Roope Näsi

2.1k total citations
47 papers, 1.5k citations indexed

About

Roope Näsi is a scholar working on Ecology, Environmental Engineering and Geology. According to data from OpenAlex, Roope Näsi has authored 47 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Ecology, 31 papers in Environmental Engineering and 14 papers in Geology. Recurrent topics in Roope Näsi's work include Remote Sensing and LiDAR Applications (30 papers), Remote Sensing in Agriculture (29 papers) and 3D Surveying and Cultural Heritage (14 papers). Roope Näsi is often cited by papers focused on Remote Sensing and LiDAR Applications (30 papers), Remote Sensing in Agriculture (29 papers) and 3D Surveying and Cultural Heritage (14 papers). Roope Näsi collaborates with scholars based in Finland, Brazil and United Kingdom. Roope Näsi's co-authors include Eija Honkavaara, Teemu Hakala, Niko Viljanen, Markus Holopainen, Jere Kaivosoja, Päivi Lyytikäinen‐Saarenmaa, Lauri Markelin, Tuula Kantola, Minna Blomqvist and Oiva Niemeläinen and has published in prestigious journals such as SHILAP Revista de lepidopterología, Remote Sensing of Environment and Sensors.

In The Last Decade

Roope Näsi

46 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Roope Näsi Finland 18 1.0k 826 317 306 192 47 1.5k
Niko Viljanen Finland 15 1.1k 1.1× 988 1.2× 335 1.1× 290 0.9× 247 1.3× 30 1.6k
Grant D. Pearse New Zealand 18 653 0.6× 776 0.9× 221 0.7× 220 0.7× 164 0.9× 32 1.1k
Jan van Aardt United States 23 1.2k 1.2× 1.1k 1.3× 442 1.4× 409 1.3× 259 1.3× 107 2.1k
Huaguo Huang China 23 1.1k 1.1× 1.0k 1.2× 707 2.2× 319 1.0× 74 0.4× 134 1.8k
Antônio Maria Garcia Tommaselli Brazil 23 841 0.8× 1.0k 1.2× 223 0.7× 206 0.7× 520 2.7× 148 1.9k
Jonathan P. Dash New Zealand 17 586 0.6× 699 0.8× 240 0.8× 180 0.6× 120 0.6× 24 1.1k
Rachel Gaulton United Kingdom 24 1.1k 1.0× 1.2k 1.4× 549 1.7× 277 0.9× 189 1.0× 49 1.9k
Päivi Lyytikäinen‐Saarenmaa Finland 22 884 0.9× 518 0.6× 408 1.3× 263 0.9× 103 0.5× 56 1.4k
Yuchu Qin China 19 526 0.5× 573 0.7× 336 1.1× 100 0.3× 116 0.6× 31 1.2k
Jonathan P. Dandois United States 10 764 0.8× 1.1k 1.3× 333 1.1× 103 0.3× 507 2.6× 12 1.4k

Countries citing papers authored by Roope Näsi

Since Specialization
Citations

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

Fields of papers citing papers by Roope Näsi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Roope Näsi

