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:


Recent Submissions

  • 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)
  • Kivekäs, Riikka (2021)
  • Seppänen, EILA; Mikkanen, ULLA; Saari, Timo (2021)
  • Järvenpää, Elise; Pyysalo, Ulla; Haakana, Markus; Korhonen, Kari T.; Munck, Anders (2021)
  • 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.
  • Maanpää, Jyri; Taher, Josef; Manninen, Petri; Pakola, Leo; Melekhov, Iaroslav; Hyyppä, Juha (IEEE, 2021)
    Proceedings of ICPR 2020: 25th International Conference on Pattern Recognition, Milan, 10 – 15 January 2021
    Autonomous driving is challenging in adverse road and weather conditions in which there might not be lane lines, the road might be covered in snow and the visibility might be poor. We extend the previous work on end-to-end learning for autonomous steering to operate in these adverse real-life conditions with multimodal data. We collected 28 hours of driving data in several road and weather conditions and trained convolutional neural networks to predict the car steering wheel angle from front-facing color camera images and lidar range and reflectance data. We compared the CNN model performances based on the different modalities and our results show that the lidar modality improves the performances of different multimodal sensor-fusion models. We also performed on-road tests with different models and they support this observation.
  • Koivula, Hannu (Aalto University, Department of Built Environment, 2019)
    FGI Publications 159
  • Jakobsson, Antti; Lehto, Lassi (2021)
  • Kukko, Antero; Kaartinen, Harri; Hyyppä, Hannu (2021)
  • Ouattara, Issouf; Hyyti, Heikki; Visala, Arto (Elsevier, 2020)
    IFAC-PapersOnLine, Proceedings of the 21th IFAC World Congress, Berlin, Germany, 12-17 July 2020
    We propose a novel method to locate spruces in a young stand with a low cost unmanned aerial vehicle. The method has three stages: 1) the forest area is mapped and a digital surface model and terrain models are generated, 2) the locations of trees are found from a canopy height model using local maximum and watershed algorithms, and 3) these locations are used in a convolution neural network architecture to detect young spruces. Our result for detecting young spruce trees among other vegetation using only color images from a single RGB camera were promising. The proposed method is able to achieve a detection accuracy of more than 91%. As low cost unmanned aerial vehicles with color cameras are versatile today, the proposed work is enabling low cost forest inventory for automating forest management.
  • Sandru, Andrei; Hyyti, Heikki; Visala, Arto; Kujala, Pentti (Elsevier, 2020)
    IFAC-PapersOnLine, Proceedings of the 21th IFAC World Congress, Berlin, Germany, 12-17 July 2020
    A sensor instrumentation and an automated process are proposed for sea-ice field analysis using ship mounted machine vision cameras with the help of inertial and satellite positioning sensors. The proposed process enables automated acquisition of sea-ice concentration, floes size and distribution. The process contains pre-processing steps such as sensor calibration, distortion removal, orthorectification of image data, and data extraction steps such as sea-ice floe clustering, detection, and analysis. In addition, we improve the state of the art of floe clustering and detection, by using an enhanced version of the k-means algorithm and the blue colour channel for increased contrast in ice detection. Comparing to manual visual observations, the proposed method gives significantly more detailed and frequent data about the size and distribution of individual floes. Through our initial experiments in pack ice conditions, the proposed system has proved to be able to segment most of the individual floes and estimate their size and area.
  • Bilker-Koivula, Mirjam (Unigrafia Oy, 2021)
    FGI Publications
    Positioning using Global Navigation Satellite Systems (GNSS) is widely used nowadays and it is getting more and more accurate. This requires also better geoid models for the transformation between heights measured with GNSS and heights in the national height system. In Finland heights are continuously changing due to the Fennoscandian postglacial rebound. Land uplift models are developed for the Fennoscandian land uplift area, not only for the vertical velocities, but also for the gravity change related to postglacial rebound. In this dissertation geoid studies were carried out in search of the geoid model that is most suitable for the conversion of GNSS heights in the EUREF-FIN coordinate system to heights in the Finnish height system N2000 on land as well as on sea. In order to determine the relationship between gravity change rates