Hai Lan

966 total citations · 1 hit paper
30 papers, 591 citations indexed

About

Hai Lan is a scholar working on Global and Planetary Change, Ecology and Modeling and Simulation. According to data from OpenAlex, Hai Lan has authored 30 papers receiving a total of 591 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Global and Planetary Change, 6 papers in Ecology and 6 papers in Modeling and Simulation. Recurrent topics in Hai Lan's work include Land Use and Ecosystem Services (9 papers), COVID-19 epidemiological studies (6 papers) and Remote Sensing in Agriculture (6 papers). Hai Lan is often cited by papers focused on Land Use and Ecosystem Services (9 papers), COVID-19 epidemiological studies (6 papers) and Remote Sensing in Agriculture (6 papers). Hai Lan collaborates with scholars based in United States, China and United Kingdom. Hai Lan's co-authors include Yichun Xie, Zongyao Sha, Xuefeng Liu, Yongfei Bai, Ruren Li, Shujuan Chang, Xueliang Zhang, Jonathan Li, Hongmian Gong and Chaowei Yang and has published in prestigious journals such as PLoS ONE, The Science of The Total Environment and IEEE Access.

In The Last Decade

Hai Lan

29 papers receiving 575 citations

Hit Papers

The global carbon sink potential of terrestrial vegetatio... 2022 2026 2023 2024 2022 50 100 150

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Hai Lan United States 13 323 117 69 68 62 30 591
Nicholus Mboga Belgium 11 354 1.1× 113 1.0× 151 2.2× 50 0.7× 116 1.9× 16 783
Khan Rubayet Rahaman Canada 17 338 1.0× 74 0.6× 94 1.4× 26 0.4× 135 2.2× 62 798
Quanli Xu China 13 336 1.0× 113 1.0× 68 1.0× 28 0.4× 61 1.0× 56 512
Paul Isolo Mukwaya Uganda 14 274 0.8× 59 0.5× 41 0.6× 48 0.7× 38 0.6× 55 634
Ron Mahabir United States 14 300 0.9× 51 0.4× 53 0.8× 32 0.5× 80 1.3× 36 759
Andreas Rienow Germany 14 400 1.2× 76 0.6× 114 1.7× 51 0.8× 80 1.3× 65 686
Ola Hall Sweden 16 511 1.6× 265 2.3× 151 2.2× 70 1.0× 141 2.3× 38 1.0k
T. Edwin Chow United States 14 272 0.8× 66 0.6× 90 1.3× 93 1.4× 72 1.2× 38 765
Zengwang Xu United States 10 220 0.7× 76 0.6× 30 0.4× 180 2.6× 36 0.6× 22 940
Cécile Tannier France 13 406 1.3× 110 0.9× 45 0.7× 102 1.5× 99 1.6× 32 581

Countries citing papers authored by Hai Lan

Since Specialization
Citations

This map shows the geographic impact of Hai Lan'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 Hai Lan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hai Lan more than expected).

Fields of papers citing papers by Hai Lan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hai Lan. 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 Hai Lan. The network helps show where Hai Lan may publish in the future.

