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Publication:
Optimizing Data Collection in Precision Agriculture - Comparing Remote Sensing and in Situ Analyses

dc.authorwosidKebede, Endalkachew/Gvt-2355-2022
dc.authorwosidVasileva, Silviya/Aau-7967-2020
dc.authorwosidBojinov, Bojin/H-7820-2016
dc.authorwosidIvanov, Bozhidar/Hjp-4157-2023
dc.authorwosidDengiz, Orhan/Abg-7284-2020
dc.contributor.authorKebede, Endalkachew Abebe
dc.contributor.authorVasileva, Silviya
dc.contributor.authorIvanov, Bozhidar
dc.contributor.authorDengiz, Orhan
dc.contributor.authorBojinov, Bojin
dc.contributor.authorIDKebede, Endalkachew Abebe/0000-0002-5212-7340
dc.contributor.authorIDVasileva, Silviya/0000-0002-0781-1266
dc.date.accessioned2025-12-11T01:23:18Z
dc.date.issued2024
dc.departmentOndokuz Mayıs Üniversitesien_US
dc.department-temp[Kebede, Endalkachew Abebe; Vasileva, Silviya; Bojinov, Bojin] Agr Univ Plovdiv, Plovdiv 4000, Bulgaria; [Ivanov, Bozhidar] Agricultural Acad, Inst Agr Econ, Sofia 1113, Bulgaria; [Kebede, Endalkachew Abebe; Dengiz, Orhan] Ondokuz Mayis Univ, Dept Soil Sci & Plant Nutr, Samsun, Turkiyeen_US
dc.descriptionKebede, Endalkachew Abebe/0000-0002-5212-7340; Vasileva, Silviya/0000-0002-0781-1266;en_US
dc.description.abstractRemote sensing has a potential application in assessing and monitoring the plants' biophysical properties using the spectral responses of plants and soils within the electromagnetic spectrum. However, only a few reports compare the performance of different remote sensing approaches against in-situ spectral measurement. The current study assessed potential applications of open data source satellite images (Sentinel 2 and Landsat 9) in estimating the biophysical properties of a crop on a study farm. A Landsat 9 (30 m resolution) and Sentinel-2 (10 m resolution) satellite images with less than 10% cloud cover have been extracted from the open data sources for the period of December 2021 - April 2022. In addition, SpectraVue 710s Leaf Spectrometer was used to measure the spectral response of the crop in April at five different locations within the same field. Results obtained by different data collection methods were compared to evaluate them for applicability in precision agriculture.en_US
dc.description.sponsorshipBulgarian National Science Fund, Bulgarian Ministry of Education and Science; [KPcy;-06-Ncy;36/5]en_US
dc.description.sponsorshipThe authors are grateful for the financial support by the Bulgarian National Science Fund, Bulgarian Ministry of Education and Science (Grant K & Pcy;-06-& Ncy;36/5 - 13.12.2019) .en_US
dc.description.woscitationindexEmerging Sources Citation Index
dc.identifier.endpage16en_US
dc.identifier.issn1310-0351
dc.identifier.issue1en_US
dc.identifier.scopusqualityQ3
dc.identifier.startpage11en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12712/43351
dc.identifier.volume30en_US
dc.identifier.wosWOS:001181663500013
dc.language.isoenen_US
dc.publisherScientific Issues Natl Centre Agrarian Sciencesen_US
dc.relation.ispartofBulgarian Journal of Agricultural Scienceen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectPrecision Agricultureen_US
dc.subjectVegetation Indicesen_US
dc.subjectNdvien_US
dc.titleOptimizing Data Collection in Precision Agriculture - Comparing Remote Sensing and in Situ Analysesen_US
dc.typeArticleen_US
dspace.entity.typePublication

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