Zihan KanThe Chinese University of Hong Kong | CUHK · Department of Geography and Resource Management
Zihan Kan
Doctor of Philosophy
About
56
Publications
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Introduction
I strive to address the issues of the impact of the environment on human health through the lens of movement flows, transportation related emissions and traffic congestion, and built environment. My research primarily relies on large movement datasets (e.g., GPS trajectories), together with a variety of other data sources including remote sensing, land use, built environment and activity travel diaries.
Additional affiliations
February 2019 - August 2019
Education
October 2017 - December 2018
September 2014 - December 2019
Publications
Publications (56)
The energy consumption and emissions from vehicles adversely affect human health and urban sustainability. Analysis of GPS big data collected from vehicles can provide useful insights about the quantity and distribution of such energy consumption and emissions. Previous studies, which estimated fuel consumption/emissions from traffic based on GPS s...
Identifying the space-time patterns of areas with a higher risk of transmission and the associated built environment and demographic characteristics during the COVID-19 pandemic is critical for developing targeted intervention measures in response to the pandemic. This study aims to identify areas with a higher risk of COVID-19 transmission in diff...
Mining traffic congestion dynamics presents difficulties in data structure and spatiotemporal analysis. Existing studies mainly provide insights from a supply perspective, with a restricted examination of why congestion occurs and how travel demands affect congestion. This study introduces an innovative framework to mine congestion dynamics from th...
Greenspaces are crucial for enhancing mental and physical health. Recent research has shifted from static methods of assessing exposure to greenspaces, based on fixed locations, to dynamic approaches that account for individual mobility. These dynamic evaluations utilize advanced technologies like GPS tracking and remote sensing to provide more pre...
Developing walkable urban environments is crucial for enhancing urban liveability and sustainability. To evaluate the chrono‐urbanism status, this study combines conventional census and mapping data with social media check‐in big data. A composite index is proposed, which assesses the accessibility of essential urban functions under the 5/10/15‐min...
Urban traffic anomaly diagnosis is crucial for urban road management and smart city construction. Most existing methods perform anomaly detection from a data-driven perspective and ignore the unique spatiotemporal characteristics of traffic anomalies, resulting in reduced accuracy or incorrect extraction of anomalies. In this study, we integrate ge...
With the advent of the information age and rapid population growth, the urban transportation environment is deteriorating. Travel-route planning is a key issue in modern sustainable transportation systems. When conducting route planning, identifying the spatiotemporal disparities between planned routes and the routes chosen by actual drivers, as we...
Annoyance is a major health burden induced by environmental noise. However, our understanding of the health impacts of noise is seriously undermined by the fixed contextual unit and limited sound characteristics (e.g., the sound level only) used in noise exposure assessments as well as the stationarity assumption made for exposure-response relation...
A range of vehicle routing problems, from routing planning that vehicles will apply to the actual route that drivers selected in their environment, depend on many factors including travel length, traffic condition, or personalized experience, etc., raising a fundamental question: To what degree is planned route align with the actual route. Here we...
As public awareness of air quality issues becomes heightened, people’s perception of air quality is drawing increasing academic interest. However, data about people’s perceived environment need scrutiny before being used in environmental health studies. In this research, we examine the associations between people’s perceptions of air quality and th...
Good access to greenspace and healthy food has commonly been found to be positively associated with health outcomes, despite some studies finding no significant relationship between them. Examining inequalities in accessing greenspace and healthy food among different disadvantaged neighborhoods can help reveal the disadvantaged races/ethnicities in...
Exposure to green-blue space has been shown to be associated with better physical and mental health outcomes. The advent of COVID-19 has underlined the importance for people to have access to green-blue spaces in proximity to their residences due to pandemic-related restrictions on activity space. The implementation of the 15-min concept, which adv...
Community shuttle services have the potential to alleviate traffic congestion and reduce traffic pollution caused by massive short-distance taxi-hailing trips. However, few studies have evaluated and quantified the impact of community shuttle services on urban traffic and traffic-related air pollution. In this paper, we propose a complete framework...
With the ongoing spread of COVID-19, vaccination stands as an effective measure to control and mitigate the impact of the disease. However, due to the unequal distribution of COVID-19 vaccination sites, people can have different levels of spatial accessibility to COVID-19 vaccination. This study adopts an improved gravity-based model to measure the...
