Phases or regimes? Revisiting NDVI trends as proxies for land degradation

Autores
Easdale, Marcos Horacio; Bruzzone, Octavio Augusto; Mapfumo, Paul; Tittonell, Pablo Adrian
Año de publicación
2018
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
One of the main challenges in land degradation assessment is that a rigorous and systematic approach to addressing its complex dynamics is still missing. The development and application of operative tools at regional and global scales remain a challenge. Land degradation is usually defined as a long‐term decline in ecosystem function and productivity. Due to its temporal and spatial resolution as well as data availability, the use of time series of spectral vegetation indexes obtained from satellite sensors has become frequent in recent studies in this field. Slope of linear trends of the normalized difference vegetation index is usually considered an accurate indicator and is widely used as a proxy for land degradation. Yet this method is built on a number of simplifying conceptual and methodological assumptions that prevent capturing more complex dynamics, such as cyclic or periodic behaviors. Our aim was to examine the limitations associated with using linear normalized difference vegetation index trends as proxies for land degradation by comparing outcomes with an alternative methodological procedure based on wavelet autoregressive methods. We explored these issues in 5 case studies from Africa and South America. We observed that trend explained a marginal portion of total temporal variability, whereas monotonic functions, such as linear trends, were unable to capture dynamics that were non‐unidirectional, resulting in misinterpretation of actual trends. Wavelet autoregressive method results were encouraging as a step towards the application of more accurate methods to provide sound scientific information of land degradation and restoration.
Estación Experimental Agropecuaria Bariloche
Fil: Easdale, Marcos Horacio. Instituto Nacional de Tecnología Agropecuaria (INTA). Estacion Experimental Agropecuaria Bariloche. Área Desarrollo Rural. Grupo de Sistemas de Producción y Territorios; Argentina
Fil: Bruzzone, Octavio Augusto. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche; Argentina
Fil: Mapfumo, Paul. University of Zimbabwe. Department of Soil Science and Agricultural Engineering, Zimbawe
Fil: Tittonell, Pablo Adrian. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche; Argentina
Fuente
Land Degradation & Developmen 29 (3) : 433–445 (Marzo 2018)
Materia
Degradación de Tierras
Desertificación
Land Degradation
Desertification
Satellite Imagery
Reclamation
Imágenes por Satélites
Rehabilitación de Tierras
MODIS
Nivel de accesibilidad
acceso restringido
Condiciones de uso
Repositorio
INTA Digital (INTA)
Institución
Instituto Nacional de Tecnología Agropecuaria
OAI Identificador
oai:localhost:20.500.12123/4248
Acceder
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oai_identifier_str oai:localhost:20.500.12123/4248
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network_name_str INTA Digital (INTA)
spelling Phases or regimes? Revisiting NDVI trends as proxies for land degradationEasdale, Marcos HoracioBruzzone, Octavio AugustoMapfumo, PaulTittonell, Pablo AdrianDegradación de TierrasDesertificaciónLand DegradationDesertificationSatellite ImageryReclamationImágenes por SatélitesRehabilitación de TierrasMODISOne of the main challenges in land degradation assessment is that a rigorous and systematic approach to addressing its complex dynamics is still missing. The development and application of operative tools at regional and global scales remain a challenge. Land degradation is usually defined as a long‐term decline in ecosystem function and productivity. Due to its temporal and spatial resolution as well as data availability, the use of time series of spectral vegetation indexes obtained from satellite sensors has become frequent in recent studies in this field. Slope of linear trends of the normalized difference vegetation index is usually considered an accurate indicator and is widely used as a proxy for land degradation. Yet this method is built on a number of simplifying conceptual and methodological assumptions that prevent capturing more complex dynamics, such as cyclic or periodic behaviors. Our aim was to examine the limitations associated with using linear normalized difference vegetation index trends as proxies for land degradation by comparing outcomes with an alternative methodological procedure based on wavelet autoregressive methods. We explored these issues in 5 case studies from Africa and South America. We observed that trend explained a marginal portion of total temporal variability, whereas monotonic functions, such as linear trends, were unable to capture dynamics that were non‐unidirectional, resulting in misinterpretation of actual trends. Wavelet autoregressive method results were encouraging as a step towards the application of more accurate methods to provide sound scientific information of land degradation and restoration.Estación Experimental Agropecuaria BarilocheFil: Easdale, Marcos Horacio. Instituto Nacional de Tecnología Agropecuaria (INTA). Estacion Experimental Agropecuaria Bariloche. Área Desarrollo Rural. Grupo de Sistemas de Producción y Territorios; ArgentinaFil: Bruzzone, Octavio Augusto. