Jiaming Na

1.1k total citations
60 papers, 817 citations indexed

About

Jiaming Na is a scholar working on Environmental Engineering, Soil Science and Ecology. According to data from OpenAlex, Jiaming Na has authored 60 papers receiving a total of 817 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Environmental Engineering, 19 papers in Soil Science and 18 papers in Ecology. Recurrent topics in Jiaming Na's work include Soil erosion and sediment transport (19 papers), Remote Sensing and LiDAR Applications (18 papers) and Hydrology and Watershed Management Studies (11 papers). Jiaming Na is often cited by papers focused on Soil erosion and sediment transport (19 papers), Remote Sensing and LiDAR Applications (18 papers) and Hydrology and Watershed Management Studies (11 papers). Jiaming Na collaborates with scholars based in China, Austria and United Kingdom. Jiaming Na's co-authors include Guoan Tang, Xin Yang, Hu Ding, Liyang Xiong, Kai Liu, Xiaoli Huang, Jie Zhu, Wen Dai, Fei Tao and Junjie Wu and has published in prestigious journals such as SHILAP Revista de lepidopterología, Remote Sensing of Environment and IEEE Transactions on Geoscience and Remote Sensing.

In The Last Decade

Jiaming Na

53 papers receiving 799 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jiaming Na China 17 319 311 206 182 157 60 817
Sebastian d’Oleire-Oltmanns Germany 8 677 2.1× 337 1.1× 295 1.4× 168 0.9× 132 0.8× 14 1.2k
Jianli Ding China 18 434 1.4× 124 0.4× 276 1.3× 263 1.4× 74 0.5× 60 1.0k
Zhao Yanling China 14 229 0.7× 96 0.3× 272 1.3× 422 2.3× 150 1.0× 30 1.0k
Shujing Qin China 23 296 0.9× 329 1.1× 207 1.0× 725 4.0× 109 0.7× 49 1.3k
Kinh Bac Dang Vietnam 16 183 0.6× 54 0.2× 256 1.2× 396 2.2× 164 1.0× 42 925
José Alberto Gonçalves Portugal 18 566 1.8× 88 0.3× 278 1.3× 210 1.2× 104 0.7× 76 1.5k
Chuluong Choi South Korea 11 253 0.8× 168 0.5× 163 0.8× 619 3.4× 445 2.8× 61 1.2k
Eyal Ben Dor Israel 18 656 2.1× 120 0.4× 375 1.8× 193 1.1× 46 0.3× 55 1.3k
Marco Gianinetto Italy 17 194 0.6× 85 0.3× 216 1.0× 173 1.0× 36 0.2× 76 906

Countries citing papers authored by Jiaming Na

Since Specialization
Citations

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

Fields of papers citing papers by Jiaming Na

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jiaming Na

This figure shows the co-authorship network connecting the top 25 collaborators of Jiaming Na. A scholar is included among the top collaborators of Jiaming Na 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 Jiaming Na. Jiaming Na 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.
Chen, Dong, et al.. (2025). Segmentation of Individual Trees in TLS Point Clouds via Graph Optimization. IEEE Transactions on Geoscience and Remote Sensing. 63. 1–21.
2.
Chen, Yu, et al.. (2025). Improved Low-Light Image Feature Matching Algorithm Based on the SuperGlue Net Model. Remote Sensing. 17(5). 905–905. 1 indexed citations
3.
Chen, Dong, et al.. (2025). Public Building Geometric Models From Point Clouds: A multidimensional quality evaluation framework. IEEE Geoscience and Remote Sensing Magazine. 14(1). 335–361.
4.
Fu, Yingchun, et al.. (2024). SCARF: A new algorithm for continuous prediction of biomass dynamics using machine learning and Landsat time series. Remote Sensing of Environment. 314. 114348–114348. 15 indexed citations
5.
Chen, Yu, et al.. (2023). GNSS Reconstrainted Visual–Inertial Odometry System Using Factor Graphs. IEEE Geoscience and Remote Sensing Letters. 20. 1–5. 5 indexed citations
6.
Ding, Hu, Yi Liu, Xinyi Liang, et al.. (2023). Performance assessment of global open‐access digital elevation models in China mainland coastal region. Earth Surface Processes and Landforms. 48(11). 2133–2140. 5 indexed citations
7.
Yang, Ling, Xin Yang, & Jiaming Na. (2022). An Exploration of Loess Landform Development Based on Population Ecology Method. ISPRS International Journal of Geo-Information. 11(2). 104–104. 3 indexed citations
8.
Fan, Juncheng, Jie Min, Qiang Yang, Jiaming Na, & Xinyuan Wang. (2022). Spatial-Temporal Relationship Analysis of Vegetation Phenology and Meteorological Parameters in an Agro-Pasture Ecotone in China. Remote Sensing. 14(21). 5417–5417. 12 indexed citations
9.
Yang, Qiang, et al.. (2022). Fire Scenario Zone Construction and Personnel Evacuation Planning Based on a Building Information Model and Geographical Information System. ISPRS International Journal of Geo-Information. 11(2). 110–110. 7 indexed citations
10.
Tao, Fei, et al.. (2022). RAANet: A Residual ASPP with Attention Framework for Semantic Segmentation of High-Resolution Remote Sensing Images. Remote Sensing. 14(13). 3109–3109. 96 indexed citations
11.
12.
Na, Jiaming, et al.. (2020). TERRAIN MODELLING BASED ON ARCHAEOLOGICAL REMAINS IN THE LOESS PLATEAU OF CHINA. SHILAP Revista de lepidopterología. XLIII-B2-2020. 1485–1490. 1 indexed citations
13.
Na, Jiaming, Liyang Xiong, Guoan Tang, et al.. (2020). UAV-Based Terrain Modeling under Vegetation in the Chinese Loess Plateau: A Deep Learning and Terrain Correction Ensemble Framework. Remote Sensing. 12(20). 3318–3318. 7 indexed citations
14.
Dai, Wen, Jiaming Na, Guanghui Hu, et al.. (2019). Integrated edge detection and terrain analysis for agricultural terrace delineation from remote sensing images. International Journal of Geographical Information Systems. 34(3). 484–503. 36 indexed citations
15.
Dai, Wen, Xin Yang, Jiaming Na, et al.. (2019). Effects of DEM resolution on the accuracy of gully maps in loess hilly areas. CATENA. 177. 114–125. 60 indexed citations
16.
Ding, Hu, Jiaming Na, Xiaoli Huang, Guoan Tang, & Kai Liu. (2018). Stability analysis unit and spatial distribution pattern of the terrain texture in the northern Shaanxi Loess Plateau. Journal of Mountain Science. 15(3). 577–589. 12 indexed citations
17.
Fang, Xuan, Hu Ding, Josef Strobl, et al.. (2017). Extraction of Terraces on the Loess Plateau from High-Resolution DEMs and Imagery Utilizing Object-Based Image Analysis. ISPRS International Journal of Geo-Information. 6(6). 157–157. 42 indexed citations
18.
Na, Jiaming, et al.. (2017). Topographic Spatial Variation Analysis of Loess Shoulder Lines in the Loess Plateau of China Based on MF-DFA. ISPRS International Journal of Geo-Information. 6(5). 141–141. 14 indexed citations
19.
Tang, Guoan, et al.. (2017). Progress of Digital Terrain Analysis on Regional Geomorphology in China. SHILAP Revista de lepidopterología. 16 indexed citations
20.
Na, Jiaming, Xin Yang, Wen Dai, et al.. (2017). Bidirectional DEM relief shading method for extraction of gully shoulder line in loess tableland area. Physical Geography. 39(4). 368–386. 28 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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