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LicenciaThis is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.es
AutorDuarte, Efraín
AutorBarrera, Juan A.
AutorDube, Francis
AutorCasco, Fabio
AutorHernández, Alexander J.
AutorZagal, Erick
Fecha de admisión2024-09-30T23:52:32Z
Fecha disponible2024-09-30T23:52:32Z
Año2020
CitaciónDuarte, E., Barrera, J. A., Dube, F., Casco, F., Hernández, A. J., & Zagal, E. (2020). Monitoring approach for tropical coniferous forest degradation using remote sensing and field data. Remote Sensing, 12(16), 2531. Recuperado de:es
URIhttps://bvearmb.do/handle/123456789/5198
SinopsisCurrent estimates of CO2 emissions from forest degradation are generally based on insufficient information and are characterized by high uncertainty, while a global definition of ‘forest degradation’ is currently being discussed in the scientific arena. This study proposes an automated approach to monitor degradation using a Landsat time series. The methodology was developed using the Google Earth Engine (GEE) and applied in a pine forest area of the Dominican Republic.es
IdiomaEnglishes
PublicadoRemote Sensing, 12(16), 2531es
Derechos© 2020 by the author. Licensee MDPI, Basel, Switzerland.es
URI de derechoshttps://creativecommons.org/licenses/by/4.0/es
MateriaRecursos naturales - República Dominicanaes
MateriaRecursos forestaleses
MateriaInvestigación ambientales
MateriaTecnologíaes
TítuloMonitoring approach for tropical coniferous forest degradation using remote sensing and field dataes
dc.identifier.doihttps://doi.org/10.3390/rs12162531
Tipo de materialArticlees
Tipo de contenidoScientific researches
AccesoOpenes
AudienciaTechnicians, professionals and scientistses


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This is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.
La consulta y descarga de este documento están sujetas a esta licencia: This is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.
© 2020 by the author. Licensee MDPI, Basel, Switzerland.