@inbook{MTMT:35731692, title = {A szélsőséges vízháztartású szántóföldi területek térképezési lehetőségei műholdas és hatósági adatforrások alapján. Poszterabsztrakt}, url = {https://m2.mtmt.hu/api/publication/35731692}, author = {Birinyi, Edina and Hollós, Roland and Kristóf, Dániel and Barcza, Zoltán and Kern, Anikó}, booktitle = {Az elmélet és a gyakorlat találkozása a térinformatikában XV.}, unique-id = {35731692}, year = {2024}, pages = {309}, orcid-numbers = {Birinyi, Edina/0009-0008-3464-3991; Barcza, Zoltán/0000-0002-1278-0636; Kern, Anikó/0000-0002-3504-1668} } @article{MTMT:35641352, title = {Large-Scale Maize Condition Mapping to Support Agricultural Risk Management}, url = {https://m2.mtmt.hu/api/publication/35641352}, author = {Birinyi, Edina and Kristóf, Dániel and Hollós, Roland and Barcza, Zoltán and Kern, Anikó}, doi = {10.3390/rs16244672}, journal-iso = {REMOTE SENS-BASEL}, journal = {REMOTE SENSING}, volume = {16}, unique-id = {35641352}, abstract = {Crop condition mapping and yield loss detection are highly relevant scientific fields due to their economic importance. Here, we report a new, robust six-category crop condition mapping methodology based on five vegetation indices (VIs) using Sentinel-2 imagery at a 10 m spatial resolution. We focused on maize, the most drought-affected crop in the Carpathian Basin, using three selected years of data (2017, 2022, and 2023). Our methodology was validated at two different spatial scales against independent reference data. At the parcel level, we used harvester-derived precision yield data from six maize parcels. The agreement between the yield category maps and those predicted from the crop condition time series by our Random Forest model was 84.56%, while the F1 score was 0.74 with a two-category yield map. Using a six-category yield map, the accuracy decreased to 48.57%, while the F1 score was 0.42. The parcel-level analysis corroborates the applicability of the method on large scales. Country-level validation was conducted for the six-category crop condition map against official county-scale census data. The proportion of areas with the best and worst crop condition categories in July explained 64% and 77% of the crop yield variability at the county level, respectively. We found that the inclusion of the year 2022 (associated with a severe drought event) was important, as it represented a strong baseline for the scaling. The study’s novelty is also supported by the inclusion of damage claims from the Hungarian Agricultural Risk Management System (ARMS). The crop condition map was compared with these claims, with further quantitative analysis confirming the method’s applicability. This method offers a cost-effective solution for assessing damage claims and can provide early yield loss estimates using only remote sensing data.}, year = {2024}, eissn = {2072-4292}, orcid-numbers = {Birinyi, Edina/0009-0008-3464-3991; Barcza, Zoltán/0000-0002-1278-0636; Kern, Anikó/0000-0002-3504-1668} } @CONFERENCE{MTMT:35257695, title = {Field-level analysis of phenological cycles and dynamics of sunflower (Helianthus annuus L.) and oil seed rape (Brassica napus L.) flowering within various regions of Hungary}, url = {https://m2.mtmt.hu/api/publication/35257695}, author = {Ilyés-Vincze, Csilla and Birinyi, Edina and Leelőssy, Ádám and Kristóf, Dániel and Mészáros, Róbert and Kern, Anikó}, booktitle = {EMS Annual Meeting Abstracts}, unique-id = {35257695}, year = {2024}, orcid-numbers = {Ilyés-Vincze, Csilla/0000-0002-6658-0090; Birinyi, Edina/0009-0008-3464-3991; Leelőssy, Ádám/0000-0001-9583-0127; Mészáros, Róbert/0000-0002-0550-9266; Kern, Anikó/0000-0002-3504-1668} } @inproceedings{MTMT:35217623, title = {Possibilities of Radar-Based