Assessment of Grassland Biomass Prediction Using AquaCrop Model: Integrating Sentinel-2 Data and Ground Measurements in Wielkopolska and Podlasie Regions, Poland
Ewa Panek-Chwastyk (),
Ceren Nisanur Ozbilge,
Katarzyna Dąbrowska-Zielińska and
Konrad Wróblewski
Additional contact information
Ewa Panek-Chwastyk: Remote Sensing Centre, Institute of Geodesy and Cartography, 02-679 Warsaw, Poland
Ceren Nisanur Ozbilge: Remote Sensing Centre, Institute of Geodesy and Cartography, 02-679 Warsaw, Poland
Katarzyna Dąbrowska-Zielińska: Remote Sensing Centre, Institute of Geodesy and Cartography, 02-679 Warsaw, Poland
Konrad Wróblewski: Remote Sensing Centre, Institute of Geodesy and Cartography, 02-679 Warsaw, Poland
Agriculture, 2024, vol. 14, issue 6, 1-16
Abstract:
This study aimed to compare remotely sensed data with in situ data using the AquaCrop simulation model for accurately monitoring growth conditions and predict grassland biomass in the north-eastern and central-western regions of Poland from 2020 to 2022. The model was calibrated using input data, including daily climate parameters from the ERA5-Land Daily Aggregated dataset, crop characteristics (initial canopy cover, maximum canopy cover, and harvest index), and soil characteristics. Additionally, parameters such as the leaf area index (LAI), soil texture classes, and plant growth stages were obtained through field campaigns. The grassland’s biomass simulation results indicate that the root mean square error (RMSE) values for the north-eastern region ranged from 0.12 to 0.35 t·ha −1 , while for the central-western region, they ranged from 0.07 to 0.12 t·ha −1 . Overall, the outcomes obtained from Sentinel-2 data perform comparably to the in situ measurements, and in some instances, even yield superior results. This study contributes valuable insights into grass production management on farms, providing essential information and tools for managers to better understand grass growth and development.
Keywords: grassland monitoring; agricultural sustainability; data fusion techniques; farm management strategies (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
https://www.mdpi.com/2077-0472/14/6/837/pdf (application/pdf)
https://www.mdpi.com/2077-0472/14/6/837/ (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:gam:jagris:v:14:y:2024:i:6:p:837-:d:1402788
Access Statistics for this article
Agriculture is currently edited by Ms. Leda Xuan
More articles in Agriculture from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().