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resumen

Resumen
The use of time series of vegetation indices obtained from satellites has become a highly relevant source of data in studies of land degradation assessment and monitoring. However, information about future vegetation dynamics, which is key for early warnings oriented at land management decisions, is still lacking. Trend-cycle was recently proposed as an indicator that represents a smoothed version of a seasonally adjusted data series, which provides [ver mas...]
dc.contributor.authorBruzzone, Octavio Augusto
dc.contributor.authorEasdale, Marcos Horacio
dc.date.accessioned2021-04-23T14:03:30Z
dc.date.available2021-04-23T14:03:30Z
dc.date.issued2021-07
dc.identifier.issn1470-160X
dc.identifier.otherhttps://doi.org/10.1016/j.ecolind.2021.107663
dc.identifier.urihttp://hdl.handle.net/20.500.12123/9172
dc.identifier.urihttps://www.sciencedirect.com/science/article/pii/S1470160X21003289
dc.description.abstractThe use of time series of vegetation indices obtained from satellites has become a highly relevant source of data in studies of land degradation assessment and monitoring. However, information about future vegetation dynamics, which is key for early warnings oriented at land management decisions, is still lacking. Trend-cycle was recently proposed as an indicator that represents a smoothed version of a seasonally adjusted data series, which provides information on long-term movements (trend) while including changes in direction underlying the series (cycles). The aim was to estimate the direction and speed of change of the Normalized Difference Vegetation Index (NDVI) trend-cycles as a complementary information of the rhythm of change between cyclic phases of vegetation productivity. In particular, we estimate the first and second derivative of the end-point of the trendcycle function, as a measure of the direction the function is going and the speed of change, respectively. The potential advantage of our proposal is the fast processing for large areas and its sensitivity to capturing shifts in temporal dynamics for short time series data. This information can be used as a proxy to build scenarios of the future behaviour of vegetation dynamics, which is a relevant issue to move forward in the development of early warning tools for adaptive land management.eng
dc.formatapplication/pdfes_AR
dc.language.isoenges_AR
dc.publisherElsevieres_AR
dc.rightsinfo:eu-repo/semantics/openAccesses_AR
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/
dc.sourceEcological Indicators 126 : Art: 107663 (Julio 2021)es_AR
dc.subjectÍndice de Vegetaciónes_AR
dc.subjectVegetation Indexeng
dc.subjectPastizal Naturales_AR
dc.subjectNatural Pastureseng
dc.subjectPastizaleses_AR
dc.subjectPastureseng
dc.subject.otherRegión Patagónicaes_AR
dc.titleRhythm of change of trend-cycles of vegetation dynamics as an early warning indicator for land managementes_AR
dc.typeinfo:ar-repo/semantics/artículoes_AR
dc.typeinfo:eu-repo/semantics/articlees_AR
dc.typeinfo:eu-repo/semantics/publishedVersiones_AR
dc.rights.licenseCreative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.description.origenEstación Experimental Agropecuaria Barilochees_AR
dc.description.filFil: Bruzzone, Octavio Augusto. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche; Argentinaes_AR
dc.description.filFil: Bruzzone, Octavio Augusto. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Instituto de Investigaciones Forestales y Agropecuarias Bariloche; Argentinaes_AR
dc.description.filFil: Easdale, Marcos Horacio. Instituto Nacional de Tecnologia Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche. Área Desarrollo Rural; Argentinaes_AR
dc.description.filFil: Easdale, Marcos Horacio. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Instituto de Investigaciones Forestales y Agropecuarias Bariloche; Argentinaes_AR
dc.subtypecientifico


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