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Remote sensing data is a primary means of obtaining information about the Earth's surface, widely used in various fields such as geographic information, natural resource management, urban planning, and environmental monitoring. However, due to the large volume and high complexity of remote sensing image data obtained from satellites, drones, and other equipment, efficient processing of this data and visualization of the results have become important issues. This paper presents a Cesium-based platform for visualizing multi-source remote sensing data, aimed at contributing to urban development efforts and providing additional insights for surveying education.This platform allows users to intuitively understand the spatial distribution and dynamic changes of remote sensing data. It not only integrates different types of remote sensing data into a unified 3D scene but also allows users to interact with the data according to their needs. A Cesium-based urban visualization platform was developed to display the geographic location of a specific region in Hong Kong and provide spatial measurement functions. This platform has wider applications in surveying and mapping education, as it can incorporate more remote sensing and geospatial data, allowing for increased student-teacher interaction and helping students better understand surveying and mapping concepts.Focusing on the construction of smart cities, the platform improves spatial awareness and interactivity for urban planning and management. Moreover, the platform has great potential in surveying and mapping education, providing a more immersive learning experience for students and cultivating talents in the field. [ABSTRACT FROM AUTHOR]

In 2013, the first electric taxis were launched in Hong Kong. In 2021, the HKSAR government announced that no new registration of fuel-propelled private cars, including hybrid vehicles, will be granted by the year 2035. Local public policies have shown a breakthrough milestone in the passenger transport sector and fostered the development of a smart city in Hong Kong as an international metropolis. This paper aims to study the feasibility of gradually introducing electric vehicles (EVs) in the Hong Kong taxi industry in the next decade. In particular, taxi license owners' intentions of purchasing electric vehicles for operational use and the driving behavior of taxi drivers in Hong Kong are investigated. Multiagent modelling with an integrated behavioral model is then adopted to analyze the survey data collected from 250 taxi drivers in Hong Kong, followed by interviews with industrial experts. The implications for future public policies are then discussed. To achieve emission reduction, the paper suggests a gradual, step-by-step promotion and transfer from conventional taxis to electric taxis in Hong Kong, with consideration of various factors and the interests of different stakeholders in the community. [ABSTRACT FROM AUTHOR]

The challenges brought by a growing number of large-scale land development projects (e.g., Northern Metropolis, Lantau Tomorrow, and related infrastructures) in Hong Kong must be met by innovative land acquisition planning and processes. A recent quick win solution to land supply for Works projects has been in trial commissioning the provisional draft land resumption plan preparations and related survey works from the government to consultants, specifically the Authorized Land Surveyor (ALS) in the private sector. The industry therefore must consider the necessary and diverse sources of expertise available, and the existing land surveying technical resources that will render support to such new initiatives. Collaboration is called for between the spheres of public sector, education, and works industry to successfully move the use of cadastral survey for land management forwards, bridging the gap between lands and works practices for efficient processing of Works projects, and smart city development of Hong Kong.This paper will examine the new approach of professional surveying that private practicing ALSs bring, and why the overall number of ALS and engineering surveyors in the construction industry is growing so slowly. It will additionally compare Hong Kong's practice with that of the mainland China, Singapore, and the UK to grasp global learning points. The paper recommends the establishment of a Cadastral Survey Lab (CSL) firstly to explore the policy implementation of a sound cadastral system. The processing of lot boundary determination by ALS is reviewed. The regulatory roles of the Land Survey Authority (LSA) are requested in approving new land boundary plans; this both replaces the Demarcation District (DD) Sheet boundary and improves land boundary records. Secondly, the CSL can serve as a coordinating body in curating various kinds of land records from diverse sources, and aids the research and knowledge management of cadastral survey, land law, land tenure, land registration systems, land boundary record keeping, problematic lot boundary determination, etc. These topics can be considered in the refining geomatics education curriculum, and furthermore developed into guidance notes for geomatics survey practitioners.The evolution of the traditional land surveying profession into the geomatics services has become a recent international trend that is growing in popularity in the survey profession. Combining geo-spatial data from the planning and design stages, alongside the use of standardised survey data processing in project implementation and asset management, would encourage data sharing, avoid duplicate efforts, and facilitate the formation of a digital city. The spectrums of geomatics education in universities should be widened with a refined curriculum on combining geomatics with cadastral survey that has evolved from the traditional lot boundary survey to multi-purpose cadastre, city information modelling, urban informatics, smart city administration, and a full-blown Spatial Data Infrastructure (SDI). [ABSTRACT FROM AUTHOR]

