Feini Huang

677 total citations · 3 hit papers
13 papers, 390 citations indexed

About

Feini Huang is a scholar working on Environmental Engineering, Global and Planetary Change and Atmospheric Science. According to data from OpenAlex, Feini Huang has authored 13 papers receiving a total of 390 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Environmental Engineering, 5 papers in Global and Planetary Change and 4 papers in Atmospheric Science. Recurrent topics in Feini Huang's work include Soil Moisture and Remote Sensing (7 papers), Hydrology and Watershed Management Studies (3 papers) and Hydrology and Drought Analysis (3 papers). Feini Huang is often cited by papers focused on Soil Moisture and Remote Sensing (7 papers), Hydrology and Watershed Management Studies (3 papers) and Hydrology and Drought Analysis (3 papers). Feini Huang collaborates with scholars based in China, Iran and Cyprus. Feini Huang's co-authors include Wei Shangguan, Ye Zhang, Qingliang Li, Jianduo Li, Lu Li, Vahid Nourani, Yongjiu Dai, Xingjie Lu, Ruqing Zhang and Chunyan Wang and has published in prestigious journals such as Remote Sensing, Environmental Research Letters and Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences.

In The Last Decade

Feini Huang

13 papers receiving 374 citations

Hit 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.

A 1 km daily soil moisture dataset over China using in situ measurement and machine learning

2022 131 citations Qingliang Li, Wei Shangguan et al. Earth system science data profile →
How Interpretable Machine Learning Can Benefit Process Understanding in the Geosciences

2024 60 citations Shijie Jiang, Alexander Brenning et al. Earth s Future profile →
A China dataset of soil properties for land surface modelling (version 2, CSDLv2)

2025 20 citations Wei Shangguan, Zhongwang Wei et al. Earth system science data profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Feini Huang China	10	177	170	126	84	63	13	390
Zhiguo Pang China	9	266 1.5×	104 0.6×	112 0.9×	121 1.4×	86 1.4×	39	412
Naeem Saddique Pakistan	12	288 1.6×	143 0.8×	144 1.1×	186 2.2×	50 0.8×	22	482
Sat Kumar Tomer India	11	88 0.5×	247 1.5×	141 1.1×	84 1.0×	29 0.5×	14	344
Gregory Halverson United States	10	273 1.5×	208 1.2×	154 1.2×	127 1.5×	46 0.7×	15	426
Huiran Gao China	12	186 1.1×	79 0.5×	107 0.8×	83 1.0×	68 1.1×	37	372
Hui Tian China	11	137 0.8×	119 0.7×	146 1.2×	105 1.3×	58 0.9×	26	332
Mohammed El Hafyani Morocco	11	203 1.1×	120 0.7×	45 0.4×	85 1.0×	120 1.9×	26	389
Christoph Reimer Austria	10	120 0.7×	214 1.3×	237 1.9×	84 1.0×	57 0.9×	20	387
Solomon Obiri Yeboah Amankwah China	11	224 1.3×	74 0.4×	86 0.7×	55 0.7×	42 0.7×	21	345
Abdelhadi El Ouali Morocco	11	237 1.3×	184 1.1×	43 0.3×	140 1.7×	101 1.6×	20	419

Countries citing papers authored by Feini Huang

Since Specialization

Citations

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

Fields of papers citing papers by Feini Huang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Feini Huang

This figure shows the co-authorship network connecting the top 25 collaborators of Feini Huang. A scholar is included among the top collaborators of Feini 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 Feini Huang. Feini Huang 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:

13 of 13 papers shown

Slater, Louise, Anne J. Hoek van Dijke, Feini Huang, et al.. (2025). Challenges and opportunities of ML and explainable AI in large-sample hydrology. Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences. 383(2302). 20240287–20240287. 6 indexed citations

Shangguan, Wei, Zhongwang Wei, Hua Yuan, et al.. (2025). A China dataset of soil properties for land surface modelling (version 2, CSDLv2). Earth system science data. 17(2). 517–543. 20 indexed citations breakdown →

Jiang, Shijie, Alexander Brenning, Wantong Li, et al.. (2024). How Interpretable Machine Learning Can Benefit Process Understanding in the Geosciences. Earth s Future. 12(7). 60 indexed citations breakdown →

Huang, Feini, Yongkun Zhang, Ye Zhang, et al.. (2023). Towards interpreting machine learning models for predicting soil moisture droughts. Environmental Research Letters. 18(7). 74002–74002. 21 indexed citations

Zhang, Ye, et al.. (2023). Real-Time Forecast of SMAP L3 Soil Moisture Using Spatial–Temporal Deep Learning Model with Data Integration. Remote Sensing. 15(2). 366–366. 3 indexed citations

Shangguan, Wei, Vahid Nourani, Qingliang Li, et al.. (2023). A 1 km Global Carbon Flux Dataset Using In Situ Measurements and Deep Learning. Forests. 14(5). 913–913. 13 indexed citations

Huang, Feini, Yongkun Zhang, Ye Zhang, et al.. (2023). Interpreting Conv-LSTM for Spatio-Temporal Soil Moisture Prediction in China. Agriculture. 13(5). 971–971. 21 indexed citations

Huang, Feini, Wei Shangguan, Qingliang Li, Lu Li, & Ye Zhang. (2023). Beyond prediction: An integrated post-hoc approach to interpret complex model in hydrometeorology. Environmental Modelling & Software. 167. 105762–105762. 15 indexed citations

Shangguan, Wei, Ruqing Zhang, Lu Li, et al.. (2022). Assessment of Agricultural Drought Based on Reanalysis Soil Moisture in Southern China. Land. 11(4). 502–502. 18 indexed citations

10.

Li, Qingliang, Wei Shangguan, Vahid Nourani, et al.. (2022). A 1 km daily soil moisture dataset over China using in situ measurement and machine learning. Earth system science data. 14(12). 5267–5286. 131 indexed citations breakdown →

11.

Shangguan, Wei, Qingliang Li, Lu Li, et al.. (2022). A Spatial Downscaling Method for Remote Sensing Soil Moisture Based on Random Forest Considering Soil Moisture Memory and Mass Conservation. Remote Sensing. 14(16). 3858–3858. 27 indexed citations

12.

Huang, Feini, et al.. (2022). Beyond Prediction: An Integrated Post–Hoc Approach to Interpret Complex Model in Hydrometeorology. SSRN Electronic Journal. 2 indexed citations

13.

Zhang, Ruqing, Lu Li, Ye Zhang, et al.. (2021). Assessment of Agricultural Drought Using Soil Water Deficit Index Based on ERA5-Land Soil Moisture Data in Four Southern Provinces of China. Agriculture. 11(5). 411–411. 53 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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