Ling Peng

781 total citations · 1 hit paper
30 papers, 557 citations indexed

About

Ling Peng is a scholar working on Global and Planetary Change, Artificial Intelligence and Management, Monitoring, Policy and Law. According to data from OpenAlex, Ling Peng has authored 30 papers receiving a total of 557 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Global and Planetary Change, 8 papers in Artificial Intelligence and 8 papers in Management, Monitoring, Policy and Law. Recurrent topics in Ling Peng's work include Landslides and related hazards (6 papers), Fire effects on ecosystems (6 papers) and Geographic Information Systems Studies (5 papers). Ling Peng is often cited by papers focused on Landslides and related hazards (6 papers), Fire effects on ecosystems (6 papers) and Geographic Information Systems Studies (5 papers). Ling Peng collaborates with scholars based in China, Austria and United States. Ling Peng's co-authors include Yi Wang, Haoyuan Hong, Zhice Fang, Yi Yang, Weichao Li, Lina Yang, Tianhe Chi, Jiahui Song, Heping Pan and Huolin Ma and has published in prestigious journals such as Scientific Reports, Journal of Hydrology and Information Sciences.

In The Last Decade

Ling Peng

27 papers receiving 541 citations

Hit Papers

Flood susceptibility mapping using convolutional neural n... 2019 2026 2021 2023 2019 50 100 150 200
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. Flood susceptibility mapping using convolutional neural network frameworks
    2019 241 citations Yi Wang, Zhice Fang et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ling Peng China 12 302 125 110 107 99 30 557
Xiangang Luo China 16 563 1.9× 259 2.1× 277 2.5× 181 1.7× 75 0.8× 52 992
Zhanya Xu China 10 252 0.8× 206 1.6× 169 1.5× 75 0.7× 56 0.6× 26 521
Van‐Manh Pham Vietnam 15 369 1.2× 195 1.6× 139 1.3× 132 1.2× 70 0.7× 33 656
Leila Hashemi-Beni United States 13 343 1.1× 200 1.6× 106 1.0× 57 0.5× 92 0.9× 39 624
Quoc‐Huy Nguyen Vietnam 17 493 1.6× 249 2.0× 226 2.1× 165 1.5× 95 1.0× 37 780
Anselme Muzirafuti Italy 14 104 0.3× 131 1.0× 54 0.5× 57 0.5× 90 0.9× 25 709
Bo Xiang China 13 154 0.5× 83 0.7× 47 0.4× 120 1.1× 31 0.3× 46 481
Christos Vasilakos Greece 14 431 1.4× 142 1.1× 48 0.4× 144 1.3× 39 0.4× 30 672

Countries citing papers authored by Ling Peng

Since Specialization
Citations

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

Fields of papers citing papers by Ling Peng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ling Peng

This figure shows the co-authorship network connecting the top 25 collaborators of Ling Peng. A scholar is included among the top collaborators of Ling Peng 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 Ling Peng. Ling Peng 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.
Peng, Ling, Hengtao Xu, & Zhifu Wang. (2025). Innovative approaches to marine environmental protection: Assessing the impact of community engagement, technology, and policy enforcement. Multidisciplinary Science Journal. 7(8). 2025396–2025396.
2.
Peng, Ling, et al.. (2024). Research on the Exposure Risk Analysis of Wildfires with a Spatiotemporal Knowledge Graph. Fire. 7(4). 131–131. 2 indexed citations
3.
Yang, Lina, et al.. (2023). An Improved Multi-Source Data-Driven Landslide Prediction Method Based on Spatio-Temporal Knowledge Graph. Remote Sensing. 15(8). 2126–2126. 14 indexed citations
4.
5.
Peng, Ling, et al.. (2023). Spatio-Temporal Knowledge Graph-Based Research on Agro-Meteorological Disaster Monitoring. Remote Sensing. 15(18). 4403–4403. 5 indexed citations
6.
Peng, Ling, et al.. (2023). Improving Landslide Prediction: Innovative Modeling and Evaluation of Landslide Scenario with Knowledge Graph Embedding. Remote Sensing. 16(1). 145–145. 3 indexed citations
7.
Yang, Yi, et al.. (2022). Knowledge Graph Representation Learning-Based Forest Fire Prediction. Remote Sensing. 14(17). 4391–4391. 15 indexed citations
8.
9.
Yang, Yi, et al.. (2022). Spatio-Temporal Knowledge Graph Based Forest Fire Prediction with Multi Source Heterogeneous Data. Remote Sensing. 14(14). 3496–3496. 32 indexed citations
10.
Peng, Ling & Dongbo Zhang. (2021). An adaptive Lévy flight firefly algorithm for multilevel image thresholding based on Rényi entropy. The Journal of Supercomputing. 78(5). 6875–6896. 13 indexed citations
11.
Chen, Jiahui, et al.. (2021). Spatio-Temporal Knowledge Graph for Meteorological Risk Analysis. 440–447. 6 indexed citations
12.
Liu, Lili, et al.. (2021). Spatio-temporal variations of aridity index and its response to climate factors in Northwest China during 1989-2019.. PubMed. 32(11). 4050–4058. 3 indexed citations
13.
Peng, Ling & Dongbo Zhang. (2021). Correction to: An adaptive Lévy flight firefly algorithm for multilevel image thresholding based on Rényi entropy. The Journal of Supercomputing. 78(5). 6897–6897. 1 indexed citations
14.
Peng, Ling, et al.. (2021). Building Extraction and Number Statistics in WUI Areas Based on UNet Structure and Ensemble Learning. Remote Sensing. 13(6). 1172–1172. 13 indexed citations
15.
Song, Jiahui, Yi Wang, Zhice Fang, Ling Peng, & Haoyuan Hong. (2020). Potential of Ensemble Learning to Improve Tree-Based Classifiers for Landslide Susceptibility Mapping. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 13. 4642–4662. 48 indexed citations
16.
Yao, Xiaojing, Xufeng Jiang, Dacheng Wang, et al.. (2020). Efficiently mining maximal co-locations in a spatial continuous field under directed road networks. Information Sciences. 542. 357–379. 17 indexed citations
17.
18.
Peng, Ling, Chi Zhang, Huolin Ma, & Heping Pan. (2019). Estimating irreducible water saturation and permeability of sandstones from nuclear magnetic resonance measurements by fractal analysis. Marine and Petroleum Geology. 110. 565–574. 32 indexed citations
19.
Pan, Heping, Ahmed Amara Konaté, Bo Guo, et al.. (2016). Crosswell electromagnetic modeling from impulsive source: Optimization strategy for dispersion suppression in convolutional perfectly matched layer. Scientific Reports. 6(1). 32613–32613. 4 indexed citations
20.
Peng, Ling. (2008). Connected Component Labelling for Massive Remote Sensing Classification Image. Jisuanji gongcheng. 1 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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