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche; ArgentinaFil: Mapfumo, Paul. University of Zimbabwe. Department of Soil Science and Agricultural Engineering, ZimbaweFil: Tittonell, Pablo Adrian. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche; ArgentinaWiley2019-01-10T18:05:06Z2019-01-10T18:05:06Z2018-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://hdl.handle.net/20.500.12123/4248https://onlinelibrary.wiley.com/doi/abs/10.1002/ldr.28711085-3278https://doi.org/10.1002/ldr.2871Land Degradation & Developmen 29 (3) : 433–445 (Marzo 2018)reponame:INTA Digital (INTA)instname:Instituto Nacional de Tecnología Agropecuariaenginfo:eu-repo/semantics/restrictedAccess2025-09-29T13:44:33Zoai:localhost:20.500.12123/4248instacron:INTAInstitucionalhttp://repositorio.inta.gob.ar/Organismo científico-tecnológicoNo correspondehttp://repositorio.inta.gob.ar/oai/requesttripaldi.nicolas@inta.gob.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:l2025-09-29 13:44:33.359INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuariafalse
dc.title.none.fl_str_mv Phases or regimes? Revisiting NDVI trends as proxies for land degradation
title Phases or regimes? Revisiting NDVI trends as proxies for land degradation
spellingShingle Phases or regimes? Revisiting NDVI trends as proxies for land degradation
Easdale, Marcos Horacio
Degradación de Tierras
Desertificación
Land Degradation
Desertification
Satellite Imagery
Reclamation
Imágenes por Satélites
Rehabilitación de Tierras
MODIS
title_short Phases or regimes? Revisiting NDVI trends as proxies for land degradation
title_full Phases or regimes? Revisiting NDVI trends as proxies for land degradation
title_fullStr Phases or regimes? Revisiting NDVI trends as proxies for land degradation
title_full_unstemmed Phases or regimes? Revisiting NDVI trends as proxies for land degradation
title_sort Phases or regimes? Revisiting NDVI trends as proxies for land degradation
dc.creator.none.fl_str_mv Easdale, Marcos Horacio
Bruzzone, Octavio Augusto
Mapfumo, Paul
Tittonell, Pablo Adrian
author Easdale, Marcos Horacio
author_facet Easdale, Marcos Horacio
Bruzzone, Octavio Augusto
Mapfumo, Paul
Tittonell, Pablo Adrian
author_role author
author2 Bruzzone, Octavio Augusto
Mapfumo, Paul
Tittonell, Pablo Adrian
author2_role author
author
author
dc.subject.none.fl_str_mv Degradación de Tierras
Desertificación
Land Degradation
Desertification
Satellite Imagery
Reclamation
Imágenes por Satélites
Rehabilitación de Tierras
MODIS
topic Degradación de Tierras
Desertificación
Land Degradation
Desertification
Satellite Imagery
Reclamation
Imágenes por Satélites
Rehabilitación de Tierras
MODIS
dc.description.none.fl_txt_mv One of the main challenges in land degradation assessment is that a rigorous and systematic approach to addressing its complex dynamics is still missing. The development and application of operative tools at regional and global scales remain a challenge. Land degradation is usually defined as a long‐term decline in ecosystem function and productivity. Due to its temporal and spatial resolution as well as data availability, the use of time series of spectral vegetation indexes obtained from satellite sensors has become frequent in recent studies in this field. Slope of linear trends of the normalized difference vegetation index is usually considered an accurate indicator and is widely used as a proxy for land degradation. Yet this method is built on a number of simplifying conceptual and methodological assumptions that prevent capturing more complex dynamics, such as cyclic or periodic behaviors. Our aim was to examine the limitations associated with using linear normalized difference vegetation index trends as proxies for land degradation by comparing outcomes with an alternative methodological procedure based on wavelet autoregressive methods. We explored these issues in 5 case studies from Africa and South America. We observed that trend explained a marginal portion of total temporal variability, whereas monotonic functions, such as linear trends, were unable to capture dynamics that were non‐unidirectional, resulting in misinterpretation of actual trends. Wavelet autoregressive method results were encouraging as a step towards the application of more accurate methods to provide sound scientific information of land degradation and restoration.
