Mapping continuous fields of tree and shrub cover across the Gran Chaco using Landsat 8 and Sentinel-1 data

Autores
Baumann, Matthias; Levers, Christian; Macchi, Leandro; Bluhm, Hendrik; Waske, Björn; Gasparri, Nestor Ignacio; Kuemmerle, Tobias
Año de publicación
2018
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Tropical dry forests and savannas provide important ecosystem services and harbor high biodiversity, yet are globally under pressure from land-use change. Mapping changes in the condition of dry forests and savannas is therefore critical. This can be challenging given that these ecosystems are characterized by continuous gradients of tree and shrub cover, resulting in considerable structural complexity. We developed a novel approach to map, separately, continuous fields of tree cover and shrub cover across the South American Gran Chaco (1,100,000 km2), making full use of the Landsat-8 optical and Sentinel-1 synthetic aperture radar (SAR) image archives. We gathered a large training dataset digitized from very-high resolution imagery and used a gradient-boosting framework to model continuous fields of tree cover and shrub cover at 30-m resolution. Our regression models had high to moderate predictive power (85.5% for tree cover, and 68.5% for shrub cover) and resulted in reliable tree and shrub cover maps (mean squared error of 4.4% and 6.4% for tree- and shrub cover respectively). Models jointly using optical and SAR imagery performed substantially better than models using single-sensor imagery, and model predictors differed strongly in some regions, especially in areas of dense vegetation cover. Mapping tree and shrub cover separately allowed identifying distinct vegetation formations, with shrub-dominated systems mainly in the very dry Chaco, woodlands with large trees mainly in the dry Chaco, and tree-dominated savannas in the wet Chaco. Our tree and shrub cover layers also revealed considerable edge effects in terms of woody cover away from agricultural fields (edge effects extending about 2 km), smallholder ranches (about 1.2 km), and roads and railways (about 1.4 and 0.9 km, respectively). Our analyses highlight both the substantial footprint of land-use on remaining natural vegetation in the Chaco, and the potential of multi-sensoral approaches to monitor forest degradation. More broadly, our approach shows that mapping canopy structure and distinct layers of woody vegetation in dry forest and savannas is possible across large areas, and highlights the value of the growing Landsat and Sentinel archives for doing so.
Fil: Baumann, Matthias. Universität zu Berlin; Alemania
Fil: Levers, Christian.
Fil: Macchi, Leandro. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; Argentina. Universität zu Berlin; Alemania
Fil: Bluhm, Hendrik. Universität zu Berlin; Alemania
Fil: Waske, Björn. Universität zu Berlin; Alemania
Fil: Gasparri, Nestor Ignacio. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; Argentina. Universität zu Berlin; Alemania
Fil: Kuemmerle, Tobias. Universität zu Berlin; Alemania
Materia
CANOPY STRUCTURE
ESSENTIAL BIODIVERSITY VARIABLES
FOREST DEGRADATION
GRADIENT BOOSTING REGRESSION
SAVANNAS
SENSOR FUSION
TROPICAL DRY FORESTS
VEGETATION CONTINUOUS FIELDS
Nivel de accesibilidad
acceso abierto
Condiciones de uso
Atribución-NoComercial-CompartirIgual 2.5 Argentina (CC BY-NC-SA 2.5 AR)
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/90415

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network_name_str CONICET Digital (CONICET)
