Timo Tokola

4.1k total citations
116 papers, 3.3k citations indexed

About

Timo Tokola is a scholar working on Environmental Engineering, Nature and Landscape Conservation and Ecology. According to data from OpenAlex, Timo Tokola has authored 116 papers receiving a total of 3.3k indexed citations (citations by other indexed papers that have themselves been cited), including 89 papers in Environmental Engineering, 71 papers in Nature and Landscape Conservation and 48 papers in Ecology. Recurrent topics in Timo Tokola's work include Remote Sensing and LiDAR Applications (87 papers), Forest ecology and management (67 papers) and Remote Sensing in Agriculture (43 papers). Timo Tokola is often cited by papers focused on Remote Sensing and LiDAR Applications (87 papers), Forest ecology and management (67 papers) and Remote Sensing in Agriculture (43 papers). Timo Tokola collaborates with scholars based in Finland, United States and China. Timo Tokola's co-authors include Matti Maltamo, Ilkka Korpela, Jari Vauhkonen, Petteri Packalén, Olavi Luukkanen, Ping Zhou, Hans Ole Ørka, Juha Hyyppä, Jouni Kalliovirta and Zhengyang Hou and has published in prestigious journals such as SHILAP Revista de lepidopterología, Remote Sensing of Environment and IEEE Transactions on Geoscience and Remote Sensing.

In The Last Decade

Timo Tokola

113 papers receiving 3.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Timo Tokola Finland 29 2.5k 1.8k 1.5k 919 713 116 3.3k
Paul Treitz Canada 36 3.4k 1.3× 2.0k 1.2× 2.3k 1.6× 1.2k 1.3× 1.4k 1.9× 92 4.9k
L. Monika Moskal United States 29 2.4k 0.9× 1.1k 0.6× 2.0k 1.4× 443 0.5× 1.2k 1.7× 75 3.4k
Yanjun Su China 43 3.1k 1.2× 1.4k 0.8× 2.6k 1.8× 446 0.5× 1.5k 2.0× 122 5.0k
Markus Hollaus Austria 31 2.3k 0.9× 1.1k 0.6× 1.1k 0.8× 739 0.8× 637 0.9× 106 2.8k
Håkan Olsson Sweden 32 3.2k 1.3× 2.2k 1.2× 1.7k 1.2× 1.2k 1.3× 906 1.3× 93 3.9k
Mats Nilsson Sweden 21 2.4k 1.0× 1.8k 1.0× 1.3k 0.9× 912 1.0× 701 1.0× 45 2.9k
Piotr Tompalski Canada 28 2.9k 1.2× 1.6k 0.9× 1.7k 1.1× 984 1.1× 1.0k 1.4× 87 3.6k
Benoît St-Onge Canada 25 2.5k 1.0× 1.5k 0.9× 1.4k 1.0× 886 1.0× 679 1.0× 45 3.0k
Erkki Tomppo Finland 36 2.3k 0.9× 2.1k 1.2× 2.5k 1.7× 863 0.9× 1.6k 2.3× 105 4.8k
Felix Morsdorf Switzerland 37 3.5k 1.4× 2.1k 1.2× 2.5k 1.7× 991 1.1× 1.3k 1.8× 96 4.7k

