Ben Somers

10.2k total citations · 1 hit paper
185 papers, 5.4k citations indexed

About

Ben Somers is a scholar working on Ecology, Global and Planetary Change and Environmental Engineering. According to data from OpenAlex, Ben Somers has authored 185 papers receiving a total of 5.4k indexed citations (citations by other indexed papers that have themselves been cited), including 111 papers in Ecology, 84 papers in Global and Planetary Change and 60 papers in Environmental Engineering. Recurrent topics in Ben Somers's work include Remote Sensing in Agriculture (107 papers), Land Use and Ecosystem Services (58 papers) and Species Distribution and Climate Change (31 papers). Ben Somers is often cited by papers focused on Remote Sensing in Agriculture (107 papers), Land Use and Ecosystem Services (58 papers) and Species Distribution and Climate Change (31 papers). Ben Somers collaborates with scholars based in Belgium, United States and Germany. Ben Somers's co-authors include Pol Coppin, Gregory P. Asner, Laurent Tits, Stephanie Delalieux, Willem W. Verstraeten, Olivier Honnay, Wanda De Keersmaecker, Stef Lhermitte, Antonio Plaza and Jeroen Degerickx and has published in prestigious journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and Environmental Science & Technology.

In The Last Decade

Ben Somers

179 papers receiving 5.3k citations

Hit Papers

Endmember variability in Spectral Mixture Analysis: A review 2011 2026 2016 2021 2011 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
Ben Somers Belgium 41 2.8k 2.0k 1.4k 1.4k 964 185 5.4k
Ruiliang Pu United States 51 4.5k 1.6× 2.9k 1.4× 1.2k 0.8× 2.8k 2.1× 1.5k 1.6× 157 7.6k
Renaud Mathieu South Africa 38 2.9k 1.0× 1.7k 0.8× 467 0.3× 1.8k 1.3× 711 0.7× 113 4.7k
George Alan Blackburn United Kingdom 37 3.3k 1.2× 2.0k 1.0× 456 0.3× 1.6k 1.2× 664 0.7× 110 5.5k
Raymond F. Kokaly United States 31 2.4k 0.9× 1.5k 0.7× 1.5k 1.0× 1.2k 0.9× 828 0.9× 99 5.5k
James E. Vogelmann United States 32 4.3k 1.5× 3.7k 1.8× 704 0.5× 2.0k 1.5× 997 1.0× 59 6.6k
Zheng Niu China 44 4.3k 1.6× 2.8k 1.4× 610 0.4× 2.7k 2.0× 1.4k 1.4× 287 7.6k
Giorgos Mountrakis United States 26 2.6k 0.9× 1.9k 0.9× 1.6k 1.1× 1.4k 1.0× 1.2k 1.2× 68 5.1k
Liangyun Liu China 41 4.2k 1.5× 3.8k 1.9× 488 0.3× 1.7k 1.2× 1.3k 1.4× 292 6.6k
Sebastian van der Linden Germany 34 2.1k 0.8× 2.2k 1.1× 1.1k 0.7× 1.4k 1.0× 870 0.9× 85 4.2k
Jadunandan Dash United Kingdom 41 4.8k 1.7× 3.2k 1.6× 407 0.3× 2.2k 1.6× 1.1k 1.2× 157 6.7k

