Youg-Sin Cheng

942 total citations · 1 hit paper
24 papers, 717 citations indexed

About

Youg-Sin Cheng is a scholar working on Ecology, Global and Planetary Change and Environmental Engineering. According to data from OpenAlex, Youg-Sin Cheng has authored 24 papers receiving a total of 717 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Ecology, 8 papers in Global and Planetary Change and 6 papers in Environmental Engineering. Recurrent topics in Youg-Sin Cheng's work include Remote Sensing in Agriculture (8 papers), Landslides and related hazards (5 papers) and Remote Sensing and LiDAR Applications (4 papers). Youg-Sin Cheng is often cited by papers focused on Remote Sensing in Agriculture (8 papers), Landslides and related hazards (5 papers) and Remote Sensing and LiDAR Applications (4 papers). Youg-Sin Cheng collaborates with scholars based in Taiwan, United States and Italy. Youg-Sin Cheng's co-authors include Hsin‐Fu Yeh, Cheng-Haw Lee, Hung-I Lin, Nguyễn Thanh Sơn, Chi-Farn Chen, Cheng-Ru Chen, H.C. Yeh, Richard H. Pierce, Yue Zhou and C. Mitch Irvin and has published in prestigious journals such as Human Reproduction, International Journal of Remote Sensing and Remote Sensing.

In The Last Decade

Youg-Sin Cheng

21 papers receiving 692 citations

Hit Papers

Mapping groundwater recha... 2016 2026 2019 2022 2016 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Youg-Sin Cheng Taiwan 10 360 262 190 105 101 24 717
Yuping Lei China 13 221 0.6× 240 0.9× 205 1.1× 170 1.6× 49 0.5× 35 653
Sylvain Ferrant France 14 175 0.5× 207 0.8× 310 1.6× 117 1.1× 129 1.3× 27 598
Danrong Zhang China 17 245 0.7× 395 1.5× 392 2.1× 111 1.1× 32 0.3× 42 746
Shumin Han China 18 214 0.6× 359 1.4× 452 2.4× 70 0.7× 25 0.2× 39 996
Uma Seeboonruang Thailand 13 231 0.6× 140 0.5× 197 1.0× 73 0.7× 35 0.3× 37 528
Abdellah El Hmaidi Morocco 14 359 1.0× 283 1.1× 281 1.5× 123 1.2× 24 0.2× 73 826
Hongxiang Fan China 14 209 0.6× 331 1.3× 280 1.5× 138 1.3× 42 0.4× 40 606
Mohammed Hssaisoune Morocco 15 287 0.8× 248 0.9× 248 1.3× 55 0.5× 13 0.1× 49 764
David R. Steward United States 15 261 0.7× 144 0.5× 278 1.5× 53 0.5× 16 0.2× 52 741

Countries citing papers authored by Youg-Sin Cheng

Since Specialization
Citations

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

Fields of papers citing papers by Youg-Sin Cheng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Youg-Sin Cheng. 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 Youg-Sin Cheng. The network helps show where Youg-Sin Cheng may publish in the future.

