Meixu Chen
Biographic Data
| ID | 3985674 |
|---|---|
| NAME | Meixu Chen |
| GIVEN NAMES | Meixu |
| FAMILY NAME | Chen |
| SIGNATURE | CHEN M |
| AFFILIATIONS | University of Liverpool |
| ORCID | 0009-0006-7158-1035 |
| VERIFIED | Yes |
| TOTAL WORKS | 10 |
| TOTAL CITATIONS | 6 |
| AUTHOR COUNT | 10 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 1 |
A spatial typology of energy (in)efficiency in the private rental sector in England and Wales using Energy Performance Certificates
Like many countries globally, the private rental sector in England and Wales contains some of the lowest quality and energy inefficient properties, despite being home to some of the most vulnerable households. We present a new data product that classifies small areas based on the energy (in)efficiency characteristics of private rental properties. Newly available Energy Performance Certificate (EPC) data enables us to analyse detailed energy and h…
Perceptual hashing meets Hilbert curves: An innovative dimensionality reduction method for intercity morphological complexity comparison
A high-frequency city, born in the era of smart sensors and geo-big data, epitomises a self-organised urban form that sustains vitality, balances functions, and resilience, while confronting urban science with unprecedented complexity and heterogeneity. Differences in scale, morphology, and function across cities accumulate, reinforcing this rapidly evolving data landscape and shaping a dynamic, complex high-frequency urban system. To address thi…
Coping with the “new normal”: Assessing urban vibrancy resilience disparities through socioeconomic deprivation in New York City
Used For-Hire Vehicle trip data from 2019 to 2023 as a proxy for urban vibrancy. • Developed Urban Vibrancy Resilience Index (UVRI) via four resilience components. • Measured Carstairs Index (CI) from ACS to measure socioeconomic deprivation. • Unveiled a negative relationship between urban vibrancy resilience and deprivation. • Adjusted GWR model shows spatially varying CI impacts on vibrancy resilience
Mapping multidimensional energy deprivation: Socio-spatial inequalities and policy implications in Great Britain
This work provides a thorough Energy Deprivation Segmentation (EDS) for Great Britain, which aims to address the complex and varied aspects of energy poverty in different small regions. By proposing a reproducible analytical framework, we combine many data sources to provide a comprehensive segmentation that encompasses various dimensions such as energy efficiency, accessibility, demand and supply, housing conditions, and financial vulnerability.…
Vivid London: Assessing the resilience of urban vibrancy during the Covid-19 pandemic using social media data
A novel analytical framework is proposed to identify urban vibrancy. • Using Twitter and Flickr to assess the urban vibrancy resilience amid the pandemic. • Vibrant urban areas with certain common characteristics exhibit greater resilience. • Policy implications are provided for enhancing adaptability of urban vibrancy. Since COVID-19, the focus on urban resilience has intensified, particularly on cities' ability to adapt and recover while mainta…
Evaluation of green space influence on housing prices using machine learning and urban visual intelligence
Marxist foundation and historical development: Interpretation and practice in China's new era
Professor Chen Xianda's required course of Marxist Philosophy in the new era interprets the theory of socialism with Chinese characteristics in the new era theoretically, and tells people the Marxist philosophical basis of the theory of socialism with Chinese characteristics in the new era in a simple way. He wants to teach people to comprehensively and deeply understand the theory of socialism with new era characteristics on the basis of reading…
Assessing the value of user-generated images of urban surroundings for house price estimation
Determinants of housing prices are particularly significant for monitoring and understanding housing prices. Traditional variables are measured through official statistics or questionnaire surveys, which are labour intensive and time-consuming. New forms of data, such as point of interest or street view imagery, have been used to extract housing location and neighbourhood features, but they cannot capture how different individuals recognised and …
Identifying and understanding road-constrained areas of interest (AOIs) through spatiotemporal taxi GPS data: A case study in New York City
Urban areas of interest (AOIs) represent areas within the urban environment featuring high levels of public interaction, with their understanding holding utility for a wide range of urban planning applications. Within this context, our study proposes a novel space-time analytical framework and implements it to the taxi GPS data for the extent of Manhattan, NYC to identify and describe 31 road-constrained AOIs in terms of their spatiotemporal dist…
Quantifying the Characteristics of the Local Urban Environment through Geotagged Flickr Photographs and Image Recognition
Urban environments play a crucial role in the design, planning, and management of cities. Recently, as the urban population expands, the ways in which humans interact with their surroundings has evolved, presenting a dynamic distribution in space and time locally and frequently. Therefore, how to better understand the local urban environment and differentiate varying preferences for urban areas has been a big challenge for policymakers. This stud…
Evaluation of green space influence on housing prices using machine learning and urban visual intelligence
Coping with the “new normal”: Assessing urban vibrancy resilience disparities through socioeconomic deprivation in New York City
Used For-Hire Vehicle trip data from 2019 to 2023 as a proxy for urban vibrancy. • Developed Urban Vibrancy Resilience Index (UVRI) via four resilience components. • Measured Carstairs Index (CI) from ACS to measure socioeconomic deprivation. • Unveiled a negative relationship between urban vibrancy resilience and deprivation. • Adjusted GWR model shows spatially varying CI impacts on vibrancy resilience
