International Journal of Remote Sensing 41, no. 14: 5147-5165.

Journal article
Published: 28 July 2018 in Sensors
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Measuring the volume of bird eggs is a very important task for the poultry industry and ornithological research due to the high revenue generated by the industry. In this paper, we describe a prototype of a new metrological system comprising a 3D range camera, Microsoft Kinect (Version 2) and a point cloud post-processing algorithm for the estimation of the egg volume. The system calculates the egg volume directly from the egg shape parameters estimated from the least-squares method in which the point clouds of eggs captured by the Kinect are fitted to novel geometric models of an egg in a 3D space. Using the models, the shape parameters of an egg are estimated along with the egg’s position and orientation simultaneously under the least-squares criterion. Four sets of experiments were performed to verify the functionality and the performance of the system, while volumes estimated from the conventional water displacement method and the point cloud captured by a survey-grade laser scanner serve as references. The results suggest that the method is straightforward, feasible and reliable with an average egg volume estimation accuracy 93.3% when compared to the reference volumes. As a prototype, the software part of the system was implemented in a post-processing mode. However, as the proposed processing techniques is computationally efficient, the prototype can be readily transformed into a real-time egg volume system.

ACS Style

Ting On Chan; Derek D. Lichti; Adam Jahraus; Hooman Esfandiari; Herve Lahamy; Jeremy Steward; Matthew Glanzer. An Egg Volume Measurement System Based on the Microsoft Kinect. Sensors 2018, 18, 2454 .

AMA Style

Ting On Chan, Derek D. Lichti, Adam Jahraus, Hooman Esfandiari, Herve Lahamy, Jeremy Steward, Matthew Glanzer. An Egg Volume Measurement System Based on the Microsoft Kinect. Sensors. 2018; 18 (8):2454.

Chicago/Turabian Style

Ting On Chan; Derek D. Lichti; Adam Jahraus; Hooman Esfandiari; Herve Lahamy; Jeremy Steward; Matthew Glanzer. 2018. "An Egg Volume Measurement System Based on the Microsoft Kinect." Sensors 18, no. 8: 2454.

Journal article
Published: 01 August 2016 in Photogrammetrie - Fernerkundung - Geoinformation
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ACS Style

Ting On Chan; Derek D. Lichti; David Belton; Bernhard Klingseisen; Petra Helmholz. Survey Accuracy Analysis of a Hand-held Mobile LiDAR Device for Cultural Heritage Documentation. Photogrammetrie - Fernerkundung - Geoinformation 2016, 2016, 153 -165.

AMA Style

Ting On Chan, Derek D. Lichti, David Belton, Bernhard Klingseisen, Petra Helmholz. Survey Accuracy Analysis of a Hand-held Mobile LiDAR Device for Cultural Heritage Documentation. Photogrammetrie - Fernerkundung - Geoinformation. 2016; 2016 (3):153-165.

Chicago/Turabian Style

Ting On Chan; Derek D. Lichti; David Belton; Bernhard Klingseisen; Petra Helmholz. 2016. "Survey Accuracy Analysis of a Hand-held Mobile LiDAR Device for Cultural Heritage Documentation." Photogrammetrie - Fernerkundung - Geoinformation 2016, no. 3: 153-165.

Journal article
Published: 01 April 2016 in Photogrammetric Engineering & Remote Sensing
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ACS Style

Ting On Chan; Derek D. Lichti; David Belton; Hoang Long Nguyen. Automatic Point Cloud Registration Using a Single Octagonal Lamp Pole. Photogrammetric Engineering & Remote Sensing 2016, 82, 257 -269.

AMA Style

Ting On Chan, Derek D. Lichti, David Belton, Hoang Long Nguyen. Automatic Point Cloud Registration Using a Single Octagonal Lamp Pole. Photogrammetric Engineering & Remote Sensing. 2016; 82 (4):257-269.

Chicago/Turabian Style

Ting On Chan; Derek D. Lichti; David Belton; Hoang Long Nguyen. 2016. "Automatic Point Cloud Registration Using a Single Octagonal Lamp Pole." Photogrammetric Engineering & Remote Sensing 82, no. 4: 257-269.

Journal article
Published: 17 August 2015 in Remote Sensing
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The Velodyne LiDAR series is one of the most popular spinning beam LiDAR systems currently available on the market. In this paper, the temporal stability of the range measurements of the Velodyne HDL-32E LiDAR system is first investigated as motivation for the development of a new automatic calibration method that allows quick and frequent recovery of the inherent time-varying errors. The basic principle of the method is that the LiDAR’s internal systematic error parameters are estimated by constraining point clouds of some known and automatically detected cylindrical features such as lamp poles to fit to the 3D cylinder models. This is analogous to the plumb-line calibration method in which the lens distortion parameters are estimated by constraining the image points of straight lines to fit to the 2D line model. The calibration can be performed at every measurement epoch in both static and kinematic modes. Four real datasets were used to verify the method, two of which were captured in static mode and the other two in kinematic mode. The overall results indicate that up to approximately 72% and 41% accuracy improvement were realized as a result of the calibration for the static and kinematic datasets, respectively.

ACS Style

Ting On Chan; Derek D. Lichti. Automatic In Situ Calibration of a Spinning Beam LiDAR System in Static and Kinematic Modes. Remote Sensing 2015, 7, 10480 -10500.

AMA Style

Ting On Chan, Derek D. Lichti. Automatic In Situ Calibration of a Spinning Beam LiDAR System in Static and Kinematic Modes. Remote Sensing. 2015; 7 (8):10480-10500.

Chicago/Turabian Style

Ting On Chan; Derek D. Lichti. 2015. "Automatic In Situ Calibration of a Spinning Beam LiDAR System in Static and Kinematic Modes." Remote Sensing 7, no. 8: 10480-10500.