Estación Experimental Agropecuaria Bariloche
Fil: Easdale, Marcos Horacio. Instituto Nacional de Tecnología Agropecuaria (INTA). Estacion Experimental Agropecuaria Bariloche. Área Desarrollo Rural. Grupo de Sistemas de Producción y Territorios; Argentina
Fil: Bruzzone, Octavio Augusto. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche; Argentina
Fil: Mapfumo, Paul. University of Zimbabwe. Department of Soil Science and Agricultural Engineering, Zimbawe
Fil: Tittonell, Pablo Adrian. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche; Argentina
description One of the main challenges in land degradation assessment is that a rigorous and systematic approach to addressing its complex dynamics is still missing. The development and application of operative tools at regional and global scales remain a challenge. Land degradation is usually defined as a long‐term decline in ecosystem function and productivity. Due to its temporal and spatial resolution as well as data availability, the use of time series of spectral vegetation indexes obtained from satellite sensors has become frequent in recent studies in this field. Slope of linear trends of the normalized difference vegetation index is usually considered an accurate indicator and is widely used as a proxy for land degradation. Yet this method is built on a number of simplifying conceptual and methodological assumptions that prevent capturing more complex dynamics, such as cyclic or periodic behaviors. Our aim was to examine the limitations associated with using linear normalized difference vegetation index trends as proxies for land degradation by comparing outcomes with an alternative methodological procedure based on wavelet autoregressive methods. We explored these issues in 5 case studies from Africa and South America. We observed that trend explained a marginal portion of total temporal variability, whereas monotonic functions, such as linear trends, were unable to capture dynamics that were non‐unidirectional, resulting in misinterpretation of actual trends. Wavelet autoregressive method results were encouraging as a step towards the application of more accurate methods to provide sound scientific information of land degradation and restoration.
publishDate 2018
dc.date.none.fl_str_mv 2018-03
2019-01-10T18:05:06Z
2019-01-10T18:05:06Z
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/20.500.12123/4248
https://onlinelibrary.wiley.com/doi/abs/10.1002/ldr.2871
1085-3278
https://doi.org/10.1002/ldr.2871
url http://hdl.handle.net/20.500.12123/4248
https://onlinelibrary.wiley.com/doi/abs/10.1002/ldr.2871
https://doi.org/10.1002/ldr.2871
identifier_str_mv 1085-3278
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/restrictedAccess
eu_rights_str_mv restrictedAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Wiley
publisher.none.fl_str_mv Wiley
dc.source.none.fl_str_mv Land Degradation & Developmen 29 (3) : 433–445 (Marzo 2018)
reponame:INTA Digital (INTA)
instname:Instituto Nacional de Tecnología Agropecuaria
reponame_str INTA Digital (INTA)
collection INTA Digital (INTA)
instname_str Instituto Nacional de Tecnología Agropecuaria
repository.name.fl_str_mv INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuaria
repository.mail.fl_str_mv tripaldi.nicolas@inta.gob.ar
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score 12.559606

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