Eija Honkavaara

Eija Honkavaara
National Land Survey of Finland, Finnish Geospatial Research Institute FGI · Remote Sensing and Photogrammetry

PhD

About

218
Publications
85,231
Reads
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5,756
Citations
Citations since 2016
127 Research Items
4773 Citations
20162017201820192020202120220200400600800
20162017201820192020202120220200400600800
20162017201820192020202120220200400600800
20162017201820192020202120220200400600800
Introduction
I am currently working at the department of Remote Sensing and Photogrammetry, National Land Survey of Finland, Finnish Geospatial Research Institute FGI and I am leading the DroneFinland team. My research focuses UAV based remote sensing, where I am developing autonomous technologies for environmental remote sensing. Especially for precision agriculture, forestry and security applications.
Additional affiliations
January 1992 - December 2014
Finnish Geodetic Institute
Position
  • Project Manager

Publications

Publications (218)
Article
Full-text available
Structural complexity of trees is related to various ecological processes and ecosystem services. To support management for complexity, there is a need to assess the level of structural complexity objectively. The fractal-based box dimension (Db) provides a holistic measure of the structural complexity of individual trees. This study aimed to compa...
Article
Full-text available
The objective of this study is to investigate the potential of novel neural network architectures for measuring the quality and quantity parameters of silage grass swards, using drone RGB and hyperspectral images (HSI), and compare the results with the random forest (RF) method and handcrafted features. The parameters included fresh and dry biomass...
Article
Full-text available
Agricultural grasslands are globally important for food production, biodiversity, and greenhouse gas mitigation. Effective strategies to monitor grass sward properties, such as dry matter yield (DMY) and nitrogen concentration, are crucial when aiming to improve the sustainable use of grasslands in the context of food production. UAV-borne spectral...
Article
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The Atlantic Forest is the most fragmented and threatened domain in Brazil. The main remnants are in the coastal regions. This paper describes a study performed at a protected federal reserve in Brazil located in western of São Paulo state, which is a transition with the Savannah. A forestry survey was made for understanding the forest structure, d...
Article
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An accurate onboard irradiance measurement on drones is a requirement direct reflectance transformation of aerial images and remote sensing data without use of on-ground reference targets. One of the major error sources in onboard irradiance measurement is the effect of sensor tilt to the observed irradiances. In this paper/presentation, we will pr...
Article
The recent development of lightweight and relatively low-cost hyperspectral sensors has created new perspectives for remote sensing applications. This study aimed to investigate the geometric calibration of a hyperspectral frame camera based on a tuneable Fabry–Pérot interferometer (FPI) and two sensors. The radiation passes through the optics and...
Article
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Climate change is increasing pest insects’ ability to reproduce as temperatures rise, resulting in vast tree mortality globally. Early information on pest infestation is urgently needed for timely decisions to mitigate the damage. We investigated the mapping of trees that were in decline due to European spruce bark beetle infestation using multispe...
Article
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The use of Unmanned Aerial Vehicles (UAVs) has surged in the last two decades, making them popular instruments for a wide range of applications, and leading to a remarkable number of scientific contributions in geoscience, remote sensing and engineering. However, the development of best practices for high quality of UAV mapping are often overlooked...
Chapter
The use of remote sensing in agriculture is expanding due to innovation in sensors and platforms. Uncrewed aerial vehicles (UAVs), CubeSats, and robot mounted proximal phenotyping sensors all feature in this drive. Common threads include a focus on high spatial and spectral resolution coupled with the use of machine learning methods for relating ob...
Article
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Clouds are one of the major limitations to crop monitoring using optical satellite images. Despite all efforts to provide decision-makers with high-quality agricultural statistics, there is still a lack of techniques to optimally process satellite image time series in the presence of clouds. In this regard, in this article it was proposed to add a...
Article
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The deterioration of road conditions and increasing repair deficits pose challenges for the maintenance of reliable road infrastructure, and thus threaten, for example, safety and the fluent flow of traffic. Improved and more efficient procedures for maintenance are required, and these require improved knowledge of road conditions, i.e., improved d...
