Integrating Copernicus LMS with ground measurements data for leaf area index and biomass assessment for grasslands in Poland and Norway
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dc.abstract.en | The integration of satellite data from the Copernicus Land Monitoring Service (CLMS) with ground-based measurements represents a pioneering approach to the assessment of leaf area index (LAI) and in situ biomass at grasslands in Poland and Norway. The aim of this study was to develop a method for assessing grass growth conditions and predicting biomass yield based on Sentinel-2 data and CLMS products. LAI values derived from CLMS were compared with in-situ measurements on grassland plots in the two regions of Podlaskie (PL84) and Wielkopolskie (PL41). Small random statistical errors observed in the differences represent a significant opportunity to use Copernicus data to develop a relationship model for biomass prediction. The NDII index calculated using Sentinel2 was considered important for biomass assessment in the humid areas of Norway. This relational biomass prediction model could provide valuable information to farmers, improving their ability to manage grasslands effectively. As a result of the research, relational models were developed has been developed to predict grassland fresh biomass yield with an R2 accuracy of 0.72 for the first cut, 0.81 for the second cut and 0.91 for the third cut. This allows farmers to effectively manage and monitor grassland throughout the growing season. | |
dc.abstract.pl | Integracja danych satelitarnych z Copernicus Land Monitoring Service (CLMS) z pomiarami naziemnymi stanowi pionierskie podejście do oceny wskaźnika powierzchni liści (LAI) i biomasy in situ na użytkach zielonych w Polsce i Norwegii. Celem tego badania było opracowanie metody oceny warunków wzrostu runi trawiastej i prognozowania plonu biomasy na podstawie danych Sentinel-2 i produktów CLMS. Wartości LAI pochodzące z CLMS porównano z pomiarami in situ na powierzchniach użytków zielonych w dwóch regionach: podlaskim (PL84) i wielkopolskim (PL41). Małe losowe błędy statystyczne zaobserwowane w różnicach stanowią znaczącą okazję do wykorzystania danych Copernicus do opracowania modelu relacji do prognozowania biomasy. Wskaźnik NDII obliczony przy użyciu Sentinel2 uznano za ważny dla oceny biomasy na wilgotnych obszarach Norwegii. Ten relacyjny model prognozowania biomasy może dostarczyć cennych informacji rolnikom, poprawiając ich zdolność do skutecznego zarządzania użytkami zielonymi. W wyniku badań opracowano modele relacyjne, aby prognozować plon świeżej biomasy użytków zielonych z dokładnością R2 wynoszącą 0,72 dla pierwszego pokosu, 0,81 dla drugiego pokosu i 0,91 dla trzeciego pokosu. Pozwala to rolnikom na efektywne zarządzanie i monitorowanie użytków zielonych przez cały sezon wegetacyjny. | |
dc.affiliation | Wydział Rolnictwa, Ogrodnictwa i Biotechnologii | |
dc.affiliation.institute | Katedra Łąkarstwa i Krajobrazu Przyrodniczego | |
dc.contributor.author | Dąbrowska-Zielińska, Katarzyna | |
dc.contributor.author | Wróblewski, Konrad | |
dc.contributor.author | Goliński, Piotr | |
dc.contributor.author | Malińska, Alicja | |
dc.contributor.author | Bartold, Maciej | |
dc.contributor.author | Łągiewska, Magdalena | |
dc.contributor.author | Kluczek, Marcin | |
dc.contributor.author | Panek-Chwastyk, Ewa | |
dc.contributor.author | Ziółkowski, Dariusz | |
dc.contributor.author | Golińska, Barbara | |
dc.contributor.author | Markowska, Anna | |
dc.contributor.author | Paradowski, Karol | |
dc.date.access | 2024-11-11 | |
dc.date.accessioned | 2024-11-27T11:16:29Z | |
dc.date.available | 2024-11-27T11:16:29Z | |
dc.date.copyright | 2024-11-11 | |
dc.date.issued | 2024 | |
dc.description.accesstime | at_publication | |
dc.description.bibliography | il., bibliogr. | |
dc.description.finance | publication_research | |
dc.description.financecost | 12526,38 | |
dc.description.if | 3,7 | |
dc.description.number | 1 | |
dc.description.points | 100 | |
dc.description.version | final_published | |
dc.description.volume | 17 | |
dc.identifier.doi | 10.1080/17538947.2024.2425165 | |
dc.identifier.eissn | 1753-8955 | |
dc.identifier.issn | 1753-8947 | |
dc.identifier.uri | https://sciencerep.up.poznan.pl/handle/item/2105 | |
dc.identifier.weblink | https://www.tandfonline.com/doi/full/10.1080/17538947.2024.2425165?scroll=top&needAccess=true#abstract | |
dc.language | en | |
dc.pbn.affiliation | agriculture and horticulture | |
dc.relation.ispartof | International Journal of Digital Earth | |
dc.relation.pages | art. 2425165 | |
dc.relation.project | GrasSAT – Tools for Providing Farmers with Information on Grassland Yields Under Stressed Conditions to Support Management Practices | |
dc.rights | CC-BY | |
dc.sciencecloud | send | |
dc.share.type | OPEN_JOURNAL | |
dc.subject.en | Copernicus land monitoring service | |
dc.subject.en | sentinel-2 | |
dc.subject.en | leaf area index | |
dc.subject.en | biomass | |
dc.subject.en | NDII | |
dc.subject.en | grasslands | |
dc.subject.en | precision agriculture | |
dc.subject.pl | Usługa monitoringu gruntów Copernicus | |
dc.subject.pl | Sentinel-2 | |
dc.subject.pl | indeks powierzchni liści | |
dc.subject.pl | biomasa | |
dc.subject.pl | NDII | |
dc.subject.pl | użytki zielone | |
dc.subject.pl | rolnictwo precyzyjne | |
dc.title | Integrating Copernicus LMS with ground measurements data for leaf area index and biomass assessment for grasslands in Poland and Norway | |
dc.type | JournalArticle | |
dspace.entity.type | Publication | |
oaire.citation.issue | 1 | |
oaire.citation.volume | 17 | |
project.funder.name | Projekt badawczy NOR/POLNOR/GrasSAT/0031/2019-0 |