Refereed publications

 

Peer-reviewed scientific articles such as journal articles, book sections, chapters in research books, or peer-reviewed articles in conference proceedings.

Recent Submissions

  • Kettunen, Pyry; Rönneberg, Mikko (2022)
    Proceedings of International Conference on Location Based Services
  • Latvala, Pekka; Huuhko, Kim; Kokkonen, Matti (Copernicus Publications, 2022)
    Abstracts of the International Cartographic Association Series
  • Bonnevie, Ida Maria; Hansen, Henning Sten; Schrøder, Lise; Rönneberg, Mikko; Kettunen, Pyry; Koski, Christian; Oksanen, Juha (Elsevier BV, 2022)
    SSRN Electronic Journal
    Collaborative spatial decision support tools can contribute with setups for including stakeholders into marine spatial planning (MSP) processes with the purpose of increasing trust in planning outcomes, facilitate shared planning goals, and provide transparent, scientific, inclusive, and technical foundations for planning. A new collaborative spatial decision support setup based on the combination of functionalities from two spatial decision support tools called SEANERGY and Baltic Explorer was designed for and tested in a workshop in 2020 targeted local authorities, NGOs, and citizens in Denmark with an interest in MSP. The findings illustrate promising potentials from ranking conflicts and synergies in collaborative settings to make marine activity interests visible in MSP and gain an overview of opportunities for sea use multi-functionality. The use of a visual platform such as Baltic Explorer to systematically explore locations of marine uses was positively evaluated to facilitate the workshop conflict-synergy discussions. Challenges relate to how to deal with disagreements on conflict-synergy scores and the subjectivity of opinions, but the iterative, transparent way to test the sensitivity of spatial patterns to differences in input conflict-synergy scores is found to provide a promising setup for including stakeholder opinions through collaborative settings, a setup adjustable to supplementary large-scale, individual, more representative surveys as well.
  • Prol, F. S.; Ferre, R. Morales; Saleem, Z.; Valisuo, P.; Pinell, C.; Lohan, E. S.; Elsanhoury, M.; Elmusrati, M.; Islam, S.; Celikbilek, K.; Selvan, K.; Yliaho, J.; Rutledge, K.; Ojala, A.; Ferranti, L.; Praks, J.; Bhuiyan, M. Z. H.; Kaasalainen, S.; Kuusniemi, H. (Institute of Electrical and Electronics Engineers (IEEE), 2022)
    IEEE Access
    More and more satellites are populating the sky nowadays in the Low Earth orbits (LEO). Most of the targeted applications are related to broadband and narrowband communications, Earth observation, synthetic aperture radar, and internet-of-Things (IoT) connectivity. In addition to these targeted applications, there is yet-to-be-harnessed potential for LEO and positioning, navigation, and timing (PNT) systems, or what is nowadays referred to as LEO-PNT. No commercial LEO-PNT solutions currently exist and there is no unified research on LEO-PNT concepts. Our survey aims to fill the gaps in knowledge regarding what a LEO-PNT system entails, its technical design steps and challenges, what physical layer parameters are viable solutions, what tools can be used for a LEO-PNT design (e.g., optimisation steps, hardware and software simulators, etc.), the existing models of wireless channels for satellite-to-ground and ground-to-satellite propagation, and the commercial prospects of a future LEO-PNT system. A comprehensive and multidisciplinary survey is provided by a team of authors with complementary expertise in wireless communications, signal processing, navigation and tracking, physics, machine learning, Earth observation, remote sensing, digital economy, and business models.
  • Prol, Fabricio dos Santos (2022)
    This work provides a brief overview of the main challenges found by the author when developing a global ionospheric electron density estimation using tomography and Global Navigation Satellite System (GNSS) data.