Journal article
Published: 01 January 2015 in ISPRS Journal of Photogrammetry and Remote Sensing
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ACS Style

Ting On Chan; Derek D. Lichti; David Belton. A rigorous cylinder-based self-calibration approach for terrestrial laser scanners. ISPRS Journal of Photogrammetry and Remote Sensing 2015, 99, 84 -99.

AMA Style

Ting On Chan, Derek D. Lichti, David Belton. A rigorous cylinder-based self-calibration approach for terrestrial laser scanners. ISPRS Journal of Photogrammetry and Remote Sensing. 2015; 99 ():84-99.

Chicago/Turabian Style

Ting On Chan; Derek D. Lichti; David Belton. 2015. "A rigorous cylinder-based self-calibration approach for terrestrial laser scanners." ISPRS Journal of Photogrammetry and Remote Sensing 99, no. : 84-99.

Original article
Published: 21 February 2014 in The Photogrammetric Record
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Time‐of‐flight range cameras offer numerous advantages for the measurement of dynamic phenomena, thanks to their ability to directly measure three‐dimensional coordinates of objects at video rates using only one sensor. This paper reports the results of an investigation into the development of a range camera based system for measuring the deflection of reinforced concrete beams subjected to cyclic fatigue loading. New data segmentation methods and reconstruction algorithms have been developed to reconstruct the time‐dependent displacement of the beam with sub‐millimetre amplitude and millihertz‐level frequency precision and accuracy in all three dimensions along the entire beam length. Moreover, sub‐millimetre changes in displacement measurements due to stiffness degradation caused by fatigue are also reported.

ACS Style

Xiaojuan Qi; Derek D. Lichti; Mamdouh El-Badry; Ting On Chan; Sherif Ibrahim El-Halawany; Hervé Lahamy; Jeremy Steward. Structural Dynamic Deflection Measurement With Range Cameras. The Photogrammetric Record 2014, 29, 89 -107.

AMA Style

Xiaojuan Qi, Derek D. Lichti, Mamdouh El-Badry, Ting On Chan, Sherif Ibrahim El-Halawany, Hervé Lahamy, Jeremy Steward. Structural Dynamic Deflection Measurement With Range Cameras. The Photogrammetric Record. 2014; 29 (145):89-107.

Chicago/Turabian Style

Xiaojuan Qi; Derek D. Lichti; Mamdouh El-Badry; Ting On Chan; Sherif Ibrahim El-Halawany; Hervé Lahamy; Jeremy Steward. 2014. "Structural Dynamic Deflection Measurement With Range Cameras." The Photogrammetric Record 29, no. 145: 89-107.

Journal article
Published: 01 August 2013 in ISPRS Journal of Photogrammetry and Remote Sensing
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ACS Style

Ting On Chan; Derek D. Lichti; Craig L. Glennie. Multi-feature based boresight self-calibration of a terrestrial mobile mapping system. ISPRS Journal of Photogrammetry and Remote Sensing 2013, 82, 112 -124.

AMA Style

Ting On Chan, Derek D. Lichti, Craig L. Glennie. Multi-feature based boresight self-calibration of a terrestrial mobile mapping system. ISPRS Journal of Photogrammetry and Remote Sensing. 2013; 82 ():112-124.

Chicago/Turabian Style

Ting On Chan; Derek D. Lichti; Craig L. Glennie. 2013. "Multi-feature based boresight self-calibration of a terrestrial mobile mapping system." ISPRS Journal of Photogrammetry and Remote Sensing 82, no. : 112-124.

Journal article
Published: 01 May 2012 in Journal of Surveying Engineering
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Range cameras offer great potential for the measurement of structural deformations because of their ability to directly measure video sequences of three-dimensional coordinates of entire surfaces, their compactness, and their relatively low cost compared with other active imaging technologies such as terrestrial laser scanners. Identified limitations of range cameras for high-precision metrology applications such as deformation measurement include the high (centimeter level) noise level and scene-dependent errors. This paper proposes models and methodologies to overcome these limitations and reports on the use of a SwissRanger SR4000 range camera for the measurement of deflections in concrete beams subjected to flexural load-testing. Results from three separate tests show that submillimeter precision and accuracy—assessed by comparison with estimates derived from terrestrial laser scanner data—can be achieved. The high-accuracy range camera results were realized by eliminating the systematic, scene-dependent bias of internal scattering through measurement differencing and by reducing the influence of random errors with temporal and spatial filtering strategies. Additional experiments to validate some of the fundamental modeling assumptions and to explain the possible causes of residual, submillimeter biases in the deflection estimates are also reported.

ACS Style

Derek D. Lichti; Sonam Jamtsho; Sherif Ibrahim El-Halawany; Hervé Lahamy; Jacky Chow; Ting On Chan; Mamdouh El-Badry. Structural Deflection Measurement with a Range Camera. Journal of Surveying Engineering 2012, 138, 66 -76.

AMA Style

Derek D. Lichti, Sonam Jamtsho, Sherif Ibrahim El-Halawany, Hervé Lahamy, Jacky Chow, Ting On Chan, Mamdouh El-Badry. Structural Deflection Measurement with a Range Camera. Journal of Surveying Engineering. 2012; 138 (2):66-76.

Chicago/Turabian Style

Derek D. Lichti; Sonam Jamtsho; Sherif Ibrahim El-Halawany; Hervé Lahamy; Jacky Chow; Ting On Chan; Mamdouh El-Badry. 2012. "Structural Deflection Measurement with a Range Camera." Journal of Surveying Engineering 138, no. 2: 66-76.