Anting Guo

1.0k total citations
31 papers, 767 citations indexed

About

Anting Guo is a scholar working on Ecology, Plant Science and Analytical Chemistry. According to data from OpenAlex, Anting Guo has authored 31 papers receiving a total of 767 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Ecology, 24 papers in Plant Science and 10 papers in Analytical Chemistry. Recurrent topics in Anting Guo's work include Remote Sensing in Agriculture (27 papers), Smart Agriculture and AI (12 papers) and Spectroscopy and Chemometric Analyses (10 papers). Anting Guo is often cited by papers focused on Remote Sensing in Agriculture (27 papers), Smart Agriculture and AI (12 papers) and Spectroscopy and Chemometric Analyses (10 papers). Anting Guo collaborates with scholars based in China, Australia and Italy. Anting Guo's co-authors include Wenjiang Huang, Yingying Dong, Huichun Ye, Huiqin Ma, Yu Ren, Chao Ruan, Yun Geng, Linyi Liu, Shanyu Huang and Yu Jin and has published in prestigious journals such as Sensors, Agricultural and Forest Meteorology and Remote Sensing.

In The Last Decade

Anting Guo

27 papers receiving 740 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Anting Guo China 14 516 465 272 124 85 31 767
Linyi Liu China 16 610 1.2× 460 1.0× 355 1.3× 127 1.0× 76 0.9× 29 949
Jaafar Abdulridha United States 14 799 1.5× 517 1.1× 372 1.4× 116 0.9× 39 0.5× 20 1.0k
Davoud Ashourloo Iran 12 537 1.0× 541 1.2× 302 1.1× 154 1.2× 125 1.5× 16 862
Kaihua Wu China 12 485 0.9× 350 0.8× 262 1.0× 84 0.7× 46 0.5× 56 840
Chao Ruan China 13 353 0.7× 301 0.6× 193 0.7× 84 0.7× 65 0.8× 39 586
Sourav Bhadra United States 9 350 0.7× 328 0.7× 188 0.7× 94 0.8× 54 0.6× 16 584
Rocío Calderón Spain 10 773 1.5× 765 1.6× 282 1.0× 252 2.0× 56 0.7× 12 1.2k
C. Camino Spain 18 641 1.2× 604 1.3× 198 0.7× 143 1.2× 180 2.1× 35 1.1k
Nadia Shakoor United States 16 829 1.6× 592 1.3× 150 0.6× 347 2.8× 65 0.8× 36 1.4k
Nicolas Virlet United Kingdom 11 622 1.2× 423 0.9× 136 0.5× 166 1.3× 28 0.3× 19 806

Countries citing papers authored by Anting Guo

Since Specialization
Citations

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

Fields of papers citing papers by Anting Guo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anting Guo

