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Teemu Hakala
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2020 – today
- 2025
- [j41]Zuoya Liu
, Harri Kaartinen
Tracking foresters and mapping tree stem locations with decimeter-level accuracy under forest canopies using UWB. Expert Syst. Appl. 262: 125519 (2025) - 2024
- [j40]Ziyi Feng
Feasibility of using Ku-band helicopter-borne microwave radar for stem volume and biomass estimation in boreal forest. Int. J. Appl. Earth Obs. Geoinformation 131: 103966 (2024) - [j39]Jesse Muhojoki
Benchmarking Under- and Above-Canopy Laser Scanning Solutions for Deriving Stem Curve and Volume in Easy and Difficult Boreal Forest Conditions. Remote. Sens. 16(10): 1721 (2024) - [j38]Tamás Faitli
Integration of a Mobile Laser Scanning System with a Forest Harvester for Accurate Localization and Tree Stem Measurements. Remote. Sens. 16(17): 3292 (2024) - [j37]Zuoya Liu
Data-Driven Antenna Delay Calibration for UWB Devices for Network Positioning. IEEE Trans. Instrum. Meas. 73: 1-11 (2024) - [j36]Zuoya Liu
Performance Analysis of Standalone UWB Positioning Inside Forest Canopy. IEEE Trans. Instrum. Meas. 73: 1-14 (2024) - [i3]Julius Pesonen, Teemu Hakala, Väinö Karjalainen, Niko Koivumäki, Lauri Markelin, Anna-Maria Raita-Hakola, Juha Suomalainen, Ilkka Pölönen, Eija Honkavaara:
Detecting Wildfires on UAVs with Real-time Segmentation Trained by Larger Teacher Models. CoRR abs/2408.10843 (2024) - 2023
- [j35]Einari Heinaro
Evaluating Factors Impacting Fallen Tree Detection from Airborne Laser Scanning Point Clouds. Remote. Sens. 15(2): 382 (2023) - [j34]Jaakko Oivukkamäki, Jon Atherton
Investigating Foliar Macro- and Micronutrient Variation with Chlorophyll Fluorescence and Reflectance Measurements at the Leaf and Canopy Scales in Potato. Remote. Sens. 15(10): 2498 (2023) - [j33]Emma Turkulainen, Eija Honkavaara
Comparison of Deep Neural Networks in the Classification of Bark Beetle-Induced Spruce Damage Using UAS Images. Remote. Sens. 15(20): 4928 (2023) - 2022
- [j32]Heini Kanerva, Eija Honkavaara
Estimating Tree Health Decline Caused by Ips typographus L. from UAS RGB Images Using a Deep One-Stage Object Detection Neural Network. Remote. Sens. 14(24): 6257 (2022) - [j31]Josef Taher
Feasibility of Hyperspectral Single Photon Lidar for Robust Autonomous Vehicle Perception. Sensors 22(15): 5759 (2022) - 2021
- [j30]Kai Du, Huaguo Huang
Using Microwave Profile Radar to Estimate Forest Canopy Leaf Area Index: Linking 3D Radiative Transfer Model and Forest Gap Model. Remote. Sens. 13(2): 297 (2021) - [j29]Hui Zhou, Yuwei Chen
The Penetration Analysis of Airborne Ku-Band Radar Versus Satellite Infrared Lidar Based on the Height and Energy Percentiles in the Boreal Forest. Remote. Sens. 13(9): 1650 (2021) - 2020
- [j28]Yuwei Chen, Ziyi Feng, Fashuai Li
Lidar-aided analysis of boreal forest backscatter at Ku band. Int. J. Appl. Earth Obs. Geoinformation 91: 102133 (2020) - [j27]Hui Zhou, Yuwei Chen
The Determination of Effective Beamwidth of Ku Band Profiling Radar Based on Waveform Matching Method in the Boreal Forest of Finland. Remote. Sens. 12(17): 2710 (2020) - [j26]Kai Du, Huaguo Huang
Erratum: Du, K., et al. Simulation of Ku-Band Profile Radar Waveform by Extending Radiosity Applicable to Porous Individual Objects (RAPID2) Model. Remote Sensing 2020, 12, 684. Remote. Sens. 12(17): 2830 (2020) - [j25]Eric Hyyppä, Xiaowei Yu
