Junho Yeom

973 total citations
48 papers, 766 citations indexed

About

Junho Yeom is a scholar working on Environmental Engineering, Ecology and Ocean Engineering. According to data from OpenAlex, Junho Yeom has authored 48 papers receiving a total of 766 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Environmental Engineering, 17 papers in Ecology and 11 papers in Ocean Engineering. Recurrent topics in Junho Yeom's work include Remote Sensing and LiDAR Applications (21 papers), Remote Sensing in Agriculture (17 papers) and Remote-Sensing Image Classification (9 papers). Junho Yeom is often cited by papers focused on Remote Sensing and LiDAR Applications (21 papers), Remote Sensing in Agriculture (17 papers) and Remote-Sensing Image Classification (9 papers). Junho Yeom collaborates with scholars based in South Korea, United States and China. Junho Yeom's co-authors include Anjin Chang, Jinha Jung, Juan Landivar, Murilo Maeda, Akash Ashapure, Kihak Im, C. Kessel, Hyoung Chan Kim, Yongil Kim and T. Brown and has published in prestigious journals such as International Journal of Remote Sensing, Remote Sensing and ISPRS Journal of Photogrammetry and Remote Sensing.

In The Last Decade

Junho Yeom

41 papers receiving 747 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Junho Yeom South Korea 14 339 326 213 154 124 48 766
I. Burud Norway 19 196 0.6× 123 0.4× 270 1.3× 65 0.4× 48 0.4× 82 1.3k
P. C. Robert France 17 282 0.8× 429 1.3× 443 2.1× 76 0.5× 13 0.1× 189 1.2k
Daniel Pflugfelder Germany 14 52 0.2× 563 1.7× 105 0.5× 25 0.2× 16 0.1× 28 1.1k
Xiaoxia Wang China 13 209 0.6× 27 0.1× 127 0.6× 18 0.1× 13 0.1× 45 622
Jian Jin United States 14 260 0.8× 452 1.4× 79 0.4× 21 0.1× 9 0.1× 31 829
Hui-Ping Tsai Taiwan 11 262 0.8× 218 0.7× 172 0.8× 41 0.3× 15 0.1× 29 593
Zhongqiu Sun China 14 367 1.1× 186 0.6× 189 0.9× 38 0.2× 15 0.1× 61 646
Xianfeng Zhou China 16 543 1.6× 460 1.4× 141 0.7× 34 0.2× 23 0.2× 42 848
Jussi Mäkynen Finland 15 491 1.4× 147 0.5× 481 2.3× 238 1.5× 12 0.1× 37 1.1k

