Petteri Packalen
Orcid: 0000-0003-1804-0011
According to our database1,
Petteri Packalen
authored at least 24 papers
between 2010 and 2024.
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Collaborative distances:
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Bibliography
2024
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., 2024
2023
SoftwareX, December, 2023
Leveraging remotely sensed non-wall-to-wall data for wall-to-wall upscaling in forest inventory.
Int. J. Appl. Earth Obs. Geoinformation, May, 2023
2022
A Comparison of Linear-Mode and Single-Photon Airborne LiDAR in Species-Specific Forest Inventories.
IEEE Trans. Geosci. Remote. Sens., 2022
Estimation of forest stand characteristics using individual tree detection, stochastic geometry and a sequential spatial point process model.
Int. J. Appl. Earth Obs. Geoinformation, 2022
2021
Transferability of ALS-based forest attribute models when predicting with drone-based image point cloud data.
Int. J. Appl. Earth Obs. Geoinformation, 2021
Fusion of crown and trunk detections from airborne UAS based laser scanning for small area forest inventories.
Int. J. Appl. Earth Obs. Geoinformation, 2021
2020
Using ALS Data to Improve Co-Registration of Photogrammetry-Based Point Cloud Data in Urban Areas.
Remote. Sens., 2020
Utility of image point cloud data towards generating enhanced multitemporal multisensor land cover maps.
Int. J. Appl. Earth Obs. Geoinformation, 2020
A method for vertical adjustment of digital aerial photogrammetry data by using a high-quality digital terrain model.
Int. J. Appl. Earth Obs. Geoinformation, 2020
2019
Gaussian Process Regression for Forest Attribute Estimation From Airborne Laser Scanning Data.
IEEE Trans. Geosci. Remote. Sens., 2019
Multispectral Airborne LiDAR Data in the Prediction of Boreal Tree Species Composition.
IEEE Trans. Geosci. Remote. Sens., 2019
Do airborne laser scanning biomass prediction models benefit from Landsat time series, hyperspectral data or forest classification in tropical mosaic landscapes?
Int. J. Appl. Earth Obs. Geoinformation, 2019
2018
How much can airborne laser scanning based forest inventory by tree species benefit from auxiliary optical data?
Int. J. Appl. Earth Obs. Geoinformation, 2018
2017
Uncertainty Quantification in ALS-Based Species-Specific Growing Stock Volume Estimation.
IEEE Trans. Geosci. Remote. Sens., 2017
Forest Change Detection by Using Point Clouds From Dense Image Matching Together With a LiDAR-Derived Terrain Model.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2017
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.
Int. J. Appl. Earth Obs. Geoinformation, 2017
2016
Int. J. Appl. Earth Obs. Geoinformation, 2016
Effect of flying altitude, scanning angle and scanning mode on the accuracy of ALS based forest inventory.
Int. J. Appl. Earth Obs. Geoinformation, 2016
2015
Edge-Tree Correction for Predicting Forest Inventory Attributes Using Area-Based Approach With Airborne Laser Scanning.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2015
Estimating Tree Height Distribution Using Low-Density ALS Data With and Without Training Data.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2015
2013
Assessing and modeling moose (Alces alces) habitats with airborne laser scanning data.
Int. J. Appl. Earth Obs. Geoinformation, 2013
2011
Airborne Laser Scanning for the Site Type Identification of Mature Boreal Forest Stands.
Remote. Sens., 2011
2010
Neural Networks for the Prediction of Species-Specific Plot Volumes Using Airborne Laser Scanning and Aerial Photographs.
IEEE Trans. Geosci. Remote. Sens., 2010