Peng Wan

1.9k total citations · 1 hit paper
18 papers, 1.4k citations indexed

About

Peng Wan is a scholar working on Environmental Engineering, Geology and Nature and Landscape Conservation. According to data from OpenAlex, Peng Wan has authored 18 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Environmental Engineering, 9 papers in Geology and 6 papers in Nature and Landscape Conservation. Recurrent topics in Peng Wan's work include Remote Sensing and LiDAR Applications (13 papers), 3D Surveying and Cultural Heritage (9 papers) and Forest ecology and management (6 papers). Peng Wan is often cited by papers focused on Remote Sensing and LiDAR Applications (13 papers), 3D Surveying and Cultural Heritage (9 papers) and Forest ecology and management (6 papers). Peng Wan collaborates with scholars based in China, Netherlands and France. Peng Wan's co-authors include Wuming Zhang, Guangjian Yan, Jianbo Qi, Xiaoyan Wang, Donghui Xie, Hongtao Wang, Shangshu Cai, Tiejun Wang, Xiuliang Jin and Yiming Chen and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Geoscience and Remote Sensing and Agricultural and Forest Meteorology.

In The Last Decade

Peng Wan

17 papers receiving 1.4k citations

Hit Papers

An Easy-to-Use Airborne LiDAR Data Filtering Method Based... 2016 2026 2019 2022 2016 250 500 750 1000

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Peng Wan China 11 1.2k 702 473 344 210 18 1.4k
Frédéric Bretar France 12 1.2k 1.0× 558 0.8× 534 1.1× 316 0.9× 182 0.9× 27 1.4k
Anssi Krooks Finland 18 929 0.7× 479 0.7× 480 1.0× 241 0.7× 119 0.6× 25 1.2k
Carlos Çabo Spain 15 957 0.8× 530 0.8× 281 0.6× 281 0.8× 201 1.0× 34 1.2k
Peter Axelsson Sweden 4 1.5k 1.2× 823 1.2× 632 1.3× 504 1.5× 311 1.5× 8 1.7k
Jonathan P. Dandois United States 10 1.1k 0.9× 507 0.7× 764 1.6× 246 0.7× 230 1.1× 12 1.4k
Martin Mokroš Czechia 18 908 0.7× 513 0.7× 239 0.5× 318 0.9× 238 1.1× 46 1.1k
Stefano Puliti Norway 22 1.6k 1.3× 579 0.8× 873 1.8× 567 1.6× 479 2.3× 46 1.9k
Aloysius Wehr Germany 5 894 0.7× 454 0.6× 327 0.7× 191 0.6× 127 0.6× 12 1.1k
Matti Vaaja Finland 23 1.3k 1.0× 642 0.9× 629 1.3× 470 1.4× 291 1.4× 83 1.9k
Xuelian Meng United States 13 939 0.8× 480 0.7× 633 1.3× 174 0.5× 78 0.4× 23 1.3k

Countries citing papers authored by Peng Wan

Since Specialization
Citations

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

Fields of papers citing papers by Peng Wan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Peng Wan

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

All Works

18 of 18 papers shown
1.
Wan, Peng, et al.. (2025). Closed and Structural Optimization for 3D Line Segment Extraction in Building Point Clouds. Remote Sensing. 17(18). 3234–3234.
2.
Chen, Xijiang, et al.. (2023). Point Cloud Deep Learning Network Based on Local Domain Multi-Level Feature. Applied Sciences. 13(19). 10804–10804. 2 indexed citations
3.
Zhang, Wuming, et al.. (2022). Estimation of Larch Growth at the Stem, Crown, and Branch Levels Using Ground-Based LiDAR Point Cloud. SHILAP Revista de lepidopterología. 2022. 7 indexed citations
4.
Shao, Jie, Wei Yao, Peng Wan, et al.. (2022). Efficient co-registration of UAV and ground LiDAR forest point clouds based on canopy shapes. International Journal of Applied Earth Observation and Geoinformation. 114. 103067–103067. 29 indexed citations
5.
Wan, Peng, et al.. (2021). A novel and efficient method for wood–leaf separation from terrestrial laser scanning point clouds at the forest plot level. Methods in Ecology and Evolution. 12(12). 2473–2486. 26 indexed citations
6.
Li, Linyuan, Xihan Mu, Peng Wan, et al.. (2020). An Iterative-Mode Scan Design of Terrestrial Laser Scanning in Forests for Minimizing Occlusion Effects. IEEE Transactions on Geoscience and Remote Sensing. 59(4). 3547–3566. 21 indexed citations
7.
Wan, Peng, Tiejun Wang, Wuming Zhang, et al.. (2019). Quantification of occlusions influencing the tree stem curve retrieving from single-scan terrestrial laser scanning data. Forest Ecosystems. 6(1). 20 indexed citations
8.
Cai, Shangshu, Wuming Zhang, Xinlian Liang, et al.. (2019). Filtering Airborne LiDAR Data Through Complementary Cloth Simulation and Progressive TIN Densification Filters. Remote Sensing. 11(9). 1037–1037. 65 indexed citations
9.
Zhang, Wuming, Peng Wan, Tiejun Wang, et al.. (2019). A Novel Approach for the Detection of Standing Tree Stems from Plot-Level Terrestrial Laser Scanning Data. Remote Sensing. 11(2). 211–211. 92 indexed citations
10.
Wan, Peng, Wuming Zhang, Andrew K. Skidmore, et al.. (2018). A simple terrain relief index for tuning slope-related parameters of LiDAR ground filtering algorithms. ISPRS Journal of Photogrammetry and Remote Sensing. 143. 181–190. 26 indexed citations
11.
Chen, Yiming, Wuming Zhang, Ronghai Hu, et al.. (2018). Estimation of forest leaf area index using terrestrial laser scanning data and path length distribution model in open-canopy forests. Agricultural and Forest Meteorology. 263. 323–333. 28 indexed citations
12.
Shao, Jie, Wuming Zhang, Nicolas Mellado, et al.. (2018). Automated markerless registration of point clouds from TLS and structured light scanner for heritage documentation. Journal of Cultural Heritage. 35. 16–24. 42 indexed citations
13.
Cai, Shangshu, et al.. (2018). APPLICABILITY ANALYSIS OF CLOTH SIMULATION FILTERING ALGORITHM FOR MOBILE LIDAR POINT CLOUD. SHILAP Revista de lepidopterología. XLII-3. 107–111. 10 indexed citations
14.
Zhang, Wuming, Jianbo Qi, Peng Wan, et al.. (2016). An Easy-to-Use Airborne LiDAR Data Filtering Method Based on Cloth Simulation. Remote Sensing. 8(6). 501–501. 1017 indexed citations breakdown →
15.
Wang, Fei, Yuanjun Laili, Zhang Li, et al.. (2014). Parallel plants collaborative growth algorithm for virtual machine migration. 1(3). 211–211. 2 indexed citations
16.
Wan, Peng, et al.. (2010). Balancing load of shaper in WikiWinWin requirements negotiation environment. 8–11. 2 indexed citations
17.
Wan, Peng. (2008). Effects of the fertilization applications on tea(Camellia sinensis(L.) Kuntze) photosynthesis and the diurnal variation of the eco-physiological factors. 1 indexed citations
18.
Wan, Peng, Liwu Liu, & Ophir Frieder. (2003). Grooming of arbitrary traffic in SONET/WDM rings. 1b. 1012–1016. 13 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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