Pankaj Prasad

621 total citations
20 papers, 436 citations indexed

About

Pankaj Prasad is a scholar working on Global and Planetary Change, Environmental Engineering and Atmospheric Science. According to data from OpenAlex, Pankaj Prasad has authored 20 papers receiving a total of 436 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Global and Planetary Change, 8 papers in Environmental Engineering and 6 papers in Atmospheric Science. Recurrent topics in Pankaj Prasad's work include Flood Risk Assessment and Management (13 papers), Groundwater and Watershed Analysis (5 papers) and Hydrology and Watershed Management Studies (4 papers). Pankaj Prasad is often cited by papers focused on Flood Risk Assessment and Management (13 papers), Groundwater and Watershed Analysis (5 papers) and Hydrology and Watershed Management Studies (4 papers). Pankaj Prasad collaborates with scholars based in India, Saudi Arabia and United Kingdom. Pankaj Prasad's co-authors include Victor J. Loveson, Mahender Kotha, Bappa Das, Anirudh Ram, Sumit Das, Luc Cimusa Kulimushi, Ahmed Elbeltagi, Nand Lal Kushwaha, Pandurang Choudhari and Safwan Mohammed and has published in prestigious journals such as SHILAP Revista de lepidopterología, Marine Pollution Bulletin and Geomorphology.

In The Last Decade

Pankaj Prasad

17 papers receiving 428 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Pankaj Prasad India 9 275 207 146 68 61 20 436
Siyu Lu China 9 194 0.7× 135 0.7× 116 0.8× 88 1.3× 37 0.6× 11 420
Yamei Wang China 4 258 0.9× 169 0.8× 261 1.8× 49 0.7× 35 0.6× 6 512
Parthasarathy Kulithalai Shiyam Sundar India 9 273 1.0× 209 1.0× 147 1.0× 71 1.0× 51 0.8× 12 426
Amobichukwu C. Amanambu United States 9 211 0.8× 140 0.7× 250 1.7× 76 1.1× 42 0.7× 14 497
Surendra Kumar Chandniha India 12 212 0.8× 183 0.9× 191 1.3× 51 0.8× 37 0.6× 21 423
Matteo Gentilucci Italy 13 250 0.9× 108 0.5× 119 0.8× 160 2.4× 80 1.3× 51 490
Héctor Aguilera Spain 13 170 0.6× 167 0.8× 189 1.3× 39 0.6× 35 0.6× 36 457
Ahmad Nohegar Iran 11 197 0.7× 119 0.6× 192 1.3× 45 0.7× 23 0.4× 49 438
Anis Chaabani Saudi Arabia 12 216 0.8× 135 0.7× 194 1.3× 36 0.5× 41 0.7× 25 417
Devanantham Abijith India 13 423 1.5× 310 1.5× 213 1.5× 95 1.4× 78 1.3× 21 595

Countries citing papers authored by Pankaj Prasad

Since Specialization
Citations

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

Fields of papers citing papers by Pankaj Prasad

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pankaj Prasad

This figure shows the co-authorship network connecting the top 25 collaborators of Pankaj Prasad. A scholar is included among the top collaborators of Pankaj Prasad 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 Pankaj Prasad. Pankaj Prasad 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.
Abdo, Hazem Ghassan, et al.. (2025). Multi-criteria Assessment of Potential Check Dam Location for Sustainable Development in Urban River Basins of the Eastern Mediterranean. Water Resources Management. 39(5). 2149–2175. 1 indexed citations
2.
Abdo, Hazem Ghassan, Pankaj Prasad, Okan Mert Katipoğlu, et al.. (2025). Mapping landslide susceptibility in the Eastern Mediterranean mountainous region: a machine learning perspective. Environmental Earth Sciences. 84(9). 4 indexed citations
3.
4.
Abdo, Hazem Ghassan, Taorui Zeng, Saeed Alqadhi, et al.. (2025). Machine learning-based assessment of flood susceptibility in the Eastern Mediterranean: a case study of Baniyas River basin. Geomatics Natural Hazards and Risk. 16(1).
5.
Prasad, Pankaj, et al.. (2024). Integration of multi-temporal SAR data and robust machine learning models for improvement of flood susceptibility assessment in the southwest coast of India. SHILAP Revista de lepidopterología. 24. 100189–100189. 8 indexed citations
6.
Prasad, Pankaj, et al.. (2024). Threshold-based inventory for flood susceptibility assessment of the world’s largest river island using multi-temporal SAR data and ensemble machine learning algorithms. Stochastic Environmental Research and Risk Assessment. 39(1). 251–269. 4 indexed citations
7.
Abdo, Hazem Ghassan, et al.. (2024). A hybrid machine learning modelling for optimization of flood susceptibility mapping in the eastern Mediterranean. Natural Hazards. 121(6). 7199–7228. 1 indexed citations
8.
Abdo, Hazem Ghassan, et al.. (2024). Multi-criteria analysis and geospatial applications-based mapping flood vulnerable areas: a case study from the eastern Mediterranean. Natural Hazards. 121(1). 1003–1031. 8 indexed citations
9.
10.
Prasad, Pankaj, et al.. (2023). Heavy metal accumulation in a moderately polluted Ulhas estuary, Western India. Regional Studies in Marine Science. 60. 102818–102818. 20 indexed citations
11.
12.
Prasad, Pankaj, Victor J. Loveson, & Mahender Kotha. (2023). Probabilistic coastal wetland mapping with integration of optical, SAR and hydro-geomorphic data through stacking ensemble machine learning model. Ecological Informatics. 77. 102273–102273. 22 indexed citations
13.
Kulimushi, Luc Cimusa, Pankaj Prasad, Nand Lal Kushwaha, et al.. (2022). Soil erosion susceptibility mapping using ensemble machine learning models: A case study of upper Congo river sub-basin. CATENA. 222. 106858–106858. 43 indexed citations
14.
Ramteke, Karankumar, et al.. (2021). Monitoring of current land use pattern of Ramsar designated Kolleru Wetland, India using geospatial technologies. Journal of Environmental Biology. 42(1). 106–111. 3 indexed citations
15.
Luis, Alvarinho J., et al.. (2021). Spatio-temporal assessment of COVID-19 lockdown impact on beach litter status and composition in Goa, India. Marine Pollution Bulletin. 174. 113293–113293. 10 indexed citations
16.
Prasad, Pankaj, Victor J. Loveson, Bappa Das, & Mahender Kotha. (2021). Novel ensemble machine learning models in flood susceptibility mapping. Geocarto International. 37(16). 4571–4593. 105 indexed citations
17.
Prasad, Pankaj, et al.. (2021). Evaluation and comparison of the earth observing sensors in land cover/land use studies using machine learning algorithms. Ecological Informatics. 68. 101522–101522. 49 indexed citations
18.
Prasad, Pankaj, et al.. (2021). Artificial intelligence approaches for spatial prediction of landslides in mountainous regions of western India. Environmental Earth Sciences. 80(21). 23 indexed citations
19.
Prasad, Pankaj, et al.. (2020). Application of machine learning techniques in groundwater potential mapping along the west coast of India. GIScience & Remote Sensing. 57(6). 735–752. 123 indexed citations
20.
Prasad, Pankaj & Victor J. Loveson. (2020). Signature of buried channels as deduced from subsurface GPR survey at Southwest coast of Tamil Nadu, India. Arabian Journal of Geosciences. 13(12). 8 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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