S. Saran

840 total citations · 1 hit paper
23 papers, 622 citations indexed

About

S. Saran is a scholar working on Artificial Intelligence, Ecology and Ecological Modeling. According to data from OpenAlex, S. Saran has authored 23 papers receiving a total of 622 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 6 papers in Ecology and 5 papers in Ecological Modeling. Recurrent topics in S. Saran's work include Remote Sensing in Agriculture (5 papers), Species Distribution and Climate Change (5 papers) and Geographic Information Systems Studies (3 papers). S. Saran is often cited by papers focused on Remote Sensing in Agriculture (5 papers), Species Distribution and Climate Change (5 papers) and Geographic Information Systems Studies (3 papers). S. Saran collaborates with scholars based in India, Netherlands and China. S. Saran's co-authors include P. S. Roy, S. P. S. Kushwaha, Jianchu Xu, Xueqing Yang, V. K. Dadhwal, Hitendra Padalia, Rajesh Joshi, Subrat Sharma, K. V. Ramana and Bhaskar Sinha and has published in prestigious journals such as SHILAP Revista de lepidopterología, Ecological Engineering and Geocarto International.

In The Last Decade

S. Saran

20 papers receiving 601 citations

Hit Papers

Maxent modeling for predicting the potential distribution... 2013 2026 2017 2021 2013 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
S. Saran India 6 428 245 214 166 93 23 622
Emad Kaky Iraq 7 386 0.9× 180 0.7× 204 1.0× 142 0.9× 52 0.6× 10 506
André Felipe Alves de Andrade Brazil 12 338 0.8× 225 0.9× 268 1.3× 168 1.0× 116 1.2× 22 591
Jorge Velásquez‐Tibatá United States 10 359 0.8× 209 0.9× 260 1.2× 108 0.7× 79 0.8× 19 533
Alba Cuena‐Lombraña Italy 12 331 0.8× 185 0.8× 167 0.8× 195 1.2× 45 0.5× 28 562
Brian J. Stucky United States 12 316 0.7× 123 0.5× 244 1.1× 199 1.2× 132 1.4× 18 600
Sven Pompe Germany 10 264 0.6× 319 1.3× 168 0.8× 206 1.2× 97 1.0× 14 535
Victoria Nolan United Kingdom 6 262 0.6× 139 0.6× 173 0.8× 87 0.5× 63 0.7× 16 414
Abdulaziz S. Alatawi Saudi Arabia 6 283 0.7× 132 0.5× 186 0.9× 84 0.5× 59 0.6× 17 408
Robert Stafford United States 9 284 0.7× 173 0.7× 258 1.2× 95 0.6× 88 0.9× 15 536
Salvador Arenas‐Castro Spain 15 469 1.1× 256 1.0× 433 2.0× 112 0.7× 226 2.4× 39 838

