Aditya Singh

4.8k total citations
141 papers, 3.3k citations indexed

About

Aditya Singh is a scholar working on Ecology, Plant Science and Environmental Engineering. According to data from OpenAlex, Aditya Singh has authored 141 papers receiving a total of 3.3k indexed citations (citations by other indexed papers that have themselves been cited), including 55 papers in Ecology, 48 papers in Plant Science and 21 papers in Environmental Engineering. Recurrent topics in Aditya Singh's work include Remote Sensing in Agriculture (38 papers), Species Distribution and Climate Change (20 papers) and Remote Sensing and LiDAR Applications (14 papers). Aditya Singh is often cited by papers focused on Remote Sensing in Agriculture (38 papers), Species Distribution and Climate Change (20 papers) and Remote Sensing and LiDAR Applications (14 papers). Aditya Singh collaborates with scholars based in United States, India and United Kingdom. Aditya Singh's co-authors include Philip A. Townsend, Clayton C. Kingdon, Shawn Serbin, Brenden E. McNeil, John J. Couture, Jeannine Cavender‐Bares, S. L. Jat, C.M. Parihar, M.L. Jat and Eric L. Kruger and has published in prestigious journals such as SHILAP Revista de lepidopterología, The Science of The Total Environment and Remote Sensing of Environment.

In The Last Decade

Aditya Singh

128 papers receiving 3.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Aditya Singh United States 31 1.6k 1.1k 839 573 561 141 3.3k
Yue Shi China 26 1.4k 0.8× 1.2k 1.0× 489 0.6× 424 0.7× 130 0.2× 70 3.0k
J. H. Everitt United States 36 3.1k 1.9× 1.2k 1.1× 939 1.1× 1.1k 1.9× 555 1.0× 206 4.4k
Allard de Wit Netherlands 28 2.1k 1.3× 1.4k 1.3× 1.9k 2.3× 886 1.5× 243 0.4× 86 4.1k
Shawn Serbin United States 39 2.7k 1.6× 2.2k 2.0× 2.5k 2.9× 819 1.4× 581 1.0× 114 4.9k
Michael S. Watt New Zealand 37 1.4k 0.9× 1.1k 1.0× 1.3k 1.5× 1.3k 2.2× 265 0.5× 209 4.5k
Ilkka Leinonen United Kingdom 30 1.2k 0.7× 1.1k 1.0× 979 1.2× 586 1.0× 155 0.3× 75 3.2k
Kensuke Kawamura Japan 26 1.0k 0.6× 536 0.5× 518 0.6× 521 0.9× 115 0.2× 104 2.4k
Wouter H. Maes Belgium 28 1.0k 0.6× 1.2k 1.1× 967 1.2× 595 1.0× 83 0.1× 51 3.0k
Mirco Boschetti Italy 39 3.0k 1.9× 2.0k 1.8× 1.7k 2.0× 1.4k 2.4× 194 0.3× 156 5.1k
Rocío Hernández‐Clemente Spain 22 1.7k 1.0× 984 0.9× 1.1k 1.3× 635 1.1× 263 0.5× 54 2.7k

Countries citing papers authored by Aditya Singh

Since Specialization
Citations

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

Fields of papers citing papers by Aditya Singh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Aditya Singh

