MeteoSerbia1km is the first daily gridded meteorological dataset at a 1-km spatial resolution across Serbia for the 2000–2019 period
The dataset consists of five daily variables: maximum, minimum and mean temperature, mean sea level pressure, and total precipitation. Besides daily summaries, it contains monthly and annual summaries, daily, monthly, and annual long term means (LTM). Daily gridded data were interpolated using the Random Forest Spatial Interpolation (RFSI) methodology based on Random Forest and using nearest observations and distances to them as spatial covariates, together with environmental covariates.
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U okviru konferencije za primenjenu veštačku inteligenciju održane u Kragujevcu prezentovan je rad:
M. Kovacevic, P. Burasc, B. Bajat, M. Kilibarda , AI in Agriculture, 11st Serbian International Conference on Applied Artificial Intelligence (SICAAI)
Milan Kilibarda i Ognjen Antonijević su učestvovali u istraživanju publikovanom pod naslovom “A spatiotemporal ensemble Machine Learning framework for generating land use/land cover time-series maps for Europe (2000–2019) based on LUCAS, CORINE and GLAD Landsat” koje je usko vezano za ciljeve CERES projekta.
Istraživači sa projekta CERES su učestvovali na konferenciji Open Data Science Europe workshop 2022. U okviru konrerencije Milan Kilibarda je održao predavanje na temu “Introduction to Web Mapping Services”
U okviru projekta CERES publikovan je rad na temu transfera znanja mašinskog učenja za proračun organskog ugljenika u zemljištu kada su poznati drugi fizički i hemijski parametri.
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