Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/25901
DC FieldValueLanguage
dc.contributor.advisorHadjimitsis, Diofantos G.-
dc.contributor.authorChristoforou, Michalakis-
dc.date.accessioned2022-03-04T09:46:22Z-
dc.date.available2022-03-04T09:46:22Z-
dc.date.issued2020-03-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/25901-
dc.description.abstractSlurry lakes are increasing in Cyprus due to the increase of livestock farming especially those intended for meat production such as Pig farming. It is well known that Pig Slurry lakes have a huge environmental impact in the atmosphere and the ecosystem by releasing greenhouse gas and polluting nearby habitats with human and animal pathogens, heavy metals, biogenic elements and pharmaceuticals, respectively. Therefore, the detection, record and mapping of slurry lakes is essential for the environmental authorities as also the monitoring of fullness and / or the leaking of each lake especially during the raining season. Through this study we were able to detect pig slurry lakes using Sentinel-2 images processed into the Sentinel Application Platform (Snap). Slurry lake positions and areas similar to slurry lakes, such as Dams and Mine lakes, were detected, pined and analyzed using satellite and ground spectral signatures. Data revealed the ability to detect and distinguish slurry lakes using the vegetation index TSAVI. Due to their small size, irrigation lakes where not detectable as the images from Landsat and Sentinel have 30- and 20-meter spatial resolution. Furthermore, the use of Sentinel Hub EO browser allowed the instant monitoring of slurry lakes but also the elevation level of the slurry lakes during time, using time-lapse images and comparison of images, in combination with the false color Agriculture index. Our observation can be used by the state authorities for the real-time remote sensing monitoring of Slurry lakes.en_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.publisherDepartment of Civil Engineering and Geomatics, Faculty of Engineering and Technology, Cyprus University of Technologyen_US
dc.rightsΑπαγορεύεται η δημοσίευση ή αναπαραγωγή, ηλεκτρονική ή άλλη χωρίς τη γραπτή συγκατάθεση του δημιουργού και κάτοχου των πνευματικών δικαιωμάτων.en_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectSlurry lakesen_US
dc.subjectSentinel-2en_US
dc.subjectImage processingen_US
dc.subjectVegetation indicesen_US
dc.subjectSnapen_US
dc.titleArtificial farm lake detection using spectroradiometric and satellite dataen_US
dc.typeMSc Thesisen_US
dc.affiliationCyprus University of Technologyen_US
dc.relation.deptDepartment of Civil Engineering and Geomaticsen_US
dc.description.statusCompleteden_US
cut.common.academicyear2019-2020en_US
dc.relation.facultyFaculty of Engineering and Technologyen_US
item.openairetypemasterThesis-
item.cerifentitytypePublications-
item.fulltextWith Fulltext-
item.grantfulltextopen-
item.openairecristypehttp://purl.org/coar/resource_type/c_bdcc-
item.languageiso639-1en-
crisitem.author.deptDepartment of Civil Engineering and Geomatics-
crisitem.author.facultyFaculty of Engineering and Technology-
crisitem.author.orcid0000-0002-2684-547X-
crisitem.author.parentorgFaculty of Engineering and Technology-
Appears in Collections:Μεταπτυχιακές Εργασίες/ Master's thesis
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