Countries citing papers authored by Timo Tokola

Since Specialization
Citations

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

Fields of papers citing papers by Timo Tokola

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Timo Tokola

This figure shows the co-authorship network connecting the top 25 collaborators of Timo Tokola. A scholar is included among the top collaborators of Timo Tokola 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 Timo Tokola. Timo Tokola 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.
Palander, Teijo, Timo Tokola, Stelian Alexandru Borz, & Peter Rauch. (2024). Forest Supply Chains During Digitalization: Current Implementations and Prospects in Near Future. Current Forestry Reports. 10(3). 223–238. 4 indexed citations
2.
Heinonen, Tero, et al.. (2024). How can optimized forest management plan regulate noise levels from wind turbines?. European Journal of Forest Research. 143(5). 1513–1524.
3.
Tokola, Timo, et al.. (2024). Predicting the roadway width of forest roads by means of airborne laser scanning. International Journal of Applied Earth Observation and Geoinformation. 133. 104109–104109. 1 indexed citations
4.
Rana, Parvez, et al.. (2024). Forest landscape shield models for assessing audio-visual disturbances of wind turbines. Journal of Environmental Management. 352. 120070–120070. 2 indexed citations
5.
Tokola, Timo, et al.. (2023). Utilisation of Spatial Data in Energy Biomass Supply Chain Research—A Review. Energies. 16(2). 893–893. 4 indexed citations
6.
Malinen, Jukka, et al.. (2020). A Topographic Wetness Index for Forest Road Quality Assessment: An Application in the Lakeland Region of Finland. Forests. 11(11). 1165–1165. 8 indexed citations
7.
8.
Xu, Qing, Бо Ли, Matti Maltamo, Timo Tokola, & Zhengyang Hou. (2018). Predicting tree diameter using allometry described by non-parametric locally-estimated copulas from tree dimensions derived from airborne laser scanning. Forest Ecology and Management. 434. 205–212. 15 indexed citations
9.
Tokola, Timo, et al.. (2016). COMPARISON OF HIGH AND LOW DENSITY AIRBORNE LIDAR DATA FOR FOREST ROAD QUALITY ASSESSMENT. ISPRS annals of the photogrammetry, remote sensing and spatial information sciences. III-8. 167–172. 7 indexed citations
10.
Hou, Zhengyang, et al.. (2016). Simple approach to improving the extraction of canopy metrics from airborne laser scanning data for tropical forests. Journal of Applied Remote Sensing. 10(1). 16019–16019. 1 indexed citations
11.
Korhonen, Lauri, et al.. (2015). Tropical forest canopy cover estimation using satellite imagery and airborne lidar reference data. Silva Fennica. 49(5). 22 indexed citations
12.
Valbuena, Rubén, Petteri Packalén, Timo Tokola, & Matti Maltamo. (2014). Canonical correlation analysis for interpreting airborne laser scanning metrics along the lorenz curve of tree size inequality. BALTIC FORESTRY. 20(2). 326–332. 1 indexed citations
13.
Härkönen, Sanna, Timo Tokola, Petteri Packalén, Lauri Korhonen, & Annikki Mäkelä. (2013). Predicting forest growth based on airborne light detection and ranging data, climate data, and a simplified process-based model. Canadian Journal of Forest Research. 43(4). 364–375. 6 indexed citations
14.
Korpela, Ilkka, et al.. (2011). Variation and directional anisotropy of reflectance at the crown scale — Implications for tree species classification in digital aerial images. Remote Sensing of Environment. 115(8). 2062–2074. 54 indexed citations
15.
Mäkinen, Antti, Annika Kangas, & Timo Tokola. (2010). Identifying the Presence of Assessment Errors in Forest Inventory Data by Data Mining. Forest Science. 56(3). 301–312. 2 indexed citations
16.
Luukkanen, Olavi, et al.. (2009). Comparison of forest stand characteristics and species diversity indices under different human impacts along an altitudinal gradient. SHILAP Revista de lepidopterología. 3 indexed citations
17.
Härkönen, Sanna, Antti Mäkinen, Timo Tokola, Jussi Rasinmäki, & Jouni Kalliovirta. (2009). Evaluation of forest growth simulators with NFI permanent sample plot data from Finland. Forest Ecology and Management. 259(3). 573–582. 22 indexed citations
18.
Tokola, Timo, et al.. (2009). A GIS-based stand management system for estimating local energy wood supplies. Biomass and Bioenergy. 33(9). 1278–1288. 17 indexed citations
19.
Luukkanen, Olavi, et al.. (2007). Vegetation Dynamics and Forest Landscape Restoration in the Upper Min River Watershed, Sichuan, China. Restoration Ecology. 16(2). 348–358. 20 indexed citations
20.
Korpela, Ilkka & Timo Tokola. (2006). Potential of Aerial Image-Based Monoscopic and Multiview Single-Tree Forest Inventory: A Simulation Approach. Forest Science. 52(2). 136–147. 28 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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