Matt Aitkenhead

3.8k total citations
73 papers, 1.5k citations indexed

About

Matt Aitkenhead is a scholar working on Environmental Engineering, Ecology and Artificial Intelligence. According to data from OpenAlex, Matt Aitkenhead has authored 73 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Environmental Engineering, 23 papers in Ecology and 16 papers in Artificial Intelligence. Recurrent topics in Matt Aitkenhead's work include Soil Geostatistics and Mapping (21 papers), Remote Sensing in Agriculture (12 papers) and Geochemistry and Geologic Mapping (11 papers). Matt Aitkenhead is often cited by papers focused on Soil Geostatistics and Mapping (21 papers), Remote Sensing in Agriculture (12 papers) and Geochemistry and Geologic Mapping (11 papers). Matt Aitkenhead collaborates with scholars based in United Kingdom, France and Australia. Matt Aitkenhead's co-authors include Malcolm Coull, A.J.S. McDonald, Inge Aalders, H. I. J. Black, Norval J. C. Strachan, Chris Mullins, W. Towers, G. Hudson, Richard P. Smart and E. A. Fitzpatrick and has published in prestigious journals such as PLoS ONE, The Science of The Total Environment and Remote Sensing of Environment.

In The Last Decade

Matt Aitkenhead

70 papers receiving 1.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Matt Aitkenhead United Kingdom 24 434 385 365 284 281 73 1.5k
Bappa Das India 25 459 1.1× 372 1.0× 733 2.0× 402 1.4× 319 1.1× 114 1.9k
Qi Yang China 19 617 1.4× 506 1.3× 552 1.5× 265 0.9× 322 1.1× 58 1.5k
Shahbaz Khan Australia 22 407 0.9× 600 1.6× 430 1.2× 409 1.4× 366 1.3× 102 2.3k
Alfonso García-Ferrer Spain 23 648 1.5× 936 2.4× 364 1.0× 353 1.2× 148 0.5× 47 1.8k
Zhigang Sun China 25 844 1.9× 601 1.6× 503 1.4× 693 2.4× 405 1.4× 99 2.0k
Sami Khanal United States 15 557 1.3× 394 1.0× 565 1.5× 229 0.8× 140 0.5× 39 1.6k
Montserrat Jurado-Expósito Spain 24 945 2.2× 577 1.5× 809 2.2× 308 1.1× 185 0.7× 50 1.8k
Aimrun Wayayok Malaysia 22 360 0.8× 448 1.2× 689 1.9× 401 1.4× 357 1.3× 145 1.8k

Countries citing papers authored by Matt Aitkenhead

Since Specialization
Citations

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

Fields of papers citing papers by Matt Aitkenhead

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matt Aitkenhead

This figure shows the co-authorship network connecting the top 25 collaborators of Matt Aitkenhead. A scholar is included among the top collaborators of Matt Aitkenhead 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 Matt Aitkenhead. Matt Aitkenhead 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.
Minasny, Budiman, José Padarian, Federico Maggi, et al.. (2025). Digital mapping of peat thickness and carbon stock of global peatlands. CATENA. 258. 109243–109243. 1 indexed citations
2.
Coull, Malcolm, D. Gary Miller, Thomas C. Parker, et al.. (2024). A deep learning approach for high‐resolution mapping of Scottish peatland degradation. European Journal of Soil Science. 75(4). 4 indexed citations
3.
Moran, Dominic, et al.. (2023). Why do French winegrowers adopt soil organic carbon sequestration practices? Understanding motivations and barriers. Frontiers in Sustainable Food Systems. 6. 5 indexed citations
4.
Davis, Natalie, Andrew Jarvis, Matt Aitkenhead, & Gary Polhill. (2020). Trajectories toward maximum power and inequality in resource distribution networks. PLoS ONE. 15(3). e0229956–e0229956. 2 indexed citations
5.
Aitkenhead, Matt & Malcolm Coull. (2019). Digital mapping of soil ecosystem services in Scotland using neural networks and relationship modelling—Part 1: Mapping of soil classes. Soil Use and Management. 35(2). 205–216. 11 indexed citations
6.
Artz, Rebekka, Patricia Bruneau, Andrea J. Britton, et al.. (2018). The potential for modelling peatland habitat condition in Scotland using long-term MODIS data. The Science of The Total Environment. 660. 429–442. 17 indexed citations
7.
McCallum, Susan, H. G. Jones, Matt Aitkenhead, et al.. (2017). A method for automatic segmentation and splitting of hyperspectral images of raspberry plants collected in field conditions. Plant Methods. 13(1). 74–74. 29 indexed citations
8.
Palacio, Sara, Matt Aitkenhead, Adrián Escudero, et al.. (2014). Gypsophile Chemistry Unveiled: Fourier Transform Infrared (FTIR) Spectroscopy Provides New Insight into Plant Adaptations to Gypsum Soils. PLoS ONE. 9(9). e107285–e107285. 85 indexed citations
9.
Aitkenhead, Matt, David Donnelly, Lee‐Ann Sutherland, et al.. (2014). Predicting Scottish topsoil organic matter content from colour and environmental factors. European Journal of Soil Science. 66(1). 112–120. 23 indexed citations
10.
Aitkenhead, Matt, S. M. Rhind, Zulin Zhang, C. E. Kyle, & Malcolm Coull. (2013). Neural network integration of field observations for soil endocrine disruptor characterisation. The Science of The Total Environment. 468-469. 240–248. 5 indexed citations
11.
Cresser, Malcolm S., Matt Aitkenhead, & Ishaq Ahmad Mian. (2008). A reappraisal of the terrestrial nitrogen cycle: What can we learn by extracting concepts from Gaia theory?. The Science of The Total Environment. 400(1-3). 344–355. 5 indexed citations
12.
13.
Aitkenhead, Matt & Inge Aalders. (2008). Predicting land cover using GIS, Bayesian and evolutionary algorithm methods. Journal of Environmental Management. 90(1). 236–250. 54 indexed citations
14.
Aitkenhead, Matt, et al.. (2007). Remote sensing‐based neural network mapping of tsunami damage in Aceh, Indonesia. Disasters. 31(3). 217–226. 11 indexed citations
15.
Aitkenhead, Matt, et al.. (2007). Improving Land-cover Classification Using Recognition Threshold Neural Networks. Photogrammetric Engineering & Remote Sensing. 73(4). 413–421. 11 indexed citations
16.
Aitkenhead‐Peterson, Jacqueline A., Richard P. Smart, Matt Aitkenhead, Malcolm S. Cresser, & William H. McDowell. (2007). Spatial and temporal variation of dissolved organic carbon export from gauged and ungauged watersheds of Dee Valley, Scotland: Effect of land cover and C:N. Water Resources Research. 43(5). 37 indexed citations
17.
Aitkenhead, Matt & A.J.S. McDonald. (2006). The state of play in machine/environment interactions. Artificial Intelligence Review. 25(3). 247–276. 7 indexed citations
18.
Aitkenhead, Matt & A.J.S. McDonald. (2004). Complex environments, complex behaviour. Engineering Applications of Artificial Intelligence. 17(6). 611–621. 1 indexed citations
19.
Aitkenhead, Matt, et al.. (2004). Using neural networks to predict spatial structure in ecological systems. Ecological Modelling. 179(3). 393–403. 13 indexed citations
20.
Standing, Dominic, et al.. (2003). The emergence of primary strategies in evolving virtual-plant populations. Evolutionary ecology research. 5(7). 1067–1081. 17 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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