This paper develops an empirical framework to better understand social and residential mobility i... more This paper develops an empirical framework to better understand social and residential mobility in terms of outcomes as revealed using Linked Consumer Registers that detail individual level origins and destinations throughout the nations of the UK. We describe work to analyse these data at a range of geographic scales and to link them to further data sources. We discuss the value and applicability of the data sources and set out a research agenda.
This research applies a hierarchical k-means clustering method on the TF-IDF weighted 2019 cyclin... more This research applies a hierarchical k-means clustering method on the TF-IDF weighted 2019 cycling transactions from the Citi Bike bike-sharing system operating in New York City, with the primary goal of investigating the spatiotemporal usage pattern of its docking points. With a particular focus on bike-sharing stations in Manhattan, we classify 504 stations into four main clusters featuring heterogeneous dynamic usages, including leisure-oriented, residential- oriented, workplace-oriented, and off-peak oriented. We interpret each cluster based on their salient characteristics and anticipate possible future directions of this work.
Satellite imagery is often used to study and monitor Earth surface changes. The open availability... more Satellite imagery is often used to study and monitor Earth surface changes. The open availability and extensive temporal coverage of Landsat imagery has enabled changes in temperature, wind, vegetation and ice melting speed for a period of up to 46 years. Yet, the use of satellite imagery to study cities has remained underutilised, partly due to the lack of a methodological approach to capture features and changes in the urban environment. This notebook offers a framework based on Python tools to demonstrate how to batch-download high-resolution satellite imagery; and enable the extraction, analysis and visualisation of features of the built environment to capture long-term urban changes.
This paper develops an empirical framework to better understand social and residential mobility i... more This paper develops an empirical framework to better understand social and residential mobility in terms of outcomes as revealed using Linked Consumer Registers that detail individual level origins and destinations throughout the nations of the UK. We describe work to analyse these data at a range of geographic scales and to link them to further data sources. We discuss the value and applicability of the data sources and set out a research agenda.
This research applies a hierarchical k-means clustering method on the TF-IDF weighted 2019 cyclin... more This research applies a hierarchical k-means clustering method on the TF-IDF weighted 2019 cycling transactions from the Citi Bike bike-sharing system operating in New York City, with the primary goal of investigating the spatiotemporal usage pattern of its docking points. With a particular focus on bike-sharing stations in Manhattan, we classify 504 stations into four main clusters featuring heterogeneous dynamic usages, including leisure-oriented, residential- oriented, workplace-oriented, and off-peak oriented. We interpret each cluster based on their salient characteristics and anticipate possible future directions of this work.
Satellite imagery is often used to study and monitor Earth surface changes. The open availability... more Satellite imagery is often used to study and monitor Earth surface changes. The open availability and extensive temporal coverage of Landsat imagery has enabled changes in temperature, wind, vegetation and ice melting speed for a period of up to 46 years. Yet, the use of satellite imagery to study cities has remained underutilised, partly due to the lack of a methodological approach to capture features and changes in the urban environment. This notebook offers a framework based on Python tools to demonstrate how to batch-download high-resolution satellite imagery; and enable the extraction, analysis and visualisation of features of the built environment to capture long-term urban changes.
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Papers by Meixu Chen