Using Hong Kong's smart city development as the case study, this paper aims to discover the influence of public trust on citizens' perception of Hong Kong's smart city performance in an international dimension, comparing with the smart city ranking by research agencies. Our central investigation further focuses on the association of public trust and digital trust, using COVID19 contact tracing app as an example. This paper uses data from a Hong Kong-based territory-wide survey in 2021 to conduct the analysis. The result suggests a positive relationship between public trust, subjective perception and digital trust, and supports that public acceptability is a cornerstone of an effective public policy. [ABSTRACT FROM AUTHOR]

Photorealistic three-dimensional (3D) models play an indispensable role in the spatial data infrastructure (SDI) of a smart city. Recent developments in aerial oblique photogrammetry, and the popularity of terrestrial mobile mapping systems (MMSs) offer possibilities for deriving 3D models with centimeter-level accuracy in urban areas. Additionally, advances in image matching and bundle adjustment have allowed 3D models derived from the integration of aerial and ground imagery to overcome typical problems related to 3D mapping in urban areas (e.g., geometric defects, blurred textures on building façades). Nevertheless, this approach may not be suitable for all scenarios owing to innate differences between each platform. Besides, MMS images may not cover regions that cannot be reached by mobile vehicles in urban areas (e.g., narrow alleys, areas far from roads). Meanwhile, backpack systems have garnered attention from the photogrammetry community in recent years due to their flexibility, and regions neglected in previous works can be adequately reconstructed from images collected by backpack systems. This paper presents an approach for effectively integrating multi-source images collected by aerial, MMS, and backpack platforms for seamless 3D mapping in urban areas. The approach includes three main steps: (1) data pre-processing, (2) combined structure-from-motion, and (3) optimal generation of a textured 3D mesh model. The experimental results using aerial, MMS, and backpack datasets collected in a typical urban area in Hong Kong demonstrate the promising performance of the proposed approach. The described work is significant for boosting various types of imagery for integrated 3D mapping in both city scale and street level to facilitate various applications. [ABSTRACT FROM AUTHOR]

Intelligent Parking Information Systems (IPIS) being implemented in the built environment are regarded as an effective measure for transport management in smart cities, where congestion due to parking search has caused air pollution apart from time wastage. An IPIS improves the efficiency of disseminating real time parking vacancy information and provides convenience to drivers via Apps installed in their smart phones. After giving an overview of various IPISs being applied globally, this research on a typical IPIS is aimed at valuing the benefits to drivers and modelling how variations in the independent variables affect their use. A stated preference approach is presented with a discrete choice survey conducted in Hong Kong with more than 800 valid samples. Contingent Valuation (CV) is applied to evaluate the intangible benefits associated with the use of IPIS, based on the estimation of Willingness-to-Pay (WTP) for its installation with a binary logit model. An aggregated WTP would be useful to policy makers when making decisions to scale up the system. It was found that three factors (download habit , parking time , and parking App usage) have positive impacts on WTP, whereas length of driving experience turned out to have a significantly negative influence. The econometric analysis provides useful contributions for the objective assessment of the viability of IPIS projects and their further investment in an emerging smart city environment. • Intelligent Parking Information Systems are increasing popular in smart cities. • Intangible benefits include reductions of congestion, parking time, pollution and accidents. • Contingent valuation is useful to evaluate the intangible benefits with demonstrable results. • Three related econometric models have been built to identify significant factors affecting the Willingness-to-Pay. [ABSTRACT FROM AUTHOR]