This figure shows the co-authorship network connecting the top 25 collaborators of Anting Guo. A scholar is included among the top collaborators of Anting Guo 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 Anting Guo. Anting Guo 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.
Huang, Wenjiang, Anting Guo, Zhiying Cai, et al.. (2025). Monitoring of rubber tree powdery mildew by combining spatial-spectral features and plant traits quantified from UAV hyperspectral imagery. Computers and Electronics in Agriculture. 241. 111274–111274.
2.
Guo, Anting, Chao Ruan, Wenjiang Huang, et al.. (2025). Inversion of plant functional traits from hyperspectral imagery enhances the distinction of wheat stripe rust severity. Artificial Intelligence in Agriculture. 16(1). 206–223.
3.
Guo, Anting, et al.. (2024). Improved early detection of wheat stripe rust through integration pigments and pigment-related spectral indices quantified from UAV hyperspectral imagery. International Journal of Applied Earth Observation and Geoinformation. 135. 104281–104281.
4.
Guo, Anting, et al.. (2024). Early Monitoring of Maize Northern Leaf Blight Using Vegetation Indices and Plant Traits from Multiangle Hyperspectral Data. Agriculture. 14(8). 1311–1311. 6 indexed citations
5.
Guo, Anting, et al.. (2024). Inversion of maize leaf nitrogen using UAV hyperspectral imagery in breeding fields. International journal of agricultural and biological engineering. 17(3). 144–155. 1 indexed citations
6.
Guo, Anting, Wenjiang Huang, Zhiying Cai, et al.. (2024). Early Detection of Rubber Tree Powdery Mildew by Combining Spectral and Physicochemical Parameter Features. Remote Sensing. 16(9). 1634–1634. 8 indexed citations
7.
Guo, Anting, et al.. (2023). Inversion of maize leaf area index from UAV hyperspectral and multispectral imagery. Computers and Electronics in Agriculture. 212. 108020–108020. 45 indexed citations
8.
Huang, Wenjiang, Donghui Xie, Huichun Ye, et al.. (2023). Coupled maize model: A 4D maize growth model based on growing degree days. Computers and Electronics in Agriculture. 212. 108124–108124. 13 indexed citations
9.
Guo, Anting, Huichun Ye, Guoqing Li, et al.. (2023). Evaluation of Hybrid Models for Maize Chlorophyll Retrieval Using Medium- and High-Spatial-Resolution Satellite Images. Remote Sensing. 15(7). 1784–1784. 10 indexed citations
10.
Guo, Anting, Wenjiang Huang, Zhiying Cai, et al.. (2023). Detection of Rubber Tree Powdery Mildew from Leaf Level Hyperspectral Data Using Continuous Wavelet Transform and Machine Learning. Remote Sensing. 16(1). 105–105. 9 indexed citations
12.
Ruan, Chao, Yingying Dong, Wenjiang Huang, et al.. (2022). Integrating Remote Sensing and Meteorological Data to Predict Wheat Stripe Rust. Remote Sensing. 14(5). 1221–1221. 17 indexed citations
13.
Ruan, Chao, Yingying Dong, Wenjiang Huang, et al.. (2021). Prediction of Wheat Stripe Rust Occurrence with Time Series Sentinel-2 Images. Agriculture. 11(11). 1079–1079. 21 indexed citations
14.
Guo, Anting, Wenjiang Huang, Yingying Dong, et al.. (2021). Wheat Yellow Rust Detection Using UAV-Based Hyperspectral Technology. Remote Sensing. 13(1). 123–123. 133 indexed citations
15.
Dong, Yingying, Linyi Liu, Xiaoping Du, et al.. (2020). Automatic System for Crop Pest and Disease Dynamic Monitoring and Early Forecasting. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 13. 4410–4418. 45 indexed citations
16.
Guo, Anting, Wenjiang Huang, Huichun Ye, et al.. (2020). Identification of Wheat Yellow Rust Using Spectral and Texture Features of Hyperspectral Images. Remote Sensing. 12(9). 1419–1419. 93 indexed citations
17.
Ren, Yu, Yanhua Meng, Wenjiang Huang, et al.. (2020). Novel Vegetation Indices for Cotton Boll Opening Status Estimation Using Sentinel-2 Data. Remote Sensing. 12(11). 1712–1712. 6 indexed citations
18.
Ye, Huichun, Wenjiang Huang, Shanyu Huang, et al.. (2020). Recognition of Banana Fusarium Wilt Based on UAV Remote Sensing. Remote Sensing. 12(6). 938–938. 97 indexed citations
19.
Ye, Huichun, Wenjiang Huang, Shanyu Huang, et al.. (2020). Identification of banana fusarium wilt using supervised classification algorithms with UAV-based multi-spectral imagery. International journal of agricultural and biological engineering. 13(3). 136–142. 40 indexed citations
20.
Ma, Huiqin, Wenjiang Huang, Yuanshu Jing, et al.. (2019). Identification of Fusarium Head Blight in Winter Wheat Ears Using Continuous Wavelet Analysis. Sensors. 20(1). 20–20. 49 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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