On 23 November 2023, the Board of Directors of the Croatian Science Foundation decided to accept the financing of project proposals submitted to the “Research projects” tender IP-2022-10.
The project proposal “Assessment of the long-term effect of climatic and anthropogenic influences on the spatio-temporal dynamics of vegetation cover in Croatia using satellite observations” was accepted for funding.
| Proposal’s full title: | Assessment of the Long-term Climatic and Anthropogenic Effects on the Spatio-temporal Vegetated Land Surface Dynamics in Croatia using Earth Observation Data |
|---|---|
| Proposal acronym: | ALCAR |
| Founder: | Croatia Science Foundation (HRZZ) |
| CID: | IP-2022-10-5711 |
| Host institution: | University of Zagreb Faculty of Geodesy |
| Principal Investigator: | assoc. prof. Mateo Gašparović |
| Duration in months: | 48 |
| Total requested grant from HRZZ: | 197180.00 EUR |
| Budget for Period 1: | 53870.00 EUR |
| Budget for Period 2: | 57670.00 EUR |
| Budget for Period 3: | 47970.00 EUR |
| Budget for Period 4: | 37670.00 EUR |
| Keywords: | remote sensing, vegetation, climate change, anthropogenic effects, land use land cover |
| Scientific area: | Technological sciences |
| Scientific field: | Geodesy |
| Scientific area by ERC classification: | Physical Sciences and Engineering PE10 Earth System Science: Physical geography, geology, geophysics, atmospheric sciences, oceanography, climatology, ecology, global environmental change, biogeochemical cycles, natural resources management PE10_14 Earth observations from space/remote sensing |
Objectives and hypotheses
Satellite remote sensing presents an inevitable global source of synoptic data that enable retrospective characterization into the dynamics of the vegetated land surface and associated biogeophysical and biogeochemical processes. Remote sensing enables acquisition both of long-term observations and information about the intra-seasonal dynamics of vegetation, or “land surface phenology”. Since there are no existing nationwide studies with very high spatial sensitivity of the land cover changes as a consequence of historical political and socio-economic trends, this project project will use recent advances in state-of-the-art predictive modelling and machine learning. In that sense, the main scientific research objectives of the project are:
- To develop technical framework, based on the long-term Earth observation and advanced data processing, statistical and machine learning algorithms, for evaluation of the spatio-temporal land cover dynamics due to institutional changes and regional impacts of global environmental change.
- To provide results that enable precise evaluation of the impact, vulnerability and adaptation capacity of the main vegetation types and land-use classes (forests, semi natural areas and agriculture areas) across the regional environmental settings in Croatia.
- To develop early warning systems for agriculture and forestry based on near-real-time meteorological data and short-term forecasting of phenological responses.
The project is based on stated hypotheses:
- Is it possible to assess the long-term climatic and anthropogenic effects on the spatio-temporal vegetated land surface earth observation data?
- Is it possible to determine degree of adaptation of each vegetation type to climate change? Or simplified. Which forest type and agricultural crops are least and most affected by climate change?
- Is it possible to provide short-term forecasting of climate impacts on vegetation classes?