Ling Bian

59 papers receiving 2.2k citations

Ling Bian's Hit Papers

Next-generation Digital Earth 2012 · 260 citations
2600+4+9Years since publication50100150200250

Peers

Ling Bian
Comparison fields: 5 of 151
  • Geography, Planning and Development 320
  • Transportation 335
  • Modeling and Simulation 204
  • Media Technology 199
  • Signal Processing 240
Replace Zhu Yunqiang with:
Zhu Yunqiang China
Antônio Miguel Vieira Monteiro Brazil
Robert Haining United Kingdom
Ali Asghar Alesheikh Iran
Suzana Dragićević Canada
Michael Keith McCall Mexico
Yunyan Du China
Budhendra Bhaduri United States
Stefan Leyk United States
Ashton M. Shortridge United States
Ling Bian relative to Zhu Yunqiang China Zhu Yunqiang's profile →
Citations per field
00.5×2×2.9×
Zhu Yunqiang · 1×
Citations per year

Countries citing papers authored by Ling Bian

Since Specialization
Citations

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

Fields of papers citing papers by Ling Bian

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Ling Bian, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ling Bian Line = papers co-authored together Ling Bian links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 63 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Next-generation Digital Earth
Hit paper breakdown →
2012260
2 2011225
3 2014201
4 2007180
5 2014132
6 2012127
7 2006124
8 1993122
9 2006103
10 200486
11 200757
12 200251
13 201050
14
GIS modeling of elk calving habitat in a prairie environment with statistics
199745
15 201036
16 201233
17 199933
18 199332
19 200732
20 201232

About Ling Bian

Ling Bian is a scholar working on Modeling and Simulation, Geography, Planning and Development, Transportation, Signal Processing and Ecological Modeling, having authored 63 papers that have together received 2.3k indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (16 papers), Human Mobility and Location-Based Analysis (9 papers), Geographic Information Systems Studies (9 papers), Data-Driven Disease Surveillance (8 papers), Data Management and Algorithms (7 papers), Influenza Virus Research Studies (6 papers), Land Use and Ecosystem Services (6 papers) and Complex Network Analysis Techniques (6 papers). The work is most often cited by research in Geography, Planning and Development (320 citations), Transportation (335 citations), Modeling and Simulation (204 citations), Media Technology (199 citations) and Signal Processing (240 citations). Ling Bian has collaborated with scholars based in United States, China and Australia. Frequent co-authors include Yuxia Huang, Stephen James Walsh, Peter A. Rogerson, Hoehun Ha, James R. Olson, Liang Mao, Jingtao Ma, Cynthia Chen, Huadong Guo and Anthony Lewis. Their work appears in journals such as Transactions in GIS, Annals of the American Association of Geographers, Photogrammetric Engineering & Remote Sensing, Computers Environment and Urban Systems and The Professional Geographer.

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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