Comparison of Backpack, Handheld, Under-Canopy UAV, and Above-Canopy UAV Laser Scanning for Field Reference Data Collection in Boreal Forests. Remote. Sens. 12(20): 3327 (2020) - [c12]Shan Xu
On the Estimation of the Leaf Angle Distribution from Drone Based Photogrammetry. IGARSS 2020: 4379-4382
2010 – 2019
- 2019
- [j24]Juha Kainulainen
Airborne Wind Vector Scatterometer for Sea Surface Measurements. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 12(7): 2470-2476 (2019) - 2018
- [j23]Ninni Saarinen
Assessing Biodiversity in Boreal Forests with UAV-Based Photogrammetric Point Clouds and Hyperspectral Imaging. Remote. Sens. 10(2): 338 (2018) - [j22]Hui Zhou, Yuwei Chen
The Comparison of Canopy Height Profiles Extracted from Ku-band Profile Radar Waveforms and LiDAR Data. Remote. Sens. 10(5): 701 (2018) - [j21]Sakari Tuominen
Assessment of Classifiers and Remote Sensing Features of Hyperspectral Imagery and Stereo-Photogrammetric Point Clouds for Recognition of Tree Species in a Forest Area of High Species Diversity. Remote. Sens. 10(5): 714 (2018) - [j20]Roope Näsi
Estimating Biomass and Nitrogen Amount of Barley and Grass Using UAV and Aircraft Based Spectral and Photogrammetric 3D Features. Remote. Sens. 10(7): 1082 (2018) - [j19]Juha Suomalainen
A Novel Tilt Correction Technique for Irradiance Sensors and Spectrometers On-Board Unmanned Aerial Vehicles. Remote. Sens. 10(12): 2068 (2018) - [j18]Mariana Batista Campos
A Backpack-Mounted Omnidirectional Camera with Off-the-Shelf Navigation Sensors for Mobile Terrestrial Mapping: Development and Forest Application. Sensors 18(3): 827 (2018) - [j17]Teemu Hakala, Lauri Markelin
Direct Reflectance Measurements from Drones: Sensor Absolute Radiometric Calibration and System Tests for Forest Reflectance Characterization. Sensors 18(5): 1417 (2018) - [j16]Hui Zhou, Yuwei Chen
Estimation of Canopy Height Using an Airborne Ku-Band Frequency-Modulated Continuous Waveform Profiling Radar. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 11(10): 3590-3597 (2018) - [j15]Ziyi Feng
Estimating Ground Level and Canopy Top Elevation With Airborne Microwave Profiling Radar. IEEE Trans. Geosci. Remote. Sens. 56(4): 2283-2294 (2018) - [c11]Juha Kainulainen, Sampo Salo, Janne Lahtinen, Guifré Molera Calvés
Fully Polarimetric Airborne Wind Vector Scatterometer to Support Space-Borne Gnss-R Measurements. IGARSS 2018: 2011-2014 - [c10]Jon Atherton
Drone Measurements of Solar-Induced Chlorophyll Fluorescence Acquired with a Low-Weight DFOV Spectrometer System. IGARSS 2018: 8834-8836 - [c9]Ilkka Pölönen, Leevi Annala, Samuli Rahkonen
Tree Species Identification Using 3D Spectral Data and 3D Convolutional Neural Network. WHISPERS 2018: 1-5 - [i2]Nikos Fotiou, George Xylomenos, George C. Polyzos, Hasan M. A. Islam, Dmitrij Lagutin, Teemu Hakala, Eero Hakala:
ICN enabling CoAP Extensions for IP based IoT devices. CoRR abs/1802.05198 (2018) - 2017
- [j14]Yuwei Chen
UAV-Borne Profiling Radar for Forest Research. Remote. Sens. 9(1): 58 (2017) - [j13]Olli Nevalainen
Individual Tree Detection and Classification with UAV-Based Photogrammetric Point Clouds and Hyperspectral Imaging. Remote. Sens. 9(3): 185 (2017) - [j12]Livia Piermattei
An Analysis of Ku-Band Profiling Radar Observations of Boreal Forest. Remote. Sens. 9(12): 1252 (2017) - [c8]Nikos Fotiou, George Xylomenos
ICN enabling CoAP extensions for IP based IoT devices. ICN 2017: 218-219 - [c7]Jere Kaivosoja
