Tongfei Liu

1.3k total citations · 1 hit paper
42 papers, 1.0k citations indexed

About

Tongfei Liu is a scholar working on Media Technology, Atmospheric Science and Ecology. According to data from OpenAlex, Tongfei Liu has authored 42 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Media Technology, 24 papers in Atmospheric Science and 14 papers in Ecology. Recurrent topics in Tongfei Liu's work include Remote-Sensing Image Classification (30 papers), Remote Sensing and Land Use (24 papers) and Remote Sensing in Agriculture (14 papers). Tongfei Liu is often cited by papers focused on Remote-Sensing Image Classification (30 papers), Remote Sensing and Land Use (24 papers) and Remote Sensing in Agriculture (14 papers). Tongfei Liu collaborates with scholars based in China, Iceland and United Kingdom. Tongfei Liu's co-authors include Jón Atli Benediktsson, Zhiyong Lv, Maoguo Gong, Fenlong Jiang, Mingyang Zhang, Hanhong Zheng, Di Lu, Nicola Falco, Cheng Shi and Tao Zhan and has published in prestigious journals such as IEEE Transactions on Geoscience and Remote Sensing, IEEE Transactions on Image Processing and IEEE Access.

In The Last Decade

Tongfei Liu

36 papers receiving 1.0k citations

Hit Papers

Land Cover Change Detection Techniques: Very-high-resolut... 2021 2026 2022 2024 2021 50 100 150

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tongfei Liu China 17 786 547 329 170 145 42 1.0k
Sudipan Saha Germany 17 877 1.1× 574 1.0× 388 1.2× 252 1.5× 245 1.7× 60 1.3k
Rodrigo Caye Daudt Switzerland 11 557 0.7× 373 0.7× 254 0.8× 197 1.2× 122 0.8× 20 871
Daifeng Peng China 13 1.1k 1.4× 788 1.4× 518 1.6× 259 1.5× 218 1.5× 24 1.5k
Hongruixuan Chen Japan 13 733 0.9× 454 0.8× 268 0.8× 166 1.0× 151 1.0× 25 949
Shanxiong Chen China 13 460 0.6× 281 0.5× 197 0.6× 120 0.7× 110 0.8× 28 882
Seyd Teymoor Seydi Iran 17 451 0.6× 333 0.6× 383 1.2× 128 0.8× 102 0.7× 52 1.1k
Boyi Shangguan China 8 766 1.0× 524 1.0× 367 1.1× 129 0.8× 138 1.0× 21 1.0k
Zhao Zhan China 6 389 0.5× 280 0.5× 183 0.6× 95 0.6× 101 0.7× 10 638
K. Arnason Iceland 8 805 1.0× 509 0.9× 227 0.7× 247 1.5× 132 0.9× 17 1.0k
Da He China 16 493 0.6× 258 0.5× 240 0.7× 232 1.4× 71 0.5× 38 808

