Niko Viljanen

2.0k total citations · 1 hit paper
30 papers, 1.6k citations indexed

About

Niko Viljanen is a scholar working on Ecology, Environmental Engineering and Geology. According to data from OpenAlex, Niko Viljanen has authored 30 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Ecology, 27 papers in Environmental Engineering and 15 papers in Geology. Recurrent topics in Niko Viljanen's work include Remote Sensing and LiDAR Applications (27 papers), Remote Sensing in Agriculture (25 papers) and 3D Surveying and Cultural Heritage (15 papers). Niko Viljanen is often cited by papers focused on Remote Sensing and LiDAR Applications (27 papers), Remote Sensing in Agriculture (25 papers) and 3D Surveying and Cultural Heritage (15 papers). Niko Viljanen collaborates with scholars based in Finland, Brazil and United Kingdom. Niko Viljanen's co-authors include Eija Honkavaara, Teemu Hakala, Roope Näsi, Markus Holopainen, Päivi Lyytikäinen‐Saarenmaa, Jere Kaivosoja, Ilkka Pölönen, Tuula Kantola, Heikki Saari and Minna Blomqvist 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

Niko Viljanen

30 papers receiving 1.6k citations

Hit Papers

Individual Tree Detection... 2017 2026 2020 2023 2017 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Individual Tree Detection and Classification with UAV-Based Photogrammetric Point Clouds and Hyperspectral Imaging
    2017 344 citations Olli Nevalainen, Eija Honkavaara et al. Remote Sensing profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Niko Viljanen Finland 15 1.1k 988 335 290 247 30 1.6k
Roope Näsi Finland 18 1.0k 0.9× 826 0.8× 317 0.9× 306 1.1× 192 0.8× 47 1.5k
Jan van Aardt United States 23 1.2k 1.1× 1.1k 1.1× 442 1.3× 409 1.4× 259 1.0× 107 2.1k
Antônio Maria Garcia Tommaselli Brazil 23 841 0.8× 1.0k 1.0× 223 0.7× 206 0.7× 520 2.1× 148 1.9k
Grant D. Pearse New Zealand 18 653 0.6× 776 0.8× 221 0.7× 220 0.8× 164 0.7× 32 1.1k
Rachel Gaulton United Kingdom 24 1.1k 1.0× 1.2k 1.2× 549 1.6× 277 1.0× 189 0.8× 49 1.9k
Huaguo Huang China 23 1.1k 1.0× 1.0k 1.0× 707 2.1× 319 1.1× 74 0.3× 134 1.8k
Jonathan P. Dandois United States 10 764 0.7× 1.1k 1.1× 333 1.0× 103 0.4× 507 2.1× 12 1.4k
Jonathan P. Dash New Zealand 17 586 0.5× 699 0.7× 240 0.7× 180 0.6× 120 0.5× 24 1.1k
Päivi Lyytikäinen‐Saarenmaa Finland 22 884 0.8× 518 0.5× 408 1.2× 263 0.9× 103 0.4× 56 1.4k
Francesca Giannetti Italy 24 723 0.7× 990 1.0× 605 1.8× 113 0.4× 186 0.8× 69 1.7k

Countries citing papers authored by Niko Viljanen

Since Specialization
Citations

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

Fields of papers citing papers by Niko Viljanen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Niko Viljanen

