Anup Das

1.6k total citations
90 papers, 1.1k citations indexed

About

Anup Das is a scholar working on Aerospace Engineering, Environmental Engineering and Media Technology. According to data from OpenAlex, Anup Das has authored 90 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 55 papers in Aerospace Engineering, 40 papers in Environmental Engineering and 16 papers in Media Technology. Recurrent topics in Anup Das's work include Synthetic Aperture Radar (SAR) Applications and Techniques (50 papers), Soil Moisture and Remote Sensing (25 papers) and Remote-Sensing Image Classification (16 papers). Anup Das is often cited by papers focused on Synthetic Aperture Radar (SAR) Applications and Techniques (50 papers), Soil Moisture and Remote Sensing (25 papers) and Remote-Sensing Image Classification (16 papers). Anup Das collaborates with scholars based in India, United States and Canada. Anup Das's co-authors include Lipi B. Mahanta, Shiv Mohan, Azlan Zahid, Md Sultan Mahmud, Ajeet Kumar, Y. S. Rao, Mahendra Singh Nathawat, Kangkana Bora, Muhammad Usman Khan and Muhammad Muzammil and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Geoscience and Remote Sensing and Journal of Environmental Management.

In The Last Decade

Anup Das

82 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Anup Das India 19 373 338 229 205 153 90 1.1k
Gintautas Palubinskas Germany 17 189 0.5× 364 1.1× 86 0.4× 250 1.2× 86 0.6× 84 997
Jaan Praks Finland 27 811 2.2× 1.1k 3.2× 59 0.3× 423 2.1× 469 3.1× 175 2.3k
Chao Chen China 22 284 0.8× 73 0.2× 85 0.4× 453 2.2× 362 2.4× 124 1.6k
Helmut Mayer Germany 24 1.1k 3.0× 243 0.7× 94 0.4× 183 0.9× 411 2.7× 122 2.4k
Shenghui Fang China 19 554 1.5× 143 0.4× 157 0.7× 658 3.2× 420 2.7× 54 2.0k
Fabio Giulio Tonolo Italy 16 367 1.0× 299 0.9× 91 0.4× 92 0.4× 141 0.9× 64 1.1k
Juntao Yang China 15 400 1.1× 120 0.4× 26 0.1× 114 0.6× 249 1.6× 56 882
Ralf Reulke Germany 15 390 1.0× 324 1.0× 91 0.4× 264 1.3× 153 1.0× 122 1.5k
W.H. Bakker Netherlands 16 397 1.1× 55 0.2× 831 3.6× 428 2.1× 188 1.2× 40 1.6k

Countries citing papers authored by Anup Das

Since Specialization
Citations

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

Fields of papers citing papers by Anup Das

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anup Das

This figure shows the co-authorship network connecting the top 25 collaborators of Anup Das. A scholar is included among the top collaborators of Anup Das 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 Anup Das. Anup Das 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.
Yadav, Vikash Kumar, Shreya Anand, Rohan Kumar Raman, et al.. (2025). Current challenges and solutions for sustainability of Farmers Producer Organisations through grassroots organisational ecosystem. Current Science. 128(7). 699–709.
2.
Rosen, P. A., G. W. Bawden, Bruce Chapman, et al.. (2025). The NASA-ISRO SAR Mission: A summary. IEEE Geoscience and Remote Sensing Magazine. 13(2). 8–34. 1 indexed citations
3.
Sahoo, Sashikanta, et al.. (2025). Multi-frequency SAR polarimetry and Ground Penetrating Radar for paleochannel identification in the Thar Desert, India. Remote Sensing Applications Society and Environment. 38. 101533–101533.
5.
Das, Anup, et al.. (2023). Estimation of lunar surface roughness using Chandrayaan-2 full-polarimetric DFSAR data. Icarus. 406. 115720–115720. 5 indexed citations
6.
Mahmud, Md Sultan, Azlan Zahid, & Anup Das. (2023). Sensing and Automation Technologies for Ornamental Nursery Crop Production: Current Status and Future Prospects. Sensors. 23(4). 1818–1818. 13 indexed citations
7.
Bora, Kangkana, et al.. (2022). A comparative assessment of deep object detection models for blood smear analysis. Tissue and Cell. 76. 101761–101761. 14 indexed citations
8.
Behera, Mukunda Dev, et al.. (2022). A new synergistic approach for Sentinel-1 and PALSAR-2 in a machine learning framework to predict aboveground biomass of a dense mangrove forest. Ecological Informatics. 72. 101900–101900. 34 indexed citations
9.
Lal, Preet, Amit Kumar, Purabi Saikia, et al.. (2021). Effect of vegetation structure on above ground biomass in tropical deciduous forests of Central India. Geocarto International. 37(21). 6294–6310. 18 indexed citations
10.
Chaudhary, Sumit Kumar, Prashant K. Srivastava, Dileep Kumar Gupta, et al.. (2021). Machine learning algorithms for soil moisture estimation using Sentinel-1: Model development and implementation. Advances in Space Research. 69(4). 1799–1812. 58 indexed citations
11.
Chaudhary, Sumit Kumar, Dileep Kumar Gupta, Prashant K. Srivastava, et al.. (2021). Evaluation of Radar/Optical Based Vegetation Descriptors in Water Cloud Model for Soil Moisture Retrieval. IEEE Sensors Journal. 21(18). 21030–21037. 5 indexed citations
12.
Das, Anup, et al.. (2015). Investigation of the Capability of H-α Decomposition of Compact Polarimetric SAR Data with Application to Lunar Surface. Lunar and Planetary Science Conference. 1916. 3 indexed citations
13.
Das, Anup, et al.. (2014). Regolith Properties in the North Polar Region of the Moon from 12.6-cm Radar Polarimetry. LPI. 1985. 1 indexed citations
14.
Pandey, Dharmendra Kumar, et al.. (2014). Synthesis of Hybrid Dual-Polarimetric Radar Signatures with Application to Lunar Surface. Lunar and Planetary Science Conference. 2045. 1 indexed citations
15.
Pandey, Dharmendra Kumar, et al.. (2013). Scattering Characteristics of Lunar Regolith with Respect to Dual Frequency SAR: Preliminary Simulation Results. Lunar and Planetary Science Conference. 1269. 2 indexed citations
16.
De, Shaunak, et al.. (2013). Classification of RISAT-1 hybrid polarimetric data for various land features. IEEE Asia-Pacific Conference on Synthetic Aperture Radar. 494–497. 4 indexed citations
17.
Sharma, Mayank, et al.. (2013). Cornered Difference Weighted Mean SAR speckle filter. IEEE Asia-Pacific Conference on Synthetic Aperture Radar. 400–403. 3 indexed citations
18.
Rao, Y. S., et al.. (2013). Region growing based improved SAR speckle filter for polarimetric data. IEEE Asia-Pacific Conference on Synthetic Aperture Radar. 517–520. 3 indexed citations
19.
Mohan, Shiv, et al.. (2011). Monitoring and retrieval of vegetation parameter using multi-frequency polarimetric SAR data. IEEE Asia-Pacific Conference on Synthetic Aperture Radar. 1–4. 9 indexed citations
20.
Nathawat, Mahendra Singh, et al.. (2011). Accuracy assessment of DEMs derived from multi-frequency SAR images. IEEE Asia-Pacific Conference on Synthetic Aperture Radar. 1–4. 3 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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