spelling Mapping continuous fields of tree and shrub cover across the Gran Chaco using Landsat 8 and Sentinel-1 dataBaumann, MatthiasLevers, ChristianMacchi, LeandroBluhm, HendrikWaske, BjörnGasparri, Nestor IgnacioKuemmerle, TobiasCANOPY STRUCTUREESSENTIAL BIODIVERSITY VARIABLESFOREST DEGRADATIONGRADIENT BOOSTING REGRESSIONSAVANNASSENSOR FUSIONTROPICAL DRY FORESTSVEGETATION CONTINUOUS FIELDShttps://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1https://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1https://purl.org/becyt/ford/4.1https://purl.org/becyt/ford/4Tropical dry forests and savannas provide important ecosystem services and harbor high biodiversity, yet are globally under pressure from land-use change. Mapping changes in the condition of dry forests and savannas is therefore critical. This can be challenging given that these ecosystems are characterized by continuous gradients of tree and shrub cover, resulting in considerable structural complexity. We developed a novel approach to map, separately, continuous fields of tree cover and shrub cover across the South American Gran Chaco (1,100,000 km2), making full use of the Landsat-8 optical and Sentinel-1 synthetic aperture radar (SAR) image archives. We gathered a large training dataset digitized from very-high resolution imagery and used a gradient-boosting framework to model continuous fields of tree cover and shrub cover at 30-m resolution. Our regression models had high to moderate predictive power (85.5% for tree cover, and 68.5% for shrub cover) and resulted in reliable tree and shrub cover maps (mean squared error of 4.4% and 6.4% for tree- and shrub cover respectively). Models jointly using optical and SAR imagery performed substantially better than models using single-sensor imagery, and model predictors differed strongly in some regions, especially in areas of dense vegetation cover. Mapping tree and shrub cover separately allowed identifying distinct vegetation formations, with shrub-dominated systems mainly in the very dry Chaco, woodlands with large trees mainly in the dry Chaco, and tree-dominated savannas in the wet Chaco. Our tree and shrub cover layers also revealed considerable edge effects in terms of woody cover away from agricultural fields (edge effects extending about 2 km), smallholder ranches (about 1.2 km), and roads and railways (about 1.4 and 0.9 km, respectively). Our analyses highlight both the substantial footprint of land-use on remaining natural vegetation in the Chaco, and the potential of multi-sensoral approaches to monitor forest degradation. More broadly, our approach shows that mapping canopy structure and distinct layers of woody vegetation in dry forest and savannas is possible across large areas, and highlights the value of the growing Landsat and Sentinel archives for doing so.Fil: Baumann, Matthias. Universität zu Berlin; AlemaniaFil: Levers, Christian.Fil: Macchi, Leandro. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; Argentina. Universität zu Berlin; AlemaniaFil: Bluhm, Hendrik. Universität zu Berlin; AlemaniaFil: Waske, Björn. Universität zu Berlin; AlemaniaFil: Gasparri, Nestor Ignacio. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; Argentina. Universität zu Berlin; AlemaniaFil: Kuemmerle, Tobias. Universität zu Berlin; AlemaniaElsevier Science Inc2018-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/90415Baumann, Matthias; Levers, Christian; Macchi, Leandro; Bluhm, Hendrik; Waske, Björn; et al.; Mapping continuous fields of tree and shrub cover across the Gran Chaco using Landsat 8 and Sentinel-1 data; Elsevier Science Inc; Remote Sensing of Environment; 216; 10-2018; 201-2110034-4257CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/abs/pii/S0034425718303249info:eu-repo/semantics/altIdentifier/doi/10.1016/j.rse.2018.06.044info:eu-repo/semantics/openAccessAtribución-NoComercial-CompartirIgual 2.5 Argentina (CC BY-NC-SA 2.5 AR)https://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T14:20:56Zoai:ri.conicet.gov.ar:11336/90415instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-15 14:20:56.907CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Mapping continuous fields of tree and shrub cover across the Gran Chaco using Landsat 8 and Sentinel-1 data
title Mapping continuous fields of tree and shrub cover across the Gran Chaco using Landsat 8 and Sentinel-1 data
spellingShingle Mapping continuous fields of tree and shrub cover across the Gran Chaco using Landsat 8 and Sentinel-1 data
Baumann, Matthias
CANOPY STRUCTURE
ESSENTIAL BIODIVERSITY VARIABLES
FOREST DEGRADATION
