Anshu Zhang
Biographic Data
| ID | 4181823 |
|---|---|
| NAME | Anshu Zhang |
| GIVEN NAMES | Anshu |
| FAMILY NAME | Zhang |
| SIGNATURE | ZHANG A |
| AFFILIATIONS | Hong Kong Polytechnic University |
| ORCID | 0000-0001-7158-8292 |
| VERIFIED | Yes |
| TOTAL WORKS | 12 |
| TOTAL CITATIONS | 1 |
| AUTHOR COUNT | 12 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2018 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 1 |
Exploring affordable and effective pandemic containment measures in lower-income countries with a spatial Seir model: A case study in South Africa
This research provides essential insights for lower-income countries to manage current and future pandemics within their economic and healthcare constraints, especially regarding targeted mobility restriction, quarantine, prioritized vaccination, and timing of containment measures
Evaluation of the Resilience of the Catering Industry in Hong Kong before and after the Covid-19 Outbreak Based on Point-of-Interest Data
COVID-19 has caused a serious economic shock which challenges the resilience of businesses around the world. Understanding the spatial distribution pattern of business resilience, as well as identifying factors that promote business resilience, is crucial to economic recovery. Most existing studies mainly analyze one side of the concept of resilience, such as how businesses closed, expanded, and innovated, while no studies take all the characteri…
Predicting onset risk of Covid-19 symptom to support healthy travel route planning in the new normal of long-term coexistence with Sars-CoV-2
Due to the increased outdoor transmission risk of new SARS-COV-2 variants, the health of urban residents in daily travel is being threatened. In the new normal of long-term coexistence with SARS-CoV-2, how to avoid being infected by SARS-CoV-2 in daily travel has become a key issue. Hence, a spatiotemporal solution has been proposed to assist healthy travel route planning. Firstly, an enhanced urban-community-scale geographic model was proposed t…
Online public opinion during the first epidemic wave of Covid-19 in China based on Weibo data
As COVID-19 spread around the world, epidemic prevention and control policies have been adopted by many countries. This process has prompted online social platforms to become important channels to enable people to socialize and exchange information. The massive use of social media data mining techniques, to analyze the development online of public opinion during the epidemic, is of great significance in relation to the management of public opinio…
How to control the spatiotemporal spread of Omicron in the region with low vaccination rates
Currently, finding ways to effectively control the spread of Omicron in regions with low vaccination rates is an urgent issue. In this study, we use a district-level model for predicting the COVID-19 symptom onset risk to explore and control the whole process of spread of Omicron in South Africa at a finer spatial scale. We found that in the early stage of the accelerated spread, Omicron spreads rapidly from the districts at the center of human m…
Understanding spatiotemporal symptom onset risk of Omicron BA.1, BA.2 and hamster-related Delta AY.127
Purpose: Investigation of the community-level symptomatic onset risk regarding severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern, is crucial to the pandemic control in the new normal. Methods: Investigated in this study is the spatiotemporal symptom onset risk with Omicron BA.1, BA.2, and hamster-related Delta AY.127 by a joint analysis of community-based human mobility, virus genomes, and vaccinations in Hong Kong.…
Extracting Human Activity Areas from Large-Scale Spatial Data with Varying Densities
Human activity area extraction, a popular research topic, refers to mining meaningful location clusters from raw activity data. However, varying densities of large-scale spatial data create a challenge for existing extraction methods. This research proposes a novel area extraction framework (ELV) aimed at tackling the challenge by using clustering with an adaptive distance parameter and a re-segmentation strategy with noise recovery. Firstly, a d…
A Data-Driven Framework for Analyzing Spatial Distribution of the Elderly Cardholders by Using Smart Card Data
In this era of population aging, it is essential to understand the spatial distribution patterns of the elderly. Based on the smart card data of the elderly, this study aims to detect the home location and examine the spatial distribution patterns of the elderly cardholders in Beijing. A framework is proposed that includes three methods. First, a rule-based approach is proposed to identify the home location of the elderly cardholders based on ind…
Detecting home countries of social media users with machine-learned ranking approach: A case study in Hong Kong
Advances in urban informatics
Analysis of the Temporal Characteristics of the Elderly Traveling by Bus Using Smart Card Data
Many cities around the world face the challenge of an aging population. A full understanding of the mobility behavior characteristics of the elderly is one necessary and urgent consideration as regards the current aging trend if sustainable urban development is to be fully realized. This paper presents a systematic approach to analyzing the dynamic mobility characteristics of the elderly who travel by bus using smart card big data. The characteri…
Challenges and Prospects of Uncertainties in Spatial Big Data Analytics
Knowledge extraction from spatial big data (SBD) with advanced analytics has become a major trend in research and industry. Meanwhile, the increasingly complex SBD and its analytics face proliferating challenges posed by uncertainties in them. Linked to various characteristics of SBD, the uncertainties emerge and propagate in each stage of SBD analytics. To avoid unreliable knowledge and losses resulting from the uncertainties and to ensure the v…
Challenges and Prospects of Uncertainties in Spatial Big Data Analytics
