Dexuan Sha
Impact in
- Modeling and Simulation top 5%
- COVID-19 epidemiological studies
- Transportation top 10%
- Human Mobility and Location-Based Analysis
- Urban Transport and Accessibility
Papers in
-
- COVID-19 impact on air quality 4
-
- Cryospheric studies and observations 3
- Co-authors
- Chaowei Yang (17 shared papers)Xiaodong Mu (2 shared papers)Yun Li (6 shared papers)Hai Lan (9 shared papers)Qian Liu (11 shared papers)Mei Li (1 shared paper)Yanfang Su (1 shared paper)Manzhu Yu (2 shared papers)
- Journals
- Remote Sensing (3 papers)Big Earth Data (2 papers)IEEE Access (2 papers)IEEE Geoscience and Remote Sensing Letters (1 paper)International Journal of Environmental Research and Public Health (1 paper)
- Partner nations
- United StatesChinaFrance
In The Last Decade
Dexuan Sha
23 papers receiving 356 citations
Peers
Comparison fields: 5 of 84
- Modeling and Simulation 89
- Transportation 44
- Health Informatics 7
- Media Technology 45
- Global and Planetary Change 99
Countries citing papers authored by Dexuan Sha
This map shows the geographic impact of Dexuan Sha's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Dexuan Sha with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dexuan Sha more than expected).
Fields of papers citing papers by Dexuan Sha
This network shows the impact of papers produced by Dexuan Sha. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Dexuan Sha. The network helps show where Dexuan Sha may publish in the future.
Co-authors
The 25 scholars most cited alongside Dexuan Sha, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 61 | |
| 2 | 2019 | 47 | |
| 3 | 2019 | 46 | |
| 4 | 2020 | 28 | |
| 5 | 2023 | 26 | |
| 6 | 2020 | 22 | |
| 7 | 2020 | 19 | |
| 8 | 2021 | 17 | |
| 9 | 2020 | 15 | |
| 10 | 2021 | 13 | |
| 11 | 2021 | 10 | |
| 12 | 2020 | 9 | |
| 13 | 2020 | 9 | |
| 14 | 2021 | 8 | |
| 15 | 2020 | 8 | |
| 16 | 2023 | 7 | |
| 17 | 2021 | 6 | |
| 18 | 2017 | 5 | |
| 19 | 2022 | 4 | |
| 20 | 2022 | 3 |
About Dexuan Sha
Dexuan Sha is a scholar working on Global and Planetary Change, Atmospheric Science, Modeling and Simulation, Health and Epidemiology, having authored 24 papers that have together received 368 indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (6 papers), Remote-Sensing Image Classification (4 papers), COVID-19 impact on air quality (4 papers), Cryospheric studies and observations (3 papers), Data-Driven Disease Surveillance (3 papers), Health disparities and outcomes (3 papers), Data Management and Algorithms (2 papers) and COVID-19 diagnosis using AI (2 papers). The work is most often cited by research in Modeling and Simulation (89 citations), Transportation (44 citations), Health Informatics (7 citations), Media Technology (45 citations) and Global and Planetary Change (99 citations). Dexuan Sha has collaborated with scholars based in United States, China and France. Frequent co-authors include Chaowei Yang, Xiaodong Mu, Yun Li, Hai Lan, Qian Liu, Mei Li, Yanfang Su, Manzhu Yu, Fei Hu and Zhiran Zhang. Their work appears in journals such as Remote Sensing, Big Earth Data, IEEE Access, IEEE Geoscience and Remote Sensing Letters and International Journal of Environmental Research and Public Health.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.