Qingyun Du
Biographic Data
| ID | 6002197 |
|---|---|
| NAME | Qingyun Du |
| GIVEN NAMES | Qingyun |
| FAMILY NAME | Du |
| SIGNATURE | DU Q |
| AFFILIATIONS | Wuhan University |
| ORCID | 0000-0003-4615-2029 |
| VERIFIED | Yes |
| TOTAL WORKS | 22 |
| TOTAL CITATIONS | 62 |
| AUTHOR COUNT | 22 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2013 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 4 |
Mapping the Intellectual Landscape of Corporate Social Irresponsibility: A Bibliometric Review and Future Research Agenda
Corporate Social Irresponsibility (CSI) has emerged as a critical research domain because of its adverse social, environmental, and economic impacts on affected stakeholders. The increasing prevalence of corporate scandals and irresponsible practices in recent decades has raised concerns among academics, policymakers, and the public, creating the need for a systematic understanding of CSI as a field of study. Despite this growing interest, the in…
"Natural or man-made disaster? Lessons from the extreme rain and flood disaster in Zhengzhou, China on "2021.7.20
A Semantically Enhanced Label Prediction Method for Imbalanced POI Data Category Distribution
POI data play an important role in various location-based services, including navigation, positioning, and local search applications. However, as cities rapidly develop, a substantial amount of new POI data are generated daily, often accompanied by issues with the quality of their labels. Therefore, there is an urgent need to implement intelligent inference and enhancement processing for POI data labels. Conventional neural network models primari…
The Development of a Short Chinese Version of the State-Trait Anxiety Inventory
The short Chinese version of the STAI demonstrates sound psychometric properties and is applicable in evaluating the level of anxiety in Chinese populations
Setting the Flow Accumulation Threshold Based on Environmental and Morphologic Features to Extract River Networks from Digital Elevation Models
Determining the flow accumulation threshold (FAT) is a key task in the extraction of river networks from digital elevation models (DEMs). Several methods have been developed to extract river networks from Digital Elevation Models. However, few studies have considered the geomorphologic complexity in the FAT estimation and river network extraction. Recent studies estimated influencing factors’ impacts on the river length or drainage density withou…
A Tourist Attraction Recommendation Model Fusing Spatial, Temporal, and Visual Embeddings for Flickr-Geotagged Photos
The rapid development of social media data, including geotagged photos, has benefited the research of tourism geography; additionally, tourists’ increasing demand for personalized travel has encouraged more researchers to pay attention to tourism recommendation models. However, few studies have comprehensively considered the content and contextual information that may influence the recommendation accuracy, especially tourist attractions’ visual c…
Techniques for the Automatic Detection and Hiding of Sensitive Targets in Emergency Mapping Based on Remote Sensing Data
Emergency remote sensing mapping can provide support for decision making in disaster assessment or disaster relief, and therefore plays an important role in disaster response. Traditional emergency remote sensing mapping methods use decryption algorithms based on manual retrieval and image editing tools when processing sensitive targets. Although these traditional methods can achieve target recognition, they are inefficient and cannot meet the hi…
Construction of Urban Flooding Prevention System under “One City, One Executor, and One Network” Model: Case Study of Kunming, China
Flood disasters have plagued developing countries and impeded sustainable city development as a result of global climate change and economic development. Chaotic urban flooding prevention system management is the current governance bottleneck in many cities and exacerbates flooding events. Sustainable rainwater management strategies require flexible implementation considering local characteristics, space-time factors, governance, and economic and…
Extracting Representative Images of Tourist Attractions from Flickr by Combining an Improved Cluster Method and Multiple Deep Learning Models
Extracting representative images of tourist attractions from geotagged photos is beneficial to many fields in tourist management, such as applications in touristic information systems. This task usually begins with clustering to extract tourist attractions from raw coordinates in geotagged photos. However, most existing cluster methods are limited in the accuracy and granularity of the places of interest, as well as in detecting distinct tags, du…
Recognition Method of New Address Elements in Chinese Address Matching Based on Deep Learning
Location services based on address matching play an important role in people’s daily lives. However, with the rapid development of cities, new addresses are constantly emerging. Due to the untimely updating of word segmentation dictionaries and address databases, the accuracy of address segmentation and the certainty of address matching face severe challenges. Therefore, a new address element recognition method for address matching is proposed. T…
Analysing the spatial configuration of urban bus networks based on the geospatial network analysis method
