Haiou Guan

587 total citations
29 papers, 419 citations indexed

About

Haiou Guan is a scholar working on Plant Science, Ecology and Atmospheric Science. According to data from OpenAlex, Haiou Guan has authored 29 papers receiving a total of 419 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Plant Science, 17 papers in Ecology and 7 papers in Atmospheric Science. Recurrent topics in Haiou Guan's work include Remote Sensing in Agriculture (17 papers), Smart Agriculture and AI (15 papers) and Leaf Properties and Growth Measurement (12 papers). Haiou Guan is often cited by papers focused on Remote Sensing in Agriculture (17 papers), Smart Agriculture and AI (15 papers) and Leaf Properties and Growth Measurement (12 papers). Haiou Guan collaborates with scholars based in China. Haiou Guan's co-authors include Xiaodan Ma, Song Yu, Jiarui Feng, Gang Liu, Chen Yang, Xia Wu, Gang Liu, Meng Liu, Feiyi Wang and Haichao Zhou and has published in prestigious journals such as Sensors, Frontiers in Plant Science and International Journal of Remote Sensing.

In The Last Decade

Haiou Guan

29 papers receiving 408 citations

Peers

Haiou Guan
Comparison fields: 5 of 63
  • Plant Science 312
  • Ecology 207
  • Environmental Engineering 111
  • Analytical Chemistry 69
  • Atmospheric Science 38
Ran Nisim Lati Israel
Gawain Jones France
Érika Akemi Saito Moriya Brazil
Mauro dos Santos de Arruda Brazil
Brenon Diennevan Souza Barbosa Brazil
Chengjian Zhang China
Renato Herrig Furlanetto Brazil
Nik Norasma Che’Ya Malaysia
Jan Dupuis Germany
P. Boissard France
Ran Nisim Lati Israel View profile →
Citations per field, relative to Haiou Guan
Haiou Guan · 1×
Citations per year, relative to Haiou Guan
Haiou Guan · 1×

Countries citing papers authored by Haiou Guan

Since Specialization
Citations

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

Fields of papers citing papers by Haiou Guan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Haiou Guan

This figure shows the co-authorship network connecting the top 25 collaborators of Haiou Guan. A scholar is included among the top collaborators of Haiou Guan 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 Haiou Guan. Haiou Guan 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
# Work Indexed citations
1 1
2 27
3 2
4 27
5 7
6 3
7 13
8 16
9 29
10 20
11 6
12 8
13 3
14 14
15 36
16 27
17 1
18
Image segmentation model of plant lesion based on genetic algorithm and fuzzy neural network.
1
19 2
20
Timetabling for university classes with genetic algorithm
2

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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