  • Koski, Christian; Kettunen, Pyry; Poutanen, Justus; Oksanen, Juha (Copernicus publications, 2022)
    AGILE: GIScience Series
    Deep learning methods for semantic segmentation have shown great potential in automating mapping of geospatial features, including small watercourses such as streams and ditches. There are a variety of small watercourse types. In many use cases users are only interested in specific types of watercourses. However, the impact on results from neural networks trained with only some types of small watercourses, compared to all types of watercourses is not well known. We trained four deep learning models to semantically segment watercourses from an elevation model. One model was trained with all small watercourses in the labels as a single class, while three models were trained each with a single type of watercourse in the label data. The results show that training the network with a single type of watercourse results in worse recall for all three watercourse types, compared to when training all of them together. This indicates that if the goal is to get as complete set of features as possible, it is better to include all watercourse types in the training data. Future studies could use multi-class output from neural network to determine how well networks could automatically classify features when training with all small watercourses in an area.
  • Prol, Fabricio S.; Smirnov, Artem G.; Hoque, M. Mainul; Shprits, Yuri Y. (Springer Science and Business Media LLC, 2022)
    Scientific Reports
    In the last years, electron density profile functions characterized by a linear dependence on the scale height showed good results when approximating the topside ionosphere. The performance above 800 km, however, is not yet well investigated. This study investigates the capability of the semi-Epstein functions to represent electron density profiles from the peak height up to 20,000 km. Electron density observations recorded by the Van Allen Probes were used to resolve the scale height dependence in the plasmasphere. It was found that the linear dependence of the scale height in the topside ionosphere cannot be directly used to extrapolate profiles above 800 km. We find that the dependence of scale heights on altitude is quadratic in the plasmasphere. A statistical model of the scale heights is therefore proposed. After combining the topside ionosphere and plasmasphere by a unified model, we have obtained good estimations not only in the profile shapes, but also in the Total Electron Content magnitude and distributions when compared to actual measurements from 2013, 2014, 2016 and 2017. Our investigation shows that Van Allen Probes can be merged to radio-occultation data to properly represent the upper ionosphere and plasmasphere by means of a semi-Epstein function.
  • Karila, Kirsi; Alves Oliveira, Raquel; Ek, Johannes; Kaivosoja, Jere; Koivumäki, Niko; Korhonen, Panu; Niemeläinen, Oiva; Nyholm, Laura; Näsi, Roope; Pölönen, Ilkka; Honkavaara, Eija (MDPI AG, 2022)
    Remote Sensing
    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 (FY, DMY), the digestibility of organic matter in dry matter (D-value), neutral detergent fiber (NDF), indigestible neutral detergent fiber (iNDF), water-soluble carbohydrates (WSC), nitrogen concentration (Ncont) and nitrogen uptake (NU); datasets from spring and summer growth were used. Deep pre-trained neural network architectures, the VGG16 and the Vision Transformer (ViT), and simple 2D and 3D convolutional neural networks (CNN) were studied. In most cases, the neural networks outperformed RF. The normalized root-mean-square errors (NRMSE) of the best models were for FY 19% (2104 kg/ha), DMY 21% (512 kg DM/ha), D-value 1.2% (8.6 g/kg DM), iNDF 12% (5.1 g/kg DM), NDF 1.1% (6.2 g/kg DM), WSC 10% (10.5 g/kg DM), Ncont 9% (2 g N/kg DM), and NU 22% (11.9 N kg/ha) using independent test dataset. The RGB data provided good results, particularly for the FY, DMY, WSC and NU. The HSI datasets provided advantages for some parameters. The ViT and VGG provided the best results with the RGB data, whereas the simple 3D-CNN was the most consistent with the HSI data.
  • Junttila, Samuli; Campos, Mariana; Hölttä, Teemu; Lindfors, Lauri; El Issaoui, Aimad; Vastaranta, Mikko; Hyyppä, Hannu; Puttonen, Eetu (MDPI AG, 2022)
    Forests
    Physiological processes cause movements of tree stems and branches that occur in a circadian rhythm and over longer time periods, but there is a lack of quantitative understanding of the cause-and-effect relationships. We investigated the movement of tree branches in a long-term drought experiment and at a circadian time scale using time-series of terrestrial laser scanning measurements coupled with measurements of environmental drivers and tree water status. Our results showed that movement of branches was largely explained by leaf water status measured as leaf water potential in a controlled environment for both measured trees (R2 = 0.86 and R2 = 0.75). Our hypothesis is that changes in leaf and branch water status would cause branch movements was further supported by strong relationship between vapor pressure deficit and overnight branch movement (R2 = [0.57–0.74]). Due to lower atmospheric water demand during the nighttime, tree branches settle down as the amount of water in leaves increases. The results indicate that the quantified movement of tree branches could help us to further monitor and understand the water relations of tree communities.
