TY - JOUR AU - Kern, Anikó AU - Dobor, Laura AU - Hollós, Roland AU - Marjanović, Hrvoje AU - Torma, Csaba AU - Kis, Anna AU - Fodor, Nándor AU - Barcza, Zoltán TI - Seamlessly combined historical and projected daily meteorological datasets for impact studies in Central Europe: The FORESEE v4.0 and the FORESEE-HUN v1.0 JF - CLIMATE SERVICES J2 - CLIM SERV VL - 33 PY - 2024 SN - 2405-8807 DO - 10.1016/j.cliser.2023.100443 UR - https://m2.mtmt.hu/api/publication/34472868 ID - 34472868 N1 - ELTE Eötvös Loránd University, Institute of Geography and Earth Sciences, Department of Geophysics and Space Science, Space Research Group, Budapest H-1117, Pázmány P. st. 1/A, Hungary Czech University of Life Sciences Prague, Faculty of Forestry and Wood Sciences, 165 21 Prague 6, Kamýcká 129, Czech Republic ELTE Eötvös Loránd University, Institute of Geography and Earth Sciences, Department of Meteorology, Budapest H-1117, Pázmány P. st. 1/A, Hungary ELTE Eötvös Loránd University, Excellence Center, Faculty of Science, H-2462 Martonvásár, Brunszvik u. 2., Hungary Agricultural Institute, Centre for Agricultural Research, H-2462 Martonvásár, Brunszvik u. 2, Hungary Croatian Forest Research Institute, Department of Forest Management and Forestry Economics, Jastrebarsko HR-10450, Cvjetno naselje 41, Croatia Cited By :1 Export Date: 28 March 2024 Correspondence Address: Kern, A.; ELTE Eötvös Loránd University, Budapest H-1117, Pázmány P. st. 1/A, Hungary; email: aniko.kern@ttk.elte.hu LA - English DB - MTMT ER - TY - BOOK AU - Vincze, Csilla AU - Birinyi, Edina AU - Leelőssy, Ádám AU - Kern, Anikó AU - Kristóf, Dániel TI - A napraforgó virágzási időszakának becslése űrfelvétel-idősorok és in situ kaptár-adatok felhasználásával C1 - Visegrád PY - 2023 UR - https://m2.mtmt.hu/api/publication/34782160 ID - 34782160 LA - Hungarian DB - MTMT ER - TY - CONF AU - Pongrácz, Rita AU - Barcza, Zoltán AU - Kern, Anikó TI - Az éghajlati adatok mint bemenő feltételek a hatásvizsgálatokban T2 - 48. Meteorológiai Tudományos Napok. PB - Országos Meteorológiai Szolgálat (OMSZ) C1 - Budapest PY - 2023 SP - 23 UR - https://m2.mtmt.hu/api/publication/34172176 ID - 34172176 LA - Hungarian DB - MTMT ER - TY - CHAP AU - Birinyi, Edina AU - Kristóf, Dániel AU - Kern, Anikó AU - Rotterné, Kulcsár Anikó ED - Abriha-Molnár, Vanda Éva TI - Radaralapú belvízdetektálási lehetőségek Google Earth Engineben egy hazai mintaterület példáján T2 - Az elmélet és gyakorlat találkozása a térinformatikában XIV. : Theory meets practice in GIS PB - Debreceni Egyetemi Kiadó CY - Debrecen SN - 9789636150846 PY - 2023 SP - 41 EP - 51 PG - 11 UR - https://m2.mtmt.hu/api/publication/34141639 ID - 34141639 LA - Hungarian DB - MTMT ER - TY - GEN AU - Kern, Anikó AU - Barcza, Zoltán AU - Dobor, Laura AU - Hollós,, R., AU - Marjanović,, H., AU - Torma, Csaba AU - Kis,, A., AU - Fodor, N TI - A FORESEE éghajlati adatbázis CY - 2022.08.30-09.01. PY - 2022 UR - https://m2.mtmt.hu/api/publication/34177994 ID - 34177994 LA - Hungarian DB - MTMT ER - TY - GEN AU - Kern, Anikó AU - Barcza, Zoltán AU - Dobor, Laura TI - Meteorológiai adatok 1951-2100-ra: a FORESEE adatbázis PY - 2022 UR - https://m2.mtmt.hu/api/publication/34177976 ID - 34177976 LA - Hungarian DB - MTMT ER - TY - CHAP AU - Dávid, Réka Ágnes AU - Barcza, Zoltán AU - Kern, Anikó ED - Pongrácz, Rita ED - Mészáros, Róbert ED - Kis, Anna TI - Magyarországi gyepek fenológiai ciklusának vizsgálata műholdas távérzékelés segítségével T2 - Aktuális meteorológiai kutatások: Az éghajlatváltozás és hatásainak vizsgálata, levegőminőségi elemzések PB - ELTE TTK Meteorológiai Tanszék CY - Budapest SN - 9789634895619 T3 - Egyetemi meteorológiai füzetek, ISSN 0865-7920 ; 34. PY - 2022 SP - 22 EP - 30 PG - 9 DO - 10.31852/EMF.34.2022.022.030 UR - https://m2.mtmt.hu/api/publication/33680985 ID - 33680985 LA - Hungarian DB - MTMT ER - TY - CHAP AU - Birinyi, Edina AU - Kern, Anikó AU - Kristóf, Dániel AU - Barcza, Zoltán ED - Abriha-Molnár, Vanda Éva TI - Nagyfelbontású kukorica és napraforgó állapot-térképezés a Mezőgazdasági Kockázatkezelési Rendszerben: a 2022-es aszály hatása T2 - Az elmélet és gyakorlat találkozása a térinformatikában XIII. PB - Debreceni Egyetemi Kiadó CY - Debrecen SN - 9789636150396 PY - 2022 SP - 75 EP - 81 PG - 7 UR - https://m2.mtmt.hu/api/publication/33642018 ID - 33642018 AB - In the summer of 2022, extreme drought events hit a large part of Europe including Hungary, with severe impacts on agricultural production. In this work, we developed a methodology for creating high-resolution, crop-specific condition maps based on