Pramit Kumar Deb Burman

597 total citations
32 papers, 377 citations indexed

About

Pramit Kumar Deb Burman is a scholar working on Global and Planetary Change, Ecology and Atmospheric Science. According to data from OpenAlex, Pramit Kumar Deb Burman has authored 32 papers receiving a total of 377 indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Global and Planetary Change, 12 papers in Ecology and 10 papers in Atmospheric Science. Recurrent topics in Pramit Kumar Deb Burman's work include Plant Water Relations and Carbon Dynamics (21 papers), Climate variability and models (11 papers) and Remote Sensing in Agriculture (7 papers). Pramit Kumar Deb Burman is often cited by papers focused on Plant Water Relations and Carbon Dynamics (21 papers), Climate variability and models (11 papers) and Remote Sensing in Agriculture (7 papers). Pramit Kumar Deb Burman collaborates with scholars based in India, China and United Kingdom. Pramit Kumar Deb Burman's co-authors include Supriyo Chakraborty, Anandakumar Karipot, Dipankar Sarma, Palingamoorthy Gnanamoorthy, Mathew Williams, R. Nagarajan, V. Selvam, Nirmali Gogoi, Ross Morrison and Qinghai Song and has published in prestigious journals such as The Science of The Total Environment, Scientific Reports and Global Change Biology.

In The Last Decade

Pramit Kumar Deb Burman

29 papers receiving 371 citations

Peers

Pramit Kumar Deb Burman
Pramit Kumar Deb Burman
Citations per year, relative to Pramit Kumar Deb Burman Pramit Kumar Deb Burman (= 1×) peers Kiran Chand Thumaty

Countries citing papers authored by Pramit Kumar Deb Burman

Since Specialization
Citations

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

Fields of papers citing papers by Pramit Kumar Deb Burman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pramit Kumar Deb Burman. 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 Pramit Kumar Deb Burman. The network helps show where Pramit Kumar Deb Burman may publish in the future.

Co-authorship network of co-authors of Pramit Kumar Deb Burman

This figure shows the co-authorship network connecting the top 25 collaborators of Pramit Kumar Deb Burman. A scholar is included among the top collaborators of Pramit Kumar Deb Burman 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 Pramit Kumar Deb Burman. Pramit Kumar Deb Burman 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.
Burman, Pramit Kumar Deb, Palingamoorthy Gnanamoorthy, Qinghai Song, et al.. (2025). Estimating latent heat flux of subtropical forests using machine learning algorithms. Meteorological Applications. 32(1). 1 indexed citations
2.
Rao, K. Ranga, et al.. (2025). Subtropical forest floor CO2 emission at the Kaziranga National Park in Northeast India. Environmental Monitoring and Assessment. 197(2). 133–133. 1 indexed citations
3.
Chakraborty, Supriyo, A. K. Sarkar, Pramit Kumar Deb Burman, et al.. (2025). Precipitation isotopes and monsoon dynamics in the core monsoon zone of India. Scientific Reports. 15(1). 6761–6761.
4.
5.
Pandey, Varsha, et al.. (2024). Gross primary productivity of terrestrial ecosystems: a review of observations, remote sensing, and modelling studies over South Asia. Theoretical and Applied Climatology. 155(9). 8461–8491. 8 indexed citations
6.
Burman, Pramit Kumar Deb, et al.. (2024). Simulating the ecosystem-atmosphere carbon, water and energy fluxes at a subtropical Indian forest using an ecosystem model. Ecological Modelling. 490. 110637–110637. 5 indexed citations
7.
Sarkar, A. K., et al.. (2024). Evaluating tree-ring proxies for representing the ecosystem productivity in India. International Journal of Biometeorology. 69(1). 137–155.
8.
Burman, Pramit Kumar Deb & Pulakesh Das. (2024). A Data‐Driven Approach to Assess the Impact of Climate Change on a Tropical Mangrove in India. Journal of Geophysical Research Biogeosciences. 129(8). 4 indexed citations
9.
Burman, Pramit Kumar Deb, Yogesh K. Tiwari, U.C. Dumka, et al.. (2023). Understanding carbon sequestration trends using model and satellite data under different ecosystems in India. The Science of The Total Environment. 897. 166381–166381. 5 indexed citations
10.
Burman, Pramit Kumar Deb, et al.. (2023). Investigating Terrestrial Carbon Uptake Over India Using Multimodel Simulations of Gross Primary Productivity and Satellite‐Based Biophysical Product. Journal of Geophysical Research Biogeosciences. 128(11). 5 indexed citations
11.
Gnanamoorthy, Palingamoorthy, Qinghai Song, Junbin Zhao, et al.. (2022). Seasonal fog enhances crop water productivity in a tropical rubber plantation. Journal of Hydrology. 611. 128016–128016. 5 indexed citations
12.
Singha, Mrinal, Jinsong Wang, Jinwei Dong, et al.. (2021). Mismatches between vegetation greening and primary productivity trends in South Asia – A satellite evidence. International Journal of Applied Earth Observation and Geoinformation. 104. 102561–102561. 31 indexed citations
13.
Sarma, Dipankar, et al.. (2021). Quantifying the net ecosystem exchange at a semi-deciduous forest in northeast India from intra-seasonal to the seasonal time scale. Agricultural and Forest Meteorology. 314. 108786–108786. 17 indexed citations
14.
Gnanamoorthy, Palingamoorthy, Qinghai Song, Junbin Zhao, et al.. (2021). Altered albedo dominates the radiative forcing changes in a subtropical forest following an extreme snow event. Global Change Biology. 27(23). 6192–6205. 11 indexed citations
15.
Burman, Pramit Kumar Deb, Supriyo Chakraborty, Tarek S. El‐Madany, et al.. (2021). A comparative study of ecohydrologies of a tropical mangrove and a broadleaf deciduous forest using eddy covariance measurement. Meteorology and Atmospheric Physics. 134(1). 11 indexed citations
16.
Tiwari, Yogesh K., et al.. (2021). An intensification of atmospheric CO2 concentrations due to the surface temperature extremes in India. Meteorology and Atmospheric Physics. 133(6). 1647–1659. 1 indexed citations
17.
Chowdhuri, Subharthi & Pramit Kumar Deb Burman. (2019). Representation of the Reynolds stress tensor through quadrant analysis for a near-neutral atmospheric surface layer flow. Environmental Fluid Mechanics. 20(1). 51–75. 9 indexed citations
18.
Gnanamoorthy, Palingamoorthy, V. Selvam, R. Nagarajan, et al.. (2019). Diurnal and seasonal patterns of soil CO2 efflux from the Pichavaram mangroves, India. Environmental Monitoring and Assessment. 191(4). 258–258. 21 indexed citations
19.
Burman, Pramit Kumar Deb, Dipankar Sarma, Ross Morrison, Anandakumar Karipot, & Supriyo Chakraborty. (2019). Seasonal variation of evapotranspiration and its effect on the surface energy budget closure at a tropical forest over north-east India. Journal of Earth System Science. 128(5). 24 indexed citations
20.
Burman, Pramit Kumar Deb, Dipankar Sarma, Mathew Williams, Anandakumar Karipot, & Supriyo Chakraborty. (2017). Estimating gross primary productivity of a tropical forest ecosystem over north-east India using LAI and meteorological variables. Journal of Earth System Science. 126(7). 44 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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