Article
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Multi- and hyperspectral cameras on drones can be valuable tools in environmental monitoring. A significant shortcoming complicating their usage in quantitative remote sensing applications is insufficient robust radiometric calibration methods. In a direct reflectance transformation method, the drone is equipped with a camera and an irradiance sens...
Article
The vegetative growth of forest canopies changes their spectral response, which can be detected by multispectral sensors and enhanced by utilizing the normalized difference vegetation index (NDVI). The structural variability of canopies in heterogeneous forests can also be related to successional stages. Thereby, a spatiotemporal methodology is pre...
Article
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Most methods developed to map crop fields with high-quality are based on optical image time-series. However, often accuracy of these approaches is deteriorated due to clouds and cloud shadows, which can decrease the availably of optical data required to represent crop phenological stages. In this sense, the objective of this study was to implement...
Article
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Data collection and estimation of variables that describe the structure of tropical forests, diversity, and richness of tree species are challenging tasks. Light detection and ranging (LiDAR) is a powerful technique due to its ability to penetrate small openings and cracks in the forest canopy, enabling the collection of structural information in c...
Article
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Solar-induced Fluorescence (SIF) has an advantage over greenness-based Vegetation Indices in detecting drought. This advantage is the mechanistic coupling between SIF and Gross Primary Productivity (GPP). Under water stress, SIF tends to decrease with photosynthesis, due to an increase in non-photochemical quenching (NPQ), resulting in rapid and/or...
Article
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The development of UAV (unmanned aerial vehicle) imaging technologies for precision farming applications is rapid, and new studies are published frequently. In cases where measurements are based on aerial imaging, there is the need to have ground truth or reference data in order to develop reliable applications. However, in several precision farmin...
Article
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Canopy height is an important attribute that allows characterizing the forest vertical structure and analyze changes in vegetation cover over time. The objective of this study is to develop an approach for a spatio-temporal analysis of the tropical forest canopy using multi-temporal photogrammetric images. The datasets based on film and digital cam...
Article
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The objective of this study is to evaluate the spectral difference between and within 11 tree species belonging to Brazilian Atlantic Forest located in the countryside of São Paulo State, Brazil. Tree species with different development stages may have different reflectance spectra because of the structural and phenological influence on it. Tree str...
Article
Full-text available
Forest management alters the growing conditions and thus further development of trees. However, quantitative assessment of forest management on tree growth has been demanding as methodologies for capturing changes comprehensively in space and time have been lacking. Terrestrial laser scanning (TLS) has shown to be capable of providing three-dimensi...
Article
Full-text available
Simultaneous localization and mapping (SLAM) of a monocular projective camera installed on an unmanned aerial vehicle (UAV) is a challenging task in photogrammetry, computer vision, and robotics. This paper presents a novel real-time monocular SLAM solution for UAV applications. It is based on two steps: consecutive construction of the UAV path, an...
Conference Paper
Full-text available
Leaf angle distribution (LAD) is a key canopy structural parameter, playing an important role in light transfer. LAD can be estimated from fixed point of view photography, however this is time consuming and spatially limited. Recently, Terrestrial LiDAR Scanning (TLS) has been used to estimate LAD through 3D canopy space. The downside of TLS it is...
Conference Paper
There are many advantages of using unmanned aerial vehicles (UAVs) in remote sensing but when using radiometrically corrected multispectral images. This study focuses on two techniques of obtain a multispectral orthomosaic with suitable radiometric quality considering a day period with minor variations in illumination and clouds. The first techniqu...
Article
Full-text available
Drones offer entirely new prospects for precision agriculture. This study investigates the utilisation of drone remote sensing for managing and monitoring silage grass swards. In northern countries, grass swards are fertilised and harvested three times per season when aiming to maximise the yield. Information about the grass quantity and quality is...