This figure shows the co-authorship network connecting the top 25 collaborators of Roope Näsi. A scholar is included among the top collaborators of Roope Näsi 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 Roope Näsi. Roope Näsi 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.
Näsi, Roope, Eija Honkavaara, Miroslav Blaženec, et al.. (2025). Spectral signatures discrimination of Norway spruce trees under experimentally induced drought and acute thermal stress using hyperspectral imaging. Forest Ecology and Management. 586. 122692–122692. 1 indexed citations
2.
Honkavaara, Eija, Raquel Alves de Oliveira, Roope Näsi, et al.. (2024). Exploring forest changes in an Ips typographus L. outbreak area: insights from multi-temporal multispectral UAS remote sensing. European Journal of Forest Research. 143(6). 1871–1892. 2 indexed citations
3.
Peltonen‐Sainio, Pirjo, Lauri Jauhiainen, Roope Näsi, Eetu Puttonen, & Eija Honkavaara. (2024). Harmonization potential of the fragmented farmlands in Finland: The pros and cons for critical parcel characteristics. Land Use Policy. 147. 107380–107380. 1 indexed citations
4.
Oliveira, Raquel Alves de, Niko Koivumäki, Kirsi Karila, et al.. (2024). Towards scalable wide area UAS monitoring of forest disturbance using hydrogen powered airships. International Journal of Remote Sensing. 46(1). 177–204.
5.
Näsi, Roope, Hannu Mikkola, Eija Honkavaara, et al.. (2023). Can Basic Soil Quality Indicators and Topography Explain the Spatial Variability in Agricultural Fields Observed from Drone Orthomosaics?. Agronomy. 13(3). 669–669. 14 indexed citations
6.
Oliveira, Raquel Alves de, Roope Näsi, Panu Korhonen, et al.. (2023). High-precision estimation of grass quality and quantity using UAS-based VNIR and SWIR hyperspectral cameras and machine learning. Precision Agriculture. 25(1). 186–220. 13 indexed citations
7.
Näsi, Roope, et al.. (2023). A Novel Deep Multi-Image Object Detection Approach for Detecting Alien Barleys in Oat Fields Using RGB UAV Images. Remote Sensing. 15(14). 3582–3582. 6 indexed citations
8.
Junttila, Samuli, Roope Näsi, Niko Koivumäki, et al.. (2022). Multispectral Imagery Provides Benefits for Mapping Spruce Tree Decline Due to Bark Beetle Infestation When Acquired Late in the Season. Remote Sensing. 14(4). 909–909. 28 indexed citations
9.
Oliveira, Raquel Alves de, José Marcato, Roope Näsi, et al.. (2022). Silage Grass Sward Nitrogen Concentration and Dry Matter Yield Estimation Using Deep Regression and RGB Images Captured by UAV. Agronomy. 12(6). 1352–1352. 17 indexed citations
10.
Karila, Kirsi, Raquel Alves de Oliveira, Jere Kaivosoja, et al.. (2022). Estimating Grass Sward Quality and Quantity Parameters Using Drone Remote Sensing with Deep Neural Networks. Remote Sensing. 14(11). 2692–2692. 18 indexed citations
11.
Suomalainen, Juha, Raquel Alves de Oliveira, Teemu Hakala, et al.. (2021). Direct reflectance transformation methodology for drone-based hyperspectral imaging. Remote Sensing of Environment. 266. 112691–112691. 45 indexed citations
12.
Saarinen, Ninni, Lauri Markelin, Tomi Rosnell, et al.. (2019). Characterizing Seedling Stands Using Leaf-Off and Leaf-On Photogrammetric Point Clouds and Hyperspectral Imagery Acquired from Unmanned Aerial Vehicle. Forests. 10(5). 415–415. 38 indexed citations
13.
Puttonen, Eetu, Matti Lehtomäki, Paula Litkey, et al.. (2019). A Clustering Framework for Monitoring Circadian Rhythm in Structural Dynamics in Plants From Terrestrial Laser Scanning Time Series. Frontiers in Plant Science. 10. 486–486. 19 indexed citations
14.
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
15.
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
16.
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
17.
Saarinen, Ninni, Mikko Vastaranta, Roope Näsi, et al.. (2018). Assessing Biodiversity in Boreal Forests with UAV-Based Photogrammetric Point Clouds and Hyperspectral Imaging. Remote Sensing. 10(2). 338–338. 69 indexed citations
18.
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
19.
Miyoshi, Gabriela Takahashi, et al.. (2017). TIME SERIES OF IMAGES TO IMPROVE TREE SPECIES CLASSIFICATION. SHILAP Revista de lepidopterología. XLII-3/W3. 123–128. 4 indexed citations
20.
Markelin, Lauri, Eija Honkavaara, Roope Näsi, Kimmo Nurminen, & Teemu Hakala. (2014). Geometric processing workflow for vertical and oblique hyperspectral frame images collected using UAV. SHILAP Revista de lepidopterología. XL-3. 205–210. 9 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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