Akash Ashapure

972 total citations · 1 hit paper
19 papers, 689 citations indexed

About

Akash Ashapure is a scholar working on Ecology, Environmental Engineering and Plant Science. According to data from OpenAlex, Akash Ashapure has authored 19 papers receiving a total of 689 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Ecology, 8 papers in Environmental Engineering and 8 papers in Plant Science. Recurrent topics in Akash Ashapure's work include Remote Sensing in Agriculture (13 papers), Remote Sensing and LiDAR Applications (8 papers) and Smart Agriculture and AI (7 papers). Akash Ashapure is often cited by papers focused on Remote Sensing in Agriculture (13 papers), Remote Sensing and LiDAR Applications (8 papers) and Smart Agriculture and AI (7 papers). Akash Ashapure collaborates with scholars based in United States, South Korea and Brazil. Akash Ashapure's co-authors include Jinha Jung, Anjin Chang, Murilo Maeda, Juan Landivar, Mahendra Bhandari, Sungchan Oh, Junho Yeom, Nothabo Dube, Steve Hague and C. Wayne Smith and has published in prestigious journals such as Current Opinion in Biotechnology, Remote Sensing and ISPRS Journal of Photogrammetry and Remote Sensing.

In The Last Decade

Akash Ashapure

16 papers receiving 663 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
Akash Ashapure United States	8	417	360	206	79	63	19	689
Ma. Luisa Buchaillot Spain	8	316 0.8×	331 0.9×	144 0.7×	102 1.3×	84 1.3×	22	588
Xiaolei Qiu China	16	507 1.2×	360 1.0×	197 1.0×	129 1.6×	82 1.3×	30	871
Mahendra Bhandari United States	10	334 0.8×	235 0.7×	147 0.7×	92 1.2×	55 0.9×	27	704
Danielle Elis Garcia Furuya Brazil	10	300 0.7×	335 0.9×	190 0.9×	78 1.0×	107 1.7×	22	561
Xun Yu China	12	290 0.7×	314 0.9×	202 1.0×	105 1.3×	78 1.2×	34	583
Tao Duan China	9	445 1.1×	465 1.3×	286 1.4×	86 1.1×	42 0.7×	36	751
Irene Borra‐Serrano Belgium	12	388 0.9×	414 1.1×	368 1.8×	89 1.1×	83 1.3×	25	742
Karl‐Heinz Dammer Germany	17	562 1.3×	418 1.2×	244 1.2×	83 1.1×	111 1.8×	47	836
Marco Sozzi Italy	14	520 1.2×	353 1.0×	159 0.8×	119 1.5×	85 1.3×	50	836

Countries citing papers authored by Akash Ashapure

Since Specialization

Citations

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

Fields of papers citing papers by Akash Ashapure

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Akash Ashapure

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

All Works

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19 of 19 papers shown

Maciel, Daniel Andrade, Cláudio Clemente Faria Barbosa, Evlyn Márcia Leão de Moraes Novo, et al.. (2025). Accuracy assessment of PlanetScope SuperDove products for aquatic reflectance retrieval over Brazilian inland and coastal waters. ISPRS Journal of Photogrammetry and Remote Sensing. 227. 678–690.

Barnes, Brian B., et al.. (2025). Feasibility of PlanetScope SuperDove constellation for water quality monitoring of inland and coastal waters. Frontiers in Remote Sensing. 6.

Pahlevan, Nima, Sundarabalan V. Balasubramanian, Akash Ashapure, et al.. (2024). A Retrospective Analysis of Remote-Sensing Reflectance Products in Coastal and Inland Waters. IEEE Geoscience and Remote Sensing Letters. 21. 1–5. 7 indexed citations

Oh, Sungchan, Da-Young Lee, Akash Ashapure, et al.. (2021). Tar Spot Disease Quantification Using Unmanned Aircraft Systems (UAS) Data. Remote Sensing. 13(13). 2567–2567. 11 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.

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 →

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

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

Oh, Sungchan, Anjin Chang, Akash Ashapure, et al.. (2020). Plant Counting of Cotton from UAS Imagery Using Deep Learning-Based Object Detection Framework. Remote Sensing. 12(18). 2981–2981. 61 indexed citations

10.

Oh, Sungchan, Da-Young Lee, Akash Ashapure, et al.. (2020). Estimation of Visual Rating of TAR Spot Disease of Corn Using Unmanned Aerial Systems (UAS) Data and Machine Learning Techniques. 4882–4885. 1 indexed citations

11.

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

12.

Ashapure, Akash, Jinha Jung, Anjin Chang, et al.. (2019). A Comparative Study of RGB and Multispectral Sensor-Based Cotton Canopy Cover Modelling Using Multi-Temporal UAS Data. Remote Sensing. 11(23). 2757–2757. 70 indexed citations

13.

Oh, Sungchan, Akash Ashapure, Thiago G. Marconi, Jinha Jung, & Juan Landivar. (2019). UAS based Tomato Yellow Leaf Curl Virus (TYLCV) disease detection system. 7 indexed citations

14.

Ashapure, Akash, Sungchan Oh, Thiago G. Marconi, et al.. (2019). Unmanned aerial system based tomato yield estimation using machine learning. 22–22. 27 indexed citations

15.

Marconi, Thiago G., Sungchan Oh, Akash Ashapure, et al.. (2019). Application of unmanned aerial system for management of tomato cropping system. 36–36. 4 indexed citations

16.

Yeom, Junho, Jinha Jung, Anjin Chang, et al.. (2019). Comparison of Vegetation Indices Derived from UAV Data for Differentiation of Tillage Effects in Agriculture. Remote Sensing. 11(13). 1548–1548. 78 indexed citations

17.

Jung, Jinha, Akash Ashapure, Murilo Maeda, et al.. (2018). Unmanned aerial system based cotton genotype selection using machine learning (Conference Presentation). 36–36. 1 indexed citations

18.

Ashapure, Akash, et al.. (2017). Ensemble classifier based training data refinement technique for classification of remotely sensed optical images. 3246–3249. 1 indexed citations

19.

Ashapure, Akash, et al.. (2015). Segmentation-based classification of hyperspectral imagery using projected and correlation clustering techniques. Geocarto International. 31(10). 1045–1057. 6 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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