Optimizing the Predictive Ability of Machine Learning Methods for Landslide Susceptibility Mapping Using SMOTE for Lishui City in Zhejiang Province, China
The main goal of this study was to use the synthetic minority oversampling technique (SMOTE) to expand the quantity of landslide samples for machine learning methods (i.e., support vector machine (SVM), logistic regression (LR), artificial neural network (ANN), and random forest (RF)) to produce high-quality landslide susceptibility maps for Lishui City in Zhejiang Province, China. Landslide-related factors were extracted from topographic maps, g…
Assessing Spatial Accessibility to Hierarchical Urban Parks by Multi-Types of Travel Distance in Shenzhen, China
Urban green spaces play a critical role in public health and human wellbeing for urban residents. Due to the uneven spatial distribution of urban green spaces in most of cities, the issue of the disparity between supply and demand has aroused public concern. In a case of Shenzhen, a modified Gaussian-based two-step floating catchment area (2SFCA) method is adopted to evaluate the disparity between park provision and the demanders in terms of acce…
Check-in behaviour and spatio-temporal vibrancy: An exploratory analysis in Shenzhen, China
Evaluating the Effects of Landscape on Housing Prices in Urban China
The rapid urbanisation of China has received growing attention regarding its urban residential environments. In this article, we model the spatial heterogeneity of housing prices and explore the spatial discrepancy of landscape effects on property values in Shenzhen, a large Chinese city. In contrast to previous studies, this paper integrates the official housing transaction records and housing attributes from open data along with field surveys. …
Spatiotemporal Changes in Fine Particulate Matter Pollution and the Associated Mortality Burden in China between 2015 and 2016
In recent years, research on the spatiotemporal distribution and health effects of fine particulate matter (PM 2.5 ) has been conducted in China. However, the limitations of different research scopes and methods have led to low comparability between regions regarding the mortality burden of PM 2.5 . A kriging model was used to simulate the distribution of PM 2.5 in 2015 and 2016. Relative risk (RR) at a specified PM 2.5 exposure concentration was…
Spatial effects of accessibility to parks on housing prices in Shenzhen, China
Spatial Patterns of Ischemic Heart Disease in Shenzhen, China: A Bayesian Multi-Disease Modelling Approach to Inform Health Planning Policies
Incorporating the information of hypertension, this paper applies Bayesian multi-disease analysis to model the spatial patterns of Ischemic Heart Disease (IHD) risks. Patterns of harmful alcohol intake (HAI) and overweight/obesity are also modelled as they are common risk factors contributing to both IHD and hypertension. The hospitalization data of IHD and hypertension in 2012 were analyzed with three Bayesian multi-disease models at the sub-dis…
Spatio-Temporal Variation and Prediction of Ischemic Heart Disease Hospitalizations in Shenzhen, China
Ischemic heart disease (IHD) is a leading cause of death worldwide. Urban public health and medical management in Shenzhen, an international city in the developing country of China, is challenged by an increasing burden of IHD. This study analyzed the spatio-temporal variation of IHD hospital admissions from 2003 to 2012 utilizing spatial statistics, spatial analysis, and space-time scan statistics. The spatial statistics and spatial analysis mea…
Spatial Analysis of the Home Addresses of Hospital Patients with Hepatitis B Infection or Hepatoma in Shenzhen, China from 2010 to 2012
This study demonstrated substantial geographic variation in the incidence of hepatitis B infection and hepatoma in Shenzhen. The prediction and control of hepatitis B infections and hepatoma development and interventions for these diseases should focus on disadvantaged areas to reduce disparities. GIS and spatial analysis play an important role in public health risk-reduction programs and may become integral components in the epidemiologic descri…
Analysis of the Spatial Variation of Hospitalization Admissions for Hypertension Disease in Shenzhen, China
In China, awareness about hypertension, the treatment rate and the control rate are low compared to developed countries, even though China's aging population has grown, especially in those areas with a high degree of urbanization. However, limited epidemiological studies have attempted to describe the spatial variation of the geo-referenced data on hypertension disease over an urban area of China. In this study, we applied hierarchical Bayesian m…
Web map-based POI visualization for spatial decision support
The ability to extract useful information from data is a topic of considerable interest, especially with regard to organizing point-of-interest (POI) information containing many attributes as well as data about business. In generating intuitive results from investigations of traditional relational databases, traditional scientific visualization approaches for multidimensional data (e.g., Visualization in Scientific Computing) are inefficient, and…
Check-in behaviour and spatio-temporal vibrancy: An exploratory analysis in Shenzhen, China
Spatial effects of accessibility to parks on housing prices in Shenzhen, China
Analysing the spatial configuration of urban bus networks based on the geospatial network analysis method
Evaluating the Effects of Landscape on Housing Prices in Urban China
