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Mikko Kukkonen
Observed names:
Kukkonen, Mikko,
M. Kukkonen,
Mikko Kukkonen1
Institution:
Natural Resources Institute Finland
Observed institutions:
National Institute of Standards and Technology,
University of Eastern Finland,
University of Colorado Boulder,
Natural Resources Institute Finland,
Rice University,
Colorado State University
show all 6
ORCID:
0000-0003-4206-1680
Observed ORCID:
0000-0003-4206-1680
OpenAlex ID:
A5042201473
Multispectral Airborne LiDAR Data in the Prediction of Boreal Tree Species Composition
2019
·
Mikko Kukkonen
, Matti Maltamo
, et al.
·
IEEE Transactions on Geoscience and Remote Sensing
·
70
Assessing biodiversity using forest structure indicators based on airborne laser scanning data
2023
·
Janne Toivonen
, Annika Kangas
, et al.
·
Forest Ecology and Management
·
68
Forest inventories for small areas using drone imagery without in-situ field measurements
2019
·
Eetu Kotivuori
, Mikko Kukkonen
, et al.
·
Remote Sensing of Environment
·
46
PDF
Comparison of multispectral airborne laser scanning and stereo matching of aerial images as a single sensor solution to forest inventories by tree species
2019
·
Mikko Kukkonen
, Matti Maltamo
, et al.
·
Remote Sensing of Environment
·
45
Assessing the performance of aerial image point cloud and spectral metrics in predicting boreal forest canopy cover
2017
·
M. Melin
, L. Korhonen
, et al.
·
ISPRS Journal of Photogrammetry and Remote Sensing
·
38
Image matching as a data source for forest inventory – Comparison of Semi-Global Matching and Next-Generation Automatic Terrain Extraction algorithms in a typical managed boreal forest environment
2017
·
M. Kukkonen
, M. Maltamo
, et al.
·
International Journal of Applied Earth Observation and Geoinformation
·
23
Prediction of forest canopy fuel parameters in managed boreal forests using multispectral and unispectral airborne laser scanning data and aerial images
2020
·
Matti Maltamo
, J. Räty
, et al.
·
European Journal of Remote Sensing
·
21
PDF
Fusion of crown and trunk detections from airborne UAS based laser scanning for small area forest inventories
2021
·
Mikko Kukkonen
, Matti Maltamo
, et al.
·
International Journal of Applied Earth Observation and Geoinformation
·
20
PDF
A method for vertical adjustment of digital aerial photogrammetry data by using a high-quality digital terrain model
2019
·
Daniela Ali-Sisto
, Ranjith Gopalakrishnan
, et al.
·
International Journal of Applied Earth Observation and Geoinformation
·
16
PDF
Combination of Lidar Intensity and Texture Features Enable Accurate Prediction of Common Boreal Tree Species With Single Sensor UAS Data
2023
·
Mikko Kukkonen
, Timo Lähivaara
, et al.
·
IEEE Transactions on Geoscience and Remote Sensing
·
13
PDF
Mapping large European aspen ( Populus tremula L.) in Finland using airborne lidar and image data
2024
·
Janne Toivonen
, Annika Kangas
, et al.
·
Canadian Journal of Forest Research
·
11
Evaluation of UAS LiDAR data for tree segmentation and diameter estimation in boreal forests using trunk- and crown-based methods
2022
·
Mikko Kukkonen
, Matti Maltamo
, et al.
·
Canadian Journal of Forest Research
·
11
Volumes by tree species can be predicted using photogrammetric UAS data, Sentinel-2 images and prior field measurements
2021
·
Mikko Kukkonen
, Eetu Kotivuori
, et al.
·
Silva Fennica
·
11
Detection of standing retention trees in boreal forests with airborne laser scanning point clouds and multispectral imagery
2022
·
Alwin A. Hardenbol
, Lauri Korhonen
, et al.
·
Methods in Ecology and Evolution
·
9
Utility of image point cloud data towards generating enhanced multitemporal multisensor land cover maps
2019
·
Ranjith Gopalakrishnan
, Aku Seppänen
, et al.
·
International Journal of Applied Earth Observation and Geoinformation
·
9
PDF
Transferability of ALS-based forest attribute models when predicting with drone-based image point cloud data
2021
·
Janne Toivonen
, Lauri Korhonen
, et al.
·
International Journal of Applied Earth Observation and Geoinformation
·
8
PDF
Individual tree inventory based on uncrewed aerial vehicle data: how to utilise stand-wise field measurements of diameter for calibration?
2024
·
Johanna Jääskeläinen
, Lauri Korhonen
, et al.
·
Silva Fennica
·
3
PDF
Using ALS Data to Improve Co-Registration of Photogrammetry-Based Point Cloud Data in Urban Areas
2020
·
Ranjith Gopalakrishnan
, Daniela Ali-Sisto
, et al.
·
Remote Sensing
·
3
PDF
Classification of tree species and standing dead trees in Boreal forests using UAV‐based RGB, multispectral, and LiDAR point clouds
2026
·
Anton Kuzmin
, Lauri Korhonen
, et al.
·
Remote Sensing in Ecology and Conservation
·
2
Detection of snow disturbances in boreal forests using unitemporal airborne lidar data and aerial images
2024
·
Janne Räty
, Mikko Kukkonen
, et al.
·
Forestry An International Journal of Forest Research
·
2
PDF
Combining tree-boosting and mixed effects models improves the performance of remote-sensing based forest age predictions
2025
·
Janne Toivonen
, Annika Kangas
, et al.
·
Forestry An International Journal of Forest Research
·
1
PDF
Single sensor airborne data sources for forest inventories by tree species
2020
·
Mikko Kukkonen
·
Dissertationes Forestales
·
1
PDF
Predicting tree growth using light availability as an indicator of competition
2026
·
Jani Rannanpää
, Lauri Mehtätalo
, et al.
·
Forest Ecology and Management
PDF
A remote sensing-based tree mortality indicator for biodiversity monitoring using multispectral UAV and lidar in the Arctic region, Finland
2026
·
Katalin Waga
, Jaan Rönkkö
, et al.
·
Ecological Indicators
Implications of dissimilar geometries between training and population units in a three-dimensional deep learning–based forest inventory using airborne laser scanning and aerial image data
2026
·
Mikko Kukkonen
, Mari Myllymäki
, et al.
·
Forestry An International Journal of Forest Research
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Works count:
40
Citation count:
431
H-index:
11
I10-index:
13
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