Hanchen Yu
Biographic Data
| ID | 3635548 |
|---|---|
| NAME | Hanchen Yu |
| GIVEN NAMES | Hanchen |
| FAMILY NAME | Yu |
| SIGNATURE | YU H |
| AFFILIATIONS | Harvard University |
| ORCID | 0000-0002-3246-8586 |
| VERIFIED | Yes |
| TOTAL WORKS | 14 |
| TOTAL CITATIONS | 10 |
| WORKS AS AUTHOR | 14 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 2 |
Covid-19 pandemic and road infrastructure exerted stage-dependent spatiotemporal influences on inter-city road travel in China
As the COVID-19 pandemic recedes and travel resumes, it is important to understand how the influences on inter-city road travel varied across different stages of the pandemic. However, the underlying spatiotemporal heterogeneity in the relationship between the mobility shifts and its determinants at different pandemic stages is unclear. This research divides the pandemic timeline into four distinct stages based on the data from the Chinese Health…
Generalized geographically and temporally weighted regression
Multiscale Geographically Weighted Zero-Inflated Negative Binomial Regression
Exploring Multiscale Spatial Interactions
In this article, I develop and implement the multiscale geographically weighted negative binomial (MGWNB) model, extending the spatially weighted interaction models by integrating a multiscale framework. This model effectively tackles the multiscale nonstationarity and overdispersion issues found in spatial interaction models. By comparing it with multiscale geographically weighted Poisson regression using simulated data, I demonstrate its superi…
Understanding the Geography of Covid-19 Case Fatality Rates in China
This study employs a spatial autoregressive probit-log linear (SAP-Log) hurdle model to investigate the influencing factors on the probability of death and case fatality rate (CFR) of coronavirus disease 2019 (COVID-19) at the city level in China. The results demonstrate that the probability of death from COVID-19 and the CFR level are 2 different processes with different determinants. The number of confirmed cases and the number of doctors are c…
Assessing Reliability of Chinese Geotagged Social Media Data for Spatiotemporal Representation of Human Mobility
Understanding the space-time dynamics of human activities is essential in studying human security issues such as climate change impacts, pandemic spreading, or urban sustainability. Geotagged social media posts provide an open and space-time continuous data source with user locations which is convenient for studying human movement. However, the reliability of Chinese geotagged social media data for representing human mobility remains unclear. Thi…
Multiscale Effects of Multimodal Public Facilities Accessibility on Housing Prices Based on MGWR
The layout of public service facilities and their accessibility are important factors affecting spatial justice. Previous studies have verified the positive influence of public facilities accessibility on house prices; however, the spatial scale of the impact of various public facilities accessibility on house prices is not yet clear. This study takes transportation analysis zone of Wuhan city as the spatial unit, measure the public facilities ac…
Are We Modelling Spatially Varying Processes or Non‐linear Relationships
Studies of spatially varying parameter estimates obtained in the calibration of various types of local statistical models are commonplace. The variation in such estimates is typically explained in terms of spatially varying processes. This paper highlights that an alternative explanation for spatially varying parameter estimates, in terms of non‐linearity, should be examined prior to relating such variation to spatially varying processes. This ca…
Is dense or sprawl growth more prone to heat-related health risks? Spatial regression-based study in Delhi, India
Spatial variation in bicycling risk based on crowdsourced safety data
Bicycling‐related injury data are difficult to obtain from official reports, which capture only about 20% of crashes and often lack coordinates, injury outcomes, and narratives needed for understanding where and why incidents occurred. Crowdsourced data on bicycling safety provides new opportunities for the study of bicycling injury and risk. Our goal was to quantify factors that influence the spatial variation in unsafe bicycling across a city, …
Spatiotemporal Dynamic of Covid-19 Diffusion in China
COVID-19 has seriously threatened people’s health and well-being across the globe since it was first reported in Wuhan, China in late 2019. This study investigates the mechanism of COVID-19 transmission in different periods within and between cities in China to better understand the nature of the outbreak. We use Moran’s I, a measure of spatial autocorrelation, to examine the spatial dependency of COVID-19 and a dynamic spatial autoregressive mod…
Spatial-scale dependent risk factors of heat-related mortality
How does air pollution affect urban settlement of the floating population in China? New evidence from a push-pull migration analysis
Our results are consistent with existing studies. This study discovers that both external environment and internal factors influence migrants' settlement intentions. Specifically, the differences in population sizes, economic development levels, public services, infrastructure conditions, and environmental regulations between cities play a significant role in migration decisions. We also confirm heterogeneous sensitivities to air pollution of dif…
Inference in Multiscale Geographically Weighted Regression
A recent paper expands the well‐known geographically weighted regression (GWR) framework significantly by allowing the bandwidth or smoothing factor in GWR to be derived separately for each covariate in the model—a framework referred to as multiscale GWR (MGWR). However, one limitation of the MGWR framework is that, until now, no inference about the local parameter estimates was possible. Formally, the so‐called “hat matrix,” which projects the o…
Exploring Multiscale Spatial Interactions
In this article, I develop and implement the multiscale geographically weighted negative binomial (MGWNB) model, extending the spatially weighted interaction models by integrating a multiscale framework. This model effectively tackles the multiscale nonstationarity and overdispersion issues found in spatial interaction models. By comparing it with multiscale geographically weighted Poisson regression using simulated data, I demonstrate its superi…
Generalized geographically and temporally weighted regression
