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dc.contributor.authorRomán, Alejandro
dc.contributor.authorTovar Sánchez, Antonio
dc.contributor.authorFernández-Marín, Beatriz
dc.contributor.authorNavarro, Gabriel
dc.contributor.authorBarbero González, Luis Carlos 
dc.contributor.otherCiencias de la Tierraes_ES
dc.date.accessioned2024-04-29T12:00:40Z
dc.date.available2024-04-29T12:00:40Z
dc.date.issued2023
dc.identifier.issn1872-826X
dc.identifier.issn1569-8432
dc.identifier.urihttp://hdl.handle.net/10498/32028
dc.description.abstractPenguin colonies significantly influence the distribution and diversity of vegetation communities in Maritime Antarctica, as they serve as vital sources of nutrients for both terrestrial and aquatic ecosystems. Remote sensing techniques are becoming increasingly common for monitoring these vast Antarctic areas, especially with Unmanned Aerial Vehicles (UAVs) imagery, which provides the highest spatial resolutions to date. In fact, the use of hyperspectral (HS) sensors is crucial for accurately identifying and distinguishing between the main ground characteristics and vegetation communities in an Antarctic penguin colony, making this study one of the first UAV-based HS approaches to our knowledge. Consequently, this study provides a spectral library covering the entire spectral range from 400 to 2500 nm for the five main vegetation communities found at Hannah Point penguin colony (Livingston Island, Antarctica). Through this library, two valuable wavelength regions have been identified for distinguishing these communities based on pigments composition, specifically in the green (495–570 nm) and near-infrared (800–900 nm) ranges, that served as a reference for validating the results using 35 ground reference spectrometry data collected in 1667 wavelength bands within the 320–876 nm range. In addition, the supervised classification approach known as the “Spectral Angle Mapper” has been employed to monitor the coverage of each vegetation community based on the information provided by the aforementioned spectral library. The observed ecological gradient, which reveals an increase in vegetation complexity away from the high-nutrient content guano areas, highlights the influence of guano on the distribution of the main vegetation patterns across the entire penguin colony. The results of this study could serve as a reference point for more sophisticated research involving the use of UAV-based HS or MS sensors in Antarctica, offering unique opportunities to detect small variations in these remote ecosystems resulting from climate change.es_ES
dc.formatapplication/pdfes_ES
dc.language.isoenges_ES
dc.publisherElsevier B.V.es_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.sourceInternational Journal of Applied Earth Observation and Geoinformation - Vol. 125, artículo número 103565es_ES
dc.subjectAntarctic vegetationes_ES
dc.subjectBiological mappinges_ES
dc.subjectDroneses_ES
dc.subjectMultispectrales_ES
dc.subjectRemote sensinges_ES
dc.subjectSpectral libraryes_ES
dc.titleCharacterization of an antarctic penguin colony ecosystem using high-resolution UAV hyperspectral imageryes_ES
dc.typejournal articlees_ES
dc.rights.accessRightsopen accesses_ES
dc.identifier.doi10.1016/j.jag.2023.103565
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-098048-B-I00/ES/EL PAPEL DE LOS PINGUINOS EN LOS CICLOS BIOGEOQUIMICOS DE METALES TRAZA EN EL OCEANO AUSTRAL/ es_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI//PID2021-1257830-B-100es_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI//EQC2018-004446-Pes_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI//EQC2019-005721 es_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI//RYC2021-031321-Ies_ES
dc.type.hasVersionVoRes_ES


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Attribution-NonCommercial-NoDerivatives 4.0 Internacional
Esta obra está bajo una Licencia Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 Internacional