Inland Excess Water Mapping in Google Earth Engine During the Single-Satellite Sentinel-1 ERA for a Study Area in Hungary}, url = {https://m2.mtmt.hu/api/publication/35217623}, author = {Birinyi, Edina and Kristóf, Dániel and Kern, Anikó}, booktitle = {IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium}, doi = {10.1109/IGARSS53475.2024.10640894}, unique-id = {35217623}, year = {2024}, pages = {5117-5120}, orcid-numbers = {Birinyi, Edina/0009-0008-3464-3991; Kern, Anikó/0000-0002-3504-1668} } @article{MTMT:34472868, title = {Seamlessly combined historical and projected daily meteorological datasets for impact studies in Central Europe: The FORESEE v4.0 and the FORESEE-HUN v1.0}, url = {https://m2.mtmt.hu/api/publication/34472868}, author = {Kern, Anikó and Dobor, Laura and Hollós, Roland and Marjanović, Hrvoje and Torma, Csaba and Kis, Anna and Fodor, Nándor and Barcza, Zoltán}, doi = {10.1016/j.cliser.2023.100443}, journal-iso = {CLIM SERV}, journal = {CLIMATE SERVICES}, volume = {33}, unique-id = {34472868}, issn = {2405-8807}, year = {2024}, eissn = {2405-8807}, orcid-numbers = {Kern, Anikó/0000-0002-3504-1668; Dobor, Laura/0000-0001-6712-9827; Torma, Csaba/0000-0002-4240-0788; Kis, Anna/0000-0002-3227-1230; Barcza, Zoltán/0000-0002-1278-0636} } @{MTMT:35731690, title = {A Sentinel-1A műhold felszállóágú felvételeinek alkalmazása belvíztérképezésre egy alföldi mintaterületen}, url = {https://m2.mtmt.hu/api/publication/35731690}, author = {Birinyi, Edina and Kern, Anikó and Kristóf, Dániel}, booktitle = {Aktuális doktori kutatások a levegőkémia, a klímaváltozás és a meteorológia témakörében}, doi = {10.31852/EMF.35.2023.006.012}, unique-id = {35731690}, year = {2023}, pages = {6-12}, orcid-numbers = {Birinyi, Edina/0009-0008-3464-3991; Kern, Anikó/0000-0002-3504-1668} } @misc{MTMT:34782160, title = {A napraforgó virágzási időszakának becslése űrfelvétel-idősorok és in situ kaptár-adatok felhasználásával}, url = {https://m2.mtmt.hu/api/publication/34782160}, author = {Ilyés-Vincze, Csilla and Birinyi, Edina and Leelőssy, Ádám and Kern, Anikó and Kristóf, Dániel}, unique-id = {34782160}, year = {2023}, orcid-numbers = {Ilyés-Vincze, Csilla/0000-0002-6658-0090; Birinyi, Edina/0009-0008-3464-3991; Leelőssy, Ádám/0000-0001-9583-0127; Kern, Anikó/0000-0002-3504-1668} } @CONFERENCE{MTMT:34172176, title = {Az éghajlati adatok mint bemenő feltételek a hatásvizsgálatokban}, url = {https://m2.mtmt.hu/api/publication/34172176}, author = {Pongrácz, Rita and Barcza, Zoltán and Kern, Anikó}, booktitle = {48. Meteorológiai Tudományos Napok.}, unique-id = {34172176}, year = {2023}, pages = {23}, orcid-numbers = {Pongrácz, Rita/0000-0001-7591-7989; Barcza, Zoltán/0000-0002-1278-0636; Kern, Anikó/0000-0002-3504-1668} } @inproceedings{MTMT:34141639, title = {Radaralapú belvízdetektálási lehetőségek Google Earth Engineben egy hazai mintaterület példáján}, url = {https://m2.mtmt.hu/api/publication/34141639}, author = {Birinyi, Edina and Kristóf, Dániel and Kern, Anikó and Rotterné, Kulcsár Anikó}, booktitle = {Az elmélet és gyakorlat találkozása a térinformatikában XIV. : Theory meets practice in GIS}, unique-id = {34141639}, year = {2023}, pages = {41-51}, orcid-numbers = {Birinyi, Edina/0009-0008-3464-3991; Kern, Anikó/0000-0002-3504-1668} } @misc{MTMT:34177994, title = {A FORESEE éghajlati adatbázis}, url = {https://m2.mtmt.hu/api/publication/34177994}, author = {Kern, Anikó and Barcza, Zoltán and Dobor, Laura and Hollós,, R., and Marjanović,, H., and Torma, Csaba and Kis,, A., and Fodor, Nándor}, unique-id = {34177994}, year = {2022}, orcid-numbers = {Kern, Anikó/0000-0002-3504-1668; Barcza, Zoltán/0000-0002-1278-0636; Dobor, Laura/0000-0001-6712-9827; Torma, Csaba/0000-0002-4240-0788} }