Tao Shi

873 citations
46 papers · 599 indexed · h-index 13

Tao Shi

43 papers receiving 573 citations

Peers

Tao Shi
Comparison fields: 5 of 94
  • Environmental Engineering 218
  • Statistics and Probability 85
  • Media Technology 85
  • Global and Planetary Change 154
  • Computational Mathematics 4
Replace Orietta Nicolis with:
Orietta Nicolis Chile
Pedro Delicado Spain
Oscar H. Bustos Brazil
Hanlin Yin China
Sophie Dabo‐Niang France
Hexiang Bai China
Vladimir A. Krylov Italy
Elisabetta Binaghi Italy
Xianfeng Huang China
Jinming Zhang China
Tao Shi relative to Orietta Nicolis Chile Orietta Nicolis's profile →
Citations per field
00.5×2.7×
Orietta Nicolis · 1×
Citations per year

Countries citing papers authored by Tao Shi

Since Specialization
Citations

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

Fields of papers citing papers by Tao Shi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20222
2 20214
3 20211
4 20211
5 20207
6 20201
7 20191
8 201856
9 20173
10 20144
11
Local spatial-predictor selection
20133
12 20125
13
Cairn detection in southern arabia using a supervised automatic detection algorithm and multiple sample data spectroscopic clustering
20101
14 201055
15 200944
16 200848
17 200818
18 200618
19
Polar cloud detection using satellite data with analysis and application of kernel learning algorithms
20051
20
The design of a hypermedia knowledge base for promoting the transfer of knowledge and skills
19970

About Tao Shi

Tao Shi is a scholar working on Computer Vision and Pattern Recognition, Environmental Engineering and Media Technology, having authored 46 papers that have together received 599 indexed citations. Recurring topics across this work include Atmospheric aerosols and clouds (9 papers), Soil Geostatistics and Mapping (8 papers), Atmospheric and Environmental Gas Dynamics (7 papers), Spatial and Panel Data Analysis (7 papers), Video Surveillance and Tracking Methods (5 papers), Atmospheric chemistry and aerosols (5 papers), Remote Sensing in Agriculture (4 papers) and Remote-Sensing Image Classification (4 papers). The work is most often cited by research in Environmental Engineering (218 citations), Statistics and Probability (85 citations) and Media Technology (85 citations). Tao Shi has collaborated with scholars based in United States, China and Australia. Frequent co-authors include Noel Cressie, Emily L. Kang, Jonathan R. Bradley, Mikhail A. Belkin, Bin Yu, Qiang Zhang, Fan Wang, Jungong Han, Rick S. Blum and Ningchuan Xiao. Their work appears in journals such as Journal of the American Statistical Association, Remote Sensing of Environment and IEEE Access.

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026