TY  - CONF
AU  - Kocsis, Mihály
AU  - Hernádi, Hilda Ágnes
AU  - Makó, András
AU  - Tóth, Brigitta
AU  - Kassai, Piroska
AU  - Szatmári, Gábor
AU  - Laborczi, Annamária
AU  - Takács, Katalin
AU  - Balog, Kitti
AU  - Mészáros, János
AU  - Benő, András
AU  - Bakacsi, Zsófia
AU  - Pásztor, László
TI  - Development of a high spatial resolution legacy soil profile database for the Southern Great Hungarian Plain
T2  - EGU General Assembly 2024 : abstracts
PB  - European Geosciences Union (EGU)
C1  - Wien
PY  - 2024
PG  - 1
DO  - 10.5194/egusphere-egu24-18732
UR  - https://m2.mtmt.hu/api/publication/34798282
ID  - 34798282
LA  - English
DB  - MTMT
ER  - 

TY  - CONF
AU  - Pásztor, László
AU  - Tóth, Brigitta
AU  - Makó, András
AU  - Kocsis, Mihály
AU  - Mészáros, János
AU  - Laborczi, Annamária
AU  - Takács, Katalin
AU  - Szatmári, Gábor
TI  - Elaboration of 3D Soil Hydraulic Databases in Hungary
T2  - EGU General Assembly 2024 : abstracts
PB  - European Geosciences Union (EGU)
C1  - Wien
PY  - 2024
PG  - 1
DO  - 10.5194/egusphere-egu24-11606
UR  - https://m2.mtmt.hu/api/publication/34798229
ID  - 34798229
LA  - English
DB  - MTMT
ER  - 

TY  - CONF
AU  - Takáts, Tünde
AU  - László, Péter
AU  - Takács, Katalin
AU  - Mészáros, János
AU  - Kovács, Zsófia Adrienn
AU  - Koós, Sándor
AU  - Balog, Kitti
AU  - Pásztor, László
AU  - Árvai, Mátyás
TI  - Citizen Science Programs as Scientific Data Collection Approach of Soil Medium
T2  - EGU General Assembly 2024 : abstracts
PB  - European Geosciences Union (EGU)
C1  - Wien
PY  - 2024
DO  - 10.5194/egusphere-egu24-16755
UR  - https://m2.mtmt.hu/api/publication/34798201
ID  - 34798201
LA  - English
DB  - MTMT
ER  - 

TY  - JOUR
AU  - Tóth, Brigitta
AU  - Mészáros, János
AU  - Laborczi, Annamária
AU  - Takács, Katalin
AU  - Szatmári, Gábor
AU  - Bakacsi, Zsófia
AU  - Makó, András
AU  - Pásztor, László
TI  - From EU-SoilHydroGrids to HU-SoilHydroGrids: A leap forward in soil hydraulic mapping
JF  - SCIENCE OF THE TOTAL ENVIRONMENT
J2  - SCI TOTAL ENVIRON
VL  - 921
PY  - 2024
SN  - 0048-9697
DO  - 10.1016/j.scitotenv.2024.171258
UR  - https://m2.mtmt.hu/api/publication/34717981
ID  - 34717981
LA  - English
DB  - MTMT
ER  - 

TY  - CONF
AU  - Tóth, Brigitta
AU  - Mészáros, János
AU  - Laborczi, Annamária
AU  - Takács, Katalin
AU  - Szatmári, Gábor
AU  - Bakacsi, Zsófia
AU  - Makó, András
AU  - Pásztor, László
ED  - Colby, Brungard
ED  - Alexandre, Wadoux
ED  - Shawn, Salley
TI  - 3D Soil Hydraulic Database of Hungary at 100 m resolution (HU‐SoilHydroGrids)
T2  - Pedometrics 2024 Las Cruces
PB  - University of New Mexico
C1  - Las Cruces (NM)
PY  - 2024
SP  - 67
EP  - 68
PG  - 1
UR  - https://m2.mtmt.hu/api/publication/34590830
ID  - 34590830
LA  - English
DB  - MTMT
ER  - 

TY  - CONF
AU  - Szatmári, Gábor
AU  - Laborczi, Annamária
AU  - Takács, Katalin
AU  - Mészáros, János
AU  - Benő, András
AU  - Bakacsi, Zsófia
AU  - Pirkó, Béla
AU  - Koós, Sándor
AU  - Pásztor, László
ED  - Colby, Brungard
ED  - Alexandre, Wadoux
ED  - Shawn, Salley
TI  - Modelling soil organic carbon stock in space and time at multiple scales. Case study from Hungary
TS  - Case study from Hungary
T2  - Pedometrics 2024 Las Cruces
PB  - University of New Mexico
C1  - Las Cruces (NM)
PY  - 2024
SP  - 57
EP  - 58
PG  - 1
UR  - https://m2.mtmt.hu/api/publication/34590764
ID  - 34590764
LA  - English
DB  - MTMT
ER  - 