Preprint
TO READ AND DOWNLOAD THIS PREPRINT; CLICK ON THE DOI, WHICH SHOULD TAKE YOU TO THE EARTHARXIV (https://doi.org/10.31223/osf.io/eayph). The use of remote sensing in agriculture is expanding due to innovation in sensors and platforms. Drones, high resolution instruments on CubeSats, and robot mounted proximal phenotyping sensors all feature in this...
Article
Full-text available
Various biotic and abiotic stresses are threatening forests. Modern remote sensing technologies provide powerful means for monitoring forest health, and provide a sustainable basis for forest management and protection. The objective of this study was to develop unmanned aerial vehicle (UAV) based spectral remote sensing technologies for tree health...
Article
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Terrestrial laser scanning (TLS) provides a detailed three-dimensional representation of surrounding forest structures. However, due to close-range hemispherical scanning geometry, the ability of TLS technique to comprehensively characterize all trees, and especially upper parts of forest canopy, is often limited. In this study, we investigated how...
Article
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Deep neural networks are currently the focus of many remote sensing approaches related to forest management. Although they return satisfactory results in most tasks, some challenges related to hyperspectral data remain, like the curse of data dimensionality. In forested areas, another common problem is the highly-dense distribution of trees. In thi...
Preprint
Wind damage is known for causing threats to sustainable forest management and yield value in boreal forests. Information about wind damage risk can aid forest managers in understanding and possibly mitigating damage impacts especially when wind damage events have increased in recent years.The objective of this research was to better understand and...
Article
Full-text available
Interest in drone solutions in forestry applications is growing. Using drones, datasets can be captured flexibly and at high spatial and temporal resolutions when needed. In forestry applications, fundamental tasks include the detection of individual trees, tree species classification, biomass estimation, etc. Deep neural networks (DNN) have shown...
Preprint
Full-text available
Terrestrial laser scanning (TLS) provides detailed three-dimensional representation of the surrounding forest structure. However, due to close-range hemispherical scanning geometry, the ability of TLS technique to comprehensively characterize all trees and especially the upper parts of forest canopy is often limited. In this study, we investigated...
Preprint
National Land Survey of Finland (NLS) started collecting ALS-data in 2008 to provide a new national elevation model. The data is available at free of charge and has great potential and a wide variety of possible applications in spatial modelling. The objective of this study was to test the feasibility of ALS-data from NLS in mapping the risk of for...
Preprint
Full-text available
Quantitative assessment of the effects of forest management on tree size and shape has been challenging as there has been a lack of methodologies for characterizing differences and possible changes comprehensively in space and time. Terrestrial laser scanning (TLS) and photogrammetric point clouds provide three-dimensional (3D) information on tree...
Preprint
Full-text available
Forest management alters the growing conditions and thus further development of trees. However, quantitative assessment of forest management on tree growth has been demanding as methodologies for capturing changes comprehensively in space and time have been lacking. Terrestrial laser scanning (TLS) has shown to be capable of providing three-dimensi...
Chapter
Full-text available
In near future it is assumable that automated unmanned aerial platforms are coming more common. There are visions that transportation of different goods would be done with large planes, which can handle over 1000 kg payloads. While these planes are used for transportation they could similarly be used for remote sensing applications by adding sensor...
Preprint
Full-text available
Interest in drone solutions in forestry applications is growing. Using drones, datasets can be captured flexibly and at high spatial and temporal resolutions when needed. In forestry applications, fundamental tasks include the detection of individual trees, tree species classification, bio-mass estimation, etc. Deep Neural Networks (DNN) have shown...
Cover Page
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HyperMLPA is an interdisciplinary workshop which aims at bringing together people of different communities and disciplines involved in hyperspectral sensing, machine learning, and pattern analysis. People are invited to contribute in sensor development and calibration, to present and publish new datasets, to present innovative methodological advanc...
Article
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Miniaturized hyperspectral imaging techniques have developed rapidly in recent years and have become widely available for different applications. Combining calibrated hyperspectral imagery with inverse physically based reflectance models is an interesting approach for estimating chlorophyll concentrations that are good indicators of vegetation heal...
