Finnish Geospatial Research Institute National Land Survey
Organisation type:
Research institutions
Country:
Finland
Short name:
FGI
Description:
The Finnish Geospatial Research Institute (FGI) is a part of the National Land Survey (NLS) of Finland, which a governmental organization under the Ministry of Agriculture and Forestry in Finlan. The NLS is responsible for land surveying tasks in Finland, from parcelling and reallocations of pieces of land to the maintenance of the Cadastral registry and the national topographic database, which form the foundation of the digital maps in Finland. The FGI (formerly the Finnish Geodetic Institute) is a highly international research organization having the staff of about 120 people at the moment. The core task of the FGI is to carry out scientific research in the fields of geodesy, positioning, navigation, cartography, geographic information sciences, photogrammetry and remote sensing, and to transfer this knowledge into the society at all levels. The FGI department of Remote Sensing and Photogrammetry of the FGI focuses on novel remote sensing techniques; hyper- and multispectral imaging, Laser scanning technology, applications of Earth Observation data, and digital photogrammetry. Starting from 2013, the RSP dept. has hosted the Center of Excellence in Laser Scanning of the Academy of Finland (http://laserscanning.fi/) and coordinated the EU/FP7-Space Advanced_SAR project (http://www.fgi.fi/advancedsar). Today we also coordinate Academy of Finland STN project @pointcloudfi, (www.pointcloud.fi) as well as the EuroSDR TLS comparison project, and Science and Innovation center for drone mapping technology (www.dronefinland.fi). The RSP dept. has participated in satellite projects funded by the European Space Agency, e.g., demonstrated the use of satellite data in rice monitoring in Vietnam for the UN-IFAD. Moreover, the RSP dept. has actively participated in the scientific satellite projects of the ESA, DLR and CSA.
The FGI @dronefinland team (www.dronefinland.fi; led by Prof. E. Honkavaara) provides extensive empirical RS facilities and know-how on drone remote sensing, including hardware, calibration, and machine learning. Examples of the relevant hardware/software include several multirotor UAVs, GNSS/IMU, multi- and hyperspectral (400-1700 nm; Senop, Specim, Micasense), RGB, 360-, and thermal cameras, lightweight laser scanners (e.g. Riegl MiniVUX), spectrometers, on-board computers (Nvidia Jetson TX2, Xavier), and extensive in-house, open, and commercial software. Team is developing scientific grade techniques for vegetation measurements, phenotyping, and health analysis. Furthermore, team is developing real-time capable hardware systems to enable crop analysis in real-time. Previous application studies have included the silage grass quality and quantity estimation and barley biomass and N-content estimation for precision agriculture, and tree species and insect disturbance detection for forestry.
The FGI research group "Mapping and Change Analysis Applications with Multiple Scale Remote Sensing" (https://www.maanmittauslaitos.fi/en/node/11108; contact: Dr. Eetu Puttonen & Dr. (Tech.) Mika Karjalainen) develops automatic methods to interpret remote sensing and Earth observation data and their changes. The group uses several, different scale, data sources including satellite data and dense laser scanning point clouds. The main study aim of the group is to improve the efficiency of mapping applications, map updating, and land use monitoring by combining data from different sources and increasing their automatic processing. The group exploits several different data sources in its research, including open Earth observation data (ESA Sentinel-2), state-of-the-art multiwavelength laser scanning data (Optech Titan), and datasets collected with in FGI developed UAV and mobile mapping platforms (NLS Roamer). The data interpretation techniques include object-based approaches and efficient classification and machine learning algorithms. The group has created it's own toolbox ("EODIE": https://www.researchgate.net/project/EODIE-Processing-pipeline-toolbox-for-Sentinel-2-time-series) for Sentinel-2 time series extraction on object level.
Finnish Geospatial Research Institute
National Land Survey
The Finnish Geospatial Research Institute (FGI) is a part of the National Land Survey (NLS) of Finland, which a governmental organization under the Ministry of Agriculture and Forestry in Finlan. The NLS is responsible for land surveying tasks in Finland, from parcelling and reallocations of pieces of land to the maintenance of the Cadastral registry and the national topographic database, which form the foundation of the digital maps in Finland. The FGI (formerly the Finnish Geodetic Institute) is a highly international research organization having the staff of about 120 people at the moment. The core task of the FGI is to carry out scientific research in the fields of geodesy, positioning, navigation, cartography, geographic information sciences, photogrammetry and remote sensing, and to transfer this knowledge into the society at all levels. The FGI department of Remote Sensing and Photogrammetry of the FGI focuses on novel remote sensing techniques; hyper- and multispectral imaging, Laser scanning technology, applications of Earth Observation data, and digital photogrammetry. Starting from 2013, the RSP dept. has hosted the Center of Excellence in Laser Scanning of the Academy of Finland (http://laserscanning.fi/) and coordinated the EU/FP7-Space Advanced_SAR project (http://www.fgi.fi/advancedsar). Today we also coordinate Academy of Finland STN project @pointcloudfi, (www.pointcloud.fi) as well as the EuroSDR TLS comparison project, and Science and Innovation center for drone mapping technology (www.dronefinland.fi). The RSP dept. has participated in satellite projects funded by the European Space Agency, e.g., demonstrated the use of satellite data in rice monitoring in Vietnam for the UN-IFAD. Moreover, the RSP dept. has actively participated in the scientific satellite projects of the ESA, DLR and CSA.
The FGI @dronefinland team (www.dronefinland.fi; led by Prof. E. Honkavaara) provides extensive empirical RS facilities and know-how on drone remote sensing, including hardware, calibration, and machine learning. Examples of the relevant hardware/software include several multirotor UAVs, GNSS/IMU, multi- and hyperspectral (400-1700 nm; Senop, Specim, Micasense), RGB, 360-, and thermal cameras, lightweight laser scanners (e.g. Riegl MiniVUX), spectrometers, on-board computers (Nvidia Jetson TX2, Xavier), and extensive in-house, open, and commercial software. Team is developing scientific grade techniques for vegetation measurements, phenotyping, and health analysis. Furthermore, team is developing real-time capable hardware systems to enable crop analysis in real-time. Previous application studies have included the silage grass quality and quantity estimation and barley biomass and N-content estimation for precision agriculture, and tree species and insect disturbance detection for forestry.
The FGI research group "Mapping and Change Analysis Applications with Multiple Scale Remote Sensing" (https://www.maanmittauslaitos.fi/en/node/11108; contact: Dr. Eetu Puttonen & Dr. (Tech.) Mika Karjalainen) develops automatic methods to interpret remote sensing and Earth observation data and their changes. The group uses several, different scale, data sources including satellite data and dense laser scanning point clouds. The main study aim of the group is to improve the efficiency of mapping applications, map updating, and land use monitoring by combining data from different sources and increasing their automatic processing. The group exploits several different data sources in its research, including open Earth observation data (ESA Sentinel-2), state-of-the-art multiwavelength laser scanning data (Optech Titan), and datasets collected with in FGI developed UAV and mobile mapping platforms (NLS Roamer). The data interpretation techniques include object-based approaches and efficient classification and machine learning algorithms. The group has created it's own toolbox ("EODIE": https://www.researchgate.net/project/EODIE-Processing-pipeline-toolbox-for-Sentinel-2-time-series) for Sentinel-2 time series extraction on object level.
Contacts: