Onkar Dikshit

1.9k total citations
119 papers, 1.4k citations indexed

About

Onkar Dikshit is a scholar working on Atmospheric Science, Aerospace Engineering and Media Technology. According to data from OpenAlex, Onkar Dikshit has authored 119 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 53 papers in Atmospheric Science, 46 papers in Aerospace Engineering and 36 papers in Media Technology. Recurrent topics in Onkar Dikshit's work include Remote-Sensing Image Classification (33 papers), Synthetic Aperture Radar (SAR) Applications and Techniques (28 papers) and Remote Sensing and Land Use (27 papers). Onkar Dikshit is often cited by papers focused on Remote-Sensing Image Classification (33 papers), Synthetic Aperture Radar (SAR) Applications and Techniques (28 papers) and Remote Sensing and Land Use (27 papers). Onkar Dikshit collaborates with scholars based in India, United States and Australia. Onkar Dikshit's co-authors include Divyesh Varade, Brajesh Kumar, Sumanta Pasari, R. S. Dwivedi, Manoj Kumar Singh, Ashutosh Tiwari, Mohamed Shaban, Surendar Manickam, Mukesh Sharma and S. N. Behera and has published in prestigious journals such as SHILAP Revista de lepidopterología, Remote Sensing of Environment and Scientific Reports.

In The Last Decade

Onkar Dikshit

113 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Onkar Dikshit India 21 568 421 285 270 223 119 1.4k
Bruno Adriano Japan 22 386 0.7× 388 0.9× 153 0.5× 99 0.4× 363 1.6× 73 1.3k
Shuichi Rokugawa Japan 14 736 1.3× 303 0.7× 300 1.1× 1.1k 4.1× 188 0.8× 63 1.8k
A.R.L. Tatnall United Kingdom 13 255 0.4× 282 0.7× 141 0.5× 252 0.9× 95 0.4× 52 1.3k
Marc Wieland Germany 22 430 0.8× 355 0.8× 96 0.3× 368 1.4× 114 0.5× 52 1.6k
Valentyn Tolpekin Netherlands 20 352 0.6× 438 1.0× 268 0.9× 513 1.9× 56 0.3× 87 1.5k
Simon Plank Germany 21 721 1.3× 231 0.5× 575 2.0× 333 1.2× 162 0.7× 78 1.9k
Wooil M. Moon Canada 26 277 0.5× 450 1.1× 507 1.8× 526 1.9× 416 1.9× 147 2.0k
F. Sunar Türkiye 18 378 0.7× 267 0.6× 312 1.1× 379 1.4× 45 0.2× 63 1.5k
Junhuan Peng China 19 264 0.5× 265 0.6× 250 0.9× 156 0.6× 47 0.2× 98 1.1k
Anne H. Schistad Solberg Norway 20 270 0.5× 751 1.8× 188 0.7× 207 0.8× 296 1.3× 60 3.1k

Countries citing papers authored by Onkar Dikshit

Since Specialization
Citations

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

Fields of papers citing papers by Onkar Dikshit

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Onkar Dikshit

This figure shows the co-authorship network connecting the top 25 collaborators of Onkar Dikshit. A scholar is included among the top collaborators of Onkar Dikshit 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 Onkar Dikshit. Onkar Dikshit 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.
3.
Heinkelmann, Robert, Santiago Belda, Harald Schuh, et al.. (2024). Combining evolutionary computation with machine learning technique for improved short-term prediction of UT1-UTC and length-of-day. Earth Planets and Space. 76(1). 3 indexed citations
4.
Singh, Shivangi, Johannes Böhm, Hana Krásná, Nagarajan Balasubramanian, & Onkar Dikshit. (2024). Evaluation of VGOS and legacy S/X VLBI observations with non-tidal loading corrections. Advances in Space Research. 75(6). 4502–4515.
5.
Glaser, Susanne, et al.. (2023). Favorable locations for new VGOS antennas in India depending on the assessment of geodetic parameters and environmental factors. Earth Planets and Space. 75(1). 2 indexed citations
6.
Dikshit, Onkar, et al.. (2023). Addressing the unresolved proximity conflicts during the generalization of buildings using CartAGen. Abstracts of the ICA. 6. 1–3. 1 indexed citations
7.
Saatchi, Sassan, et al.. (2023). Mapping tropical forest aboveground biomass using airborne SAR tomography. Scientific Reports. 13(1). 6233–6233. 14 indexed citations
8.
Balasubramanian, Nagarajan, et al.. (2022). Stable and upgraded horizontal datum for India. Current Science. 123(1). 43–43. 4 indexed citations
9.
Deshpande, Prasad, et al.. (2021). Historical land cover classification from CORONA imagery using convolutional neural networks and geometric moments. International Journal of Remote Sensing. 42(13). 5144–5171. 17 indexed citations
10.
Ågren, Jonas, et al.. (2021). Empirical comparison between stochastic and deterministic modifiers over the French Auvergne geoid computation test-bed. Survey Review. 54(382). 57–69. 17 indexed citations
11.
Varade, Divyesh, Surendar Manickam, Onkar Dikshit, Gulab Singh, & Snehmani. (2020). Modelling of early winter snow density using fully polarimetric C-band SAR data in the Indian Himalayas. Remote Sensing of Environment. 240. 111699–111699. 21 indexed citations
12.
Varade, Divyesh, et al.. (2019). Unsupervised band selection of hyperspectral data based on mutual information derived from weighted cluster entropy for snow classification. Geocarto International. 36(15). 1709–1731. 11 indexed citations
13.
Tebaldini, Stefano, et al.. (2019). Comparative Analysis of Forest Biomass Estimation using SAR Tomographic Techniques. 1–5. 1 indexed citations
14.
Varade, Divyesh & Onkar Dikshit. (2017). A novel linear physical model for remote sensing of snow wetness and snow density using the visible and infrared bands. AGUFM. 2017. 5 indexed citations
15.
Tiwari, Ashutosh, et al.. (2017). Persistent Scatter Identification and Look-Angle Error Estimation Using Similar Time-Series Interferometric Pixels. IEEE Geoscience and Remote Sensing Letters. 15(1). 147–150. 7 indexed citations
16.
Dikshit, Onkar, et al.. (2017). Segmentation-based clustering of hyperspectral images using local band selection. Journal of Applied Remote Sensing. 11(1). 15028–15028. 8 indexed citations
17.
Tiwari, Ashutosh, R. S. Dwivedi, Onkar Dikshit, & Ajai K. Singh. (2016). A study on measuring surface deformation of the L’Aquila region using the StaMPS technique. International Journal of Remote Sensing. 37(4). 819–830. 23 indexed citations
18.
Kumar, Brajesh & Onkar Dikshit. (2016). Spectral Contextual Classification of Hyperspectral Imagery With Probabilistic Relaxation Labeling. IEEE Transactions on Cybernetics. 47(12). 4380–4391. 22 indexed citations
19.
Behera, S. N., Mukesh Sharma, Onkar Dikshit, & Sheo Prasad Shukla. (2010). GIS-Based Emission Inventory, Dispersion Modeling, and Assessment for Source Contributions of Particulate Matter in an Urban Environment. Water Air & Soil Pollution. 218(1-4). 423–436. 37 indexed citations
20.
Katiyar, Sunil Kumar, Onkar Dikshit, & Krishna Kumar. (2004). Ground control for the geometric correction of PAN imagery from Indian remote sensing (IRS) satellites. 6. 4041–4043. 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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