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Overview

Teemu Hakala is affiliated with the Finnish Geospatial Research Institute in Finland. Their research spans multiple areas within environmental science and engineering, focusing particularly on remote sensing and its diverse applications. The main fields of study include Environmental Science and Engineering, with subfields such as Environmental Engineering, Ecology, Insect Science, Aerospace Engineering, and Nature and Landscape Conservation.

The scientist's work extensively covers topics related to remote sensing technology and its implementation in environmental and forestry studies. Key topics include:

  • Remote Sensing and LiDAR Applications
  • Forest Ecology and Biodiversity Studies
  • Forest Ecology and Management
  • 3D Surveying and Cultural Heritage
  • Remote Sensing in Agriculture
  • Fire Effects on Ecosystems
  • Robotics and Sensor-Based Localization

Among recent publications by Teemu Hakala are works published mainly in well-known journals related to photogrammetry, remote sensing, and environmental monitoring. Selected papers include:

  • Under-canopy UAV laser scanning for accurate forest field measurements, 2020, ISPRS Journal of Photogrammetry and Remote Sensing
  • Comparison of Backpack, Handheld, Under-Canopy UAV, and Above-Canopy UAV Laser Scanning for Field Reference Data Collection in Boreal Forests, 2020, Remote Sensing
  • Machine learning estimators for the quantity and quality of grass swards used for silage production using drone-based imaging spectrometry and photogrammetry, 2020, Remote Sensing of Environment
  • Direct reflectance transformation methodology for drone-based hyperspectral imaging, 2021, Remote Sensing of Environment
  • Effect of small-scale snow surface roughness on snow albedo and reflectance, 2021, The Cryosphere

Teemu Hakala frequently collaborates with various researchers. Notable co-authors include Juha Hyyppä, Antero Kukko, Harri Kaartinen, Eija Honkavaara, and Juha Suomalainen. The collaboration with these co-authors reflects a sustained engagement in multidisciplinary research within the geospatial and remote sensing communities.

The scientist publishes regularly in several reputable venues. The most frequent publication venues are:

  • Remote Sensing
  • The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
  • SSRN Electronic Journal
  • ISPRS Open Journal of Photogrammetry and Remote Sensing
  • ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences

Best Publications

  • Processing and assessment of spectrometric, stereoscopic imagery collected using a lightweight UAV spectral camera for precision agriculture

    Eija Honkavaara;Heikki Saari;Jere Kaivosoja;Ilkka Pölönen

  • Individual Tree Detection and Classification with UAV-Based Photogrammetric Point Clouds and Hyperspectral Imaging

    Olli Nevalainen;Eija Honkavaara;Sakari Tuominen;Niko Viljanen

  • Using UAV-based photogrammetry and hyperspectral imaging for mapping bark beetle damage at tree-level

    Roope Näsi;Eija Honkavaara;Päivi Marja Emilia Lyytikäinen-Saarenmaa;Minna Blomqvist

  • Full waveform hyperspectral LiDAR for terrestrial laser scanning

    Teemu Hakala;Juha Suomalainen;Sanna Kaasalainen;Yuwei Chen

  • Remote sensing of bark beetle damage in urban forests at individual tree level using a novel hyperspectral camera from UAV and aircraft

    Roope Näsi;Eija Honkavaara;Minna Blomqvist;Päivi Marja Emilia Lyytikäinen-Saarenmaa

  • A Novel Machine Learning Method for Estimating Biomass of Grass Swards Using a Photogrammetric Canopy Height Model, Images and Vegetation Indices Captured by a Drone

    Niko Viljanen;Eija Honkavaara;Roope Näsi;Teemu Hakala

  • Estimating Biomass and Nitrogen Amount of Barley and Grass Using UAV and Aircraft Based Spectral and Photogrammetric 3D Features

    Roope Näsi;Niko Viljanen;Jere Kaivosoja;Katja Alhonoja

  • Under-canopy UAV laser scanning for accurate forest field measurements

    Eric Hyyppä;Juha Hyyppä;Juha Hyyppä;Teemu Hakala;Antero Kukko;Antero Kukko

  • Comparison of Backpack, Handheld, Under-Canopy UAV, and Above-Canopy UAV Laser Scanning for Field Reference Data Collection in Boreal Forests

    Eric Hyyppä;Xiaowei Yu;Harri Kaartinen;Teemu Hakala

  • Two-channel Hyperspectral LiDAR with a Supercontinuum Laser Source

    Yuwei Chen;Esa Räikkönen;Sanna Kaasalainen;Juha Suomalainen

  • Structural and photosynthetic dynamics mediate the response of SIF to water stress in a potato crop

    Shan Xu;Shan Xu;Shan Xu;Jon Atherton;Anu Riikonen;Chao Zhang

  • Polarised bidirectional reflectance factor measurements from soil, stones, and snow

    Jouni Peltoniemi;Teemu Hakala;Juha Suomalainen;Eetu Puttonen

  • SLAM-Aided Stem Mapping for Forest Inventory with Small-Footprint Mobile LiDAR

    Jian Tang;Yuwei Chen;Antero Kukko;Harri Kaartinen

  • Machine learning estimators for the quantity and quality of grass swards used for silage production using drone-based imaging spectrometry and photogrammetry

    Raquel Alves Oliveira;Roope Näsi;Oiva Niemeläinen;Laura Nyholm

  • Hyperspectral reflectance signatures and point clouds for precision agriculture by light weight UAV imaging system

    Eija Honkavaara;Jere Kaivosoja;Jussi Mäkynen;Ismo Pellikka

  • Fast and nondestructive method for leaf level chlorophyll estimation using hyperspectral LiDAR

    Olli Nevalainen;Teemu Hakala;Juha Suomalainen;Juha Suomalainen;Raisa Mäkipää

  • 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)

    Eija Honkavaara;Matti A. Eskelinen;Ilkka Polonen;Heikki Saari

  • Assessing Biodiversity in Boreal Forests with UAV-Based Photogrammetric Point Clouds and Hyperspectral Imaging

    Ninni Saarinen;Mikko Vastaranta;Roope Näsi;Tomi Rosnell

  • Acquisition of Bidirectional Reflectance Factor Dataset Using a Micro Unmanned Aerial Vehicle and a Consumer Camera

    Teemu Hakala;Juha Suomalainen;Jouni I. Peltoniemi

  • Polarised Multiangular Reflectance Measurements Using the Finnish Geodetic Institute Field Goniospectrometer

    Juha Suomalainen;Teemu Hakala;Jouni Peltoniemi;Eetu Puttonen

  • Tree species classification from fused active hyperspectral reflectance and LIDAR measurements.

    Eetu Puttonen;Juha Suomalainen;Teemu Hakala;Esa Räikkönen

Frequent Co-Authors

Eija Honkavaara
Eija Honkavaara Finnish Geospatial Research Institute
Juha Suomalainen
Juha Suomalainen Wageningen University & Research
Sanna Kaasalainen
Sanna Kaasalainen Finnish Geospatial Research Institute
Juha Hyyppä
Juha Hyyppä Finnish Geospatial Research Institute
Harri Kaartinen
Harri Kaartinen University of Turku
Antero Kukko
Antero Kukko Aalto University
Mikko Vastaranta
Mikko Vastaranta University of Eastern Finland
Anttoni Jaakkola
Anttoni Jaakkola Finnish Geospatial Research Institute
Hui Zhou
Hui Zhou Huazhong University of Science and Technology
Albert Porcar-Castell
Albert Porcar-Castell University of Helsinki

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