GRADIENT BOOSTING REGRESSION
SAVANNAS
SENSOR FUSION
TROPICAL DRY FORESTS
VEGETATION CONTINUOUS FIELDS
title_short Mapping continuous fields of tree and shrub cover across the Gran Chaco using Landsat 8 and Sentinel-1 data
title_full Mapping continuous fields of tree and shrub cover across the Gran Chaco using Landsat 8 and Sentinel-1 data
title_fullStr Mapping continuous fields of tree and shrub cover across the Gran Chaco using Landsat 8 and Sentinel-1 data
title_full_unstemmed Mapping continuous fields of tree and shrub cover across the Gran Chaco using Landsat 8 and Sentinel-1 data
title_sort Mapping continuous fields of tree and shrub cover across the Gran Chaco using Landsat 8 and Sentinel-1 data
dc.creator.none.fl_str_mv Baumann, Matthias
Levers, Christian
Macchi, Leandro
Bluhm, Hendrik
Waske, Björn
Gasparri, Nestor Ignacio
Kuemmerle, Tobias
author Baumann, Matthias
author_facet Baumann, Matthias
Levers, Christian
Macchi, Leandro
Bluhm, Hendrik
Waske, Björn
Gasparri, Nestor Ignacio
Kuemmerle, Tobias
author_role author
author2 Levers, Christian
Macchi, Leandro
Bluhm, Hendrik
Waske, Björn
Gasparri, Nestor Ignacio
Kuemmerle, Tobias
author2_role author
author
author
author
author
author
dc.subject.none.fl_str_mv CANOPY STRUCTURE
ESSENTIAL BIODIVERSITY VARIABLES
FOREST DEGRADATION
GRADIENT BOOSTING REGRESSION
SAVANNAS
SENSOR FUSION
TROPICAL DRY FORESTS
VEGETATION CONTINUOUS FIELDS
topic CANOPY STRUCTURE
ESSENTIAL BIODIVERSITY VARIABLES
FOREST DEGRADATION
GRADIENT BOOSTING REGRESSION
SAVANNAS
SENSOR FUSION
TROPICAL DRY FORESTS
VEGETATION CONTINUOUS FIELDS
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.5
https://purl.org/becyt/ford/1
https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
https://purl.org/becyt/ford/4.1
https://purl.org/becyt/ford/4
dc.description.none.fl_txt_mv Tropical dry forests and savannas provide important ecosystem services and harbor high biodiversity, yet are globally under pressure from land-use change. Mapping changes in the condition of dry forests and savannas is therefore critical. This can be challenging given that these ecosystems are characterized by continuous gradients of tree and shrub cover, resulting in considerable structural complexity. We developed a novel approach to map, separately, continuous fields of tree cover and shrub cover across the South American Gran Chaco (1,100,000 km2), making full use of the Landsat-8 optical and Sentinel-1 synthetic aperture radar (SAR) image archives. We gathered a large training dataset digitized from very-high resolution imagery and used a gradient-boosting framework to model continuous fields of tree cover and shrub cover at 30-m resolution. Our regression models had high to moderate predictive power (85.5% for tree cover, and 68.5% for shrub cover) and resulted in reliable tree and shrub cover maps (mean squared error of 4.4% and 6.4% for tree- and shrub cover respectively). Models jointly using optical and SAR imagery performed substantially better than models using single-sensor imagery, and model predictors differed strongly in some regions, especially in areas of dense vegetation cover. Mapping tree and shrub cover separately allowed identifying distinct vegetation formations, with shrub-dominated systems mainly in the very dry Chaco, woodlands with large trees mainly in the dry Chaco, and tree-dominated savannas in the wet Chaco. Our tree and shrub cover layers also revealed considerable edge effects in terms of woody cover away from agricultural fields (edge effects extending about 2 km), smallholder ranches (about 1.2 km), and roads and railways (about 1.4 and 0.9 km, respectively). Our analyses highlight both the substantial footprint of land-use on remaining natural vegetation in the Chaco, and the potential of multi-sensoral approaches to monitor forest degradation. More broadly, our approach shows that mapping canopy structure and distinct layers of woody vegetation in dry forest and savannas is possible across large areas, and highlights the value of the growing Landsat and Sentinel archives for doing so.