  • Wang, Di; Puttonen, Eetu; Casella, Eric (Elsevier BV, 2022)
    International Journal of Applied Earth Observation and Geoinformation
    The mechanisms involved in organ motions are central to our understanding of how plants develop and respond to environmental stimuli such as light quality, gravity, and water availability throughout time. Recent studies have shown that motions in plants such as circadian rhythms and growth patterns, can be recorded and quantified from time series of terrestrial laser scans (TLS). However, most works monitored the changes of certain functional traits such as height and volume to detect and analyze structural dynamics. A generic method for retrieving fine-scale three-dimensional (3D) motion fields of plant structural movements is still missing. We present PlantMove, a new fully automatic tool to quantify 3D motion fields of plant structural movements with varied magnitudes using TLS point clouds acquired over different time periods. The method uses spatio-temporal point cloud registration embedded in a progressive and coarse-to-fine framework, enabling an efficient processing of large datasets with complex structures. PlantMove was first demonstrated on synthetic plant datasets, displaying millimeter to centimeter level accuracy of retrieved motion fields. In addition, PlantMove was used to assess circadian rhythms on a birch tree from TLS data acquired over the course of one night with about one-hour time intervals, and growth patterns on an English oak from a four-year TLS survey. PlantMove can help to better monitor plant phenotypic plasticity with fine level of details, and can contribute to improve our understanding in plant dynamics across various spatial and temporal scales.
  • Monico, João Francisco Galera; de Paula, Eurico Rodrigues; Moraes, Alison de Oliveira; Costa, Emanoel; Shimabukuro, Milton Hirokazu; Alves, Daniele Barroca Marra; de Souza, Jonas Rodrigues; Camargo, Paulo de Oliveira; Prol, Fabricio dos Santos; Vani, Bruno César; Pereira, Vinicius Stuani Amadeo; de Oliveira Junior, Paulo Sergio; Tsuchiya, Italo; Aguiar, Claudinei Rodrigues (2022)
    Journal of Aerospace Technology and Management
    Air navigation is increasingly dependent on the use of Global Navigation Satellite Systems (GNSS). It allows the determination of the aircraft’s position in all phases of the flight and brings many advantages. Although GNSS navigation results in gains, the radio signals from these systems are strongly influenced by the ionospheric environment. It introduces errors that can affect the accuracy, integrity, availability and continuity requirements established by the International Civil Aviation Organization (ICAO). The ionospheric layer has different behaviors depending on the latitude, time of day, season of the year, geomagnetic activity and solar cycle. Since Brazil is located in a region of low latitudes, it experiences a series of unique challenges when compared to regions of mid-latitudes. For this reason, the application of GNSS-based technologies in aviation over the Brazilian territory requires an in-depth assessment of the ionosphere effects. Therefore, the Instituto Nacional de Ciência e Tecnologia (INCT) named GNSS Technology for Supporting Air Navigation was formed in 2017 to better assess the ionosphere impacts and assist government agencies and companies in the development of safe air navigation procedures over Brazil in a near future. This paper presents the most relevant advances achieved so far within this multidisciplinary project that involves Brazilian research centers and universities.