Countries citing papers authored by S. Saran

Since Specialization
Citations

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

Fields of papers citing papers by S. Saran

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of S. Saran

This figure shows the co-authorship network connecting the top 25 collaborators of S. Saran. A scholar is included among the top collaborators of S. Saran 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 S. Saran. S. Saran 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.
Saran, S., et al.. (2025). A high gain filtenna with radiation nulls using a novel split-merge feed line on a slot-loaded rectangular patch for X-band RADAR application. AEU - International Journal of Electronics and Communications. 196. 155789–155789.
3.
Priya, E., et al.. (2023). Characterization of Wrist Pulse Using Machine Learning Techniques. 1–5. 1 indexed citations
4.
Murugesan, M., et al.. (2023). A Survey on Recommendation System for Future Researchers Using Classifiers. 724–729. 6 indexed citations
5.
Saran, S., et al.. (2020). MAXIMUM ENTROPY MODELING USING CITIZEN SCIENCE: USE CASE ON JACOBIN CUCKOO AS AN INDICATOR OF INDIAN MONSOON. SHILAP Revista de lepidopterología. V-5-2020. 23–30. 1 indexed citations
6.
Saran, S., et al.. (2018). SITE SUITABILITY ANALYSIS FOR INDUSTRIES USING GIS ANDMULTI CRITERIA DECISION MAKING. SHILAP Revista de lepidopterología. IV-5. 447–454. 14 indexed citations
7.
Sinha, Bhaskar, et al.. (2018). MULTITEMPORAL ANALYSIS OF FOREST COVER CHANGE USING REMOTE SENSING AND GIS OF KANHA TIGER RESERVE, CENTRAL INDIA. SHILAP Revista de lepidopterología. XLII-5. 211–219. 8 indexed citations
8.
Jaiswal, Abhishek, et al.. (2018). GEOSPATIAL MULTI-CRITERIA DECISION BASED SITE SUITABILITY ANALYSIS FOR SOLID WASTE DISPOSAL USING TOPSIS ALGORITHM. SHILAP Revista de lepidopterología. IV-5. 431–438. 4 indexed citations
9.
Gupta, Prasun Kumar, et al.. (2018). ONLINE GEOPROCESSING USING MULTI-DIMENSIONAL GRIDDED DATA. SHILAP Revista de lepidopterología. IV-5. 29–36. 1 indexed citations
10.
Shankar, Hari, et al.. (2018). DEVELOPMENT OF WEBGIS BASED REAL TIME ROAD TRAFFIC INFORMATION SYSTEM. SHILAP Revista de lepidopterología. IV-5. 37–45. 2 indexed citations
11.
Sinha, Bhaskar, et al.. (2018). ASSESSING IMPACTS OF CLIMATE CHANGE ON TEAK AND SAL LANDSCAPE USING MODIS TIME SERIES DATA. SHILAP Revista de lepidopterología. XLII-5. 305–313. 3 indexed citations
12.
Saran, S., et al.. (2018). INTEROPERABLE MODEL FOR BIORESOURCE DISTRIBUTED DATABASES. SHILAP Revista de lepidopterología. XLII-5. 791–800. 1 indexed citations
13.
Saran, S., et al.. (2018). FUSION OF HYPERSPECTRAL AND MULTISPECTRAL IMAGERY WITH REGRESSION KRIGING AND THE LULU OPERATORS; A COMPARISON. SHILAP Revista de lepidopterología. XLII-5. 583–588. 3 indexed citations
14.
Srivastava, Ashutosh, et al.. (2018). APPLICATION OF VARIOUS OPEN SOURCE VISUALIZATION TOOLS FOR EFFECTIVE MINING OF INFORMATION FROM GEOSPATIAL PETROLEUM DATA. SHILAP Revista de lepidopterología. XLII-5. 167–174. 1 indexed citations
15.
Sinha, Satish, et al.. (2015). Markov random field-based method for super-resolution mapping of forest encroachment from remotely sensed ASTER image. Geocarto International. 31(4). 428–445. 10 indexed citations
16.
Saran, S., et al.. (2014). Geospatial Modelling Approach for Interlinking of Rivers: A Case Study of Vamsadhara and Nagavali River Systems in Srikakulam, Andhra Pradesh. ˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences. XL-8. 127–132. 2 indexed citations
17.
Kumar, Kavisha & S. Saran. (2014). Web based geoprocessing tool for coverage data handling. ˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences. XL-8. 1139–1143. 1 indexed citations
18.
Yang, Xueqing, S. P. S. Kushwaha, S. Saran, Jianchu Xu, & P. S. Roy. (2013). Maxent modeling for predicting the potential distribution of medicinal plant, Justicia adhatoda L. in Lesser Himalayan foothills. Ecological Engineering. 51. 83–87. 523 indexed citations breakdown →
19.
Saran, S., G. Sterk, P.J. van Oevelen, & V. K. Dadhwal. (2011). Potential of ASAR-ENVISAT for Estimating Near Surface Soil Moisture in a Sloping Terrain of a Himalayan Watershed. Journal of the Indian Society of Remote Sensing. 40(3). 541–550. 1 indexed citations
20.
Roy, Priyom, et al.. (2004). GML based model of Indian NSDE format for geo spatial data interoperability. University of Twente Research Information. 1–20. 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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