Countries citing papers authored by Ben Somers

Since Specialization
Citations

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

Fields of papers citing papers by Ben Somers

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ben Somers

This figure shows the co-authorship network connecting the top 25 collaborators of Ben Somers. A scholar is included among the top collaborators of Ben Somers 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 Ben Somers. Ben Somers 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.
Keersmaecker, Wanda De, Stéphanie Horion, Stefan Oehmcke, et al.. (2025). Predictability of abrupt shifts in dryland ecosystem functioning. Nature Climate Change. 15(1). 86–91. 8 indexed citations
2.
Dewaelheyns, Valérie, et al.. (2024). From gardens to neighbourhoods: Characterizing the climate adaptation contribution of the garden landscape in Flanders. Urban forestry & urban greening. 102. 128588–128588. 3 indexed citations
3.
Dewaelheyns, Valérie, et al.. (2024). What can Nature-based Solutions in domestic gardens contribute to climate change adaption in Western-Europe? a systematic review. Frontiers in Environmental Science. 12. 4 indexed citations
4.
Verbist, Bruno, et al.. (2024). Wetness severity increases abrupt shifts in ecosystem functioning in arid savannas. Global Change Biology. 30(3). e17235–e17235. 6 indexed citations
5.
Oliveira, Rafael S., et al.. (2024). Estimating vegetation water content from Sentinel-1 C-band SAR data over savanna and grassland ecosystems. Environmental Research Letters. 19(3). 34019–34019. 8 indexed citations
6.
Aerts, Raf, et al.. (2024). Spatial configuration of green space matters: Associations between urban land cover and air temperature. Landscape and Urban Planning. 249. 105121–105121. 37 indexed citations
7.
Diels, Jan, et al.. (2023). Maximising runoff retention by vegetated landscape elements positioned through spatial optimisation. Landscape and Urban Planning. 243. 104968–104968. 3 indexed citations
8.
Somers, Ben, et al.. (2022). Sentinel-Based Adaptation of the Local Climate Zones Framework to a South African Context. Remote Sensing. 14(15). 3594–3594. 2 indexed citations
9.
Keersmaecker, Wanda De, et al.. (2022). Climatic legacy effects on the drought response of the Amazon rainforest. Global Change Biology. 28(19). 5808–5819. 11 indexed citations
10.
Mertens, Koen, Kurt Heungens, David Nuyttens, et al.. (2022). Ultra-High-Resolution UAV-Based Detection of Alternaria solani Infections in Potato Fields. Remote Sensing. 14(24). 6232–6232. 15 indexed citations
11.
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13.
Souverijns, Niels, Marcel Buchhorn, Stéphanie Horion, et al.. (2020). Thirty Years of Land Cover and Fraction Cover Changes over the Sudano-Sahel Using Landsat Time Series. Remote Sensing. 12(22). 3817–3817. 24 indexed citations
14.
Degerickx, Jeroen, et al.. (2020). Urban Tree Health Classification Across Tree Species by Combining Airborne Laser Scanning and Imaging Spectroscopy. Remote Sensing. 12(15). 2435–2435. 20 indexed citations
15.
Helsen, Kenny, et al.. (2019). Community assembly on extensive green roofs: Effects of dispersal‐, abiotic‐ and biotic filtering on the spontaneous species‐ and functional diversity. Journal of Vegetation Science. 30(6). 1078–1088. 12 indexed citations
16.
Somers, Ben, et al.. (2019). Remote sensing of coastal vegetation: Dealing with high species turnover by mapping multiple floristic gradients. Applied Vegetation Science. 22(4). 534–546. 5 indexed citations
17.
Ewald, Michael, Raf Aerts, Jonathan Lenoir, et al.. (2018). LiDAR derived forest structure data improves predictions of canopy N and P concentrations from imaging spectroscopy. Remote Sensing of Environment. 211. 13–25. 22 indexed citations
18.
Vranken, Liesbet, et al.. (2018). Do Looks Matter? A Case Study on Extensive Green Roofs Using Discrete Choice Experiments. Sustainability. 10(2). 309–309. 40 indexed citations
19.
Keersmaecker, Wanda De, Stef Lhermitte, Michael J. Hill, et al.. (2017). Assessment of Regional Vegetation Response to Climate Anomalies: A Case Study for Australia Using GIMMS NDVI Time Series between 1982 and 2006. Remote Sensing. 9(1). 34–34. 46 indexed citations
20.
Kimirei, Ismael A., et al.. (2016). The decline in phytoplankton biomass and prawn catches in the Rufiji-Mafia Channel, Tanzania. 15(1). 15–29. 10 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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