Kenneth Nyström

566 total citations
32 papers, 376 citations indexed

About

Kenneth Nyström is a scholar working on Nature and Landscape Conservation, Environmental Engineering and Global and Planetary Change. According to data from OpenAlex, Kenneth Nyström has authored 32 papers receiving a total of 376 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Nature and Landscape Conservation, 18 papers in Environmental Engineering and 15 papers in Global and Planetary Change. Recurrent topics in Kenneth Nyström's work include Forest ecology and management (22 papers), Remote Sensing and LiDAR Applications (18 papers) and Plant Water Relations and Carbon Dynamics (7 papers). Kenneth Nyström is often cited by papers focused on Forest ecology and management (22 papers), Remote Sensing and LiDAR Applications (18 papers) and Plant Water Relations and Carbon Dynamics (7 papers). Kenneth Nyström collaborates with scholars based in Sweden, Norway and New Zealand. Kenneth Nyström's co-authors include Göran Ståhl, Nils Fahlvik, Urban Nilsson, Håkan Olsson, K. Fredriksson, B. Galle, Sune Svanberg, Anton Grafström, Eric Agestam and Emma Holmström and has published in prestigious journals such as Forest Ecology and Management, Remote Sensing and Clinical Nutrition.

In The Last Decade

Kenneth Nyström

31 papers receiving 334 citations

Peers

Kenneth Nyström

NLC

GPC

ECOLO

John Paul McTague United States

Peter H. Wyckoff United States

G. A. Bauer United States

Thom Erdle Canada

Kathy Gray United States

Joshua J. Puhlick United States

Sally E. Dahir United States

Alexey Mikhailov Russia

Ayu Konishi Japan

M. Fabrika Slovakia

John Paul McTague United States

Kenneth Nyström

525 ×2.2

NLC

273 ×1.5

GPC

269 ×1.5

40 ×0.5

ECOLO

30 ×0.5

Citations per year, relative to Kenneth Nyström Kenneth Nyström (= 1×) peers John Paul McTague

Countries citing papers authored by Kenneth Nyström

Since Specialization

Citations

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

Fields of papers citing papers by Kenneth Nyström

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kenneth Nyström

This figure shows the co-authorship network connecting the top 25 collaborators of Kenneth Nyström. A scholar is included among the top collaborators of Kenneth Nyström 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 Kenneth Nyström. Kenneth Nyström is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Ståhl, Göran, Terje Gobakken, Svetlana Saarela, et al.. (2024). Why ecosystem characteristics predicted from remotely sensed data are unbiased and biased at the same time – and how this affects applications. Forest Ecosystems. 11. 100164–100164. 10 indexed citations

Nyström, Kenneth, et al.. (2023). Stem volume and above ground biomass models for Sitka spruce (Picea sitchensis (Bong.) Carr.) in Iceland. 36. 69–80. 1 indexed citations

Nyström, Kenneth, et al.. (2023). Mapping site index in coniferous forests using bi-temporal airborne laser scanning data and field data from the Swedish national forest inventory. Forest Ecology and Management. 547. 121395–121395. 11 indexed citations

Nyström, Kenneth, et al.. (2022). Importance of Calibration for Improving the Efficiency of Data Assimilation for Predicting Forest Characteristics. Remote Sensing. 14(18). 4627–4627. 7 indexed citations

Nyström, Kenneth, et al.. (2021). Updating of forest stand data by using recent digital photogrammetry in combination with older airborne laser scanning data. Scandinavian Journal of Forest Research. 36(5). 401–407. 5 indexed citations

Olsson, Håkan, et al.. (2021). Data Assimilation of Growing Stock Volume Using a Sequence of Remote Sensing Data from Different Sensors. Canadian Journal of Remote Sensing. 48(2). 127–143. 9 indexed citations

Wallerman, Jörgen, Kenneth Nyström, Mats Nilsson, et al.. (2020). Nation-Wide Mapping of Tree Growth using Repeated Airborne Laser Scanning. 4822–4825. 1 indexed citations

Karlsson, Bo, et al.. (2018). Effects of phenotypic selection on height-diameter ratio of Norway spruce and Scots pine in Sweden. Silva Fennica. 52(2). 4 indexed citations

Persson, Henrik, Mattias Nyström, Kenneth Nyström, et al.. (2017). Improved Prediction of Forest Variables Using Data Assimilation of Interferometric Synthetic Aperture Radar Data. Canadian Journal of Remote Sensing. 43(4). 374–383. 15 indexed citations

10.

Nilsson, Urban, et al.. (2017). Modeling early height growth in trials of genetically improved Norway spruce and Scots pine in southern Sweden. Silva Fennica. 51(3). 10 indexed citations

11.

Cronie, Ottmar, Kenneth Nyström, & Jun Yu. (2013). Spatiotemporal Modeling of Swedish Scots Pine Stands. Forest Science. 59(5). 505–516. 5 indexed citations

12.

Nyström, Kenneth, et al.. (2012). Assessment of bias due to random measurement errors in stem volume growth estimation by the Swedish National Forest Inventory. Scandinavian Journal of Forest Research. 28(2). 174–183. 5 indexed citations

13.

Fahlvik, Nils & Kenneth Nyström. (2006). Models for predicting individual tree height increment and tree diameter in young stands in southern Sweden. Scandinavian Journal of Forest Research. 21(S7). 16–28. 23 indexed citations

14.

Fahlvik, Nils, Eric Agestam, Urban Nilsson, & Kenneth Nyström. (2005). Simulating the influence of initial stand structure on the development of young mixtures of Norway spruce and birch. Forest Ecology and Management. 213(1-3). 297–311. 30 indexed citations

15.

Nyström, Kenneth & Göran Ståhl. (2001). Forecasting probability distributions of forest yield allowing for a Bayesian approach to management planning. Silva Fennica. 35(2). 15 indexed citations

16.

Nyström, Kenneth. (2000). Funktioner för att skatta höjdtillväxten i ungskog. ACS Chemical Biology. 16(12). 2798–2807. 13 indexed citations

17.

Fridman, Jonas, Hampus Holmström, Kenneth Nyström, et al.. (1999). Sveriges skogsmarksarealer enligt internationella ägoslagsdefinitioner. Epsilon Open Archive (Sveriges lantbruksuniversitet biblioteket (Swedish University of Agricultural Sciences)). 2 indexed citations

18.

Nyström, Kenneth & P. Gemmel. (1988). Models for predicting height and diameter of individual trees in young Picea abies (L) karst. stands. Scandinavian Journal of Forest Research. 3(1-4). 213–228. 5 indexed citations

19.

Fredriksson, K., B. Galle, Kenneth Nyström, & S. Svanberg. (1979). Lidar system applied in atmospheric pollution monitoring. Applied Optics. 18(17). 2998–2998. 18 indexed citations

20.

Lundberg, H., et al.. (1979). Hyperfine-structure study in the P sequence of²³Na using quantum-beam spectroscopy. Journal of Physics B Atomic and Molecular Physics. 12(16). 2645–2654. 8 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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