The rapid urbanisation of China has received growing attention regarding its urban residential environments. In this article, we model the spatial heterogeneity of housing prices and explore the spatial discrepancy of landscape effects on property values in Shenzhen, a large Chinese city. In contrast to previous studies, this paper integrates the official housing transaction records and housing attributes from open data along with field surveys. …
Web map-based POI visualization for spatial decision support
The ability to extract useful information from data is a topic of considerable interest, especially with regard to organizing point-of-interest (POI) information containing many attributes as well as data about business. In generating intuitive results from investigations of traditional relational databases, traditional scientific visualization approaches for multidimensional data (e.g., Visualization in Scientific Computing) are inefficient, and…
Spatio-Temporal Variation and Prediction of Ischemic Heart Disease Hospitalizations in Shenzhen, China
Ischemic heart disease (IHD) is a leading cause of death worldwide. Urban public health and medical management in Shenzhen, an international city in the developing country of China, is challenged by an increasing burden of IHD. This study analyzed the spatio-temporal variation of IHD hospital admissions from 2003 to 2012 utilizing spatial statistics, spatial analysis, and space-time scan statistics. The spatial statistics and spatial analysis mea…
Spatial Analysis of the Home Addresses of Hospital Patients with Hepatitis B Infection or Hepatoma in Shenzhen, China from 2010 to 2012
This study demonstrated substantial geographic variation in the incidence of hepatitis B infection and hepatoma in Shenzhen. The prediction and control of hepatitis B infections and hepatoma development and interventions for these diseases should focus on disadvantaged areas to reduce disparities. GIS and spatial analysis play an important role in public health risk-reduction programs and may become integral components in the epidemiologic descri…
Analysis of the Spatial Variation of Hospitalization Admissions for Hypertension Disease in Shenzhen, China
In China, awareness about hypertension, the treatment rate and the control rate are low compared to developed countries, even though China's aging population has grown, especially in those areas with a high degree of urbanization. However, limited epidemiological studies have attempted to describe the spatial variation of the geo-referenced data on hypertension disease over an urban area of China. In this study, we applied hierarchical Bayesian m…
Spatial Patterns of Ischemic Heart Disease in Shenzhen, China: A Bayesian Multi-Disease Modelling Approach to Inform Health Planning Policies
Incorporating the information of hypertension, this paper applies Bayesian multi-disease analysis to model the spatial patterns of Ischemic Heart Disease (IHD) risks. Patterns of harmful alcohol intake (HAI) and overweight/obesity are also modelled as they are common risk factors contributing to both IHD and hypertension. The hospitalization data of IHD and hypertension in 2012 were analyzed with three Bayesian multi-disease models at the sub-dis…
Spatiotemporal Changes in Fine Particulate Matter Pollution and the Associated Mortality Burden in China between 2015 and 2016
In recent years, research on the spatiotemporal distribution and health effects of fine particulate matter (PM 2.5 ) has been conducted in China. However, the limitations of different research scopes and methods have led to low comparability between regions regarding the mortality burden of PM 2.5 . A kriging model was used to simulate the distribution of PM 2.5 in 2015 and 2016. Relative risk (RR) at a specified PM 2.5 exposure concentration was…
Spatial effects of accessibility to parks on housing prices in Shenzhen, China
Check-in behaviour and spatio-temporal vibrancy: An exploratory analysis in Shenzhen, China
Evaluating the Effects of Landscape on Housing Prices in Urban China
The rapid urbanisation of China has received growing attention regarding its urban residential environments. In this article, we model the spatial heterogeneity of housing prices and explore the spatial discrepancy of landscape effects on property values in Shenzhen, a large Chinese city. In contrast to previous studies, this paper integrates the official housing transaction records and housing attributes from open data along with field surveys. …
Optimizing the Predictive Ability of Machine Learning Methods for Landslide Susceptibility Mapping Using SMOTE for Lishui City in Zhejiang Province, China
The main goal of this study was to use the synthetic minority oversampling technique (SMOTE) to expand the quantity of landslide samples for machine learning methods (i.e., support vector machine (SVM), logistic regression (LR), artificial neural network (ANN), and random forest (RF)) to produce high-quality landslide susceptibility maps for Lishui City in Zhejiang Province, China. Landslide-related factors were extracted from topographic maps, g…
Assessing Spatial Accessibility to Hierarchical Urban Parks by Multi-Types of Travel Distance in Shenzhen, China
Urban green spaces play a critical role in public health and human wellbeing for urban residents. Due to the uneven spatial distribution of urban green spaces in most of cities, the issue of the disparity between supply and demand has aroused public concern. In a case of Shenzhen, a modified Gaussian-based two-step floating catchment area (2SFCA) method is adopted to evaluate the disparity between park provision and the demanders in terms of acce…
