Shanyu Huang

1.7k total citations
26 papers, 1.4k citations indexed

About

Shanyu Huang is a scholar working on Ecology, Plant Science and Environmental Engineering. According to data from OpenAlex, Shanyu Huang has authored 26 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Ecology, 15 papers in Plant Science and 5 papers in Environmental Engineering. Recurrent topics in Shanyu Huang's work include Remote Sensing in Agriculture (17 papers), Smart Agriculture and AI (7 papers) and Rice Cultivation and Yield Improvement (6 papers). Shanyu Huang is often cited by papers focused on Remote Sensing in Agriculture (17 papers), Smart Agriculture and AI (7 papers) and Rice Cultivation and Yield Improvement (6 papers). Shanyu Huang collaborates with scholars based in China, Germany and United States. Shanyu Huang's co-authors include Yuxin Miao, Georg Bareth, Qiang Cao, Fei Yuan, Martin L. Gnyp, Yinkun Yao, Victoria Lenz-Wiedemann, Hongye Wang, Huichun Ye and Kang Yu and has published in prestigious journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and Frontiers in Plant Science.

In The Last Decade

Shanyu Huang

24 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shanyu Huang China 17 1.1k 762 616 253 197 26 1.4k
Shouyang Liu China 21 987 0.9× 1.1k 1.5× 537 0.9× 324 1.3× 239 1.2× 45 1.7k
Yonggui Xiao China 19 900 0.8× 1.1k 1.5× 391 0.6× 167 0.7× 213 1.1× 36 1.6k
Liyuan Zhang China 17 680 0.6× 619 0.8× 418 0.7× 244 1.0× 97 0.5× 38 1.1k
M. R. Schlemmer United States 11 1.0k 1.0× 1.0k 1.3× 390 0.6× 293 1.2× 241 1.2× 13 1.5k
Montserrat Jurado-Expósito Spain 24 945 0.9× 809 1.1× 577 0.9× 308 1.2× 281 1.4× 50 1.8k
Chenwei Nie China 18 673 0.6× 641 0.8× 295 0.5× 176 0.7× 219 1.1× 60 1.1k
Fábio Henrique Rojo Baio Brazil 18 681 0.6× 823 1.1× 243 0.4× 200 0.8× 241 1.2× 123 1.4k
Raúl López‐Lozano France 18 1.1k 1.1× 878 1.2× 458 0.7× 559 2.2× 202 1.0× 43 1.7k
Eddy De Pauw Syria 15 1.0k 1.0× 724 1.0× 460 0.7× 394 1.6× 252 1.3× 33 1.7k
Li He China 22 829 0.8× 853 1.1× 246 0.4× 170 0.7× 382 1.9× 53 1.3k

Countries citing papers authored by Shanyu Huang

Since Specialization
Citations

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

Fields of papers citing papers by Shanyu Huang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shanyu Huang

This figure shows the co-authorship network connecting the top 25 collaborators of Shanyu Huang. A scholar is included among the top collaborators of Shanyu Huang 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 Shanyu Huang. Shanyu Huang 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
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Wei, Peng, et al.. (2023). Early Crop Mapping Based on Sentinel-2 Time-Series Data and the Random Forest Algorithm. Remote Sensing. 15(13). 3212–3212. 32 indexed citations
4.
Huang, Wenjiang, Yingying Dong, Huichun Ye, et al.. (2023). Remote Sensing Monitoring of Rice Diseases and Pests from Different Data Sources: A Review. Agronomy. 13(7). 1851–1851. 37 indexed citations
5.
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
6.
Ye, Huichun, Wenjiang Huang, Shanyu Huang, et al.. (2020). Identification of banana fusarium wilt using supervised classification algorithms with UAV-based multi-spectral imagery. 13(3). 136–142. 4 indexed citations
7.
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
8.
Huang, Shanyu, Yuxin Miao, Fei Yuan, et al.. (2019). In-Season Diagnosis of Rice Nitrogen Status Using Proximal Fluorescence Canopy Sensor at Different Growth Stages. Remote Sensing. 11(16). 1847–1847. 33 indexed citations
9.
Huang, Shanyu, Haowen Luo, Umair Ashraf, et al.. (2019). SEED TREATMENT WITH PACLOBUTRAZOL AFFECTS EARLY GROWTH, PHOTOSYNTHESIS, CHLOROPHYLL FLUORESCENCE AND PHYSIOLOGY OF RICE. Applied Ecology and Environmental Research. 17(1). 999–1012. 8 indexed citations
10.
Ye, Huichun, et al.. (2018). Remote Estimation of Nitrogen Vertical Distribution by Consideration of Maize Geometry Characteristics. Remote Sensing. 10(12). 1995–1995. 30 indexed citations
11.
Huang, Shanyu, Yuxin Miao, Fei Yuan, et al.. (2017). Potential of RapidEye and WorldView-2 Satellite Data for Improving Rice Nitrogen Status Monitoring at Different Growth Stages. Remote Sensing. 9(3). 227–227. 76 indexed citations
12.
Huang, Shanyu, Yuxin Miao, Fei Yuan, et al.. (2017). Proximal fluorescence sensing for in-season diagnosis of rice nitrogen status. Advances in Animal Biosciences. 8(2). 343–348. 2 indexed citations
13.
Ye, Huichun, Wenjiang Huang, Shanyu Huang, et al.. (2017). Effects of different sampling densities on geographically weighted regression kriging for predicting soil organic carbon. Spatial Statistics. 20. 76–91. 45 indexed citations
14.
Ye, Huichun, Yuanfang Huang, Pengfei Chen, et al.. (2016). Effects of land use change on the spatiotemporal variability of soil organic carbon in an urban-rural ecotone of Beijing, China. Journal of Integrative Agriculture. 15(4). 918–928. 14 indexed citations
15.
Huang, Shanyu, Yuxin Miao, Guangming Zhao, et al.. (2015). Satellite Remote Sensing-Based In-Season Diagnosis of Rice Nitrogen Status in Northeast China. Remote Sensing. 7(8). 10646–10667. 110 indexed citations
16.
Tilly, Nora, Dirk Hoffmeister, Qiang Cao, et al.. (2014). Multitemporal crop surface models: accurate plant height measurement and biomass estimation with terrestrial laser scanning in paddy rice. Journal of Applied Remote Sensing. 8(1). 83671–83671. 171 indexed citations
17.
Gnyp, Martin L., Kang Yu, Helge Aasen, et al.. (2013). Analysis of Crop Reflectance for Estimating Biomass in Rice Canopies at Different Phenological Stages. Photogrammetrie - Fernerkundung - Geoinformation. 2013(4). 351–365. 33 indexed citations
18.
Cao, Qiang, Yuxin Miao, Shanyu Huang, et al.. (2013). Estimating rice nitrogen status with the Crop Circle multispectral active canopy sensor. 95–101. 3 indexed citations
19.
Huang, Shanyu, Yuxin Miao, Guangming Zhao, et al.. (2013). Estimating rice nitrogen status with satellite remote sensing in Northeast China. 550–557. 5 indexed citations
20.
Gnyp, Martin L., Yinkun Yao, Kang Yu, et al.. (2012). HYPERSPECTRAL ANALYSIS OF RICE PHENOLOGICAL STAGES IN NORTHEAST CHINA. SHILAP Revista de lepidopterología. I-7. 77–82. 4 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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