National Land Survey of Finland

The National Land Survey of Finland performs cadastral surveys, maintains property information, produces geospatial information, handles registrations of title and mortgages, develops ICT systems, and promotes the research of spatial data.

The Finnish Geospatial Research Institute (FGI) acts as a research unit in the National Land Survey of Finland, and it conducts research and expert work within the field of spatial data. The esteemed international research institute offers reliable information for the benefit of society. More information: www.fgi.fi

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  • 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.
  • Kilpeläinen, Tiina (Finnish Geodetic Institute, 1997)
    FGI Publications 124
  • Kivekäs, Riikka (2021)
    Positio
  • Heikkinen, Markku (Finnish Geodetic Institute, 1981)
    FGI Reports 81:2
  • 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.
  • Ahonen-Rainio, Paula; Kilpelä, Niina; Majurinen, Hanna; Myllymäki, Tarja; Niemi, Tommi; Nurmi, Tomi; Uotila, Suvi; Uusitalo, Jaakko; Suhonen, Sirpa (Maanmittauslaitos, 2021)
    Sanastokeskus TSK 56
  • 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.
  • Reini, Jari; Kivekäs, Riikka (2021)
    Positio
  • Kivekäs, Riikka (2021)
    Positio
  • Seppänen, EILA; Mikkanen, ULLA; Saari, Timo (2021)
    Positio
  • Järvenpää, Elise; Pyysalo, Ulla; Haakana, Markus; Korhonen, Kari T.; Munck, Anders (2021)
    Positio

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