Description: The masses in the Earth’s atmosphere and surface cause the crust to deform. Part of these mass movements are periodic, e.g. tides in the oceans and in the atmosphere, but there are also non-periodic movements. Periodic (tidal) phenomena are quite well understood and modelled, whereas the non-periodic (non-tidal) phenomena are harder to model due to non-repeating patterns in the mass changes. Understanding the tidal and non-tidal loading improves the quality of the geodetic time series and thus, improves the stability of the reference frames. The tidal corrections to geodetic time series are done routinely, following recommendations and guidelines of the IERS Conventions. We investigated the 3D deformations in Fennoscandia induced by non-tidal atmospheric loading (NTAL) through GNSS time series modeling using GAMIT/GLOBK software. We have used 5 months of data from continuous GNSS stations belonging to FinnRef (Finnish Permanent GNSS Network) and EPN (EUREF Permanent GNSS Network) from year 2015. Two coordinate time series solutions were generated: first (reference) solution was estimated without applying loading model, while for the second solution a gridded loading model was used. We also downloaded loading correction time series from an openly available server and created the third time series by subtracting the loading correction from the reference time series. We compared the variance of three time series to see which method produces the most stable time series. The effect of NTAL correction is quite small, but not insignificant and the implementation trough the software is the most straightforward way of doing it.

Description: What are the skills that we are teaching in our Master’s program in Geoinformatics? How useful those skills are for the new graduates and which skills do they end up using in their working life? What are the skills that the companies that are hiring the new graduates are looking for? As part of renewing our Master’s program we asked our alumni which skills they have found useful in the working life. We also asked a group of our stakeholders to evaluate the same skills for the people they might be hiring. We had a set of predefined skills, both general and field-specific, that we asked the answerers to rate based on their usefulness in the working life. There was also option for commenting the skill set and adding something that was missing. The results show that both groups find the problem-solving skills the most important general skill. For the alumni the other two skills in top three were project management and team-work skills, whereas the people who might be hiring the graduates ranked programming and writing skills above them. From the field-specific skills understanding and implementing theories was the ranked as the most important. Other skills, such as data analysis or management of measuring process, were ranked in varying places depending on the duties of the person answering. Based on the results we are going to critically evaluate our course contents and add components of problem solving and team working where possible.

Description: The Earth’s surface is continuously deforming at various temporal and spatial scales. The deformation is caused by the changing mass distribution of atmospheric, oceanic, hydrological masses, glaciers and ice sheets as well as earthquakes and/or human activities. Some of the mass changes are periodic and rather well known (e.g., ocean and solid Earth tides), whereas the non-periodic mass changes are not that well known or easy to model. The latter part is often referred to as non-tidal loading (NTL) and is the focus of the study. A deeper understanding of the NTL in geodetic time series, particularly in regional and/or local scales, will result in insights in modelling and removing the effect from the time series, thus improving the stability of the geodetic time series. Examining the impacts of different loading products in our region is critical for accurately removing the loading signal. Currently, there are several open sources for loading products. In this study, we compared the performance of these loading products and investigated their impact on the scatter of GNSS time series in the permanent GNSS stations in Finland (FinnRef). We studied five different hydrological loading models, six different non-tidal atmospheric loading models, and three different non-tidal oceanic loading models to see how various loading configurations operate and how they affect the noise characteristics of GNSS 3D time series, and ultimately figure out which models is most realistic in Finland.

Description: Coastal meadows are an ecologically important habitat type and provide suitable conditions for a wide variety of species, many of which are specialized to live in this environment. In addition, many bird species are dependent on coastal meadows as nesting and feeding areas. Coastal meadows remain open and treeless either because of grazing or naturally due to the effect of waves, sea level variations, and sea ice.Because of their location on low-lying ground at the immediate vicinity of the seashore, coastal meadows are particularly vulnerable to sea level rise. We investigate this vulnerability and potential adaptation on the northern (Finnish) coast of the Gulf of Finland. The rate of land uplift is 3-4 mm/a in the area, which approximately equals the current rate of sea level rise. However, by 2100 mean sea level in the region is projected to rise by 15, 30 or 60 cm depending on the emission scenario (SSP1-2.6, SSP2-4.5, or SSP5-8.5, respectively). Even a higher rise is possible.Due to the relatively steep topography, the coastal zone in the area is rather narrow and coastal meadows are predominantly small. When the sea level rises, the meadows can adapt by moving inland, if there is suitable low-lying open space and the spreading is not prevented by roads, other infrastructure, or rocky terrain. In this analysis, we utilize geospatial data of habitat types and land use, a digital elevation model, and projections of mean sea level rise to investigate the adaptation potential of coastal meadows.