Co-authorship network of co-authors of Youg-Sin Cheng

This figure shows the co-authorship network connecting the top 25 collaborators of Youg-Sin Cheng. A scholar is included among the top collaborators of Youg-Sin Cheng 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 Youg-Sin Cheng. Youg-Sin Cheng 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.
Sơn, Nguyễn Thanh, Chi-Farn Chen, Youg-Sin Cheng, et al.. (2024). Machine learning-based early prediction of rice-growing fields using multi-temporal Sentinel-1 synthetic aperture radar and Sentinel-2 multispectral data. Journal of Applied Remote Sensing. 18(3).
2.
Cheng, Youg-Sin, et al.. (2024). Multi-Index Drought Analysis in Choushui River Alluvial Fan, Taiwan. Environments. 11(11). 233–233. 2 indexed citations
3.
Sơn, Nguyễn Thanh, Chi-Farn Chen, Youg-Sin Cheng, et al.. (2024). Combining satellite data and artificial intelligence with a crop growth model to enhance rice yield estimation and crop management practices. Applied Geomatics. 16(3). 639–654. 2 indexed citations
4.
5.
Sơn, Nguyễn Thanh, Chi-Farn Chen, Youg-Sin Cheng, et al.. (2022). Field-scale rice yield prediction from Sentinel-2 monthly image composites using machine learning algorithms. Ecological Informatics. 69. 101618–101618. 47 indexed citations
6.
Sơn, Nguyễn Thanh, Chi-Farn Chen, Youg-Sin Cheng, et al.. (2022). Exploiting Sentinel-1 data and machine learning–based random forest for collectively mapping rice fields in Taiwan. Applied Geomatics. 14(2). 405–419. 5 indexed citations
7.
Cheng, Youg-Sin, et al.. (2021). Random Forests for Landslide Prediction in Tsengwen River Watershed, Central Taiwan. Remote Sensing. 13(2). 199–199. 21 indexed citations
8.
Sơn, Nguyễn Thanh, et al.. (2021). A phenological object-based approach for rice crop classification using time-series Sentinel-1 Synthetic Aperture Radar (SAR) data in Taiwan. International Journal of Remote Sensing. 42(7). 2722–2739. 35 indexed citations
9.
Sơn, Nguyễn Thanh, et al.. (2020). Machine learning approaches for rice crop yield predictions using time-series satellite data in Taiwan. International Journal of Remote Sensing. 41(20). 7868–7888. 45 indexed citations
10.
Yu, Tsu‐Wei, Youg-Sin Cheng, Wenjie Peng, & Pei‐Lin Lee. (2018). ANALYSIS OF THE TEMPORAL AND SPATIAL CONTROLLING FACTORS IN AFFECTING THE ACCURACY OF LANDSLIDE PREDICTING MODEL AT TAIWAN. ˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences. XLII-3/W4. 579–582. 1 indexed citations
11.
Cheng, Youg-Sin, et al.. (2017). Pioneer Vegetation Detection by Hyperspectral Images on Temporal Landslides: A case study of Tzengwen catchment upstream, Taiwan. EGU General Assembly Conference Abstracts. 16706. 1 indexed citations
12.
Yeh, Hsin‐Fu, Youg-Sin Cheng, Hung-I Lin, & Cheng-Haw Lee. (2016). Mapping groundwater recharge potential zone using a GIS approach in Hualian River, Taiwan. Sustainable Environment Research. 26(1). 33–43. 337 indexed citations breakdown →
13.
Cheng, Youg-Sin, et al.. (2015). Potential Landslide Detection with Fractal and Roughness by LiDAR Data in Taiwan. EGUGA. 10345. 1 indexed citations
14.
Cheng, Youg-Sin, et al.. (2015). Analysis of Factors Triggering Shallow Failure and Deep-Seated Landslides Induced by Single Rainfall Events. Journal of Disaster Research. 10(5). 966–972. 5 indexed citations
15.
Cheng, Youg-Sin, et al.. (2015). Detecting changes in long-period site responses after the M w 7.6 Chi-Chi earthquake, Taiwan, using strong motion records. Earthquake Engineering and Engineering Vibration. 14(2). 217–228. 2 indexed citations
16.
Cheng, Youg-Sin. (2006). Association of spermatogenic failure with decreased CDC25A expression in infertile men. Human Reproduction. 21(9). 2346–2352. 24 indexed citations
17.
Zhou, Yue & Youg-Sin Cheng. (2004). DOSIMETRY OF METAL TRITIDE PARTICLES AS EVALUATED BY THE ICRP 66 MODEL AND A BIOKINETIC MODEL FROM LABORATORY RATS. Health Physics. 86(2). 155–160. 11 indexed citations
18.
Zhou, Yue & Youg-Sin Cheng. (2003). DOSE ASSESSMENT FOR INHALING HAFNIUM PARTICLES BASED ON LABORATORY RATS STUDY. Health Physics. 84(4). 469–476. 7 indexed citations
19.
Inkret, W.C., M. E. Schillaci, Youg-Sin Cheng, et al.. (2001). Internal Dosimetry for Inhalation of Hafnium Tritide Aerosols. Radiation Protection Dosimetry. 93(1). 55–60. 3 indexed citations
20.
Cheng, Youg-Sin, et al.. (1984). Experimental responses of two optical particle counters. Journal of Aerosol Science. 15(4). 457–464. 34 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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