Fil: Baumann, Matthias. Universität zu Berlin; Alemania
Fil: Levers, Christian.
Fil: Macchi, Leandro. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; Argentina. Universität zu Berlin; Alemania
Fil: Bluhm, Hendrik. Universität zu Berlin; Alemania
Fil: Waske, Björn. Universität zu Berlin; Alemania
Fil: Gasparri, Nestor Ignacio. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; Argentina. Universität zu Berlin; Alemania
Fil: Kuemmerle, Tobias. Universität zu Berlin; Alemania
description Tropical dry forests and savannas provide important ecosystem services and harbor high biodiversity, yet are globally under pressure from land-use change. Mapping changes in the condition of dry forests and savannas is therefore critical. This can be challenging given that these ecosystems are characterized by continuous gradients of tree and shrub cover, resulting in considerable structural complexity. We developed a novel approach to map, separately, continuous fields of tree cover and shrub cover across the South American Gran Chaco (1,100,000 km2), making full use of the Landsat-8 optical and Sentinel-1 synthetic aperture radar (SAR) image archives. We gathered a large training dataset digitized from very-high resolution imagery and used a gradient-boosting framework to model continuous fields of tree cover and shrub cover at 30-m resolution. Our regression models had high to moderate predictive power (85.5% for tree cover, and 68.5% for shrub cover) and resulted in reliable tree and shrub cover maps (mean squared error of 4.4% and 6.4% for tree- and shrub cover respectively). Models jointly using optical and SAR imagery performed substantially better than models using single-sensor imagery, and model predictors differed strongly in some regions, especially in areas of dense vegetation cover. Mapping tree and shrub cover separately allowed identifying distinct vegetation formations, with shrub-dominated systems mainly in the very dry Chaco, woodlands with large trees mainly in the dry Chaco, and tree-dominated savannas in the wet Chaco. Our tree and shrub cover layers also revealed considerable edge effects in terms of woody cover away from agricultural fields (edge effects extending about 2 km), smallholder ranches (about 1.2 km), and roads and railways (about 1.4 and 0.9 km, respectively). Our analyses highlight both the substantial footprint of land-use on remaining natural vegetation in the Chaco, and the potential of multi-sensoral approaches to monitor forest degradation. More broadly, our approach shows that mapping canopy structure and distinct layers of woody vegetation in dry forest and savannas is possible across large areas, and highlights the value of the growing Landsat and Sentinel archives for doing so.
publishDate 2018
dc.date.none.fl_str_mv 2018-10
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/11336/90415
Baumann, Matthias; Levers, Christian; Macchi, Leandro; Bluhm, Hendrik; Waske, Björn; et al.; Mapping continuous fields of tree and shrub cover across the Gran Chaco using Landsat 8 and Sentinel-1 data; Elsevier Science Inc; Remote Sensing of Environment; 216; 10-2018; 201-211
0034-4257
CONICET Digital
CONICET
url http://hdl.handle.net/11336/90415
identifier_str_mv Baumann, Matthias; Levers, Christian; Macchi, Leandro; Bluhm, Hendrik; Waske, Björn; et al.; Mapping continuous fields of tree and shrub cover across the Gran Chaco using Landsat 8 and Sentinel-1 data; Elsevier Science Inc; Remote Sensing of Environment; 216; 10-2018; 201-211
0034-4257
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/abs/pii/S0034425718303249
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.rse.2018.06.044
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
Atribución-NoComercial-CompartirIgual 2.5 Argentina (CC BY-NC-SA 2.5 AR)
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv Atribución-NoComercial-CompartirIgual 2.5 Argentina (CC BY-NC-SA 2.5 AR)
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier Science Inc
publisher.none.fl_str_mv Elsevier Science Inc
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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