Knowledge extraction from spatial big data (SBD) with advanced analytics has become a major trend in research and industry. Meanwhile, the increasingly complex SBD and its analytics face proliferating challenges posed by uncertainties in them. Linked to various characteristics of SBD, the uncertainties emerge and propagate in each stage of SBD analytics. To avoid unreliable knowledge and losses resulting from the uncertainties and to ensure the v…
Challenges and Prospects of Uncertainties in Spatial Big Data Analytics
Knowledge extraction from spatial big data (SBD) with advanced analytics has become a major trend in research and industry. Meanwhile, the increasingly complex SBD and its analytics face proliferating challenges posed by uncertainties in them. Linked to various characteristics of SBD, the uncertainties emerge and propagate in each stage of SBD analytics. To avoid unreliable knowledge and losses resulting from the uncertainties and to ensure the v…
Analysis of the Temporal Characteristics of the Elderly Traveling by Bus Using Smart Card Data
Many cities around the world face the challenge of an aging population. A full understanding of the mobility behavior characteristics of the elderly is one necessary and urgent consideration as regards the current aging trend if sustainable urban development is to be fully realized. This paper presents a systematic approach to analyzing the dynamic mobility characteristics of the elderly who travel by bus using smart card big data. The characteri…
A Data-Driven Framework for Analyzing Spatial Distribution of the Elderly Cardholders by Using Smart Card Data
In this era of population aging, it is essential to understand the spatial distribution patterns of the elderly. Based on the smart card data of the elderly, this study aims to detect the home location and examine the spatial distribution patterns of the elderly cardholders in Beijing. A framework is proposed that includes three methods. First, a rule-based approach is proposed to identify the home location of the elderly cardholders based on ind…
Detecting home countries of social media users with machine-learned ranking approach: A case study in Hong Kong
Advances in urban informatics
Online public opinion during the first epidemic wave of Covid-19 in China based on Weibo data
As COVID-19 spread around the world, epidemic prevention and control policies have been adopted by many countries. This process has prompted online social platforms to become important channels to enable people to socialize and exchange information. The massive use of social media data mining techniques, to analyze the development online of public opinion during the epidemic, is of great significance in relation to the management of public opinio…
How to control the spatiotemporal spread of Omicron in the region with low vaccination rates
Currently, finding ways to effectively control the spread of Omicron in regions with low vaccination rates is an urgent issue. In this study, we use a district-level model for predicting the COVID-19 symptom onset risk to explore and control the whole process of spread of Omicron in South Africa at a finer spatial scale. We found that in the early stage of the accelerated spread, Omicron spreads rapidly from the districts at the center of human m…
Understanding spatiotemporal symptom onset risk of Omicron BA.1, BA.2 and hamster-related Delta AY.127
Purpose: Investigation of the community-level symptomatic onset risk regarding severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern, is crucial to the pandemic control in the new normal. Methods: Investigated in this study is the spatiotemporal symptom onset risk with Omicron BA.1, BA.2, and hamster-related Delta AY.127 by a joint analysis of community-based human mobility, virus genomes, and vaccinations in Hong Kong.…
Extracting Human Activity Areas from Large-Scale Spatial Data with Varying Densities
Human activity area extraction, a popular research topic, refers to mining meaningful location clusters from raw activity data. However, varying densities of large-scale spatial data create a challenge for existing extraction methods. This research proposes a novel area extraction framework (ELV) aimed at tackling the challenge by using clustering with an adaptive distance parameter and a re-segmentation strategy with noise recovery. Firstly, a d…
Evaluation of the Resilience of the Catering Industry in Hong Kong before and after the Covid-19 Outbreak Based on Point-of-Interest Data
COVID-19 has caused a serious economic shock which challenges the resilience of businesses around the world. Understanding the spatial distribution pattern of business resilience, as well as identifying factors that promote business resilience, is crucial to economic recovery. Most existing studies mainly analyze one side of the concept of resilience, such as how businesses closed, expanded, and innovated, while no studies take all the characteri…
Predicting onset risk of Covid-19 symptom to support healthy travel route planning in the new normal of long-term coexistence with Sars-CoV-2
Due to the increased outdoor transmission risk of new SARS-COV-2 variants, the health of urban residents in daily travel is being threatened. In the new normal of long-term coexistence with SARS-CoV-2, how to avoid being infected by SARS-CoV-2 in daily travel has become a key issue. Hence, a spatiotemporal solution has been proposed to assist healthy travel route planning. Firstly, an enhanced urban-community-scale geographic model was proposed t…
Exploring affordable and effective pandemic containment measures in lower-income countries with a spatial Seir model: A case study in South Africa
This research provides essential insights for lower-income countries to manage current and future pandemics within their economic and healthcare constraints, especially regarding targeted mobility restriction, quarantine, prioritized vaccination, and timing of containment measures
Computer Science (8 works) · Geography (8 works) · Human Mobility and Location-Based Analysis (7 works) · Medicine (7 works) · COVID-19 epidemiological studies (4 works) · Environmental health (4 works) · Urban Transport and Accessibility (4 works) · Artificial Intelligence (3 works) · Business (3 works) · China (3 works)