Avatar

Chaogui Kang

Associate Professor of GIScience

Wuhan University

Dr. Chaogui Kang is an associate professor of Geographic Information Science at Wuhan University, and currently a visiting scholar at New York University’s Center for Urban Science + Progress. He was trained in Geography, Data Science, Complex Network, and is leading a dynamic research group – Urban CoLab @ Wuhan University – with the mission to develop data-driven, human-centric, and cross-cutting methodologies for tackling urban problems from a geospatial perspective. His primary research interest lies in the intersections of Travel Behavior, Built Environment and Social Inequality with the assistance of pervasive urban sensing techniques.

Dr. Chaogui Kang graduated in Geographic Information Science from Nanjing University (BSc) and Peking University (PhD with Honor). He was also visiting scholar and research affiliate in SENSEable City Lab at Massachusetts Institute of Technology, and had held a joint position as research associate in Department of Land Surveying and Geo-Informatics at The Hong Kong Polytechnic University. In his spare time, he enjoys swimming, playing badminton and basketball.

Articles

Validating activity, time, and space diversity as essential components of urban vitality

Urbanization’s rapid progress presents an urgent challenge for developing a predictive, quantita- tive theory of “the death and life of cities” (a.k.a. “the essential diversity conditions for the urban built environment”). Despite the importance of activity diversity (i.e. serving different primary functions), existing works ignored that time diversity (i.e. attracting people at …
PDF DOI

Escaping from pollution: The effect of air quality on inter-city population mobility in China

China faces severe air pollution issues after the rapid growth of economy, causing human physical and mental health concerns as well as behavioral changes. Such adverse impacts can be mediated by individual avoidance behaviors such as traveling from polluted cities to the cleaner ones. This study utilizes smartphone-based location data and instrumental variable (IV) regression to …
PDF

Modeling Spatio-Temporal Evolution of Urban Crowd Flows

Metropolitan cities are facing many socio-economic problems (e.g., frequent traffic congestion, unexpected emergency events, and even human-made disasters) related to urban crowd flows, which can be described in terms of the gathering process of a flock of moving objects (e.g., vehicles, pedestrians) towards specific destinations during a given time period via different travel …
PDF DOI

Understanding the interplay between bus, metro, and cab ridership dynamics in Shenzhen, China

Abstract The most common mass transit modes in metropolitan cities include buses, subways, and taxicabs, each of which contribute to an interconnected complex network that delivers urban dwellers to their destinations. Understanding the intertwined usages of these three transit modes at different places and time allows for better sensing of urban mobility and the built environment. …
PDF DOI

A framework for mixed-use decomposition based on temporal activity signatures extracted from big geo-data

ABSTRACTMixed use has been extensively applied as an urban planning principle and hinders the study of single urban functions. To address this problem, it is worth decomposing the mixed use. Inspired by the concept of spectral unmixing in remote sensing applications, this paper proposes a framework for mixed-use decomposition based on big geo-data. Mixed-use decomposition in terms …
PDF DOI

Quantifying Tourist Behavior Patterns by Travel Motifs and Geo-Tagged Photos from Flickr

With millions of people traveling to unfamiliar cities to spend holidays, travel recommendation becomes necessary to assist tourists in planning their trips more efficiently. Serving as a prerequisite to travel recommender systems, understanding tourist behavior patterns is therefore of great importance. Recently, geo-tagged photos on social media platforms like Flickr have provided …
PDF DOI

Incorporating spatial interaction patterns in classifying and understanding urban land use

ABSTRACTLand use classification has benefited from the emerging big data, such as mobile phone records and taxi trajectories. Temporal activity variations derived from these data have been used to interpret and understand the land use of parcels from the perspective of social functions, complementing the outcome of traditional remote sensing methods. However, spatial interaction …
PDF DOI

Predicting vehicular emissions in high spatial resolution using pervasively measured transportation data and microscopic emissions model