Mapping multidimensional energy deprivation: Socio-spatial inequalities and policy implications in Great Britain
This work provides a thorough Energy Deprivation Segmentation (EDS) for Great Britain, which aims to address the complex and varied aspects of energy poverty in different small regions. By proposing a reproducible analytical framework, we combine many data sources to provide a comprehensive segmentation that encompasses various dimensions such as energy efficiency, accessibility, demand and supply, housing conditions, and financial vulnerability.…
Quantifying the Characteristics of the Local Urban Environment through Geotagged Flickr Photographs and Image Recognition
Urban environments play a crucial role in the design, planning, and management of cities. Recently, as the urban population expands, the ways in which humans interact with their surroundings has evolved, presenting a dynamic distribution in space and time locally and frequently. Therefore, how to better understand the local urban environment and differentiate varying preferences for urban areas has been a big challenge for policymakers. This stud…
Identifying and understanding road-constrained areas of interest (AOIs) through spatiotemporal taxi GPS data: A case study in New York City
Urban areas of interest (AOIs) represent areas within the urban environment featuring high levels of public interaction, with their understanding holding utility for a wide range of urban planning applications. Within this context, our study proposes a novel space-time analytical framework and implements it to the taxi GPS data for the extent of Manhattan, NYC to identify and describe 31 road-constrained AOIs in terms of their spatiotemporal dist…
Assessing the value of user-generated images of urban surroundings for house price estimation
Determinants of housing prices are particularly significant for monitoring and understanding housing prices. Traditional variables are measured through official statistics or questionnaire surveys, which are labour intensive and time-consuming. New forms of data, such as point of interest or street view imagery, have been used to extract housing location and neighbourhood features, but they cannot capture how different individuals recognised and …
Vivid London: Assessing the resilience of urban vibrancy during the Covid-19 pandemic using social media data
A novel analytical framework is proposed to identify urban vibrancy. • Using Twitter and Flickr to assess the urban vibrancy resilience amid the pandemic. • Vibrant urban areas with certain common characteristics exhibit greater resilience. • Policy implications are provided for enhancing adaptability of urban vibrancy. Since COVID-19, the focus on urban resilience has intensified, particularly on cities' ability to adapt and recover while mainta…
Evaluation of green space influence on housing prices using machine learning and urban visual intelligence
Marxist foundation and historical development: Interpretation and practice in China's new era
Professor Chen Xianda's required course of Marxist Philosophy in the new era interprets the theory of socialism with Chinese characteristics in the new era theoretically, and tells people the Marxist philosophical basis of the theory of socialism with Chinese characteristics in the new era in a simple way. He wants to teach people to comprehensively and deeply understand the theory of socialism with new era characteristics on the basis of reading…
A spatial typology of energy (in)efficiency in the private rental sector in England and Wales using Energy Performance Certificates
Like many countries globally, the private rental sector in England and Wales contains some of the lowest quality and energy inefficient properties, despite being home to some of the most vulnerable households. We present a new data product that classifies small areas based on the energy (in)efficiency characteristics of private rental properties. Newly available Energy Performance Certificate (EPC) data enables us to analyse detailed energy and h…
Perceptual hashing meets Hilbert curves: An innovative dimensionality reduction method for intercity morphological complexity comparison
A high-frequency city, born in the era of smart sensors and geo-big data, epitomises a self-organised urban form that sustains vitality, balances functions, and resilience, while confronting urban science with unprecedented complexity and heterogeneity. Differences in scale, morphology, and function across cities accumulate, reinforcing this rapidly evolving data landscape and shaping a dynamic, complex high-frequency urban system. To address thi…
Coping with the “new normal”: Assessing urban vibrancy resilience disparities through socioeconomic deprivation in New York City
Used For-Hire Vehicle trip data from 2019 to 2023 as a proxy for urban vibrancy. • Developed Urban Vibrancy Resilience Index (UVRI) via four resilience components. • Measured Carstairs Index (CI) from ACS to measure socioeconomic deprivation. • Unveiled a negative relationship between urban vibrancy resilience and deprivation. • Adjusted GWR model shows spatially varying CI impacts on vibrancy resilience
Mapping multidimensional energy deprivation: Socio-spatial inequalities and policy implications in Great Britain
This work provides a thorough Energy Deprivation Segmentation (EDS) for Great Britain, which aims to address the complex and varied aspects of energy poverty in different small regions. By proposing a reproducible analytical framework, we combine many data sources to provide a comprehensive segmentation that encompasses various dimensions such as energy efficiency, accessibility, demand and supply, housing conditions, and financial vulnerability.…
Computer Science (6 works) · Geography (6 works) · Sociology (4 works) · Artificial Intelligence (3 works) · Economics (3 works) · Housing Market and Economics (3 works) · Human Mobility and Location-Based Analysis (3 works) · Land Use and Ecosystem Services (3 works) · Cartography (2 works) · Cluster analysis (2 works)