  • Prol, Fabricio S.; Hoque, Mohammed Mainul (Institute of Electrical and Electronics Engineers (IEEE), 2022)
    IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
    A tomographic method has been developed for reconstructing the topside ionospheric and plasmaspheric electron density distribution using total electron content (TEC) measurements from global positioning system (GPS) receivers aboard the constellation observing system for meteorology, ionosphere, and climate/Formosa Satellite Mission 3 (COSMIC/FORMOSAT-3). Since the COSMIC/FORMOSAT-3 constellation has an orbit altitude of about 800 km, the integral TEC measurements obtained from the topside GPS navigation data are rather small and imposed relevant challenges to obtaining stable electron density reconstructions. However, the developed method can represent the natural variability of the plasma ambient in terms of latitude, altitude, solar activity, season, and local time when analyzing electron density reconstructions during 2008–2013. The method employs independent spatial grids for satellite rising and setting geometries and imposes a set of constraints to stabilize the solution in the presence of noise and ill-conditioned geometry. We further consider background ionosphere and plasmasphere models for electron density initialization and filling data gaps. The quality assessment using TEC and in-situ electron density measurements has shown that the proposed method performs better than the background model, with improvements of about 26% in TEC and 20% in terms of electron density. Our investigation also reveals the necessity of more accurate background electron density representations and precise TEC measurements in order to have better plasmaspheric specifications at high altitudes.
  • Islam, Saiful; Bhuiyan, Mohammad Zahidul H.; Thombre, Sarang; Kaasalainen, Sanna (MDPI AG, 2022)
    Sensors
    Today, a substantial portion of global trade is carried by sea. Consequently, the reliance on Global Navigation Satellite System (GNSS)-based navigation in the oceans and inland waterways has been rapidly growing. GNSS is vulnerable to various radio frequency interference. The objective of this research is to propose a resilient Multi-Frequency, Multi-Constellation (MFMC) receiver in the context of maritime navigation to identify any GNSS signal jamming incident and switch to a jamming-free signal immediately. With that goal in mind, the authors implemented a jamming event detector that can identify the start, end, and total duration of the detected jamming event on any of the impacted GNSS signal(s). By utilizing a jamming event detector, the proposed resilient MFMC receiver indeed provides a seamless positioning solution in the event of single-frequency jamming on either the lower or upper L-band. In addition, this manuscript also contains positioning performance analysis of GPS-L5-only, Galileo-E5a-only, and Galileo-E5b-only signals and their multiGNSS combinations in a maritime operational environment in the Gulf of Finland. The positioning performance of lower L-band GNSS signals in a maritime environment has not been thoroughly investigated as per the authors’ knowledge.
  • Castanheiro, Leticia; Tommaselli, Antonio; Campos, Mariana Batista; Berveglieri, Adilson (ISPRS, 2021)
    ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
    Fisheye cameras have been widely used in photogrammetric applications, but conventional techniques must be adapted to consider specific features of fisheye images, such as nonuniform resolution in the images. This work presents experimental results of an adaptive weighting of the observation in a self-calibrating bundle adjustment to cope with the nonuniform resolution of fisheye images. GoPro Fusion and Ricoh Theta dual-fisheye systems were calibrated with bundle adjustment based on equisolid-angle projection model combined with Conrady-Brown distortion model. The image observations were weighted as a function of radial distance based on combining loss of resolution and blurring in fisheye images. The results were compared with a similar trial by considering the same standard deviation for all image observations. The use of adaptive weighting of image observations reduced the estimated standard deviation of unit weight by 30 % and 50 % with GoPro Fusion and Ricoh Theta images, respectively. The estimation of relative orientation parameters (ROPs) was also improved (∼50 %) when using adaptive weighting for image observations
  • Hiremath, Santosh; Wittke, Samantha; Palosuo, Taru; Kaivosoja, Jere; Tao, Fulu; Proll, Maximilian; Puttonen, Eetu; Peltonen-Sainio, Pirjo; Marttinen, Pekka; Mamitsuka, Hiroshi (Public Library of Science, 2021)
    PLoS ONE
    Identifying crop loss at field parcel scale using satellite images is challenging: first, crop loss is caused by many factors during the growing season; second, reliable reference data about crop loss are lacking; third, there are many ways to define crop loss. This study investigates the feasibility of using satellite images to train machine learning (ML) models to classify agricultural field parcels into those with and without crop loss. The reference data for this study was provided by Finnish Food Authority (FFA) containing crop loss information of approximately 1.4 million field parcels in Finland covering about 3.5 million ha from 2000 to 2015. This reference data was combined with Normalised Difference Vegetation Index (NDVI) derived from Landsat 7 images, in which more than 80% of the possible data are missing. Despite the hard problem with extremely noisy data, among the four ML models we tested, random forest (with mean imputation and missing value indicators) achieved the average AUC (area under the ROC curve) of 0.688±0.059 over all 16 years with the range [0.602, 0.795] in identifying new crop-loss fields based on reference fields of the same year. To our knowledge, this is one of the first large scale benchmark study of using machine learning for crop loss classification at field parcel scale. The classification setting and trained models have numerous potential applications, for example, allowing government agencies or insurance companies to verify crop-loss claims by farmers and realise efficient agricultural monitoring.