Inequalities in accessibility to grocery stores can lead to disparate health outcomes among the population. Although existing studies have examined grocery accessibility inequality across income and racial/ethnic groups, little research has been dedicated to revealing the intra‐racial disparities of grocery accessibility and comparing inter‐racial...
In this study, we examined the relationships between housing characteristics, neighborhood built-environment features, and people’s mental health in Hong Kong, an Asian city well known for its high-density and high-rise housing. The potential mediating effects of people’s perceived living environment were also considered in the analysis. We collect...
Public transit is the main travel mode for residents in major urban areas to access different socioeconomic resources. Nodal accessibility can be used to measure the level of transit-based connectivity for residents from one neighborhood to socioeconomic resources in other neighborhoods. While many existing studies have measured the spatial inequal...
This paper seeks to evaluate and calibrate data collected by low-cost particulate matter (PM) sensors in different environments and using different aggregated temporal units (i.e., 5-s, 1-min, 10-min, 30 min intervals). We first collected PM concentrations (i.e., PM1, PM2.5, and PM10) data in five different environments (i.e., indoor and outdoor of...
Accurately assessing individual exposures to traffic congestion and traffic-related emissions is important for evaluating the impact of traffic congestion on human health. Existing studies on individual exposures to traffic congestion focus mainly on commuting trips, while our understanding of individual exposures to traffic congestion during diffe...
Previous studies observed that most COVID-19 infections were transmitted by a few individuals at a few high-risk places (e.g., bars or social gathering venues). These individuals, often called superspreaders, transmit the virus to an unexpectedly large number of people. Further, a small number of superspreading places (SSPs) where this occurred acc...
Public transit is indispensable for car-free households to access healthcare. Meanwhile, different households have unequal transit-based healthcare accessibility due to different socio-economic factors such as race/ethnicity and car ownership. Few studies have comprehensively explored the inequality in transit-based healthcare accessibility by inte...
The acquisition of human trajectories facilitates movement data analytics and location-based services, but gaps in trajectories limit the extent in which many tracking datasets can be utilized. We present a model to estimate place visit probabilities at time points within a gap, based on empirical mobility patterns derived from past trajectories. D...
This study compares the space‐time patterns and characteristics of high‐risk areas of COVID‐19 transmission in Hong Kong between January 23 and April 14 (the first and second waves) and between July 6 and August 29 (the third wave). Using space‐time scan statistics and the contact tracing data of individual confirmed cases, we detect the clusters o...
Many types of spatial flows, including pedestrian flows and vehicle flows, are constrained by and distribute on spatial networks. In the literature, network-constrained flows are usually modeled as a direct line in planar space using methods designed for flows in planar space. Further, in spatial statistical analysis of flow patterns, distance meas...
Origin-Destination (OD) flow, as an abstract representation of the object`s movement or interaction, has been used to reveal the urban mobility and human-land interaction pattern. As an important spatial analysis approach, the clustering methods of point events have been extended to OD flows to identify the dominant trends and spatial structures of...
This study examines the job-access inequity between the richest 10% and poorest 40% transit-based workers across space (i.e. central city, the inner-ring/outer-ring suburb) and race (i.e. white, black and Hispanic) in Chicago. The results indicate that there are job-access inequities across both space and race. In terms of job-access inequity acros...
The novel coronavirus disease (COVID-19) has become a public health problem at a global scale because of its high infection and mortality rate. It has affected most countries in the world, and the number of confirmed cases and death toll is still growing rapidly. Susceptibility studies have been conducted in specific countries, where COVID-19 infec...
An integrated analysis of housing and transport affordability provides comprehensive insights into the affordability of different locations in a city. By focusing on transit‐based workers, who constitute a significant portion of commuters but are understudied in the affordability literature, this study proposes a new, integrated method for estimati...
Urban green space (UGS) has positive impacts on people’s physical and mental health. Equal access to UGS for all people, regardless of their individual characteristics, is key to the achievement of better public health outcomes. Existing studies have focused largely on inequity in spatial UGS accessibility distribution but failed to uncover the dis...
The World Health Organization considered the widespread of COVID-19 over the world as a pandemic. There is still a lack of understanding of its origin, transmission, and treatment methods. Understanding the influencing factors of the COVID-19 can help mitigate its spread, but little research on the spatial factors has been conducted. Therefore, thi...
Understanding the relationship between the built environment and the risk of COVID-19 transmission is essential to respond to the pandemic. This study explores the relationship between the built environment and COVID-19 risk using the confirmed cases data collected in Hong Kong. Using the information on the residential buildings and places visited...