Countries citing papers authored by Junho Yeom

Since Specialization
Citations

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

Fields of papers citing papers by Junho Yeom

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Junho Yeom

This figure shows the co-authorship network connecting the top 25 collaborators of Junho Yeom. A scholar is included among the top collaborators of Junho Yeom 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 Junho Yeom. Junho Yeom 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.
Kim, Junseok, T.H. Lee, & Junho Yeom. (2023). Personal Mobility Detection through Application of YOLO Deep Learning Algorithm to Drone Images. Journal of the Korean Society of Surveying Geodesy Photogrammetry and Cartography. 41(4). 239–246.
2.
Chang, Anjin, Jinha Jung, Junho Yeom, & Juan Landivar. (2021). 3D Characterization of Sorghum Panicles Using a 3D Point Cloud Derived from UAV Imagery. Remote Sensing. 13(2). 282–282. 14 indexed citations
3.
Ashapure, Akash, Jinha Jung, Anjin Chang, et al.. (2020). Developing a machine learning based cotton yield estimation framework using multi-temporal UAS data. ISPRS Journal of Photogrammetry and Remote Sensing. 169. 180–194. 96 indexed citations
4.
Kim, Taeheon, Won Hee Lee, Junho Yeom, & Youkyung Han. (2019). Integrated Automatic Pre-Processing for Change Detection Based on SURF Algorithm and Mask Filter. Journal of the Korean Society of Surveying Geodesy Photogrammetry and Cartography. 37(3). 209–219. 1 indexed citations
5.
Han, Youkyung, Jaewan Choi, Jinha Jung, et al.. (2019). Automated Coregistration of Multisensor Orthophotos Generated from Unmanned Aerial Vehicle Platforms. Journal of Sensors. 2019. 1–10. 11 indexed citations
6.
Yeom, Junho, Won Hee Lee, Taeheon Kim, & Youkyung Han. (2019). Normalized Digital Surface Model Extraction and Slope Parameter Determination through Region Growing of UAV Data. Journal of the Korean Society of Surveying Geodesy Photogrammetry and Cartography. 37(6). 499–506. 1 indexed citations
7.
Kim, Taeheon, et al.. (2019). Coarse to Fine Image Registration of Unmanned Aerial Vehicle Images over Agricultural Area using SURF and Mutual Information Methods. National Remote Sensing Bulletin. 35(6). 945–957. 2 indexed citations
8.
Ashapure, Akash, Jinha Jung, Junho Yeom, et al.. (2019). A novel framework to detect conventional tillage and no-tillage cropping system effect on cotton growth and development using multi-temporal UAS data. ISPRS Journal of Photogrammetry and Remote Sensing. 152. 49–64. 38 indexed citations
9.
Enciso, Juan, Carlos A. Avila, Jinha Jung, et al.. (2019). Validation of agronomic UAV and field measurements for tomato varieties. Computers and Electronics in Agriculture. 158. 278–283. 45 indexed citations
10.
11.
Han, Youkyung, Taeheon Kim, & Junho Yeom. (2019). Improved Piecewise Linear Transformation for Precise Warping of Very-High-Resolution Remote Sensing Images. Remote Sensing. 11(19). 2235–2235. 11 indexed citations
12.
Yeom, Junho, Jinha Jung, Anjin Chang, Murilo Maeda, & Juan Landivar. (2018). Automated Open Cotton Boll Detection for Yield Estimation Using Unmanned Aircraft Vehicle (UAV) Data. Remote Sensing. 10(12). 1895–1895. 62 indexed citations
13.
Yeom, Junho, et al.. (2017). Hurricane Harvey Building Damage Assessment Using UAV Data. AGU Fall Meeting Abstracts. 2017. 1 indexed citations
14.
Yeom, Junho & Yong Il Kim. (2014). Automatic Extraction of the Land Readjustment Paddy for High-level Land Cover Classification. Journal of the Korean Society of Surveying Geodesy Photogrammetry and Cartography. 32(5). 443–450. 1 indexed citations
15.
Yeom, Junho, et al.. (2014). Building Matching Analysis and New Building Update for the Integrated Use of the Digital Map and the Road Name Address Map. Journal of the Korean Society of Surveying Geodesy Photogrammetry and Cartography. 32(5). 459–467.
16.
Kim, Keeman, Hyoung Chan Kim, Sangjun Oh, et al.. (2013). A preliminary conceptual design study for Korean fusion DEMO reactor. Fusion Engineering and Design. 88(6-8). 488–491. 48 indexed citations
17.
Yeom, Junho, et al.. (2012). Building damage assessment using high resolution satellite imagery for Port-au-Prince, Haiti. Disaster Advances. 5(4). 177–181. 1 indexed citations
18.
Heo, Gyunyoung, et al.. (2012). An exploratory study on the gaps and pathways to the Korean fusion DEMO. Fusion Engineering and Design. 87(5-6). 757–763. 3 indexed citations
19.
Kim, Yongmin, Youkyung Han, Junho Yeom, Dongyeob Han, & Yongil Kim. (2012). Object-based classification and building extraction by integrating airborne LiDAR data and aerial image. 6200–6202.
20.
Yeom, Junho, Jeong‐Ho Lee, Duk‐jin Kim, & Yongil Kim. (2011). Hierarchical Land Cover Classification using IKONOS and AIRSAR Images. Korean Journal of Remote Sensing. 27(4). 435–444. 4 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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