Extracting Representative Images of Tourist Attractions from Flickr by Combining an Improved Cluster Method and Multiple Deep Learning Models
Extracting representative images of tourist attractions from geotagged photos is beneficial to many fields in tourist management, such as applications in touristic information systems. This task usually begins with clustering to extract tourist attractions from raw coordinates in geotagged photos. However, most existing cluster methods are limited in the accuracy and granularity of the places of interest, as well as in detecting distinct tags, du…
Recognition Method of New Address Elements in Chinese Address Matching Based on Deep Learning
Location services based on address matching play an important role in people’s daily lives. However, with the rapid development of cities, new addresses are constantly emerging. Due to the untimely updating of word segmentation dictionaries and address databases, the accuracy of address segmentation and the certainty of address matching face severe challenges. Therefore, a new address element recognition method for address matching is proposed. T…
Analysing the spatial configuration of urban bus networks based on the geospatial network analysis method
Setting the Flow Accumulation Threshold Based on Environmental and Morphologic Features to Extract River Networks from Digital Elevation Models
Determining the flow accumulation threshold (FAT) is a key task in the extraction of river networks from digital elevation models (DEMs). Several methods have been developed to extract river networks from Digital Elevation Models. However, few studies have considered the geomorphologic complexity in the FAT estimation and river network extraction. Recent studies estimated influencing factors’ impacts on the river length or drainage density withou…
A Tourist Attraction Recommendation Model Fusing Spatial, Temporal, and Visual Embeddings for Flickr-Geotagged Photos
The rapid development of social media data, including geotagged photos, has benefited the research of tourism geography; additionally, tourists’ increasing demand for personalized travel has encouraged more researchers to pay attention to tourism recommendation models. However, few studies have comprehensively considered the content and contextual information that may influence the recommendation accuracy, especially tourist attractions’ visual c…
Techniques for the Automatic Detection and Hiding of Sensitive Targets in Emergency Mapping Based on Remote Sensing Data
Emergency remote sensing mapping can provide support for decision making in disaster assessment or disaster relief, and therefore plays an important role in disaster response. Traditional emergency remote sensing mapping methods use decryption algorithms based on manual retrieval and image editing tools when processing sensitive targets. Although these traditional methods can achieve target recognition, they are inefficient and cannot meet the hi…
Construction of Urban Flooding Prevention System under “One City, One Executor, and One Network” Model: Case Study of Kunming, China
Flood disasters have plagued developing countries and impeded sustainable city development as a result of global climate change and economic development. Chaotic urban flooding prevention system management is the current governance bottleneck in many cities and exacerbates flooding events. Sustainable rainwater management strategies require flexible implementation considering local characteristics, space-time factors, governance, and economic and…
The Development of a Short Chinese Version of the State-Trait Anxiety Inventory
The short Chinese version of the STAI demonstrates sound psychometric properties and is applicable in evaluating the level of anxiety in Chinese populations
A Semantically Enhanced Label Prediction Method for Imbalanced POI Data Category Distribution
POI data play an important role in various location-based services, including navigation, positioning, and local search applications. However, as cities rapidly develop, a substantial amount of new POI data are generated daily, often accompanied by issues with the quality of their labels. Therefore, there is an urgent need to implement intelligent inference and enhancement processing for POI data labels. Conventional neural network models primari…
Mapping the Intellectual Landscape of Corporate Social Irresponsibility: A Bibliometric Review and Future Research Agenda
Corporate Social Irresponsibility (CSI) has emerged as a critical research domain because of its adverse social, environmental, and economic impacts on affected stakeholders. The increasing prevalence of corporate scandals and irresponsible practices in recent decades has raised concerns among academics, policymakers, and the public, creating the need for a systematic understanding of CSI as a field of study. Despite this growing interest, the in…
"Natural or man-made disaster? Lessons from the extreme rain and flood disaster in Zhengzhou, China on "2021.7.20
Geography (16 works) · Computer Science (12 works) · China (9 works) · Data mining (9 works) · Artificial Intelligence (8 works) · Medicine (6 works) · Population (6 works) · Urban Transport and Accessibility (6 works) · Cartography (5 works) · Engineering (5 works)