Mingbo Bian

666 total citations · 5 hit papers
19 papers, 524 citations indexed

About

Mingbo Bian is a scholar working on Ecology, Environmental Engineering and Analytical Chemistry. According to data from OpenAlex, Mingbo Bian has authored 19 papers receiving a total of 524 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Ecology, 8 papers in Environmental Engineering and 7 papers in Analytical Chemistry. Recurrent topics in Mingbo Bian's work include Remote Sensing in Agriculture (17 papers), Remote Sensing and LiDAR Applications (8 papers) and Spectroscopy and Chemometric Analyses (7 papers). Mingbo Bian is often cited by papers focused on Remote Sensing in Agriculture (17 papers), Remote Sensing and LiDAR Applications (8 papers) and Spectroscopy and Chemometric Analyses (7 papers). Mingbo Bian collaborates with scholars based in China and Germany. Mingbo Bian's co-authors include Yiguang Fan, Haikuan Feng, Yanpeng Ma, Guijun Yang, Jibo Yue, Riqiang Chen, Xiuliang Jin, Yang Liu, Yang Liu and Xiaoyu Song and has published in prestigious journals such as Frontiers in Plant Science, Field Crops Research and Computers and Electronics in Agriculture.

In The Last Decade

Mingbo Bian

17 papers receiving 515 citations

Hit Papers

5 papers align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Estimating potato above-ground biomass based on vegetation indices and texture features constructed from sensitive bands of UAV hyperspectral imagery

2024 65 citations Yang Liu, Yiguang Fan et al. Computers and Electronics in Agriculture profile →
Improving potato AGB estimation to mitigate phenological stage impacts through depth features from hyperspectral data

2024 57 citations Yang Liu, Haikuan Feng et al. Computers and Electronics in Agriculture profile →
Improving potato above ground biomass estimation combining hyperspectral data and harmonic decomposition techniques

2024 53 citations Yang Liu, Haikuan Feng et al. Computers and Electronics in Agriculture profile →
Utilizing UAV-based hyperspectral remote sensing combined with various agronomic traits to monitor potato growth and estimate yield

2025 30 citations Yang Liu, Haikuan Feng et al. Computers and Electronics in Agriculture profile →
Estimation of potato above-ground biomass based on the VGC-AGB model and deep learning

2025 15 citations Haikuan Feng, Yiguang Fan et al. Computers and Electronics in Agriculture profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Mingbo Bian China	11	405	250	174	155	132	19	524
Yiguang Fan China	16	545 1.3×	325 1.3×	237 1.4×	200 1.3×	160 1.2×	26	690
Changwei Tan China	15	377 0.9×	380 1.5×	144 0.8×	133 0.9×	71 0.5×	44	626
Philippe Vigneault Canada	7	600 1.5×	441 1.8×	247 1.4×	159 1.0×	69 0.5×	13	749
Yinkun Yao China	7	497 1.2×	296 1.2×	282 1.6×	78 0.5×	90 0.7×	11	635
Shaoyu Han China	15	320 0.8×	256 1.0×	141 0.8×	99 0.6×	82 0.6×	29	467
Meiyan Shu China	16	584 1.4×	468 1.9×	293 1.7×	146 0.9×	108 0.8×	35	794
Dthenifer Cordeiro Santana Brazil	11	350 0.9×	362 1.4×	110 0.6×	183 1.2×	43 0.3×	51	562
Chunsong Bian China	12	393 1.0×	532 2.1×	207 1.2×	118 0.8×	41 0.3×	31	780
José Eduardo Creste Brazil	10	335 0.8×	443 1.8×	159 0.9×	134 0.9×	30 0.2×	33	612
Fabienne Maupas France	8	450 1.1×	381 1.5×	208 1.2×	100 0.6×	52 0.4×	14	636

Countries citing papers authored by Mingbo Bian

Since Specialization

Citations

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

Fields of papers citing papers by Mingbo Bian

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mingbo Bian

This figure shows the co-authorship network connecting the top 25 collaborators of Mingbo Bian. A scholar is included among the top collaborators of Mingbo Bian 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 Mingbo Bian. Mingbo Bian is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

19 of 19 papers shown

Feng, Haikuan, Yiguang Fan, Jibo Yue, et al.. (2025). Estimation of potato above-ground biomass based on the VGC-AGB model and deep learning. Computers and Electronics in Agriculture. 232. 110122–110122. 15 indexed citations breakdown →

Liu, Yang, Haikuan Feng, Yiguang Fan, et al.. (2025). Utilizing UAV-based hyperspectral remote sensing combined with various agronomic traits to monitor potato growth and estimate yield. Computers and Electronics in Agriculture. 231. 109984–109984. 30 indexed citations breakdown →

Feng, Haikuan, Yiguang Fan, Jibo Yue, et al.. (2025). Enhancing potato leaf protein content, carbon-based constituents, and leaf area index monitoring using radiative transfer model and deep learning. European Journal of Agronomy. 166. 127580–127580. 5 indexed citations

Liu, Yang, Yiguang Fan, Jibo Yue, et al.. (2025). UAV-based remote sensing estimation of above-ground biomass in different crops: A review. International Journal of Applied Earth Observation and Geoinformation. 144. 104938–104938.