Different Remote Sensing Data in Relative Biomass Determination and in Precision Fertilization Task Generation for Cereal Crops. HAICTA (Revised Selected Papers) 2017: 164-176 - [c6]Jere Kaivosoja, Roope Näsi, Teemu Hakala, Niko Viljanen, Eija Honkavaara:
Applying Different Remote Sensing Data to Determine Relative Biomass Estimations of Cereals for Precision Fertilization Task Generation. HAICTA 2017: 670-680 - [i1]Nikos Fotiou, Hasan M. A. Islam, Dmitrij Lagutin, Teemu Hakala, George C. Polyzos:
CoAP over ICN. CoRR abs/1707.03233 (2017) - 2016
- [j11]Eija Honkavaara
Remote Sensing of 3-D Geometry and Surface Moisture of a Peat Production Area Using Hyperspectral Frame Cameras in Visible to Short-Wave Infrared Spectral Ranges Onboard a Small Unmanned Airborne Vehicle (UAV). IEEE Trans. Geosci. Remote. Sens. 54(9): 5440-5454 (2016) - [c5]Ziyi Feng, Yuwei Chen
Range calibration of airborne profiling radar used in forest inventory. IGARSS 2016: 6672-6675 - [c4]Nikos Fotiou, Hasan M. A. Islam, Dmitrij Lagutin, Teemu Hakala, George C. Polyzos
CoAP over ICN. NTMS 2016: 1-4 - [c3]Yuwei Chen
Scan matching technology for forest navigation with map information. PLANS 2016: 198-203 - 2015
- [j10]Samuli Junttila
Investigating Bi-Temporal Hyperspectral Lidar Measurements from Declined Trees - Experiences from Laboratory Test. Remote. Sens. 7(10): 13863-13877 (2015) - [j9]Roope Näsi
Using UAV-Based Photogrammetry and Hyperspectral Imaging for Mapping Bark Beetle Damage at Tree-Level. Remote. Sens. 7(11): 15467-15493 (2015) - 2013
- [j8]Jari Vauhkonen, Teemu Hakala, Juha Suomalainen
Classification of Spruce and Pine Trees Using Active Hyperspectral LiDAR. IEEE Geosci. Remote. Sens. Lett. 10(5): 1138-1141 (2013) - [j7]Eija Honkavaara
Processing and Assessment of Spectrometric, Stereoscopic Imagery Collected Using a Lightweight UAV Spectral Camera for Precision Agriculture. Remote. Sens. 5(10): 5006-5039 (2013) - 2010
- [j6]Teemu Hakala, Juha Suomalainen
Acquisition of Bidirectional Reflectance Factor Dataset Using a Micro Unmanned Aerial Vehicle and a Consumer Camera. Remote. Sens. 2(3): 819-832 (2010) - [j5]Eija Honkavaara
Analysis of Properties of Reflectance Reference Targets for Permanent Radiometric Test Sites of High Resolution Airborne Imaging Systems. Remote. Sens. 2(8): 1892-1917 (2010) - [j4]Jouni I. Peltoniemi
Land Surface Albedos Computed from BRF Measurements with a Study of Conversion Formulae. Remote. Sens. 2(8): 1918-1940 (2010) - [j3]Yuwei Chen
Two-channel Hyperspectral LiDAR with a Supercontinuum Laser Source. Sensors 10(7): 7057-7066 (2010) - [c2]Sanna Kaasalainen
Active hyperspectral LIDAR methods for object classification. WHISPERS 2010: 1-4
2000 – 2009
- 2009
- [j2]Juha Suomalainen
Polarised Multiangular Reflectance Measurements Using the Finnish Geodetic Institute Field Goniospectrometer. Sensors 9(5): 3891-3907 (2009) - [j1]Eetu Puttonen
Measurement of Reflectance Properties of Asphalt Surfaces and Their Usability as Reference Targets for Aerial Photos. IEEE Trans. Geosci. Remote. Sens. 47(7-2): 2330-2339 (2009) - [c1]Jean-Louis Roujean, Terhikki Manninen
SNORTEX (Snow Reflectance Transition Experiment): Remote Sensing Measurement of the Dynamic Properties of the Boreal Snow-forest in Support to Climate and Weather Forecast: Report of IOP-2008. IGARSS (2) 2009: 859-862
Coauthor Index
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last updated on 2024-11-07 20:32 CET by the dblp team
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