Land use / land cover change (2000 – 2014) in the Rio de la Plata grasslands : an analysis based on MODIS NDVI time series

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Fil: Baeza, Santiago. Universidad de la República. Facultad de Agronomía. Departamento de Sistemas Ambientales. Montevideo, Uruguay.

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Detalles Bibliográficos
Autores principales: Baeza, Santiago, Paruelo, José María
Formato: article Artículo publishedVersion
Lenguaje:Inglés
Publicado: 2020
Materias:
PHENOLOGICAL CLASSIFICATIONS
MODIS NDVI
GRASSLAND LOSSES
RIO DE LA PLATA GRASSSLANDS
Acceso en línea:http://ri.agro.uba.ar/greenstone3/library/collection/arti/document/2020baeza
Aporte de:
FAUBA Digital - Facultad de Agronomía (UBA) de Universidad de Buenos Aires
id snrd:2020baeza
record_format dspace
spelling snrd:2020baeza2021-10-15T16:56:07Z 7006478 Plata, Río de la (estuary) Baeza, Santiago Paruelo, José María 2020 Fil: Baeza, Santiago. Universidad de la República. Facultad de Agronomía. Departamento de Sistemas Ambientales. Montevideo, Uruguay. Fil: Paruelo, José María. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura (IFEVA). Laboratorio de Análisis Regional y Teledetección (LART) Buenos Aires, Argentina. Latin America in general and the Rio de la Plata Grasslands (RPG) in particular, are one of the regions in the world with the highest rates of change in land use/land cover (LULC) in recent times. Despite the magnitude of this change process, LULC descriptions in the RPG are far from being complete, even more those that evaluate LULC change through time. In this work we described LULC and its changes over time for the first 14 years of the 21st century and for the entire grassland biome of the Rio de la Plata, one of the most extensive grassland regions in the world. We performed simple but exhaustive classifications at regional level based on vegetation phenology, using extensive LULC field database, time series of MODIS NDVI satellite images and decision trees classifiers, generating an annual map for all RPG. The used technique achieved very good levels of accuracy at the regional (94.3%–95.5%) and sub-regional (78.2%–97.6%) scales, with commission and omission errors generally low (Min = 0.6, Max = 10.3, Median = 5.7, and Min = 0, Max = 41.8, Median = 6.8 for regional and sub regional classification respectively) and evenly distributed, but fails when LULC classifications are generated in years when the climate is very dierent from those used to generate spectral signatures and train decision trees, or when the NDVI time series accumulates large volumes of lost data. Our results show that the RPG are immersed in a strong process of land use change, mainly due to the advance of the agricultural frontier and at the expense of loss of grassland areas. The agricultural area increased 23% in the analyzed period, adding over than 50,000 Km2 of new crops. Most agricultural expansion, and therefore the greatest losses of grassland, concentrates on both sides of Uruguay river (Mesopotamic Pampa and the western portion of Southern and Northern Campos) and the western portion of Inland Pampa. The generated maps open the door for more detailed and spatially explicit modeling of many important aspects of ecosystem functioning, for quantification in the provision of ecosystem services and for more efficient management of natural resources. grafs., tbls., mapas application/pdf doi:10.3390/rs12030381 issn:2072-4292 http://ri.agro.uba.ar/greenstone3/library/collection/arti/document/2020baeza eng info:eu-repo/semantics/openAccess openAccess http://ri.agro.uba.ar/greenstone3/library/page/biblioteca#section4 Remote Sensing Vol.12, no.3 22 https://www.mdpi.com PHENOLOGICAL CLASSIFICATIONS MODIS NDVI GRASSLAND LOSSES RIO DE LA PLATA GRASSSLANDS Land use / land cover change (2000 – 2014) in the Rio de la Plata grasslands : an analysis based on MODIS NDVI time series article info:eu-repo/semantics/article info:ar-repo/semantics/artículo publishedVersion info:eu-repo/semantics/publishedVersion
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-140
collection FAUBA Digital - Facultad de Agronomía (UBA)
language Inglés
orig_language_str_mv eng
topic PHENOLOGICAL CLASSIFICATIONS
MODIS NDVI
GRASSLAND LOSSES
RIO DE LA PLATA GRASSSLANDS
spellingShingle PHENOLOGICAL CLASSIFICATIONS
MODIS NDVI
GRASSLAND LOSSES
RIO DE LA PLATA GRASSSLANDS
Baeza, Santiago
Paruelo, José María
Land use / land cover change (2000 – 2014) in the Rio de la Plata grasslands : an analysis based on MODIS NDVI time series
topic_facet PHENOLOGICAL CLASSIFICATIONS
MODIS NDVI
GRASSLAND LOSSES
RIO DE LA PLATA GRASSSLANDS
description Fil: Baeza, Santiago. Universidad de la República. Facultad de Agronomía. Departamento de Sistemas Ambientales. Montevideo, Uruguay.
format article
Artículo
Artículo
publishedVersion
publishedVersion
author Baeza, Santiago
Paruelo, José María
author_facet Baeza, Santiago
Paruelo, José María
author_sort Baeza, Santiago
title Land use / land cover change (2000 – 2014) in the Rio de la Plata grasslands : an analysis based on MODIS NDVI time series
title_short Land use / land cover change (2000 – 2014) in the Rio de la Plata grasslands : an analysis based on MODIS NDVI time series
title_full Land use / land cover change (2000 – 2014) in the Rio de la Plata grasslands : an analysis based on MODIS NDVI time series
title_fullStr Land use / land cover change (2000 – 2014) in the Rio de la Plata grasslands : an analysis based on MODIS NDVI time series
title_full_unstemmed Land use / land cover change (2000 – 2014) in the Rio de la Plata grasslands : an analysis based on MODIS NDVI time series
title_sort land use / land cover change (2000 – 2014) in the rio de la plata grasslands : an analysis based on modis ndvi time series
publishDate 2020
url http://ri.agro.uba.ar/greenstone3/library/collection/arti/document/2020baeza
work_keys_str_mv AT baezasantiago landuselandcoverchange20002014intheriodelaplatagrasslandsananalysisbasedonmodisndvitimeseries
AT paruelojosemaria landuselandcoverchange20002014intheriodelaplatagrasslandsananalysisbasedonmodisndvitimeseries
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