Rong Shang

1.3k total citations · 1 hit paper
32 papers, 984 citations indexed

About

Rong Shang is a scholar working on Global and Planetary Change, Ecology and Environmental Engineering. According to data from OpenAlex, Rong Shang has authored 32 papers receiving a total of 984 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Global and Planetary Change, 22 papers in Ecology and 14 papers in Environmental Engineering. Recurrent topics in Rong Shang's work include Remote Sensing in Agriculture (22 papers), Land Use and Ecosystem Services (11 papers) and Plant Water Relations and Carbon Dynamics (10 papers). Rong Shang is often cited by papers focused on Remote Sensing in Agriculture (22 papers), Land Use and Ecosystem Services (11 papers) and Plant Water Relations and Carbon Dynamics (10 papers). Rong Shang collaborates with scholars based in China, Canada and United States. Rong Shang's co-authors include Zhe Zhu, Ronggao Liu, Yang Liu, Mingzhu Xu, Jing M. Chen, Han Y. H. Chen, Wang Li, Li Wang, Zheng Niu and Yuchu Qin and has published in prestigious journals such as SHILAP Revista de lepidopterología, The Science of The Total Environment and Remote Sensing of Environment.

In The Last Decade

Rong Shang

32 papers receiving 949 citations

Hit Papers

China’s current forest age structure will lead to weakene... 2023 2026 2024 2025 2023 25 50 75
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.

  1. China’s current forest age structure will lead to weakened carbon sinks in the near future
    2023 87 citations Rong Shang, Jing M. Chen et al. The Innovation profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Rong Shang China 14 686 487 442 180 147 32 984
Magdalena Main‐Knorn Germany 10 586 0.9× 440 0.9× 397 0.9× 150 0.8× 95 0.6× 20 1.0k
Nicolas Lauret France 17 907 1.3× 575 1.2× 874 2.0× 146 0.8× 215 1.5× 50 1.3k
Jinyan Tian China 13 804 1.2× 369 0.8× 417 0.9× 215 1.2× 134 0.9× 30 1.1k
Javier Pacheco‐Labrador Spain 22 736 1.1× 800 1.6× 269 0.6× 151 0.8× 258 1.8× 43 1.1k
Marcel Schwieder Germany 16 887 1.3× 510 1.0× 385 0.9× 238 1.3× 192 1.3× 35 1.2k
Astrid Verhegghen Italy 13 538 0.8× 522 1.1× 260 0.6× 120 0.7× 99 0.7× 29 887
Hiroki Yoshioka Japan 16 753 1.1× 464 1.0× 476 1.1× 181 1.0× 105 0.7× 86 970
Andrew Mellor Australia 13 664 1.0× 507 1.0× 503 1.1× 89 0.5× 78 0.5× 27 1.0k
Andrea Ehammer Denmark 11 512 0.7× 448 0.9× 339 0.8× 188 1.0× 91 0.6× 13 957
Matheus Pinheiro Ferreira Brazil 16 929 1.4× 346 0.7× 830 1.9× 95 0.5× 150 1.0× 43 1.3k

Countries citing papers authored by Rong Shang

Since Specialization
Citations

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

Fields of papers citing papers by Rong Shang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rong Shang

This figure shows the co-authorship network connecting the top 25 collaborators of Rong Shang. A scholar is included among the top collaborators of Rong Shang 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 Rong Shang. Rong Shang 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.
Qiu, Feng, et al.. (2025). A dataset of forest regrowth in globally key deforestation regions. Scientific Data. 12(1). 154–154. 1 indexed citations
2.
Shang, Rong, Xudong Lin, Jing M. Chen, et al.. (2025). China's annual forest age dataset at a 30 m spatial resolution from 1986 to 2022. Earth system science data. 17(7). 3219–3241. 3 indexed citations
3.
Shang, Rong, et al.. (2025). Comprehensive Comparison and Validation of Forest Disturbance Monitoring Algorithms Based on Landsat Time Series in China. Remote Sensing. 17(4). 680–680. 3 indexed citations
4.
Yan, Yulin, Bolun Li, Benjamin Dechant, et al.. (2025). Plant traits shape global spatiotemporal variations in photosynthetic efficiency. Nature Plants. 11(4). 924–934. 2 indexed citations
5.
Zhong, Deyu, et al.. (2025). Afforestation as a mitigation strategy: countering climate-induced risk of forest carbon sink in China. Carbon Balance and Management. 20(1). 18–18. 3 indexed citations
6.
Xu, Mingzhu, Jing M. Chen, Yihong Liu, et al.. (2024). Comparative assessment of leaf photosynthetic capacity datasets for estimating terrestrial gross primary productivity. The Science of The Total Environment. 926. 171400–171400. 2 indexed citations
7.
Peng, Li, Rong Shang, Jing M. Chen, et al.. (2024). Evaluation of five models for constructing forest NPP–age relationships in China based on 3121 field survey samples. Biogeosciences. 21(2). 625–639. 6 indexed citations
8.
Zhang, Haicheng, Rong Shang, Jingmin Chen, et al.. (2024). It is time to optimize forest management policy for both carbon sinks and wood harvest in China. National Science Review. 12(4). nwae464–nwae464. 1 indexed citations
9.
Miao, Guofang, Han Liu, Zhiqiang Cheng, et al.. (2024). Elevational distribution of forests and its spatiotemporal dynamics in subtropical China from 2000 to 2019. Science China Earth Sciences. 67(8). 2563–2582. 1 indexed citations
10.
Xu, Mingzhu, et al.. (2023). LACC2.0: Improving the LACC Algorithm for Reconstructing Satellite-Derived Time Series of Vegetation Biochemical Parameters. Remote Sensing. 15(13). 3277–3277. 1 indexed citations
11.
Shang, Rong, Jing M. Chen, Mingzhu Xu, et al.. (2023). China’s current forest age structure will lead to weakened carbon sinks in the near future. The Innovation. 4(6). 100515–100515. 87 indexed citations breakdown →
12.
Xu, Mingzhu, Ronggao Liu, Jing M. Chen, et al.. (2022). A 21-Year Time Series of Global Leaf Chlorophyll Content Maps From MODIS Imagery. IEEE Transactions on Geoscience and Remote Sensing. 60. 1–13. 29 indexed citations
13.
Liu, Yang, Ronggao Liu, & Rong Shang. (2022). GLOBMAP SWF: a global annual surface water cover frequency dataset during 2000–2020. Earth system science data. 14(10). 4505–4523. 9 indexed citations
14.
Xu, Mingzhu, Ronggao Liu, Jing M. Chen, et al.. (2022). Retrieving global leaf chlorophyll content from MERIS data using a neural network method. ISPRS Journal of Photogrammetry and Remote Sensing. 192. 66–82. 36 indexed citations
15.
Zhang, Junxue, Rong Shang, Chadwick D. Rittenhouse, Chandi Witharana, & Zhe Zhu. (2021). Evaluating the impacts of models, data density and irregularity on reconstructing and forecasting dense Landsat time series. SHILAP Revista de lepidopterología. 4. 100023–100023. 36 indexed citations
16.
17.
Liu, Ronggao, et al.. (2019). Effect of Mathematical Expression of Vegetation Indices on the Estimation of Phenology Trends from Satellite Data. Chinese Geographical Science. 29(5). 756–767. 9 indexed citations
18.
Xu, Mingzhu, Ronggao Liu, Jing M. Chen, et al.. (2019). Retrieving leaf chlorophyll content using a matrix-based vegetation index combination approach. Remote Sensing of Environment. 224. 60–73. 119 indexed citations
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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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