and vertical velocities, time series of absolute gravity measurements were analysed. Methods were tested for fitting a geoid model to GNSS-levelling data. The best method for Finland was found to be least-squares collocation in combination with cross-validation. The result was the height conversion surface FIN2005N00, the official model for Finland. Then, high-resolution global gravity field models were tested in geoid modelling for Finland. The resulting geoid models were better than the earlier geoid models for Finland. After correcting for an offset and tilt, the differences with other models disappeared. Also, a method was developed to validate geoid models at sea using GNSS measurements collected on a vessel. The method was successful and key elements were identified for the process of reducing the GNSS observations from the height of observation down to the geoid surface. Possible offsets between different types of absolute gravimeters were investigated by looking at the results of international comparisons, bi-lateral comparisons and of trend calculations. The trend calculations revealed significant offsets of 31.4 ± 10.9 μGal, 32.6 ± 7.4 μGal and 6.8 ± 0.8 μGal for the IMGC, GABL and JILAg-5 instruments. The time series of absolute gravity measurements at 12 stations in Finland were analysed. At seven stations reliable trends could be determined. Ratios between -0.206 ± 0.017 and -0.227 ± 0.024 μGal/mm and axis intercept values between 0.248 ± 0.089 and 0.335 ± 0.136 μGal/yr were found for the relationship between gravity change rates and vertical velocities. These values are larger than expected based on results of others. The knowledge obtained in the geoid studies will be of benefit in the determination of the next generation geoid models and height conversion surfaces for Finland. Before clear conclusions can be drawn from the absolute gravity results, more studies related to glacial isostatic adjustment, and longer high-quality time series from more stations in Finland, as well as the whole of the uplift area and its boundaries, are needed.
  • Kakkuri, Juhani (Maanmittauslaitos, 2021)
    FGI Publications
  • Koski, Christian; Rönneberg, Mikko; Kettunen, Pyry; Eliasen, Søren; Hansen, Henning Sten; Oksanen, Juha (John Wiley & Sons, 2021)
    Transactions in GIS
    Maritime spatial planning (MSP) needs tools to facilitate discussions and manage spatial data in collaborative workshops that involve actors with various backgrounds and expertise. However, the reported use of spatial tools in real‐world MSP is sparse. A better understanding is needed of how geographic information systems (GIS) can effectively support collaboration in MSP. We studied the utility of GIS tools for collaborative MSP in five steps: first, identifying shortcomings in available GIS for supporting collaborative MSP; second, defining requirements for an effective collaborative GIS (CGIS) for MSP; third, designing and developing a prototype CGIS, Baltic Explorer; fourth, demonstrating the system; and fifth, evaluating the system. In a real‐world MSP workshop, we demonstrated that the functionalities of Baltic Explorer can support and facilitate discussions in collaborative work. We also found that more research is needed about the use of spatial data in collaborative MSP and integration of model‐based geospatial analysis into CGIS.
  • Saari, Timo; Bilker-Koivula, Mirjam; Koivula, Hannu; Nordman, Maaria; Häkli, Pasi; Lahtinen, Sonja (Taylor & Francis, 2021)
    Marine Geodesy
    Traditionally, geoid models have been validated using GNSS-levelling benchmarks on land only. As such benchmarks cannot be established offshore, marine areas of geoid models must be evaluated in a different way. In this research, we present a marine GNSS/gravity campaign where existing geoid models were validated at sea areas by GNSS measurements in combination with sea surface models. Additionally, a new geoid model, calculated using the newly collected marine gravity data, was validated. The campaign was carried out with the marine geology research catamaran Geomari (operated by the Geological Survey of Finland), which sailed back and forth the eastern part of the Finnish territorial waters of the Gulf of Finland during the early summer of 2018. From the GNSS and sea surface data we were able to obtain geoid heights at sea areas with an accuracy of a few centimetres. When the GNSS derived geoid heights are compared with geoid heights from the geoid models differences between the respective models are seen in the most eastern and southern parts of the campaign area. The new gravity data changed the geoid model heights by up to 15 cm in areas of sparse/non-existing gravity data.

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