  • Prol, Fabricio dos Santos; Kodikara, Timothy; Hoque, Mohammed Mainul; Borries, Claudia (American Geophysical Union, 2021)
    Space Weather: The International Journal of Research and Applications
    The correct representation of global-scale electron density is crucial for monitoring and exploring the space weather. This study investigates whether the ground-based Global Navigation Satellite System (GNSS) tomography can be used to reflect the global spatial and temporal responses of the ionosphere under storm conditions. A global tomography of the ionosphere electron density is constructed based on data from over 2,700 GNSS stations. In comparison to previous techniques, advances are made in spatial and temporal resolution, and in the assessment of results. To demonstrate the capabilities of the approach, the developed method is applied to the March 17, 2015 geomagnetic storm. The tomographic reconstructions show good agreement with electron density observations from worldwide ionosondes, Millstone Hill incoherent scatter radar and in-situ measurements from satellite missions. Also, the results show that the tomographic technique is capable of reproducing plasma variabilities during geomagnetically disturbed periods including features such as equatorial ionization anomaly enhancements and depletion. Validation results of this brief study period show that the accuracy of our tomography is better than the Neustrelitz Electron Density Model, which is the model used as background, and physics-based thermosphere-ionosphere-electrodynamics general circulation model. The results show that our tomography approach allows us to specify the global electron density from ground to ∼900 km accurately. Given the demonstrated quality, this global electron density reconstruction has potential for improving applications such as assessment of the effects of the electron density on radio signals, GNSS positioning, computation of ray tracing for radio-signal transmission, and space weather monitoring.
  • Vantola, Renne; Luoma, Emilia; Parviainen, Tuuli; Lehikoinen, Annukka (Elsevier, 2021)
    Marine Pollution Bulletin
    Marinas are a part of coastal areas’ touristic appeal, but also hotspots for boat-sourced pollution. Considering the manifestation of sustainability in marina operation, we utilize actor-network theory (ANT) in demonstrating a conceptual systems analysis on boat-sourced sewage management (BSSM) as one important socio-eco-technical sub-system of sustainable nautical tourism. We describe a multi-material collective of dynamically interacting human and non-human entities to understand how and under what conditions BSSM facilities advance the sustainability of marina operation. Our analysis insightfully uncovers BSSM facilities as both core marina services and governance artefacts and reveals that managing boat-sourced sewage successfully is an outcome of a multi- sited network of heterogeneous elements that together enable both sustainable boating practices and marina operation. We suggest the presented ANT-based systemic thinking has potential for providing novel perspectives to sustainability analyses in diverse tourism-related contexts.
  • Lahtinen, Sonja; Jivall, Lotti; Häkli, Pasi; Nordman, Maaria (Springer, 2021)
    GPS Solutions
    In Fennoscandia, the Glacial Isostatic Adjustment (GIA) causes intraplate deformations that affect the national static reference frames. The GNSS-determined velocities are important data for constraining the GIA models, which are necessary for maintaining the national reference frames. The Nordic Geodetic Commission (NKG) has published a dense and consistent GNSS station velocity solution in 2019, and we present now an update of the solution covering additional 3.5 years of data. Undetected positional offsets are the main factor decreasing the accuracy of the velocity estimates. We developed a method for the semi-automatic offset detection to improve the quality of our solution. The results show that we could correctly detect 74% of the manually determined offsets, and the undetected offsets would have caused a median 0.1 mm/y bias in trend. The method pointed out some otherwise unnoticed offsets and will decrease the need for manual analysis in the future. The updated velocity solution especially improves the velocity estimates of the newly established stations and the quality of the velocity estimates in Baltic countries. The formal uncertainties estimated using the power-law plus white noise model were at a median of 0.06 and 0.15 mm/y for horizontal and vertical velocities, respectively. However, we concluded that the systematic velocity uncertainties due to the reference frame alignment were approximately at the same level.