This figure shows the co-authorship network connecting the top 25 collaborators of Aditya Singh. A scholar is included among the top collaborators of Aditya Singh 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 Aditya Singh. Aditya Singh 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.
Teshome, Fitsum T., Haimanote K. Bayabil, Bruce Schaffer, et al.. (2024). Simulating soil hydrologic dynamics using crop growth and machine learning models. Computers and Electronics in Agriculture. 224. 109186–109186. 5 indexed citations
2.
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Zheng, Ting, et al.. (2024). Variability in Forest Plant Traits Along the Western Ghats of India and Their Environmental Drivers at Different Resolutions. Journal of Geophysical Research Biogeosciences. 129(3). 2 indexed citations
5.
Singh, Aditya, et al.. (2023). Yield and plant height predictions of irrigated maize through unmanned aerial vehicle in North Florida. Computers and Electronics in Agriculture. 215. 108374–108374. 14 indexed citations
6.
Teshome, Fitsum T., Haimanote K. Bayabil, Gerrit Hoogenboom, et al.. (2023). Unmanned aerial vehicle (UAV) imaging and machine learning applications for plant phenotyping. Computers and Electronics in Agriculture. 212. 108064–108064. 49 indexed citations
7.
Graves, Sarah, Sergio Marconi, Ben Weinstein, et al.. (2023). Data science competition for cross-site individual tree species identification from airborne remote sensing data. PeerJ. 11. e16578–e16578. 2 indexed citations
8.
Fraisse, Clyde W., Yiannis Ampatzidis, Sandra M. Guzmán, et al.. (2022). Artificial Intelligence (AI) for Crop Yield Forecasting. SHILAP Revista de lepidopterología. 2022(2). 1 indexed citations
9.
Weinstein, Ben, Sarah Graves, Sergio Marconi, et al.. (2021). A benchmark dataset for canopy crown detection and delineation in co-registered airborne RGB, LiDAR and hyperspectral imagery from the National Ecological Observation Network. PLoS Computational Biology. 17(7). e1009180–e1009180. 28 indexed citations
10.
Singh, Aditya, et al.. (2020). Effect of planting pattern of intercropped legumes (Soybean, groundnut and mungbean) on yield and nutrient uptake of legumes from the intercropping system at mid altitude of Meghalaya. Journal of Pharmacognosy and Phytochemistry. 9(2). 2137–2140. 3 indexed citations
11.
Sahu, Chandan, et al.. (2018). GREEN AUDIT - A HOLISTIC APPROACH FOR SUSTAINABLEDEVELOPMENT. 34(2). 2115–2124.
12.
Kolka, Randall K., Brian R. Sturtevant, Jessica Miesel, et al.. (2017). Emissions of forest floor and mineral soil carbon, nitrogen and mercury pools and relationships with fire severity for the Pagami Creek Fire in the Boreal Forest of northern Minnesota. International Journal of Wildland Fire. 26(4). 296–305. 21 indexed citations
13.
Hooda, K. S., Vishal Singh, Vinod Kumar, et al.. (2017). Multi-environment field testing to identify stable sources of resistance to charcoal rot (Macrophomina phaseolina) disease in tropical maize germplasm. Maydica. 62(1). 7. 2 indexed citations
14.
Cavender‐Bares, Jeannine, José Eduardo Meireles, John J. Couture, et al.. (2016). Associations of Leaf Spectra with Genetic and Phylogenetic Variation in Oaks: Prospects for Remote Detection of Biodiversity. Remote Sensing. 8(3). 221–221. 103 indexed citations
15.
Bardhan, Sougata, et al.. (2015). Effect of topography on the distribution of tropical montane forest fragments: a predictive modelling approach.. JOURNAL OF TROPICAL FOREST SCIENCE. 27(1). 30–38. 12 indexed citations
16.
Singh, Aditya, et al.. (2015). Nutrient uptake and fertilizer-use efficiency of maize hybrids under conservation agriculture with nutrient expert based SSNM practices. Annals of Agricultural Research. 36(2). 7 indexed citations
17.
Turner, Matthew D., Bilal Butt, Aditya Singh, et al.. (2014). Variation in vegetation cover and livestock mobility needs in Sahelian West Africa. Journal of Land Use Science. 11(1). 76–95. 11 indexed citations
18.
Wolter, Peter T., et al.. (2014). Satellite-Based Management Tool for Oak Savanna Ecosystem Restoration. Journal of Fish and Wildlife Management. 5(2). 252–269. 2 indexed citations
19.
Singh, Aditya, et al.. (2012). Effect of environmental pollution on animal and human health: A review. The Indian Journal of Animal Sciences. 82(3). 11 indexed citations
20.
Singh, Aditya, et al.. (2008). Production potential prediction of maize (Zea mays) based on edaphic characters in Udaipur district of Rajasthan. The Indian Journal of Agricultural Sciences. 78(9). 776–780. 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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