Countries citing papers authored by Tongfei Liu

Since Specialization
Citations

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

Fields of papers citing papers by Tongfei Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tongfei Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Tongfei Liu. A scholar is included among the top collaborators of Tongfei Liu 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 Tongfei Liu. Tongfei Liu 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.
Gong, Maoguo, et al.. (2025). Collaborative Frequency-Aware Transformer for Unsupervised Multimodal Change Detection in Heterogeneous Remote Sensing Images. IEEE Transactions on Geoscience and Remote Sensing. 63. 1–15.
2.
Lei, Tao, et al.. (2025). SLAFormer: Skeleton-Guided Large-Kernel Attention Transformer for Road Change Detection. IEEE Transactions on Geoscience and Remote Sensing. 63. 1–15.
3.
Liu, Tongfei, Mingyang Zhang, Maoguo Gong, et al.. (2025). Commonality Feature Representation Learning for Unsupervised Multimodal Change Detection. IEEE Transactions on Image Processing. 34. 1219–1233. 11 indexed citations
4.
Liu, Tongfei, et al.. (2025). Hierarchical Feature Alignment-based Progressive Addition Network for Multimodal Change Detection. Pattern Recognition. 162. 111355–111355. 6 indexed citations
5.
Zheng, Hanhong, Mingyang Zhang, Maoguo Gong, et al.. (2024). Multi-scale hierarchical feature fusion network for change detection. Pattern Recognition. 161. 111266–111266. 7 indexed citations
6.
Gong, Maoguo, et al.. (2024). Adversarial Feature Equilibrium Network for Multimodal Change Detection in Heterogeneous Remote Sensing Images. IEEE Transactions on Geoscience and Remote Sensing. 62. 1–17. 8 indexed citations
7.
Liu, Tongfei, Tao Lei, Yingbo Wang, et al.. (2024). AEKAN: Exploring Superpixel-Based AutoEncoder Kolmogorov-Arnold Network for Unsupervised Multimodal Change Detection. IEEE Transactions on Geoscience and Remote Sensing. 63. 1–14. 10 indexed citations
8.
Zheng, Hanhong, Dongyang Li, Mingyang Zhang, et al.. (2023). Spectral Knowledge Transfer for Remote Sensing Change Detection. IEEE Transactions on Geoscience and Remote Sensing. 62. 1–16. 3 indexed citations
9.
10.
Jiang, Fenlong, Maoguo Gong, Hanhong Zheng, et al.. (2023). Self-Supervised Global–Local Contrastive Learning for Fine-Grained Change Detection in VHR Images. IEEE Transactions on Geoscience and Remote Sensing. 61. 1–13. 28 indexed citations
11.
12.
Liu, Tongfei, et al.. (2022). Self-Attention and Convolution Fusion Network for Land Cover Change Detection over a New Data Set in Wenzhou, China. Remote Sensing. 14(23). 5969–5969. 4 indexed citations
13.
Zheng, Hanhong, Maoguo Gong, Tongfei Liu, et al.. (2022). HFA-Net: High frequency attention siamese network for building change detection in VHR remote sensing images. Pattern Recognition. 129. 108717–108717. 114 indexed citations
14.
Gong, Maoguo, Fenlong Jiang, A. K. Qin, et al.. (2021). A Spectral and Spatial Attention Network for Change Detection in Hyperspectral Images. IEEE Transactions on Geoscience and Remote Sensing. 60. 1–14. 63 indexed citations
15.
Liu, Tongfei, Maoguo Gong, Di Lu, et al.. (2021). Building Change Detection for VHR Remote Sensing Images via Local–Global Pyramid Network and Cross-Task Transfer Learning Strategy. IEEE Transactions on Geoscience and Remote Sensing. 60. 1–17. 102 indexed citations
16.
Liu, Tongfei, et al.. (2021). Landslide Inventory Mapping Method Based on Adaptive Histogram-Mean Distance With Bitemporal VHR Aerial Images. IEEE Geoscience and Remote Sensing Letters. 19. 1–5. 17 indexed citations
17.
Lv, Zhiyong, Tongfei Liu, Robert Wang, Jón Atli Benediktsson, & Sudipan Saha. (2020). Automatic Landslide Inventory Mapping Approach Based on Change Detection Technique With Very-High-Resolution Images. IEEE Geoscience and Remote Sensing Letters. 19. 1–5. 12 indexed citations
18.
Liu, Tongfei, et al.. (2019). Novel Adaptive Histogram Trend Similarity Approach for Land Cover Change Detection by Using Bitemporal Very-High-Resolution Remote Sensing Images. IEEE Transactions on Geoscience and Remote Sensing. 57(12). 9554–9574. 75 indexed citations
20.
Lv, Zhiyong, Tongfei Liu, Penglin Zhang, Jón Atli Benediktsson, & Yixiang Chen. (2018). Land Cover Change Detection Based on Adaptive Contextual Information Using Bi-Temporal Remote Sensing Images. Remote Sensing. 10(6). 901–901. 19 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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