Ling Wan

1.4k citations
58 papers · 1.1k · h-index 18

Impact in

Papers in

Ling Wan

55 papers receiving 1.1k citations

Peers

Ling Wan
Comparison fields: 5 of 76
  • Media Technology 267
  • Civil and Structural Engineering 295
  • Computer Vision and Pattern Recognition 221
  • Atmospheric Science 191
  • Applied Mathematics 94
Replace Biao Wang with:
Biao Wang China
Fangling Pu China
Yuan Hu China
Yang He China
Lan Zhang China
Emmanuël Trouvé France
Yilei Shi Germany
Shanwei Liu China
Ling Wan relative to Biao Wang China Biao Wang's profile →
Citations per field
00.5×10×13.4×
Biao Wang · 1×
Citations per year

Countries citing papers authored by Ling Wan

Since Specialization
Citations

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

Fields of papers citing papers by Ling Wan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Ling Wan, 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 Wan Line = papers co-authored together Ling Wan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 58 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201098
2 201992
3 201976
4 201275
5 201267
6 201863
7 202062
8 200845
9 201844
10 200938
11 201837
12 201733
13 201933
14 201633
15 201629
16 201729
17 201925
18 201623
19 202017
20 201716

About Ling Wan

Ling Wan is a scholar working on Media Technology, Atmospheric Science, Applied Mathematics, Civil and Structural Engineering and Computer Vision and Pattern Recognition, having authored 58 papers that have together received 1.1k indexed citations. Recurring topics across this work include Remote-Sensing Image Classification (13 papers), Remote Sensing and Land Use (11 papers), Navier-Stokes equation solutions (10 papers), Synthetic Aperture Radar (SAR) Applications and Techniques (6 papers), Tailings Management and Properties (5 papers), Computational Fluid Dynamics and Aerodynamics (5 papers), Landfill Environmental Impact Studies (4 papers) and Remote Sensing in Agriculture (4 papers). The work is most often cited by research in Media Technology (267 citations), Civil and Structural Engineering (295 citations), Computer Vision and Pattern Recognition (221 citations), Atmospheric Science (191 citations) and Applied Mathematics (94 citations). Ling Wan has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Hongjian You, Yuming Xiang, Feng Wang, Zuoan Wei, Guangzhi Yin, Tao Wang, Jianguo Wang, Tao Zhang, Shixiong Xia and Shui‐Long Shen. Their work appears in journals such as IEEE Transactions on Geoscience and Remote Sensing, Remote Sensing, Journal of Differential Equations, International journal of agricultural and biological engineering and IEEE Geoscience and Remote Sensing Letters.

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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