TY  - CHAP
AU  - Nagy, Balázs
AU  - Mészáros, János
ED  - Rajnai, Zoltán
ED  - Tardy, János
TI  - Drónok a klímaváltozás vizsgálatában - térképezés magashegyi környezetben, Ojos del Salado, Chile
T2  - A jövő nagy kihívása: kiberbiztonság és kiberhadviselés
PB  - Magyar Természettudományi Társulat
CY  - Budapest
SN  - 6158210454
T3  - A Magyar Természettudományi Társulat tanulmánykötetei ; 7.
PY  - 2023
SP  - 108
EP  - 121
PG  - 14
UR  - https://m2.mtmt.hu/api/publication/34599236
ID  - 34599236
LA  - Hungarian
DB  - MTMT
ER  - 

TY  - GEN
AU  - Kovács, Zsófia Adrienn
AU  - Mészáros, János
AU  - Szűcs-Vásárhelyi, Nóra
AU  - László, Péter
AU  - Szatmári, Gábor
AU  - Árvai, Mátyás
AU  - Pásztor, László
TI  - Capabilities of the national scale TDR soil spectrum library for predicting primary soil properties and supporting their digital mapping. poster
TS  - poster
PY  - 2023
UR  - https://m2.mtmt.hu/api/publication/34521674
ID  - 34521674
LA  - English
DB  - MTMT
ER  - 

TY  - GEN
AU  - Balog, Kitti
AU  - Koós, Sándor
AU  - Pirkó, Béla
AU  - Szűcs-Vásárhelyi, Nóra
AU  - Magyar, Marianna
AU  - Mészáros, János
AU  - Árvai, Mátyás
AU  - Szabó, Anita
AU  - Kovács, Zsófia Adrienn
AU  - Takáts, Tünde
AU  - László, Péter
TI  - Options for reducing agricultural ammonia emissions on different soil types. poster
TS  - poster
PY  - 2023
UR  - https://m2.mtmt.hu/api/publication/34521635
ID  - 34521635
LA  - English
DB  - MTMT
ER  - 

TY  - JOUR
AU  - Sári-Barnácz, Fruzsina Enikő
AU  - Zalai, Mihály
AU  - Toepfer, Stefan
AU  - Milics, Gábor
AU  - Iványi, Dóra
AU  - Tóthné Kun, Mariann
AU  - Mészáros, János
AU  - Árvai, Mátyás
AU  - Kiss, József
TI  - Suitability of Satellite Imagery for Surveillance of Maize Ear Damage by Cotton Bollworm (Helicoverpa armigera) Larvae
JF  - REMOTE SENSING
J2  - REMOTE SENS-BASEL
VL  - 15
PY  - 2023
IS  - 23
PG  - 39
SN  - 2072-4292
DO  - 10.3390/rs15235602
UR  - https://m2.mtmt.hu/api/publication/34412834
ID  - 34412834
AB  - The cotton bollworm (Helicoverpa armigera, Lepidoptera: Noctuidae) poses significant risks to maize. Changes in the maize plant, such as its phenology, influence the short-distance movement and oviposition of cotton bollworm adults and, thus, the distribution of the subsequent larval damage. We aim to provide an overview of future approaches to the surveillance of maize ear damage by cotton bollworm larvae based on remote sensing. We focus on finding a near-optimal combination of Landsat 8 or Sentinel-2 spectral bands, vegetation indices, and maize phenology to achieve the best predictions. The study areas were 21 sweet and grain maze fields in Hungary in 2017, 2020, and 2021. Correlations among the percentage of damage and the time series of satellite images were explored. Based on our results, Sentinel-2 satellite imagery is suggested for damage surveillance, as 82% of all the extremes of the correlation coefficients were stronger, and this satellite provided 20–64% more cloud-free images. We identified that the maturity groups of maize are an essential factor in cotton bollworm surveillance. No correlations were found before canopy closure (BBCH 18). Visible bands were the most suitable for damage surveillance in mid–late grain maize (|rmedian| = 0.49–0.51), while the SWIR bands, NDWI, NDVI, and PSRI were suitable in mid–late grain maize fields (|rmedian| = 0.25–0.49) and sweet maize fields (|rmedian| = 0.24–0.41). Our findings aim to support prediction tools for cotton bollworm damage, providing information for the pest management decisions of advisors and farmers.
LA  - English
DB  - MTMT
ER  -