Xiao Yundan

Mrs. Xiao Yundan


Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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JLJiaxuan Li Li
Jiaxuan Li Li
PPPatrick Pang
Patrick Pang
XYXiao Yundan
Xiao Yundan
DWDennis Wong
Dennis Wong
Doctor–patient relationships (DPRs) in China have been straining. With the emergence of the COVID-19 pandemic, the relationships and interactions between patients and doctors are changing. This study investigated how patients’ attitudes toward physicians changed during the pandemic and what factors were associated with these changes, leading to insights for improving management in the healthcare sector. This paper collected 58,600 comments regarding Chinese doctors from three regions from the online health platform Good Doctors Online (haodf.com, accessed on 13 October 2022). These comments were analyzed using text mining techniques, such as sentiment and word frequency analyses. The results showed improvements in DPRs after the pandemic, and the degree of improvement was related to the extent to which a location was affected. The findings also suggest that administrative services in the healthcare sector need further improvement. Based on these results, we summarize relevant recommendations at the end of this paper.

29 January 2022 in Remote Sensing
Verified
Journal Article
Open access
PDF file
SWShengrong Wei
Shengrong Wei
WJWeili Jiao
Weili Jiao
慧刘慧婵 刘
慧婵 刘
Tengfei longTengfei long
Tengfei long
YLYaokai Liu
Yaokai Liu
XYXiao Yundan
Xiao Yundan
With the development of a sustainable lifestyle, people are paying more and more attention to the comfort of their own living environment, including public space lighting, which is immediately accessible to residents. The demand on its quality and comfort has thus gained attention recently. However, there is still a lack of related research on public space lighting comfort evaluation models that combine nighttime light remote sensing data and field measurement data, and link lighting attributes with the comfort of residents. This research uses nighttime light remote sensing data to select typical test areas, measures the lighting data of the survey points on the spot, develops an intelligent WeChat applet that collects public perception data, analyzes different lighting parameters, and builds a public space lighting comfort model based on the structural equation model analysis method. The results show that the factor that the areas with high light intensity are more comfortable than the areas with low light intensity. In areas with high light intensity, people pay more attention to the uniformity, security and comfort of the light, while in areas with low light intensity or high blue light, people’s perception of glare will be more obvious. This research can provide a basis for the intelligent optimization of public space lighting from the perspective of public preference.

12 October 2024 in Remote Sensing
Verified
Journal Article
Open access
PDF file
SWShengrong Wei
Shengrong Wei
Tao YuTao Yu
Tao Yu
JPJi Ping
Ji Ping
XYXiao Yundan
Xiao Yundan
XLXiaoyao Li
Xiaoyao Li
ZLZhenwei Liu
Zhenwei Liu
The advancement of urbanization has led to a decline in the ecological function and environmental quality of cities, seriously reducing the services and sustainable development capacity of urban ecosystems. The construction of the National Forest Urban Agglomeration of China is conducive to alleviating the ecological and environmental problems brought about by rapid urbanization and promoting sustainable urban development. A time series analysis of ecological network changes can quickly and effectively explore the development and changes of ecological spatial patterns over time. Identifying ecological protection and restoration areas in urban agglomerations is an important way to promote ecosystem restoration and optimize ecological networks. This paper takes the Pearl River Delta forest urban agglomeration as the research area, uses multi-source remote sensing data from 2000 to 2020 (every 5 years), identifies ecological sources based on the morphological spatial pattern analysis (MSPA) method, generates ecological corridors based on the minimum cumulative resistance (MCR) model, constructs a time series ecological network pattern in the Pearl River Delta region, and analyzes the evolution process of the ecological network pattern over time. The results indicate that over time, the core green area in the ecological network pattern of the Pearl River Delta first decreased and then increased, and the complexity of ecological corridors first decreased and then increased. The main reason is that the urbanization process in the early 21st century led to severe ecological fragmentation. Under the promotion of the national forest urban agglomeration construction, the ecological network pattern of the Pearl River Delta was restored in 2015 and 2020. The time series analysis of the ecological network pattern in the Pearl River Delta region of this research confirms the effectiveness of the construction of forest urban agglomerations, providing a scientific reference for the identification of ecological networks and optimization of spatial patterns in forest urban agglomerations.

31 March 2023 in China Scientific Data
Verified
Journal Article
Open access
RHRuixia Hou
Ruixia Hou
NCNational Forestry And Grassland Data Center
National Forestry And Grassland Data Center
XCXiaoming Cao
Xiaoming Cao
YFYiming Feng
Yiming Feng
LXLei Xi
Lei Xi
SWShengrong Wei
Shengrong Wei
Located in China's Inner Mongolia Plateau, Inner Mongolia Autonomous Region is the main area of the Mongolian Plateau in China, and it is also a key research area for desertification and sandification monitoring. The land in this area is severely desertified and sandificated. Carrying out annual monitoring according to the characteristics of desertification land in this region is a necessary support for the research on grasping the dynamic characteristics of desertification and comprehensively analyzing the causes of desertification. We based the monitoring research on the MODIS data from 2001 to 2021 in the Inner Mongolia Autonomous Region and selected FVC, MSAVI, LST, TVDI indicator to generate indicator discriminant values through information overlay analysis, classification, and discrimination. And according to the zoning regulations, we obtained the annual monitoring data of desertification degree from 2001 to 2021 in 4 climate zones in Inner Mongolia. This dataset can provide data support for studies on desertification changes and driving mechanisms and so on.