Eija Honkavaara

Environmental Engineering · 2013–2018

A researcher in the Science corpus: 5 papers; trusts 4 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Environmental Engineering — 52 citations into it; #3,700 of 5,479 by trust here, #1,223 by citations
• Ecology — 35 citations into it; #6,633 of 10,717 by trust here, #3,054 by citations
• Insect Science — 21 citations into it
• Nature and Landscape Conservation — 18 citations into it
• Computer Vision and Pattern Recognition — 9 citations into it
• Atmospheric Science — 7 citations into it
• Media Technology — 7 citations into it

Whom Eija Honkavaara trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. S. Kotsiantis
2. Thomas Blaschke
3. Pablo J. Zarco-Tejada
4. Erik Næsset
5. Juha Hyyppä
6. Jose A. Jiménez-Berni
7. Geert J. Verhoeven
8. David E. Goldberg
9. Anttoni Jaakkola
10. Andrea S. Laliberte

Who trusts Eija Honkavaara overall

1. Mary Bernadette Stuart
2. Helge Aasen
3. Olli Nevalainen
4. Andrew John Samuel McGonigle
5. Aleixandre Verger
6. Jon Raffe Willmott
7. Telmo Adão

Papers from Eija Honkavaara's perspective

Ordered by how strongly the researchers Eija Honkavaara trusts endorse each paper. Same corpus, a different order for every researcher.

1. Thermal and Narrowband Multispectral Remote Sensing for Vegetation Monitoring From an Unmanned Aerial Vehicle (IEEE Transactions on Geoscience and Remote Sensing)
2. Modeling the World from Internet Photo Collections (International Journal of Computer Vision)
3. Object based image analysis for remote sensing
4. Processing and Assessment of Spectrometric, Stereoscopic Imagery Collected Using a Lightweight UAV Spectral Camera for Precision Agriculture (Remote Sensing)
5. High spatial resolution three-dimensional mapping of vegetation spectral dynamics using computer vision
6. The Utility of Image-Based Point Clouds for Forest Inventory: A Comparison with Airborne Laser Scanning
7. NASA Goddard's LiDAR, Hyperspectral and Thermal (G-LiHT) Airborne Imager (Remote Sensing)
8. Lightweight unmanned aerial vehicles will revolutionize spatial ecology
9. Using UAV-Based Photogrammetry and Hyperspectral Imaging for Mapping Bark Beetle Damage at Tree-Level (Remote Sensing)
10. Three decades of hyperspectral remote sensing of the Earth: a personal view.

Their papers

• Quantitative Remote Sensing at Ultra-High Resolution with UAV Spectroscopy: A Review of Sensor Technology, Measurement Procedures, and Data Correction Workflows (2018) — 557 citations
• Individual Tree Detection and Classification with UAV-Based Photogrammetric Point Clouds and Hyperspectral Imaging (2017) — 404 citations
• Using UAV-Based Photogrammetry and Hyperspectral Imaging for Mapping Bark Beetle Damage at Tree-Level (2015) — 367 citations
• Performance of dense digital surface models based on image matching in the estimation of plot-level forest variables (2013) — 132 citations
• Processing and Assessment of Spectrometric, Stereoscopic Imagery Collected Using a Lightweight UAV Spectral Camera for Precision Agriculture (2013) — 491 citations