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Mikko Kukkonen
ORCID
Publication Activity (10 Years)
Years Active: 2019-2024
Publications (10 Years): 7
Top Topics
Multispectral
Watershed Segmentation
Urban Areas
Point Cloud Data
Top Venues
Int. J. Appl. Earth Obs. Geoinformation
IEEE Trans. Geosci. Remote. Sens.
Remote. Sens.
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Publications
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Mikko Kukkonen
,
Timo Lähivaara
,
Petteri Packalen
Combination of Lidar Intensity and Texture Features Enable Accurate Prediction of Common Boreal Tree Species With Single Sensor UAS Data.
IEEE Trans. Geosci. Remote. Sens.
62 (2024)
Mikko Kukkonen
,
Matti Maltamo
,
Lauri Korhonen
,
Petteri Packalen
Fusion of crown and trunk detections from airborne UAS based laser scanning for small area forest inventories.
Int. J. Appl. Earth Obs. Geoinformation
100 (2021)
Janne Toivonen
,
Lauri Korhonen
,
Mikko Kukkonen
,
Eetu Kotivuori
,
Matti Maltamo
,
Petteri Packalen
Transferability of ALS-based forest attribute models when predicting with drone-based image point cloud data.
Int. J. Appl. Earth Obs. Geoinformation
103 (2021)
Daniela Ali-Sisto
,
Ranjith Gopalakrishnan
,
Mikko Kukkonen
,
Pekka Savolainen
,
Petteri Packalen
A method for vertical adjustment of digital aerial photogrammetry data by using a high-quality digital terrain model.
Int. J. Appl. Earth Obs. Geoinformation
84 (2020)
Ranjith Gopalakrishnan
,
Daniela Ali-Sisto
,
Mikko Kukkonen
,
Pekka Savolainen
,
Petteri Packalen
Using ALS Data to Improve Co-Registration of Photogrammetry-Based Point Cloud Data in Urban Areas.
Remote. Sens.
12 (12) (2020)
Ranjith Gopalakrishnan
,
Aku Seppänen
,
Mikko Kukkonen
,
Petteri Packalen
Utility of image point cloud data towards generating enhanced multitemporal multisensor land cover maps.
Int. J. Appl. Earth Obs. Geoinformation
86 (2020)
Mikko Kukkonen
,
Matti Maltamo
,
Lauri Korhonen
,
Petteri Packalen
Multispectral Airborne LiDAR Data in the Prediction of Boreal Tree Species Composition.
IEEE Trans. Geosci. Remote. Sens.
57 (6) (2019)