Fan, Yiguang, Haikuan Feng, Jibo Yue, et al.. (2025). Critical nitrogen and potassium dilution curves for potato in Northeast China. Field Crops Research. 334. 110129–110129.

Liu, Yang, Yiguang Fan, Jibo Yue, et al.. (2025). Combining multiple spectral preprocessing and wavelength optimization methods improves potato aboveground biomass estimation. Information Processing in Agriculture. 12(4). 511–521. 1 indexed citations

Liu, Yang, Yiguang Fan, Jibo Yue, et al.. (2024). A model suitable for estimating above-ground biomass of potatoes at different regional levels. Computers and Electronics in Agriculture. 222. 109081–109081. 38 indexed citations

Liu, Yang, Haikuan Feng, Jibo Yue, et al.. (2024). Improving potato AGB estimation to mitigate phenological stage impacts through depth features from hyperspectral data. Computers and Electronics in Agriculture. 219. 108808–108808. 57 indexed citations breakdown →

Liu, Yang, Jibo Yue, Wanxue Zhu, et al.. (2024). Crop canopy volume weighted by color parameters from UAV-based RGB imagery to estimate above-ground biomass of potatoes. Computers and Electronics in Agriculture. 227. 109678–109678. 31 indexed citations

10.

Liu, Yang, Yiguang Fan, Yihan Yao, et al.. (2024). Estimation of potato leaf area index based on spectral information and Haralick textures from UAV hyperspectral images. Frontiers in Plant Science. 15. 1492372–1492372. 3 indexed citations

11.

Fan, Yiguang, Yang Liu, Jibo Yue, et al.. (2024). Estimation of potato yield using a semi-mechanistic model developed by proximal remote sensing and environmental variables. Computers and Electronics in Agriculture. 223. 109117–109117. 18 indexed citations

12.

Liu, Yang, Yiguang Fan, Haikuan Feng, et al.. (2024). Estimating potato above-ground biomass based on vegetation indices and texture features constructed from sensitive bands of UAV hyperspectral imagery. Computers and Electronics in Agriculture. 220. 108918–108918. 65 indexed citations breakdown →

13.

Liu, Yang, Haikuan Feng, Yiguang Fan, et al.. (2024). Improving potato above ground biomass estimation combining hyperspectral data and harmonic decomposition techniques. Computers and Electronics in Agriculture. 218. 108699–108699. 53 indexed citations breakdown →

14.

Fan, Yiguang, Haikuan Feng, Yang Liu, et al.. (2024). Transferability of models for predicting potato plant nitrogen content from remote sensing data and environmental variables across years and regions. European Journal of Agronomy. 161. 127388–127388. 8 indexed citations

15.

Liu, Yang, Haikuan Feng, Jibo Yue, et al.. (2023). Estimating potato above-ground biomass by using integrated unmanned aerial system-based optical, structural, and textural canopy measurements. Computers and Electronics in Agriculture. 213. 108229–108229. 75 indexed citations

16.

Bian, Mingbo, Zhichao Chen, Yiguang Fan, et al.. (2023). Integrating Spectral, Textural, and Morphological Data for Potato LAI Estimation from UAV Images. Agronomy. 13(12). 3070–3070. 9 indexed citations

17.

Liu, Yang, Haikuan Feng, Jibo Yue, et al.. (2023). Improved potato AGB estimates based on UAV RGB and hyperspectral images. Computers and Electronics in Agriculture. 214. 108260–108260. 77 indexed citations

18.

Fan, Yiguang, et al.. (2023). Estimating potassium in potato plants based on multispectral images acquired from unmanned aerial vehicles. Frontiers in Plant Science. 14. 1265132–1265132. 7 indexed citations

19.

Fan, Yiguang, Haikuan Feng, Jibo Yue, et al.. (2023). Using an optimized texture index to monitor the nitrogen content of potato plants over multiple growth stages. Computers and Electronics in Agriculture. 212. 108147–108147. 32 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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