Recent land use and land cover change dinamics in the Gran Chaco Americano

Autores
Banchero, Santiago; De Abelleyra, Diego; Veron, Santiago Ramón; Mosciaro, Maria Jesus; Arevalos, Fabiana; Volante, Jose Norberto
Año de publicación
2020
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Land transformation is one of the most significant human changes on the Earth’s surface processes. Therefore, land use land cover time series are a key input for environmental monitoring, natural resources management, territorial planning enforcement at national scale. We here capitalize from the MapBiomas initiative to characterize land use land cover (LULC) change in the Gran Chaco between 2010 and 2017. Specifically we sought to a) quantify annual changes in the main LULC classes; b) identify the main LULC transitions and c) relate these transitions to current land use policies. Within the MapBiomas project, Landsat based annual maps depicting natural woody vegetation, natural herbaceous vegetation, dispersed natural vegetation, cropland, pastures, bare areas and water. We used Random Forest machine learning algorithms trained by samples produced by visual interpretation of high resolution images. Annual overall accuracy ranged from 0,73 to 0,74. Our results showed that, between 2010 and 2017, agriculture and pasture lands increased ca. 3.7 Mha while natural forestry decreased by 2.3 Mha. Transitions from forests to agriculture accounted for 1.14% of the overall deforestation while 86% was associated to pastures and natural herbaceous vegetation. In Argentina, forest loss occurred primarily (39%) on areas non considered by the territorial planning Law, followed by medium (33%), high (19%) and low (9%) conservation priority classes. These results illustrate the potential contribution of remote sensing to characterize complex human environmental interactions occurring over extended areas and timeframes.
Fil: Banchero, S. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina
Fil: de Abelleyra, D. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina
Fil: Verón, S.R. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina
Fil: Arevalos, F. Asociación Guyra Paraguay; Paraguay
Fil: Volante, J.N. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Salta; Argentina
Fil: Mosciaro, M.J. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Salta; Argentina
Fuente
LAGIRS 2020 Conferencia Latinoamericana de Teledetección GRSS & ISPRS, 22 al 26 de marzo de 2020, Santiago de Chile p. 511-514
Materia
Utilización de la Tierra
Teledetección
Land Use
Remote Sensing
Land Cover
Cobertura de Suelos
Región Chaqueña
Gran Chaco, Argentina
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
INTA Digital (INTA)
Institución
Instituto Nacional de Tecnología Agropecuaria
OAI Identificador
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spelling Recent land use and land cover change dinamics in the Gran Chaco AmericanoBanchero, SantiagoDe Abelleyra, DiegoVeron, Santiago RamónMosciaro, Maria JesusArevalos, FabianaVolante, Jose NorbertoUtilización de la TierraTeledetecciónLand UseRemote SensingLand CoverCobertura de SuelosRegión ChaqueñaGran Chaco, ArgentinaLand transformation is one of the most significant human changes on the Earth’s surface processes. Therefore, land use land cover time series are a key input for environmental monitoring, natural resources management, territorial planning enforcement at national scale. We here capitalize from the MapBiomas initiative to characterize land use land cover (LULC) change in the Gran Chaco between 2010 and 2017. Specifically we sought to a) quantify annual changes in the main LULC classes; b) identify the main LULC transitions and c) relate these transitions to current land use policies. Within the MapBiomas project, Landsat based annual maps depicting natural woody vegetation, natural herbaceous vegetation, dispersed natural vegetation, cropland, pastures, bare areas and water. We used Random Forest machine learning algorithms trained by samples produced by visual interpretation of high resolution images. Annual overall accuracy ranged from 0,73 to 0,74. Our results showed that, between 2010 and 2017, agriculture and pasture lands increased ca. 3.7 Mha while natural forestry decreased by 2.3 Mha. Transitions from forests to agriculture accounted for 1.14% of the overall deforestation while 86% was associated to pastures and natural herbaceous vegetation. In Argentina, forest loss occurred primarily (39%) on areas non considered by the territorial planning Law, followed by medium (33%), high (19%) and low (9%) conservation priority classes. These results illustrate the potential contribution of remote sensing to characterize complex human environmental interactions occurring over extended areas and timeframes.Fil: Banchero, S. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; ArgentinaFil: de Abelleyra, D. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; ArgentinaFil: Verón, S.R. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; ArgentinaFil: Arevalos, F. Asociación Guyra Paraguay; ParaguayFil: Volante, J.N. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Salta; ArgentinaFil: Mosciaro, M.J. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Salta; ArgentinaLAGIRS2020-10-27T11:32:11Z2020-10-27T11:32:11Z2020-03-24info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfhttp://hdl.handle.net/20.500.12123/8133978-1-7281-4350-7LAGIRS 2020 Conferencia Latinoamericana de Teledetección GRSS & ISPRS, 22 al 26 de marzo de 2020, Santiago de Chile p. 511-514reponame:INTA Digital (INTA)instname:Instituto Nacional de Tecnología Agropecuariaenginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)2025-11-06T09:40:33Zoai:localhost:20.500.12123/8133instacron:INTAInstitucionalhttp://repositorio.inta.gob.ar/Organismo científico-tecnológicoNo correspondehttp://repositorio.inta.gob.ar/oai/requesttripaldi.nicolas@inta.gob.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:l2025-11-06 09:40:34.39INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuariafalse
dc.title.none.fl_str_mv Recent land use and land cover change dinamics in the Gran Chaco Americano
