Bappa Das

2.9k total citations
114 papers, 1.9k citations indexed

About

Bappa Das is a scholar working on Plant Science, Ecology and Environmental Engineering. According to data from OpenAlex, Bappa Das has authored 114 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Plant Science, 31 papers in Ecology and 28 papers in Environmental Engineering. Recurrent topics in Bappa Das's work include Remote Sensing in Agriculture (21 papers), Spectroscopy and Chemometric Analyses (19 papers) and Soil Geostatistics and Mapping (15 papers). Bappa Das is often cited by papers focused on Remote Sensing in Agriculture (21 papers), Spectroscopy and Chemometric Analyses (19 papers) and Soil Geostatistics and Mapping (15 papers). Bappa Das collaborates with scholars based in India, United States and Egypt. Bappa Das's co-authors include Venkatesh Paramesh, Rabi Narayan Sahoo, RN Singh, Debashis Chakraborty, Gopal Ramdas Mahajan, R. Ramesh, P. Krishnan, Mahender Kotha, Pankaj Prasad and Victor J. Loveson and has published in prestigious journals such as SHILAP Revista de lepidopterología, The Science of The Total Environment and Journal of Cleaner Production.

In The Last Decade

Bappa Das

98 papers receiving 1.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Bappa Das India 25 733 459 402 372 319 114 1.9k
Vinay Kumar Sehgal India 24 630 0.9× 447 1.0× 569 1.4× 350 0.9× 208 0.7× 157 1.8k
Aimrun Wayayok Malaysia 22 689 0.9× 360 0.8× 401 1.0× 448 1.2× 357 1.1× 145 1.8k
Wei Guo China 27 630 0.9× 886 1.9× 670 1.7× 385 1.0× 227 0.7× 125 2.1k
Qi Yang China 19 552 0.8× 617 1.3× 265 0.7× 506 1.4× 322 1.0× 58 1.5k
Bernard Tychon Belgium 23 571 0.8× 877 1.9× 624 1.6× 865 2.3× 390 1.2× 139 2.3k
Mário Cunha Portugal 30 1.4k 1.9× 956 2.1× 910 2.3× 410 1.1× 301 0.9× 139 2.9k
Zhigang Sun China 25 503 0.7× 844 1.8× 693 1.7× 601 1.6× 405 1.3× 99 2.0k
Qingrui Chang China 23 434 0.6× 693 1.5× 416 1.0× 410 1.1× 393 1.2× 92 2.0k
Rabi Narayan Sahoo India 26 1.3k 1.8× 961 2.1× 491 1.2× 634 1.7× 569 1.8× 130 2.6k
Yue Shi China 26 1.2k 1.6× 1.4k 3.0× 489 1.2× 424 1.1× 536 1.7× 70 3.0k

Countries citing papers authored by Bappa Das

Since Specialization
Citations

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

Fields of papers citing papers by Bappa Das

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bappa Das

This figure shows the co-authorship network connecting the top 25 collaborators of Bappa Das. A scholar is included among the top collaborators of Bappa 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 Bappa Das. Bappa 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.
2.
Ali, Emad, et al.. (2025). A-TIG welding in aerospace industry: mechanisms, parameters, material considerations, optimization strategies, and machine learning integration. Advances in Materials and Processing Technologies. 11(4). 3555–3585.
3.
Ghosh, Arka, et al.. (2025). Effect of Addition of CNTxGnPyhBNz Ternary Hybrid Nanofillers on Mechanical Performance of Al Nanocomposites: A Comparative Study. Journal of Materials Engineering and Performance. 34(18). 21247–21258.
4.
Ghosh, Arkasubhra, et al.. (2025). Macrostructures of carbon nanotubes for advanced battery application: A comprehensive review. Synthetic Metals. 314. 117944–117944.
5.
Saha, Saurav, et al.. (2024). Usability assessment of district level rainfall forecast in Mizoram. MAUSAM. 75(3). 885–894.
6.
Uthappa, A. R., Bappa Das, Gopal Ramdas Mahajan, et al.. (2024). Comparative analysis of soil quality indexing techniques for various tree based land use systems in semi-arid India. Frontiers in Forests and Global Change. 6. 7 indexed citations
7.
Sehgal, Vinay Kumar, et al.. (2024). Remote sensing based Multivariate Hierarchical Agricultural Drought Index (MHADI) for India. Theoretical and Applied Climatology. 155(12). 9885–9909. 2 indexed citations
8.
Haldar, Dipanwita, et al.. (2024). Rice yield prediction through integration of biophysical parameters with SAR and optical remote sensing data using machine learning models. Scientific Reports. 14(1). 21674–21674. 7 indexed citations
9.
Das, Bappa, Debashis Chakraborty, Vinod Kumar Singh, et al.. (2023). Partial least square regression based machine learning models for soil organic carbon prediction using visible–near infrared spectroscopy. Geoderma Regional. 33. e00628–e00628. 22 indexed citations
10.
Das, Bappa, Debashis Chakraborty, Bimal K. Bhattacharya, et al.. (2023). Ensemble surface soil moisture estimates at farm-scale combining satellite-based optical-thermal-microwave remote sensing observations. Agricultural and Forest Meteorology. 339. 109567–109567. 22 indexed citations
11.
Paramesh, Venkatesh, Parveen Kumar, Arun Jyoti Nath, et al.. (2023). Integrated Nutrient Management Enhances Yield, Improves Soil Quality, and Conserves Energy under the Lowland Rice–Rice Cropping System. Agronomy. 13(6). 1557–1557. 14 indexed citations
12.
Das, Bappa, et al.. (2023). Comparative Analysis of Statistical and Machine Learning Techniques for Rice Yield Forecasting for Chhattisgarh, India. Sustainability. 15(3). 2786–2786. 47 indexed citations
13.
Das, Bappa, et al.. (2022). Novel combination artificial neural network models could not outperform individual models for weather-based cashew yield prediction. International Journal of Biometeorology. 66(8). 1627–1638. 10 indexed citations
14.
Mahajan, Gopal Ramdas, et al.. (2021). Long-Term Effect of Various Organic and Inorganic Nutrient Sources on Rice Yield and Soil Quality in West Coast India Using Suitable Indexing Techniques. Communications in Soil Science and Plant Analysis. 52(15). 1819–1833. 6 indexed citations
15.
Mahajan, Gopal Ramdas, et al.. (2021). Comparison of soil quality indexing methods for salt-affected soils of Indian coastal region. Environmental Earth Sciences. 80(21). 9 indexed citations
16.
Mahajan, Gopal Ramdas, et al.. (2020). Monitoring properties of the salt-affected soils by multivariate analysis of the visible and near-infrared hyperspectral data. CATENA. 198. 105041–105041. 32 indexed citations
17.
Mahajan, Gopal Ramdas, et al.. (2020). Soil and water conservation measures improve soil carbon sequestration and soil quality under cashews. International Journal of Sediment Research. 36(2). 190–206. 37 indexed citations
18.
Mahajan, Gopal Ramdas, et al.. (2020). Soil quality assessment of coastal salt-affected acid soils of India. Environmental Science and Pollution Research. 27(21). 26221–26238. 47 indexed citations
19.
Paramesh, Venkatesh, et al.. (2018). A five years study on the selection of rice based cropping systems in Goa, for west coast region of India. Journal of Environmental Biology. 39(3). 393–399. 13 indexed citations
20.
Das, Bappa, et al.. (2013). High value flower cultivation under low cost greenhouse in NW Himalayas.. International Journal of ChemTech Research. 5(2). 789–794. 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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