Along with the increase of big data and the advancement of technologies, comprehensive data-driven knowledge of urban systems is becoming more attainable, yet the connection between big-data research and its application e.g., in smart city development, is not clearly articulated. Focusing on Human Mobility, one of the most frequently investigated applications of big data analytics, a framework for linking international academic research and city-level management policy was established and applied to the case of Hong Kong. Literature regarding human mobility research using big data are reviewed. These studies contribute to (1) discovering the spatial-temporal phenomenon, (2) identifying the difference in human behaviour or spatial attributes, (3) explaining the dynamic of mobility, and (4) applying to city management. Then, the application of the research to smart city development are scrutinised based on email queries to various governmental departments in Hong Kong. The identified challenges include data isolation, data unavailability, gaming between costs and quality of data, limited knowledge derived from rich data, as well as estrangement between public and private sectors. With further improvement in the practical value of data analytics and the utilization of data sourced from multiple sectors, paths to achieve smarter cities from policymaking perspectives are highlighted. [ABSTRACT FROM AUTHOR]

The complexity and variety of buildings and the defects of point cloud data are the main challenges faced by 3D urban reconstruction from point clouds, especially in metropolitan areas. In this paper, we developed a method that embeds multiple relations into a procedural modelling process for the automatic 3D reconstruction of buildings from photogrammetric point clouds. First, a hybrid tree of constructive solid geometry and boundary representation (CSG-BRep) was built to decompose the building bounding space into multiple polyhedral cells based on geometric-relation constraints. The cells that approximate the shapes of buildings were then selected based on topological-relation constraints and geometric building models were generated using a reconstructing CSG-BRep tree. Finally, different parts of buildings were retrieved from the CSG-BRep trees, and specific surface types were recognized to convert the building models into the City Geography Markup Language (CityGML) format. The point clouds of 105 buildings in a metropolitan area in Hong Kong were used to evaluate the performance of the proposed method. Compared with two existing methods, the proposed method performed the best in terms of robustness, regularity, and topological correctness. The CityGML building models enriched with semantic information were also compared with the manually digitized ground truth, and the high level of consistency between the results suggested that the produced models will be useful in smart city applications. [ABSTRACT FROM AUTHOR]

Urban rail system is a critical component of a smart and sustainable city. This paper applies the triple bottom line framework to assess Hong Kong's mass transit railway (MTR) performance. We collected data from MTR's annual reports and sustainability reports over the period 2008–2017. The data showed that MTR's urban rail system consumed 1,573 GW-hour (GWh) in 2017, up from 1,290 GWh in 2008. In terms of service capacity, MTR's urban rail system made 1.767 billion passenger-trips in 2017, up from 1.309 billon passenger-trips in 2008. The average passenger-km (pkm) travelled ranged from 10.4 to 11 km for city lines and from 28.4 to 29.5 km for airport express. The total pkm travelled by rail was 19.38 billion in 2017, up from 13.82 billion in 2008. Sustainability analysis showed that MTR's urban rail system had an efficiency of 0.076–0.093 kWh per pkm and produced 0.055–0.071 kg CO 2 -eq per pkm. Tobin's q value ranged from 0.638 to 1.043, suggesting that MTR's stock was undervalued in the capital market over the past decade. In terms of social performance, MTR's rail operations provided over 15 thousand jobs and handled 38.2 percent of public transport in 2017. • HK's urban rail handled 1.767 billion passenger-trips and consumed 1,573 GWh in 2017. • The total passenger-km travelled was 19.38 billion in 2017. • HK's urban rail system had an energy efficiency of 0.076–0.093 kWh per passenger-km. • HK's urban rail system emitted 0.055–0.071 kg CO 2 -eq per passenger-km. • The system's environmental and social performance has improved in the past decade. [ABSTRACT FROM AUTHOR]