This figure shows the co-authorship network connecting the top 25 collaborators of Niko Viljanen. A scholar is included among the top collaborators of Niko Viljanen 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 Niko Viljanen. Niko Viljanen 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.
Yrttimaa, Tuomas, Ninni Saarinen, Ville Kankare, et al.. (2020). Multisensorial Close-Range Sensing Generates Benefits for Characterization of Managed Scots Pine (Pinus sylvestris L.) Stands. ISPRS International Journal of Geo-Information. 9(5). 309–309. 15 indexed citations
2.
Saarinen, Ninni, Ville Kankare, Tuomas Yrttimaa, et al.. (2020). Assessing the effects of thinning on stem growth allocation of individual Scots pine trees. Forest Ecology and Management. 474. 118344–118344. 37 indexed citations
3.
Oliveira, Raquel Alves de, Roope Näsi, Oiva Niemeläinen, et al.. (2020). Machine learning estimators for the quantity and quality of grass swards used for silage production using drone-based imaging spectrometry and photogrammetry. Remote Sensing of Environment. 246. 111830–111830. 74 indexed citations
4.
Oliveira, Raquel Alves de, Roope Näsi, Oiva Niemeläinen, et al.. (2019). ASSESSMENT OF RGB AND HYPERSPECTRAL UAV REMOTE SENSING FOR GRASS QUANTITY AND QUALITY ESTIMATION. SHILAP Revista de lepidopterología. XLII-2/W13. 489–494. 8 indexed citations
5.
Hakala, Teemu, Lauri Markelin, Eija Honkavaara, et al.. (2018). Direct Reflectance Measurements from Drones: Sensor Absolute Radiometric Calibration and System Tests for Forest Reflectance Characterization. Sensors. 18(5). 1417–1417. 62 indexed citations
6.
Viljanen, Niko, Eija Honkavaara, Roope Näsi, et al.. (2018). A Novel Machine Learning Method for Estimating Biomass of Grass Swards Using a Photogrammetric Canopy Height Model, Images and Vegetation Indices Captured by a Drone. Agriculture. 8(5). 70–70. 149 indexed citations
7.
Markelin, Lauri, Juha Suomalainen, Raquel Alves de Oliveira, et al.. (2018). METHODOLOGY FOR DIRECT REFLECTANCE MEASUREMENT FROM A DRONE: SYSTEM DESCRIPTION, RADIOMETRIC CALIBRATION AND LATEST RESULTS. SHILAP Revista de lepidopterología. XLII-1. 283–288. 3 indexed citations
8.
Suomalainen, Juha, Teemu Hakala, Raquel Alves de Oliveira, et al.. (2018). A Novel Tilt Correction Technique for Irradiance Sensors and Spectrometers On-Board Unmanned Aerial Vehicles. Remote Sensing. 10(12). 2068–2068. 26 indexed citations
9.
Näsi, Roope, Niko Viljanen, Jere Kaivosoja, et al.. (2018). Estimating Biomass and Nitrogen Amount of Barley and Grass Using UAV and Aircraft Based Spectral and Photogrammetric 3D Features. Remote Sensing. 10(7). 1082–1082. 130 indexed citations
10.
Kaivosoja, Jere, Roope Näsi, Teemu Hakala, Niko Viljanen, & Eija Honkavaara. (2017). Applying Different Remote Sensing Data to Determine Relative Biomass Estimations of Cereals for Precision Fertilization Task Generation. Jukuri (Luonnonvarakeskus Tietopalvelu). 670–680. 4 indexed citations
11.
Nevalainen, Olli, Eija Honkavaara, Sakari Tuominen, et al.. (2017). Individual Tree Detection and Classification with UAV-Based Photogrammetric Point Clouds and Hyperspectral Imaging. Remote Sensing. 9(3). 185–185. 344 indexed citations breakdown →
12.
Tuominen, Sakari, Eija Honkavaara, Ilkka Pölönen, et al.. (2017). Hyperspectral UAV-imagery and photogrammetric canopy height model in estimating forest stand variables. Silva Fennica. 51(5). 25 indexed citations
13.
Markelin, Lauri, Eija Honkavaara, Roope Näsi, et al.. (2017). RADIOMETRIC CORRECTION OF MULTITEMPORAL HYPERSPECTRAL UAS IMAGE MOSAICS OF SEEDLING STANDS. SHILAP Revista de lepidopterología. XLII-3/W3. 113–118. 2 indexed citations
14.
Tuominen, Sakari, Roope Näsi, Eija Honkavaara, et al.. (2017). TREE SPECIES RECOGNITION IN SPECIES RICH AREA USING UAV-BORNE HYPERSPECTRAL IMAGERY AND STEREO-PHOTOGRAMMETRIC POINT CLOUD. SHILAP Revista de lepidopterología. XLII-3/W3. 185–194. 5 indexed citations
15.
Näsi, Roope, Eija Honkavaara, Sakari Tuominen, et al.. (2016). UAS BASED TREE SPECIES IDENTIFICATION USING THE NOVEL FPI BASED HYPERSPECTRAL CAMERAS IN VISIBLE, NIR AND SWIR SPECTRAL RANGES. ˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences. XLI-B1. 1143–1148. 3 indexed citations
16.
Honkavaara, Eija, Teemu Hakala, Olli Nevalainen, et al.. (2016). GEOMETRIC AND REFLECTANCE SIGNATURE CHARACTERIZATION OF COMPLEX CANOPIES USING HYPERSPECTRAL STEREOSCOPIC IMAGES FROM UAV AND TERRESTRIAL PLATFORMS. SHILAP Revista de lepidopterología. XLI-B7. 77–82. 5 indexed citations
17.
Honkavaara, Eija, Ilkka Pölönen, Heikki Saari, et al.. (2016). Remote Sensing of 3-D Geometry and Surface Moisture of a Peat Production Area Using Hyperspectral Frame Cameras in Visible to Short-Wave Infrared Spectral Ranges Onboard a Small Unmanned Airborne Vehicle (UAV). IEEE Transactions on Geoscience and Remote Sensing. 54(9). 5440–5454. 73 indexed citations
18.
Nevalainen, Olli, Eija Honkavaara, Teemu Hakala, et al.. (2016). Close-range environmental remote sensing with 3D hyperspectral technologies. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 10005. 1000503–1000503. 1 indexed citations
19.
Honkavaara, Eija, Teemu Hakala, Olli Nevalainen, et al.. (2016). GEOMETRIC AND REFLECTANCE SIGNATURE CHARACTERIZATION OF COMPLEX CANOPIES USING HYPERSPECTRAL STEREOSCOPIC IMAGES FROM UAV AND TERRESTRIAL PLATFORMS. ˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences. XLI-B7. 77–82. 4 indexed citations
20.
Honkavaara, Eija, Teemu Hakala, Lauri Markelin, et al.. (2014). Autonomous hyperspectral UAS photogrammetry for environmental monitoring applications. SHILAP Revista de lepidopterología. XL-1. 155–159. 12 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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