Minso Shin

639 total citations
8 papers, 433 citations indexed

About

Minso Shin is a scholar working on Atmospheric Science, Health, Toxicology and Mutagenesis and Environmental Engineering. According to data from OpenAlex, Minso Shin has authored 8 papers receiving a total of 433 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Atmospheric Science, 3 papers in Health, Toxicology and Mutagenesis and 3 papers in Environmental Engineering. Recurrent topics in Minso Shin's work include Atmospheric chemistry and aerosols (4 papers), Air Quality and Health Impacts (3 papers) and Air Quality Monitoring and Forecasting (3 papers). Minso Shin is often cited by papers focused on Atmospheric chemistry and aerosols (4 papers), Air Quality and Health Impacts (3 papers) and Air Quality Monitoring and Forecasting (3 papers). Minso Shin collaborates with scholars based in South Korea, United States and Germany. Minso Shin's co-authors include Jungho Im, Seohui Park, Yoojin Kang, Lindi J. Quackenbush, Chang‐Keun Song, Miae Kim, Sang‐Min Kim, Cheolhee Yoo, Sanggyun Lee and Hyun‐Cheol Kim and has published in prestigious journals such as Environmental Pollution, Atmospheric chemistry and physics and Remote Sensing.

In The Last Decade

Minso Shin

8 papers receiving 418 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Minso Shin South Korea	7	298	232	177	157	34	8	433
Timofey Samsonov Russia	12	137 0.5×	215 0.9×	117 0.7×	153 1.0×	32 0.9×	57	408
Xiangchen Meng China	11	227 0.8×	249 1.1×	36 0.2×	157 1.0×	39 1.1×	30	391
Jinjie Meng China	7	207 0.7×	288 1.2×	78 0.4×	140 0.9×	42 1.2×	9	394
Vasileios Salamalikis Greece	13	291 1.0×	126 0.5×	112 0.6×	313 2.0×	30 0.9×	34	562
Chen Du China	7	229 0.8×	322 1.4×	82 0.5×	156 1.0×	49 1.4×	12	427
Yoojin Kang South Korea	8	214 0.7×	233 1.0×	143 0.8×	285 1.8×	56 1.6×	18	486
Die Hu China	12	186 0.6×	513 2.2×	310 1.8×	362 2.3×	44 1.3×	23	615
Shanyou Zhu China	12	179 0.6×	258 1.1×	84 0.5×	180 1.1×	72 2.1×	48	398
Lu Jiang China	11	147 0.5×	348 1.5×	166 0.9×	167 1.1×	19 0.6×	27	404
Jay P. Hoffman United States	11	472 1.6×	56 0.2×	60 0.3×	504 3.2×	37 1.1×	13	603

Countries citing papers authored by Minso Shin

Since Specialization

Citations

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

Fields of papers citing papers by Minso Shin

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Minso Shin

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

All Works

Sort: Min cites: Since: Top N: Style:

8 of 8 papers shown

1.

Kang, Yoojin, Jungho Im, Seohui Park, et al.. (2021). Estimation of surface-level NO2 and O3 concentrations using TROPOMI data and machine learning over East Asia. Environmental Pollution. 288. 117711–117711. 118 indexed citations

2.

Kang, Yoojin, et al.. (2020). Monitoring Ground-level SO 2 Concentrations Based on a Stacking Ensemble Approach Using Satellite Data and Numerical Models. National Remote Sensing Bulletin. 36. 1053–1066. 3 indexed citations

3.

Lee, Junghee, Daehyeon Han, Minso Shin, et al.. (2020). Different Spectral Domain Transformation for Land Cover Classification Using Convolutional Neural Networks with Multi-Temporal Satellite Imagery. Remote Sensing. 12(7). 1097–1097. 15 indexed citations

4.

Park, Seohui, Minso Shin, Jungho Im, et al.. (2019). Estimation of ground-level particulate matter concentrations through the synergistic use of satellite observations and process-based models over South Korea. Atmospheric chemistry and physics. 19(2). 1097–1113. 78 indexed citations

5.

Shin, Minso, Yoojin Kang, Seohui Park, et al.. (2019). Estimating ground-level particulate matter concentrations using satellite-based data: a review. GIScience & Remote Sensing. 57(2). 174–189. 88 indexed citations

6.

Kim, Miae, Jung‐Hee Lee, Daehyeon Han, et al.. (2018). Convolutional Neural Network-Based Land Cover Classification Using 2-D Spectral Reflectance Curve Graphs With Multitemporal Satellite Imagery. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 11(12). 4604–4617. 26 indexed citations

7.

Lee, Sanggyun, Jungho Im, Jin‐Woo Kim, et al.. (2016). Arctic Sea Ice Thickness Estimation from CryoSat-2 Satellite Data Using Machine Learning-Based Lead Detection. Remote Sensing. 8(9). 698–698. 56 indexed citations

8.

Kim, Miae, Jungho Im, Hyangsun Han, et al.. (2015). Landfast sea ice monitoring using multisensor fusion in the Antarctic. GIScience & Remote Sensing. 52(2). 239–256. 49 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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