Tartu Observatory is an institute of the Faculty of Science and Technology of the University of Tartu (Tartu Ulikool). The principal tasks of Tartu Observatory are research, teaching, development and services for the society in the areas of astronomy, remote sensing, space technology, and connected fields.
Role in the project
In WP2 TU will substantially support the Use Case on ‘Farmer Performance’ (1c).
TU will also contribute to the Innovation Ecosystem of WP5 in the analysis of the state of play (T5.1). This comprises analysis and consultation about optical remote sensing data including data from Copernicus Sentinel-2 and other higher spatial resolution sensors.
Key persons involved
Dr. Mait Lang is a Senior Research Fellow in Tartu Observatory, University of Tartu and Estonian University of Life Sciences. His main research topic is estimation of forest descriptive variables from remote sensing data. He has competence on processing multispectral satellite images, airborne laser scanning data and digital hemispherical images as well long term experiences on working with spatial data in GIS. He has recently started to experiment with machine learning for the application of land cover mapping and tree species composition estimation for forest stands.
Dr. Jan Pisek is a Senior Research Fellow in Tartu Observatory, University of Tartu, PhD in physical geography and remote sensing in 2009 from the University of Toronto. He is developing remote sensing applications to earth system processes and biophysical parameter and vegetation structure mapping. Jan is a member of the editorial board for the scientific journal Remote Sensing of Environment.
Lang, Mait; Nilson, Tiit; Kuusk, Andres; Pisek, Jan; Korhonen, Lauri; Uri, Veiko (2017). Digital photography for tracking the phenology of an evergreen conifer stand. Agricultural and Forest Meteorology, 246, 15−21.10.1016/j.agrformet.2017.05.021.
Lang, Mait; Vain, Ants; Bunce, Robert Gerald Henry; Jongman, Rob; Raet, Janar; Sepp, Kalev; Kuusemets, Valdo; Kikas, Tambet; Liba, Natalja (2015). Extrapolation of in situ data from 1-km squares to adjacent squares using remote sensed imagery and airborne lidar data for the assessment of habitat diversity and extent. Environmental Monitoring and Assessment, 187 (3), 1−16.10.1007/s10661-015-4270-7.
Pisek, J.; Govind, A.; Arndt, S.; Hocking, D.; Wardlaw, T.; Fang, H.; Matteucci, G.; Longdoz, B. (2015). Intercomparison of clumping index estimates from POLDER, MODIS, and MISR satellite data over reference sites. ISPRS Journal of Photogrammetry & Remote Sensing, 101, 47−56.
Lang, M., Arumäe, T., Lükk, T., Sims, A. 2014. Estimation of standing wood volume and species composition in managed nemoral multi-layer mixed forests by using nearest neighbour classifier, multispectral satellite images and airborne lidar data. – Forestry Studies | Metsanduslikud Uurimused 61, 47–68.
Lang, M., Kõlli, R., Nikopensius, M., Nilson, T., Neumann, M., Moreno, A. 2017. Assessment of MODIS NPP algorithm-based estimates using soil fertility and forest inventory data in mixed hemiboreal forests. – Forestry Studies | Metsanduslikud Uurimused 66, 49–64.
Relevant projects and activities
• H2020: MULTIPLY - MULTIscale SENTINEL land surface information retrieval PLatform (01.01.2016−31.12.2019).
• ESA: FRM4SOC - Fiducial reference measurements for satellite ocean colour (01.06.2016- 30.11.2018).
• BalticSatApps - Speeding up Copernicus Innovation for the BSR Environment and Security (01.10.2017- 01.09.2020).
• Puistuplaan 2017 - Species composition map of forest stands in Estonia based on Sentinel-2 data (20.02.2017-31.01.2018).
• GLAMORAS - GLobAl Mapping Of forest undeRstory with ApplicationS (01.01.2017-31.12.2020)