Air pollution related to traffic emissions pose an especially significant problem in cities; this is due to its adverse impact on human health and well-being. Previous studies which have aimed to quantify emissions from the transportation sector have been limited by either simulated or coarsely resolved traffic volume data. Emissions inventories form the basis of urban pollution …
PDF DOI

Understanding operation behaviors of taxicabs in cities by matrix factorization

Taxicabs play significant roles in public transport systems in large cities. To meet repetitive demands of daily intra-urban travels, cabdrivers acquire self-organized habitual operation behaviors in space and time, largely with assistance of their longitudinal operating experience. Recognizing those collective operation behavior patterns of taxicabs will enable us to better design …
PDF DOI

Social Sensing: A New Approach to Understanding Our Socioeconomic Environments

The emergence of big data brings new opportunities for us to understand our socioeconomic environments. We use the term social sensing for such individual-level big geospatial data and the associated analysis methods. The word sensing suggests two natures of the data. First, they can be viewed as the analogue and complement of remote sensing, as big data can capture well …
PDF DOI

A Generalized Radiation Model for Human Mobility: Spatial Scale, Searching Direction and Trip Constraint

We generalized the recently introduced “radiation model”, as an analog to the generalization of the classic “gravity model”, to consolidate its nature of universality for modeling diverse mobility systems. By imposing the appropriate scaling exponent λ, normalization factor κ and system constraints including searching direction and trip OD constraint, the generalized radiation model …
PDF DOI

Analyzing Relatedness by Toponym Co-Occurrences on Web Pages

Abstract This research proposes a method for capturing “relatedness between geographical entities” based on the co-occurrences of their names on web pages. The basic assumption is that a higher count of co-occurrences of two geographical places implies a stronger relatedness between them. The spatial structure of China at the provincial level is explored from the co-occurrences of …
PDF DOI

The impact of social segregation on human mobility in developing and industrialized regions

This study leverages mobile phone data to analyze human mobility patterns in a developing nation, especially in comparison to those of a more industrialized nation. Developing regions, such as the Ivory Coast, are marked by a number of factors that may influence mobility, such as less infrastructural coverage and maturity, less economic resources and stability, and in some cases, …
PDF DOI

Uncovering Patterns of Inter-Urban Trip and Spatial Interaction from Social Media Check-In Data

The article revisits spatial interaction and distance decay from the perspective of human mobility patterns and spatially-embedded networks based on an empirical data set. We extract nationwide inter-urban movements in China from a check-in data set that covers half a million individuals within 370 cities to analyze the underlying patterns of trips and spatial interactions. By …
PDF DOI

Inferring properties and revealing geographical impacts of intercity mobile communication network of China using a subnet data set

This article provides a novel and practical approach for investigating the characteristics of intercity telecommunication network whose overall and complete information is unavailable. Using a mobile phone call data set covering 4.39 million subscribers registered in a particular region, we construct two intercity mobile communication subnets and infer characteristics of the whole …
PDF DOI

Understanding intra-urban trip patterns from taxi trajectory data

Intra-urban human mobility is investigated by means of taxi trajectory data that are collected in Shanghai, China, where taxis play an important role in urban transportation. From the taxi trajectories, approximately 1.5 million trips of anonymous customers are extracted on seven consecutive days. The globally spatio-temporal patterns of trips exhibit a significant daily regularity. …
PDF DOI

Intra-urban human mobility patterns: An urban morphology perspective

This paper provides a new perspective on human motion with an investigation of whether and how patterns of human mobility inside cities are affected by two urban morphological characteristics: compactness and size. Mobile phone data have been collected in eight cities in Northeast China and used to extract individuals’ movement trajectories. The massive mobile phone data provides a …
PDF DOI

Towards Estimating Urban Population Distributions from Mobile Call Data

Today, large-volume mobile phone call datasets are widely applied to investigate the spatio-temporal characteristics of human urban activity. This paper discusses several fundamental issues in estimating population distributions based on mobile call data. By adopting an individual-based call activity dataset that consists of nearly two million mobile subscribers who made over one …
PDF DOI