  • Suomalainen, Juha; Oliveira, Raquel A.; Hakala, Teemu; Koivumäki, Niko; Markelin, Lauri; Näsi, Roope; Honkavaara, Eija (Elsevier, 2021)
    Remote Sensing of Environment
    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 sensor, allowing transformation of image pixel values to reflectance factors without ground reference data. This method requires the sensors to be calibrated with higher accuracy than what is usually required by the empirical line method (ELM), but consequently it offers benefits in robustness, ease of operation, and ability to be used on Beyond-Visual Line of Sight flights. The objective of this study was to develop and assess a drone-based workflow for direct reflectance transformation and implement it on our hyperspectral remote sensing system. A novel atmospheric correction method is also introduced, using two reference panels, but, unlike in the ELM, the correction is not directly affected by changes in the illumination. The sensor system consists of a hyperspectral camera (Rikola HSI, by Senop) and an onboard irradiance spectrometer (FGI AIRS), which were both given thorough radiometric calibrations. In laboratory tests and in a flight experiment, the FGI AIRS tilt-corrected irradiances had accuracy better than 1.9% at solar zenith angles up to 70◦. The system’s lowaltitude reflectance factor accuracy was assessed in a flight experiment using reflectance reference panels, where the normalized root mean square errors (NRMSE) were less than ±2% for the light panels (25% and 50%) and less than ±4% for the dark panels (5% and 10%). In the high-altitude images, taken at 100–150 m altitude, the NRMSEs without atmospheric correction were within 1.4%–8.7% for VIS bands and 2.0%–18.5% for NIR bands. Significant atmospheric effects appeared already at 50 m flight altitude. The proposed atmospheric correction was found to be practical and it decreased the high-altitude NRMSEs to 1.3%–2.6% for VIS bands and to 2.3%– 5.3% for NIR bands. Overall, the workflow was found to be efficient and to provide similar accuracies as the ELM, but providing operational advantages in such challenging scenarios as in forest monitoring, large-scale autonomous mapping tasks, and real-time applications. Tests in varying illumination conditions showed that the reflectance factors of the gravel and vegetation targets varied up to 8% between sunny and cloudy conditions due to reflectance anisotropy effects, while the direct reflectance workflow had better accuracy. This suggests that the varying illumination conditions have to be further accounted for in drone-based in quantitative remote sensing applications.
  • Koski, Christian; Rönneberg, Mikko; Kettunen, Pyry; Armoškaitė, Aurelija; Strake, Solvita; Oksanen, Juha (John Wiley & Sons, 2021)
    Transactions in GIS
    Maritime spatial planning (MSP) is a decision-making process for managing human activities at sea. Stakeholder participation is critical to MSP processes. Spatial decision support systems (SDSSs) can be effective tools for analyzing problems in MSP, for example, the impact of human activities on marine ecosystems. However, despite the fact that multiple SDSSs have been developed for MSP, they are rarely used in real-world MSP processes. We aim to provide insight into stakeholders' understanding and perception of the appropriateness and completeness of SDSSs in an MSP stakeholder meeting. We studied whether SDSSs can benefit from being integrated into CGIS to support alternative methods for problem exploration and solving in groups. The results show that most, but not all, stakeholders understood well or fairly well what the tool does and how to use it, and agreed that the tool was appropriate and had the necessary requirements for problem solving. The results also show that problem exploration and solving with an SDSS in groups can benefit from the tool being integrated into a CGIS. Further research is needed to find effective solutions to overcome stakeholders' challenges in using GIS, and to develop flexible solutions that enable alternative problem-solving methods.

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