Sentinel-2 optical satellite imagery, taking into account both temporal and spatial characteristics. Five spectral indices (NDVI, kNDVI, EVI, PSRI, NDMI) were used in combination by applying the Vegetation Condition Index (VCI) principle. Six categories were determined, ranging from “not affected” to “severely affected”, based on the number of indices indicating unfavourable vegetation conditions. The current paper summarizes our results for maize and sunflower cultures. The resulting maps were provided to the National Food Chain Safety Office to facilitate field damage assessment. LA - Hungarian DB - MTMT ER - TY - JOUR AU - Birinyi, Edina AU - Kern, Anikó AU - Barcza, Zoltán AU - Kristóf, Dániel TI - A mezőgazdasági kockázatkezelési rendszerbe benyújtott aszály kárigények igazolhazóságára rendelkezésre álló sentinel-2 felvételek a jogszabályi határidők betartásával JF - EGYETEMI METEOROLÓGIAI FÜZETEK - METEOROLOGICAL NOTES OF UNIVERSITIES J2 - EGYETEMI METEOROLÓGIAI FÜZETEK VL - AKTUÁLIS METEOROLÓGIAI KUTATÁSOK: AZ ÉGHAJLATVÁLTOZÁS ÉS HATÁSAINAK VIZSGÁLATA, LEVEGŐMINŐSÉGI ELEMZÉSEK PY - 2022 IS - 34 SP - 13 EP - 21 PG - 9 SN - 0865-7920 UR - https://m2.mtmt.hu/api/publication/33641988 ID - 33641988 LA - Hungarian DB - MTMT ER - TY - JOUR AU - Kern, Anikó AU - Barcza, Zoltán AU - Hollós, Roland AU - Birinyi, Edina AU - Marjanović, Hrvoje TI - Critical Climate Periods Explain a Large Fraction of the Observed Variability in Vegetation State JF - REMOTE SENSING J2 - REMOTE SENS-BASEL VL - 14 PY - 2022 IS - 21 SN - 2072-4292 DO - 10.3390/rs14215621 UR - https://m2.mtmt.hu/api/publication/33239320 ID - 33239320 N1 - Funding Agency and Grant Number: Hungarian Scientific Research Fund [OTKA FK128709]; Croatian Science Foundation [HRZZ IP-2019-04-6325]; Janos Bolyai Research Scholarship of the Hungarian Academy of Sciences [BO/00254/20/10]; National Multidisciplinary Laboratory for Climate Change [RRF-2.3.1-21-2022-00014]; Hungarian National Research, Development and Innovation Office [TKP2021NVA.29]; OP RDE [CZ.02.1.01/0.0/0.0/16_019/0000803]; Ministry of Innovation and Technology, financed from the National Research, Development and Innovation Fund Funding text: The research has been supported by the Hungarian Scientific Research Fund (OTKA FK128709); by the Croatian Science Foundation project MODFLUX (HRZZ IP-2019-04-6325); by the Janos Bolyai Research Scholarship of the Hungarian Academy of Sciences (grant no. BO/00254/20/10); by the National Multidisciplinary Laboratory for Climate Change, RRF-2.3.1-21-2022-00014 project; by the Hungarian National Research, Development and Innovation Office under Grant number TKP2021NVA.29; and by the grant "Advanced research supporting the forestry and wood-processing sector's adaptation to global change and the 4th industrial revolution", No. CZ.02.1.01/0.0/0.0/16_019/0000803 financed by OP RDE". The research was prepared with the professional support of the Doctoral Student Scholarship Program of the Co-Operative Doctoral Program of The Ministry of Innovation and Technology, financed from the National Research, Development and Innovation Fund. AB - Previous studies have suggested that a major part of the observed variability in vegetation state might be associated with variability in climatic drivers during relatively short periods within the year. Identification of such critical climate periods, when a particular climate variable most likely has a pronounced influence on the vegetation state of a particular ecosystem, becomes increasingly important in the light of climate change. In this study, we present a method to identify critical climate periods for eight different semi-natural ecosystem categories in Hungary, in Central Europe. The analysis was based on the moving-window correlation between MODIS NDVI/LAI and six climate variables with different time lags during the period 2000–2020. Distinct differences between the important climate variables, critical period lengths, and direction (positive or negative correlations) have been found for different ecosystem categories. Multiple linear models for NDVI and LAI were constructed to quantify the multivariate influence of the environmental conditions on the vegetation state during the late summer. For grasslands, the best models for NDVI explained 65–87% variance, while for broad-leaved forests, the highest explained variance for LAI was up to 50%. The proposed method can be easily implemented in other geographical locations and can provide essential insight into the functioning of different ecosystem types. LA - English DB - MTMT ER -