Co-authorship network of co-authors of Hai Lan

This figure shows the co-authorship network connecting the top 25 collaborators of Hai Lan. A scholar is included among the top collaborators of Hai Lan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Hai Lan. Hai Lan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Lan, Hai, Ruifen Zhan, Jiuwei Zhao, & Bingyi Wu. (2024). Spring Barents Sea ice loss enhances tropical cyclone genesis over the eastern North Pacific. Climate Dynamics. 62(6). 4967–4979. 2 indexed citations
2.
Zhang, Xueliang, et al.. (2023). Diversified responses of vegetation carbon uptake to urbanization: a national-scale analysis. Frontiers in Ecology and Evolution. 11. 4 indexed citations
3.
Lan, Hai, Kathleen Stewart, Zongyao Sha, Yichun Xie, & Shujuan Chang. (2022). Data Gap Filling Using Cloud-Based Distributed Markov Chain Cellular Automata Framework for Land Use and Land Cover Change Analysis: Inner Mongolia as a Case Study. Remote Sensing. 14(3). 445–445. 7 indexed citations
4.
Wang, Zifu, Yudi Chen, Yun Li, et al.. (2022). Public Opinions on COVID-19 Vaccines—A Spatiotemporal Perspective on Races and Topics Using a Bayesian-Based Method. Vaccines. 10(9). 1486–1486. 4 indexed citations
5.
Sha, Zongyao, Yongfei Bai, Ruren Li, et al.. (2022). The global carbon sink potential of terrestrial vegetation can be increased substantially by optimal land management. Communications Earth & Environment. 3(1). 180 indexed citations breakdown →
6.
Yang, Chaowei, Shuming Bao, Weihe Wendy Guan, et al.. (2022). Challenges and opportunities of the spatiotemporal responses to the global pandemic of COVID-19. Annals of GIS. 28(4). 425–434. 1 indexed citations
7.
Lan, Hai, Dexuan Sha, Yi Liu, et al.. (2021). COVID-Scraper: An Open-Source Toolset for Automatically Scraping and Processing Global Multi-Scale Spatiotemporal COVID-19 Records. IEEE Access. 9. 84783–84798. 8 indexed citations
8.
Li, Yun, Aaron Chew, Hai Lan, et al.. (2020). Individual-Level Fatality Prediction of COVID-19 Patients Using AI Methods. Frontiers in Public Health. 8. 587937–587937. 28 indexed citations
9.
Sha, Zongyao, Yongfei Bai, Hai Lan, et al.. (2020). Can more carbon be captured by grasslands? A case study of Inner Mongolia, China. The Science of The Total Environment. 723. 138085–138085. 31 indexed citations
10.
Sha, Dexuan, Xin Miao, Hai Lan, et al.. (2020). Spatiotemporal analysis of medical resource deficiencies in the U.S. under COVID-19 pandemic. PLoS ONE. 15(10). e0240348–e0240348. 22 indexed citations
11.
Sha, Dexuan, Yi Liu, Qian Liu, et al.. (2020). A spatiotemporal data collection of viral cases for COVID-19 rapid response. Big Earth Data. 5(1). 90–111. 15 indexed citations
12.
Liu, Qian, Dexuan Sha, Shubham Kumar, et al.. (2020). An Environmental Data Collection for COVID-19 Pandemic Research. Data. 5(3). 68–68. 19 indexed citations
13.
Sha, Dexuan, Qian Liu, You Zhou, et al.. (2020). A State-Level Socioeconomic Data Collection of the United States for COVID-19 Research. Data. 5(4). 118–118. 9 indexed citations
14.
Sha, Zongyao, et al.. (2020). Modeling urban growth by coupling localized spatio-temporal association analysis and binary logistic regression. Computers Environment and Urban Systems. 81. 101482–101482. 19 indexed citations
15.
Lan, Hai & Kathleen Stewart. (2019). Gap filling in large-area and long-term land use/land cover change time series using cloud-based Markov-Cellular Automata. AGUFM. 2019. 1 indexed citations
16.
Xie, Yichun, et al.. (2018). Examining shrinking city of Detroit in the context of socio-spatial inequalities. Landscape and Urban Planning. 177. 350–361. 77 indexed citations
17.
Xie, Yichun, et al.. (2018). Investigating long-term trends of climate change and their spatial variations caused by regional and local environments through data mining. Journal of Geographical Sciences. 28(6). 802–818. 13 indexed citations
18.
Lan, Hai. (2006). Research and Suggestions on Speeding up Dissemination and Application of New Technologies for Power Grid Construction. Power System Technology. 2 indexed citations
19.
Lan, Hai, et al.. (2001). DEGREE OF GREY INCIDENCE AND VARIABLE WEIGHT SYNTHESIZING APPLIED IN BRIDGE ASSESSMENT. Journal of Tongji University. 29(1). 5 indexed citations
20.
Lan, Hai. (2000). Synthetic Monitoring System for Long-Span Cable-Stayed Bridge. Jiegou Gongchengshi. 2 indexed citations

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.

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