Anjin Chang

2.3k total citations · 1 hit paper
67 papers, 1.7k citations indexed

About

Anjin Chang is a scholar working on Ecology, Environmental Engineering and Plant Science. According to data from OpenAlex, Anjin Chang has authored 67 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Ecology, 42 papers in Environmental Engineering and 28 papers in Plant Science. Recurrent topics in Anjin Chang's work include Remote Sensing in Agriculture (44 papers), Remote Sensing and LiDAR Applications (42 papers) and Smart Agriculture and AI (19 papers). Anjin Chang is often cited by papers focused on Remote Sensing in Agriculture (44 papers), Remote Sensing and LiDAR Applications (42 papers) and Smart Agriculture and AI (19 papers). Anjin Chang collaborates with scholars based in United States, South Korea and China. Anjin Chang's co-authors include Jinha Jung, Murilo Maeda, Juan Landivar, Akash Ashapure, Junho Yeom, Mahendra Bhandari, Sungchan Oh, Yongil Kim, Sorin Popescu and Lonesome Malambo and has published in prestigious journals such as SHILAP Revista de lepidopterología, Sensors and Current Opinion in Biotechnology.

In The Last Decade

Anjin Chang

64 papers receiving 1.7k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

The potential of remote sensing and artificial intelligence as tools to improve the resilience of agriculture production systems

2020 279 citations Jinha Jung, Murilo Maeda et al. Current Opinion in Biotechnology profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Anjin Chang United States	23	974	967	657	203	133	67	1.7k
Jinha Jung United States	26	1.0k 1.0×	1.1k 1.2×	735 1.1×	256 1.3×	137 1.0×	103	2.1k
Alexis Comar France	18	1.1k 1.2×	1.2k 1.3×	668 1.0×	289 1.4×	216 1.6×	25	1.7k
Murilo Maeda United States	17	826 0.8×	794 0.8×	522 0.8×	167 0.8×	113 0.8×	31	1.3k
Frank Liebisch Switzerland	27	1.6k 1.6×	1.2k 1.2×	573 0.9×	300 1.5×	246 1.8×	62	2.7k
Shichao Jin China	27	806 0.8×	915 0.9×	1.0k 1.6×	311 1.5×	114 0.9×	69	2.0k
Sean Hartling United States	10	876 0.9×	1.2k 1.3×	787 1.2×	317 1.6×	211 1.6×	11	1.8k
Juan Landivar United States	22	993 1.0×	765 0.8×	498 0.8×	190 0.9×	106 0.8×	59	1.4k
Yeyin Shi United States	23	1.1k 1.2×	823 0.9×	436 0.7×	188 0.9×	235 1.8×	80	1.8k
Shouyang Liu China	21	1.1k 1.1×	987 1.0×	537 0.8×	324 1.6×	239 1.8×	45	1.7k
Jiangang Liu China	15	758 0.8×	771 0.8×	463 0.7×	167 0.8×	139 1.0×	56	1.4k

Countries citing papers authored by Anjin Chang

Since Specialization

Citations

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

Fields of papers citing papers by Anjin Chang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anjin Chang

This figure shows the co-authorship network connecting the top 25 collaborators of Anjin Chang. A scholar is included among the top collaborators of Anjin Chang 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 Anjin Chang. Anjin Chang 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:

20 of 20 papers shown

Duffield, Nick, Kevin Nowka, Jinha Jung, et al.. (2024). Unmanned aerial system and machine learning driven Digital-Twin framework for in-season cotton growth forecasting. Computers and Electronics in Agriculture. 228. 109589–109589. 3 indexed citations

Thomasson, J. Alex, et al.. (2023). Uncrewed aerial vehicle radiometric calibration: A comparison of autoexposure and fixed‐exposure images. SHILAP Revista de lepidopterología. 6(1). 5 indexed citations

Bhandari, Mahendra, Anjin Chang, Jinha Jung, et al.. (2023). Unmanned aerial system‐based high‐throughput phenotyping for plant breeding. SHILAP Revista de lepidopterología. 6(1). 21 indexed citations

Hague, Steve, Jinha Jung, Akash Ashapure, et al.. (2021). Cotton row spacing and unmanned aerial vehicle sensors. Agronomy Journal. 114(1). 331–339.

Bhandari, Mahendra, Shannon Baker, Jackie C. Rudd, et al.. (2021). Assessing the Effect of Drought on Winter Wheat Growth Using Unmanned Aerial System (UAS)-Based Phenotyping. Remote Sensing. 13(6). 1144–1144. 30 indexed citations

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

Jung, Jinha, et al.. (2020). The potential of remote sensing and artificial intelligence as tools to improve the resilience of agriculture production systems. Current Opinion in Biotechnology. 70. 15–22. 279 indexed citations breakdown →

Anderson, Steven L., Seth C. Murray, Yuanyuan Chen, et al.. (2020). Unoccupied aerial system enabled functional modeling of maize height reveals dynamic expression of loci. Plant Direct. 4(5). e00223–e00223. 32 indexed citations

Ashapure, Akash, Jinha Jung, Sungchan Oh, et al.. (2020). Combining UAS and Sentinel-2 Data to Estimate Canopy Parameters of a Cotton Crop Using Machine Learning. 4. 5199–5202. 2 indexed citations

10.

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

11.

Anderson, Steven L., Seth C. Murray, Lonesome Malambo, et al.. (2019). Prediction of Maize Grain Yield before Maturity Using Improved Temporal Height Estimates of Unmanned Aerial Systems. 2(1). 1–15. 56 indexed citations

12.

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

13.

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

14.

Chang, Anjin, Jinha Jung, Murilo Maeda, & Juan Landivar. (2017). Crop height monitoring with digital imagery from Unmanned Aerial System (UAS). Computers and Electronics in Agriculture. 141. 232–237. 147 indexed citations

15.

Eo, Yang Dam, et al.. (2013). Generation of a DTM and building detection based on an MPF through integrating airborne lidar data and aerial images. International Journal of Remote Sensing. 34(8). 2947–2968. 9 indexed citations

16.

Chang, Anjin, et al.. (2012). Estimation of Canopy Cover in Forest Using KOMPSAT-2 Satellite Images. Journal of Korean Society for Geospatial Information Science. 20(1). 83–91. 2 indexed citations

17.

Chang, Anjin & Yong‐Il Kim. (2010). Noise Band Extraction of Hyperion Image using Quadtree Structure and Fractal Characteristic. National Remote Sensing Bulletin. 26(5). 489–495. 1 indexed citations

18.

Chang, Anjin & Yong‐Il Kim. (2008). Noise Band Elemination of Hyperion Image using Fractal Dimension and Continuum Removal Method. National Remote Sensing Bulletin. 24(2). 125–131. 1 indexed citations

19.

Chang, Anjin, et al.. (2008). Comparison of methods to estimate individual tree attributes using color aerial photographs and LiDAR data. 4(1). 21–27. 4 indexed citations

20.

Chang, Anjin & Hyung‐Tae Kim. (2008). Study of Biomass Estimation in Forest by Aerial Photograph and LiDAR Data. Journal of the Korean Association of Geographic Information Studies. 11(3). 166–173. 2 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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