title Recent land use and land cover change dinamics in the Gran Chaco Americano
spellingShingle Recent land use and land cover change dinamics in the Gran Chaco Americano
Banchero, Santiago
Utilización de la Tierra
Teledetección
Land Use
Remote Sensing
Land Cover
Cobertura de Suelos
Región Chaqueña
Gran Chaco, Argentina
title_short Recent land use and land cover change dinamics in the Gran Chaco Americano
title_full Recent land use and land cover change dinamics in the Gran Chaco Americano
title_fullStr Recent land use and land cover change dinamics in the Gran Chaco Americano
title_full_unstemmed Recent land use and land cover change dinamics in the Gran Chaco Americano
title_sort Recent land use and land cover change dinamics in the Gran Chaco Americano
dc.creator.none.fl_str_mv Banchero, Santiago
De Abelleyra, Diego
Veron, Santiago Ramón
Mosciaro, Maria Jesus
Arevalos, Fabiana
Volante, Jose Norberto
author Banchero, Santiago
author_facet Banchero, Santiago
De Abelleyra, Diego
Veron, Santiago Ramón
Mosciaro, Maria Jesus
Arevalos, Fabiana
Volante, Jose Norberto
author_role author
author2 De Abelleyra, Diego
Veron, Santiago Ramón
Mosciaro, Maria Jesus
Arevalos, Fabiana
Volante, Jose Norberto
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Utilización de la Tierra
Teledetección
Land Use
Remote Sensing
Land Cover
Cobertura de Suelos
Región Chaqueña
Gran Chaco, Argentina
topic Utilización de la Tierra
Teledetección
Land Use
Remote Sensing
Land Cover
Cobertura de Suelos
Región Chaqueña
Gran Chaco, Argentina
dc.description.none.fl_txt_mv Land transformation is one of the most significant human changes on the Earth’s surface processes. Therefore, land use land cover time series are a key input for environmental monitoring, natural resources management, territorial planning enforcement at national scale. We here capitalize from the MapBiomas initiative to characterize land use land cover (LULC) change in the Gran Chaco between 2010 and 2017. Specifically we sought to a) quantify annual changes in the main LULC classes; b) identify the main LULC transitions and c) relate these transitions to current land use policies. Within the MapBiomas project, Landsat based annual maps depicting natural woody vegetation, natural herbaceous vegetation, dispersed natural vegetation, cropland, pastures, bare areas and water. We used Random Forest machine learning algorithms trained by samples produced by visual interpretation of high resolution images. Annual overall accuracy ranged from 0,73 to 0,74. Our results showed that, between 2010 and 2017, agriculture and pasture lands increased ca. 3.7 Mha while natural forestry decreased by 2.3 Mha. Transitions from forests to agriculture accounted for 1.14% of the overall deforestation while 86% was associated to pastures and natural herbaceous vegetation. In Argentina, forest loss occurred primarily (39%) on areas non considered by the territorial planning Law, followed by medium (33%), high (19%) and low (9%) conservation priority classes. These results illustrate the potential contribution of remote sensing to characterize complex human environmental interactions occurring over extended areas and timeframes.
Fil: Banchero, S. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina
Fil: de Abelleyra, D. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina
Fil: Verón, S.R. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina
Fil: Arevalos, F. Asociación Guyra Paraguay; Paraguay
Fil: Volante, J.N. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Salta; Argentina
Fil: Mosciaro, M.J. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Salta; Argentina
description Land transformation is one of the most significant human changes on the Earth’s surface processes. Therefore, land use land cover time series are a key input for environmental monitoring, natural resources management, territorial planning enforcement at national scale. We here capitalize from the MapBiomas initiative to characterize land use land cover (LULC) change in the Gran Chaco between 2010 and 2017. Specifically we sought to a) quantify annual changes in the main LULC classes; b) identify the main LULC transitions and c) relate these transitions to current land use policies. Within the MapBiomas project, Landsat based annual maps depicting natural woody vegetation, natural herbaceous vegetation, dispersed natural vegetation, cropland, pastures, bare areas and water. We used Random Forest machine learning algorithms trained by samples produced by visual interpretation of high resolution images. Annual overall accuracy ranged from 0,73 to 0,74. Our results showed that, between 2010 and 2017, agriculture and pasture lands increased ca. 3.7 Mha while natural forestry decreased by 2.3 Mha. Transitions from forests to agriculture accounted for 1.14% of the overall deforestation while 86% was associated to pastures and natural herbaceous vegetation. In Argentina, forest loss occurred primarily (39%) on areas non considered by the territorial planning Law, followed by medium (33%), high (19%) and low (9%) conservation priority classes. These results illustrate the potential contribution of remote sensing to characterize complex human environmental interactions occurring over extended areas and timeframes.
publishDate 2020
dc.date.none.fl_str_mv 2020-10-27T11:32:11Z
2020-10-27T11:32:11Z
2020-03-24
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dc.identifier.none.fl_str_mv http://hdl.handle.net/20.500.12123/8133
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url http://hdl.handle.net/20.500.12123/8133
identifier_str_mv 978-1-7281-4350-7
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv LAGIRS
publisher.none.fl_str_mv LAGIRS
dc.source.none.fl_str_mv LAGIRS 2020 Conferencia Latinoamericana de Teledetección GRSS & ISPRS, 22 al 26 de marzo de 2020, Santiago de Chile p. 511-514
reponame:INTA Digital (INTA)
instname:Instituto Nacional de Tecnología Agropecuaria
reponame_str INTA Digital (INTA)
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instname_str Instituto Nacional de Tecnología Agropecuaria
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