The Potential of Pan-Sharpened EnMAP Data for the Assessment of Wheat LAI

DC FieldValueLanguage
dc.contributor.authorSiegmann, Bastian
dc.contributor.authorJarmer, Thomas
dc.contributor.authorBeyer, Florian
dc.contributor.authorEhlers, Manfred
dc.date.accessioned2021-12-23T15:59:57Z-
dc.date.available2021-12-23T15:59:57Z-
dc.date.issued2015
dc.identifier.urihttps://osnascholar.ub.uni-osnabrueck.de/handle/unios/4254-
dc.description.abstractIn modern agriculture, the spatially differentiated assessment of the leaf area index (LAI) is of utmost importance to allow an adapted field management. Current hyperspectral satellite systems provide information with a high spectral but only a medium spatial resolution. Due to the limited ground sampling distance (GSD), hyperspectral satellite images are often insufficient for precision agricultural applications. In the presented study, simulated hyperspectral data of the upcoming Environmental Mapping and Analysis Program (EnMAP) mission (30 m GSD) covering an agricultural region were pan-sharpened with higher resolution panchromatic aisaEAGLE (airborne imaging spectrometer for applications EAGLE) (3 m GSD) and simulated Sentinel-2 images (10 m GSD) using the spectral preserving Ehlers Fusion. As fusion evaluation criteria, the spectral angle ((spec)) and the correlation coefficient (R) were calculated to determine the spectral preservation capability of the fusion results. Additionally, partial least squares regression (PLSR) models were built based on the EnMAP images, the fused datasets and the original aisaEAGLE hyperspectral data to spatially predict the LAI of two wheat fields. The aisaEAGLE model provided the best results (R-cv(2) = 0.87) followed by the models built with the fused datasets (EnMAP-aisaEAGLE and EnMAP-Sentinel-2 fusion each with a R-cv(2) of 0.75) and the simulated EnMAP data (R-cv(2) = 0.68). The results showed the suitability of pan-sharpened EnMAP data for a reliable spatial prediction of LAI and underlined the potential of pan-sharpening to enhance spatial resolution as required for precision agriculture applications.
dc.description.sponsorshipGerman Aerospace Center (DLR)Helmholtz AssociationGerman Aerospace Centre (DLR); Federal Ministry of Economics and TechnologyFederal Ministry for Economic Affairs and Energy (BMWi) [50 EE 1014]; This work was funded by the German Aerospace Center (DLR) with financial resources of the Federal Ministry of Economics and Technology on the basis of a decision of the German Parliament, grant number 50 EE 1014. We would like to thank the Helmholtz Centre for Environmental Research Leipzig (UFZ) and the Humboldt University at Berlin for making their field instruments available. Special thanks go to Mr. Wagner and the Wimex GmbH, owner of the investigated fields, for their cooperation and their support. Additionally, we want to thank Karl Segl, Rudolf Richter, Daniel Doktor, Sascha Klonus, Sabine Hornberg, Holger Lilienthal, Nicole Richter, Thomas Selige, Anne Bodemann, Martin Kanning, Thorben Jensen and Yevgeniya Filippovska for their assistance in field during data collection and data pre-processing.
dc.language.isoen
dc.publisherMDPI
dc.relation.ispartofREMOTE SENSING
dc.subjectaisaEAGLE
dc.subjectCROP MODELS
dc.subjectEnMAP
dc.subjectEnvironmental Sciences
dc.subjectEnvironmental Sciences & Ecology
dc.subjectFIELD
dc.subjectGeology
dc.subjectGeosciences, Multidisciplinary
dc.subjecthyperspectral
dc.subjectIMAGE FUSION
dc.subjectImaging Science & Photographic Technology
dc.subjectleaf area index
dc.subjectpan-sharpening
dc.subjectpartial least squares regression
dc.subjectPRECISION AGRICULTURE
dc.subjectRemote Sensing
dc.subjectSentinel-2
dc.subjectSPECTROSCOPY
dc.subjectTM
dc.titleThe Potential of Pan-Sharpened EnMAP Data for the Assessment of Wheat LAI
dc.typejournal article
dc.identifier.doi10.3390/rs71012737
dc.identifier.isiISI:000364328600007
dc.description.volume7
dc.description.issue10
dc.description.startpage12737
dc.description.endpage12762
dc.contributor.orcid0000-0002-9203-320X
dc.contributor.orcid0000-0002-9203-320X
dc.contributor.researcheridF-6117-2019
dc.contributor.researcheridAAV-6509-2020
dc.identifier.eissn20724292
dc.publisher.placeST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
dcterms.isPartOf.abbreviationRemote Sens.
dcterms.oaStatusgold, Green Submitted
crisitem.author.deptFB 06 - Mathematik/Informatik-
crisitem.author.deptidfb06-
crisitem.author.orcid0000-0002-4652-1640-
crisitem.author.parentorgUniversität Osnabrück-
crisitem.author.netidJaTh054-
Show simple item record

Page view(s)

7
Last Week
0
Last month
0
checked on Apr 19, 2024

Google ScholarTM

Check

Altmetric