In taxi management, taxi-driver shift behaviors play a key role in arranging the operation of taxis, which affect the balance between the demand and supply of taxis and the parking spaces. At the same time, these behaviors influence the daily travel of citizens. An analysis of the distribution of taxi-driver shifts, therefore, contributes to transp...
Cloud and cloud shadow detection is one of the most important tasks for optical remote sensing image preprocessing. It is not an easy task due to the variety and complexity of underlying surfaces, such as the low-albedo objects (water and mountain shadow) and the high-albedo objects (snow and ice). In this study, an end-to-end multiscale 3D-CNN met...
The design of urban clusters has played an important role in urban planning, but realizing the construction of these urban plans is quite a long process. Hence, how the progress is evaluated is significant for urban managers in the process of urban construction. Traditional methods for detecting urban clusters are inaccurate since the raw data is g...
The fuel-consumption and emissions from transportation present severe challenges to the human environment. This article proposes a novel approach of space-time path supported estimation for vehicles' fuel-consumption and emissions. In the proposed approach, space-time paths of vehicles are built under space-time integrated 3-dimensions coordinate f...
The conventional methods of road change detection have disadvantages in terms of the data acquisition period, data cost, algorithmic complexity, calculation difficulty, and periodic updating. In this paper, by making full use of taxi GPS trajectory data distribution and timeliness, a new road network topology change detection method based on vehicl...
The unbalanced distribution of taxi passengers in space and time affects taxi driver performance. Existing research has studied taxi driver performance by analyzing taxi driver strategies when the taxi is occupied. However, searching for passengers when vacant is costly for drivers, and it limits operational efficiency and income. Few researchers h...
Kernel density estimation (KDE) is an important method for analyzing spatial distributions of point features or linear features. So far the KDE methods for linear features analyze the features' spatial distributions by producing a smooth density surface over 2D homogeneous planar space, However, the planar KDE methods are not suited for analyzing t...
Existing studies of big data taxi GPS tracesdo not consider the characteristics and demands of out-of-service taxi driver activities, such as refueling, dining, and shifting activities. This paper studies the these short-term out-of-service behaviors, extracts short-term out-of-service behaviors from taxi trace data, and analyzes the spatio tempora...
Aiming at characteristics of low cost, rapid collection speed, wide coverage and massive traffic information in collecting floating car data (FCD), a rapid method to obtain urban lane number information based on FCD was proposed. Firstly, the density clustering method based on Delaunay triangulation network was used to choose the optimum data consi...
Intersections are the critical parts where different traffic flows converge and change directions, forming “bottlenecks” and “clog points” in urban traffic. Intersection travel time is an important parameter for public route planning, traffic management, and engineering optimization. Based on low-frequency spatial-temporal Global Positioning System...
Intersections are the critical points of urban transportation, acting as bottlenecks and clog points in urban traffic. The travel time through intersections is highly uncertain and comprises a large proportion of the overall travel time. Detecting the intersection travel time in different turning directions could contribute to improved efficiency i...
Kernel Density Estimation (KDE) is an important approach to analyse spatial distribution of point features and linear features over 2-D planar space. Some network-based KDE methods have been developed in recent years, which focus on estimating density distribution of point events over 1-D network space. However, the existing KDE methods are not app...
In this paper, we propose a novel approach for mining lane-level road network information from low-precision vehicle GPS trajectories (MLIT), which includes the number and turn rules of traffic lanes based on naïve Bayesian classification. First, the proposed method (MLIT) uses an adaptive density optimization method to remove outliers from the raw...
The spatio-temporal trajectory of taxi GPS data in streets and small lanes of Wuhan city is taken as the experiment data source, based on the “perceptual-cognition-experience” three levels of cognitive law, a new approach for track fusion and road network generation is put forward from the GPS spatio-temporal trajectories. The experiment with the t...
It is very difficult to transmit spatial data over the Internet rapidly because of huge data volume and limited network bandwidth. How to transmit spatial data over the Internet is becoming a big problem. Based on the Distance View and the Characteristic Set View, this paper proposes a Spatial Data Similarity Model (SDSM) and a set of methods to me...
Intersection is the bottleneck of city traffic and the major contributing factor to traffic delay, which has a great impact on path selection. This paper first analyzes and models the turning characteristic at typical intersections, then discusses the analysis result of typical intersections in Wuhan city based on floating car data, and finally ver...