Article
Full-text available
The monitoring of forest resources is crucial for their sustainable management, and tree species identification is one of the fundamental tasks in this process. Unmanned aerial vehicles (UAVs) and miniaturized lightweight sensors can rapidly provide accurate monitoring information. The objective of this study was to investigate the use of multitemp...
Article
Full-text available
Background: Lately, terrestrial point clouds have drawn attention as a new data source for in situ forest investigations. So far, terrestrial laser scanning (TLS) has the highest data quality among all terrestrial point cloud data in terms of geometric accuracy and level of detail (IEEE Transact Geosci Remote Sens 53: 5117–5132, 2015). The TLS poin...
Article
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Low cost imaging and positioning sensors are opening new frontiers for applications in near real-time Photogrammetry. Omnidirectional cameras acquiring images with 360° coverage, when combined with information coming from GNSS (Global Navigation Satellite Systems) and IMU (Inertial Measurement Unit), can efficiently estimate orientation and object...
Article
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Mobile mapping systems (MMS) are increasingly used for many photogrammetric and computer vision applications, especially encouraged by the fast and accurate geospatial data generation. The accuracy of point position in an MMS is mainly dependent on the quality of calibration, accuracy of sensor synchronization, accuracy of georeferencing and stabil...
Article
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This paper presents a method for characterising spatial responsivity of hyperspectral cameras. Knowing the responsivity of the camera as a function of pixel coordinates allows applying a flat-field correction on image data. The method is based on scanning the field of view of the camera with a broadband radiance source, based on an integrating sphe...
Article
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Recent studies assessing agricultural policies, including the EU's Agri-Environment Scheme, have shown that these have been successful in attaining some environmental goals. In Finland, however, the economic situation of farms has dramatically fallen and hence, the actions do not result in social acceptability. Sustainable intensification is a mean...
Article
Lightweight hyperspectral cameras based on frame geometry have been used for several applications in unmanned aerial vehicles (UAVs). The camera used in this investigation is based on a tunable Fabry-Pérot interferometer (FPI) and works on the time-sequential principle for band acquisition. Due to this feature, when collecting images in movement, h...
Article
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This Special Issue hosts papers on the integrated use of spectral imaging and 3D technologies in remote sensing, including novel sensors, evolving machine learning technologies for data analysis, and the utilization of these technologies in a variety of geospatial applications. The presented results showed improved results when multimodal data was...
Article
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Close range photogrammetry (CRP) with large field-of-view images has become widespread in recent years, especially in terrestrial mobile mapping systems (TMMS). However, feature-based matching (FBM) with omnidirectional images (e.g., fisheye) is challenging even for state-of-the-art methods, such as the scale-invariant feature transform (SIFT), bec...
Article
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A study on orientation of hyperspectral band cubes acquired with frame camera is presented in this paper. The camera technology is based on a tuneable Fabry-Perot Interferometer (FPI) and captures cubes of images sequentially using two sensors. However, the bands are not recorded at the same instant, which results different exterior orientation par...
Article
Full-text available
The objective of this work was the comparison of two different classification approaches to detect four different tree species of a highly diverse tropical Atlantic Forest area. In order to achieve the objective, images were acquired with the Rikola hyperspectral camera onboard the UX4 UAV. The study area is in the Western part of São Paulo State,...
Article
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Brazil is one of the world leaders in citrus plantation, and the production of orange juice is economically important in the export scenario, being regarded as a fundamental agricultural commodity in Brazil. The worst citrus disease is Greening, or Huanglongbing (HLB), a bacterial disease which cannot be cured and to which no plant variety is immun...
Article
Full-text available
The information on the grass quantity and quality is needed for several times in a growing season for making optimal decisions about the harvesting time and the fertiliser rate, especially in northern countries, where grass swards quality declines and yield increases rapidly in the primary growth. We studied the potential of UAV-based photogrammetr...