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
.jpg)
- Institución
- Instituto Nacional de Tecnología Agropecuaria
- OAI Identificador
- oai:localhost:20.500.12123/8133
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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. |
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2020 |
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2020-10-27T11:32:11Z 2020-10-27T11:32:11Z 2020-03-24 |
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info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_5794 info:ar-repo/semantics/documentoDeConferencia |
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eng |
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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 |
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