V. Bhanumurthy

622 total citations
20 papers, 422 citations indexed

About

V. Bhanumurthy is a scholar working on Global and Planetary Change, Atmospheric Science and Signal Processing. According to data from OpenAlex, V. Bhanumurthy has authored 20 papers receiving a total of 422 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Global and Planetary Change, 8 papers in Atmospheric Science and 6 papers in Signal Processing. Recurrent topics in V. Bhanumurthy's work include Flood Risk Assessment and Management (14 papers), Geographic Information Systems Studies (6 papers) and Data Management and Algorithms (6 papers). V. Bhanumurthy is often cited by papers focused on Flood Risk Assessment and Management (14 papers), Geographic Information Systems Studies (6 papers) and Data Management and Algorithms (6 papers). V. Bhanumurthy collaborates with scholars based in India. V. Bhanumurthy's co-authors include C. M. Bhatt, P. Manjusree, Goru Srinivasa Rao, G. Srinivasa Rao, K. Ram Mohan Rao, Majid Farooq, V. K. Dadhwal, Swati Sharma, P. G. Diwakar and K. H. V. Durga Rao and has published in prestigious journals such as Geocarto International, Geomatics Natural Hazards and Risk and International Journal of Disaster Risk Science.

In The Last Decade

V. Bhanumurthy

20 papers receiving 403 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
V. Bhanumurthy India 11 319 137 115 93 36 20 422
Karen Mulcahy United States 7 210 0.7× 107 0.8× 72 0.6× 67 0.7× 52 1.4× 9 332
Enes Yıldırım United States 12 303 0.9× 147 1.1× 121 1.1× 100 1.1× 7 0.2× 19 433
J. Michael Johnson United States 14 274 0.9× 169 1.2× 72 0.6× 71 0.8× 22 0.6× 23 417
Roberto Tomasoni Italy 3 232 0.7× 115 0.8× 99 0.9× 95 1.0× 8 0.2× 6 319
M. Maggi Italy 5 257 0.8× 112 0.8× 104 0.9× 97 1.0× 7 0.2× 7 337
Alex Ip Australia 4 347 1.1× 183 1.3× 62 0.5× 146 1.6× 38 1.1× 9 506
Rachel Melrose Australia 2 298 0.9× 174 1.3× 46 0.4× 116 1.2× 17 0.5× 3 390
P. de Fraipont France 10 376 1.2× 311 2.3× 123 1.1× 89 1.0× 7 0.2× 22 493
A Mcintyre Australia 5 369 1.2× 191 1.4× 70 0.6× 161 1.7× 28 0.8× 6 535
Simone Frigerio Italy 11 177 0.6× 34 0.2× 106 0.9× 35 0.4× 23 0.6× 23 394

Countries citing papers authored by V. Bhanumurthy

Since Specialization
Citations

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

Fields of papers citing papers by V. Bhanumurthy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of V. Bhanumurthy

This figure shows the co-authorship network connecting the top 25 collaborators of V. Bhanumurthy. A scholar is included among the top collaborators of V. Bhanumurthy 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 V. Bhanumurthy. V. Bhanumurthy 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.
Bhanumurthy, V., K. Ram Mohan Rao, G. Sankar, & P. V. Nagamani. (2017). Spatial data integration for disaster/emergency management: an Indian experience. Spatial Information Research. 25(2). 303–314. 9 indexed citations
2.
Bhatt, C. M., et al.. (2017). An open source framework for publishing flood inundation extent libraries in a Web GIS environment using open source technologies. International Journal of Cartography. 4(1). 65–77. 4 indexed citations
3.
Rao, G. Srinivasa, et al.. (2017). Automatic procedures analyzing remote sensing data to minimize flood response time: a step towards National flood mapping service. Spatial Information Research. 25(5). 657–663. 2 indexed citations
4.
Yadav, Anil Kumar, et al.. (2017). Satellite data planning for flood mapping activities based on high rainfall events generated using TRMM, GEFS and disaster news. Annals of GIS. 23(2). 131–140. 10 indexed citations
5.
6.
Roy, P. S., et al.. (2016). Extraction of detailed level flood hazard zones using multi-temporal historical satellite data-sets – a case study of Kopili River Basin, Assam, India. Geomatics Natural Hazards and Risk. 8(2). 792–802. 25 indexed citations
7.
8.
Rao, G. Srinivasa, et al.. (2016). Event-driven flood management: design and computational modules. Geo-spatial Information Science. 19(1). 39–55. 13 indexed citations
9.
Bhatt, C. M., G. Srinivasa Rao, Majid Farooq, et al.. (2016). Satellite-based assessment of the catastrophic Jhelum floods of September 2014, Jammu & Kashmir, India. Geomatics Natural Hazards and Risk. 8(2). 309–327. 73 indexed citations
10.
Manjusree, P., et al.. (2015). A decadal historical satellite data analysis for flood hazard evaluation: A case study of Bihar (North India). Singapore Journal of Tropical Geography. 36(3). 308–323. 13 indexed citations
11.
Bhanumurthy, V., et al.. (2015). Defining a framework for integration of Geospatial technologies for Emergency Management. Geocarto International. 1–31. 13 indexed citations
12.
Bhanumurthy, V., et al.. (2014). Enabling heterogenous multi-scale database for emergency service functions through geoinformation technologies. ˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences. XL-8. 7–14. 4 indexed citations
13.
Karnatak, Harish Chandra, et al.. (2012). Spatial mashup technology and real time data integration in geo-web application using open source GIS – a case study for disaster management. Geocarto International. 27(6). 499–514. 27 indexed citations
14.
Manjusree, P., et al.. (2012). Optimization of threshold ranges for rapid flood inundation mapping by evaluating backscatter profiles of high incidence angle SAR images. International Journal of Disaster Risk Science. 3(2). 113–122. 151 indexed citations
15.
Bhatt, C. M., G. Srinivasa Rao, P. Manjusree, & V. Bhanumurthy. (2011). Potential of high resolution satellite data for disaster management: a case study of Leh, Jammu & Kashmir (India) flash floods, 2010. Geomatics Natural Hazards and Risk. 2(4). 365–375. 12 indexed citations
16.
Bhatt, C. M., et al.. (2010). Space based disaster management of 2008 Kosi floods, North Bihar, India. Journal of the Indian Society of Remote Sensing. 38(1). 99–108. 40 indexed citations
17.
Diwakar, P. G., V. Jayaraman, V. Bhanumurthy, & M. Ramalingam. (2009). Geospatial Applications in Tsunami Disaster Management. International Journal of Ecology & Development. 12. 4–14. 1 indexed citations
18.
Rao, K. H. V. Durga, V. Bhanumurthy, & Priyom Roy. (2009). Application of satellite — based rainfall products and SRTM DEM in hydrological modelling of Brahmaputra basin. Journal of the Indian Society of Remote Sensing. 37(4). 587–600. 14 indexed citations
19.
Rao, G. Srinivasa, et al.. (2006). Advantage of multipolarized SAR data for flood extent delineation. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 6410. 64100Z–64100Z. 5 indexed citations
20.
Bhanumurthy, V., et al.. (2003). Application of remote sensing and GIS in water resources development. Water and Energy International. 60(2). 38–50. 1 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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