Multiscale Geographically Weighted Zero-Inflated Negative Binomial Regression
Spatial variation in bicycling risk based on crowdsourced safety data
Bicycling‐related injury data are difficult to obtain from official reports, which capture only about 20% of crashes and often lack coordinates, injury outcomes, and narratives needed for understanding where and why incidents occurred. Crowdsourced data on bicycling safety provides new opportunities for the study of bicycling injury and risk. Our goal was to quantify factors that influence the spatial variation in unsafe bicycling across a city, …
Inference in Multiscale Geographically Weighted Regression
A recent paper expands the well‐known geographically weighted regression (GWR) framework significantly by allowing the bandwidth or smoothing factor in GWR to be derived separately for each covariate in the model—a framework referred to as multiscale GWR (MGWR). However, one limitation of the MGWR framework is that, until now, no inference about the local parameter estimates was possible. Formally, the so‐called “hat matrix,” which projects the o…
Spatiotemporal Dynamic of Covid-19 Diffusion in China
COVID-19 has seriously threatened people’s health and well-being across the globe since it was first reported in Wuhan, China in late 2019. This study investigates the mechanism of COVID-19 transmission in different periods within and between cities in China to better understand the nature of the outbreak. We use Moran’s I, a measure of spatial autocorrelation, to examine the spatial dependency of COVID-19 and a dynamic spatial autoregressive mod…
Spatial-scale dependent risk factors of heat-related mortality
How does air pollution affect urban settlement of the floating population in China? New evidence from a push-pull migration analysis
Our results are consistent with existing studies. This study discovers that both external environment and internal factors influence migrants' settlement intentions. Specifically, the differences in population sizes, economic development levels, public services, infrastructure conditions, and environmental regulations between cities play a significant role in migration decisions. We also confirm heterogeneous sensitivities to air pollution of dif…
Understanding the Geography of Covid-19 Case Fatality Rates in China
This study employs a spatial autoregressive probit-log linear (SAP-Log) hurdle model to investigate the influencing factors on the probability of death and case fatality rate (CFR) of coronavirus disease 2019 (COVID-19) at the city level in China. The results demonstrate that the probability of death from COVID-19 and the CFR level are 2 different processes with different determinants. The number of confirmed cases and the number of doctors are c…
Assessing Reliability of Chinese Geotagged Social Media Data for Spatiotemporal Representation of Human Mobility
Understanding the space-time dynamics of human activities is essential in studying human security issues such as climate change impacts, pandemic spreading, or urban sustainability. Geotagged social media posts provide an open and space-time continuous data source with user locations which is convenient for studying human movement. However, the reliability of Chinese geotagged social media data for representing human mobility remains unclear. Thi…
Multiscale Effects of Multimodal Public Facilities Accessibility on Housing Prices Based on MGWR
The layout of public service facilities and their accessibility are important factors affecting spatial justice. Previous studies have verified the positive influence of public facilities accessibility on house prices; however, the spatial scale of the impact of various public facilities accessibility on house prices is not yet clear. This study takes transportation analysis zone of Wuhan city as the spatial unit, measure the public facilities ac…
Are We Modelling Spatially Varying Processes or Non‐linear Relationships
Studies of spatially varying parameter estimates obtained in the calibration of various types of local statistical models are commonplace. The variation in such estimates is typically explained in terms of spatially varying processes. This paper highlights that an alternative explanation for spatially varying parameter estimates, in terms of non‐linearity, should be examined prior to relating such variation to spatially varying processes. This ca…
Is dense or sprawl growth more prone to heat-related health risks? Spatial regression-based study in Delhi, India
Spatial variation in bicycling risk based on crowdsourced safety data
Bicycling‐related injury data are difficult to obtain from official reports, which capture only about 20% of crashes and often lack coordinates, injury outcomes, and narratives needed for understanding where and why incidents occurred. Crowdsourced data on bicycling safety provides new opportunities for the study of bicycling injury and risk. Our goal was to quantify factors that influence the spatial variation in unsafe bicycling across a city, …
Exploring Multiscale Spatial Interactions
In this article, I develop and implement the multiscale geographically weighted negative binomial (MGWNB) model, extending the spatially weighted interaction models by integrating a multiscale framework. This model effectively tackles the multiscale nonstationarity and overdispersion issues found in spatial interaction models. By comparing it with multiscale geographically weighted Poisson regression using simulated data, I demonstrate its superi…
Covid-19 pandemic and road infrastructure exerted stage-dependent spatiotemporal influences on inter-city road travel in China
As the COVID-19 pandemic recedes and travel resumes, it is important to understand how the influences on inter-city road travel varied across different stages of the pandemic. However, the underlying spatiotemporal heterogeneity in the relationship between the mobility shifts and its determinants at different pandemic stages is unclear. This research divides the pandemic timeline into four distinct stages based on the data from the Chinese Health…
Generalized geographically and temporally weighted regression
Multiscale Geographically Weighted Zero-Inflated Negative Binomial Regression
Geography (10 works) · Computer Science (7 works) · Econometrics (7 works) · Mathematics (7 works) · Medicine (7 works) · Statistics (7 works) · Urban Transport and Accessibility (7 works) · China (6 works) · Economics (5 works) · Spatial and Panel Data Analysis (5 works)