Multi-Temporal Remote Sensing for Forest Conservation and Management: A Case Study of the Gran Chaco in Central Argentina

Autores
Alaggia, Francisco Guillermo; Innangi, Michele; Cavallero, Laura; López, Dardo Rubén; Pontieri, Federica; Marzialetti, Flavio; Riera Tatché, Ramon; Gamba, Paolo; Carranza, Maria Laura
Año de publicación
2025
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Anthropogenic alteration of tropical and subtropical forests is a major driver of biodi-versity loss, with the Chaco forest, the largest dry forest in the Americas, among the most impacted regions. Sustainable forest management, a key objective of the UN´s 15th Sustainable Development Goal (SDG), underscores the need for advanced moni-toring tools. This study integrates Sentinel-2 remote sensing (RS) spectral indices with field data to analyze forests under varying management regimes and levels of altera-tion in a representative area of the Chaco region (Chancaní Provincial Reserve and surrounding areas of the West Arid Chaco). Forest structure types and conservation levels were linked to monthly spectral index behavior using Linear Mixed Models and Random Forest analysis. Spectral indices such as BI (Brightness Index), NDWI (Normalized Difference Water Index), and MCARI (Modified Chlorophyll Absorption in Reflectance Index) effectively differentiated forest stands by conservation status and structural alteration. This combined RS and field data approach proved highly effective for detecting and characterizing forests with diverse conservation and sustainability conditions. The methodology demonstrates significant potential as a reliable RS-based tool for monitoring forest health and supporting progress toward SDG targets, particularly in regions like the Chaco forest, which faces extensive anthropogenic pressures.
Fil: Alaggia, Francisco Guillermo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Córdoba. Estación Experimental Agropecuaria Manfredi. Estación Forestal Villa Dolores; Argentina
Fil: Innangi, Michele. Università degli Studi del Molise; Italia
Fil: Cavallero, Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Córdoba. Estación Experimental Agropecuaria Manfredi. Estación Forestal Villa Dolores; Argentina
Fil: López, Dardo Rubén. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Córdoba. Estación Experimental Agropecuaria Manfredi. Estación Forestal Villa Dolores; Argentina
Fil: Pontieri, Federica. Università degli Studi del Molise; Italia
Fil: Marzialetti, Flavio. National Biodiversity Future Center; Italia. University of Sassari; Italia
Fil: Riera Tatché, Ramon. Università degli Studi del Molise; Italia. Universita degli Studi di Pavia; Italia
Fil: Gamba, Paolo. Universita degli Studi di Pavia; Italia
Fil: Carranza, Maria Laura. Università degli Studi del Molise; Italia. Universita Degli Studi Di Pavia; Italia
Materia
ECOSYSTEM MONITORING
STRUCTURAL ALTERATION INDEX
INDEXES PHENOLOGY
RANDOM FOREST
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/272038
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Multi-Temporal Remote Sensing for Forest Conservation and Management: A Case Study of the Gran Chaco in Central ArgentinaAlaggia, Francisco GuillermoInnangi, MicheleCavallero, LauraLópez, Dardo RubénPontieri, FedericaMarzialetti, FlavioRiera Tatché, RamonGamba, PaoloCarranza, Maria LauraECOSYSTEM MONITORINGSTRUCTURAL ALTERATION INDEXINDEXES PHENOLOGYRANDOM FORESThttps://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1Anthropogenic alteration of tropical and subtropical forests is a major driver of biodi-versity loss, with the Chaco forest, the largest dry forest in the Americas, among the most impacted regions. Sustainable forest management, a key objective of the UN´s 15th Sustainable Development Goal (SDG), underscores the need for advanced moni-toring tools. This study integrates Sentinel-2 remote sensing (RS) spectral indices with field data to analyze forests under varying management regimes and levels of altera-tion in a representative area of the Chaco region (Chancaní Provincial Reserve and surrounding areas of the West Arid Chaco). Forest structure types and conservation levels were linked to monthly spectral index behavior using Linear Mixed Models and Random Forest analysis. Spectral indices such as BI (Brightness Index), NDWI (Normalized Difference Water Index), and MCARI (Modified Chlorophyll Absorption in Reflectance Index) effectively differentiated forest stands by conservation status and structural alteration. This combined RS and field data approach proved highly effective for detecting and characterizing forests with diverse conservation and sustainability conditions. The methodology demonstrates significant potential as a reliable RS-based tool for monitoring forest health and supporting progress toward SDG targets, particularly in regions like the Chaco forest, which faces extensive anthropogenic pressures.Fil: Alaggia, Francisco Guillermo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Córdoba. Estación Experimental Agropecuaria Manfredi. Estación Forestal Villa Dolores; ArgentinaFil: Innangi, Michele. Università degli Studi del Molise; ItaliaFil: Cavallero, Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Córdoba. Estación Experimental Agropecuaria Manfredi. Estación Forestal Villa Dolores; ArgentinaFil: López, Dardo Rubén. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Córdoba. Estación Experimental Agropecuaria Manfredi. Estación Forestal Villa Dolores; ArgentinaFil: Pontieri, Federica. Università degli Studi del Molise; ItaliaFil: Marzialetti, Flavio. National Biodiversity Future Center; Italia. University of Sassari; ItaliaFil: Riera Tatché, Ramon. Università degli Studi del Molise; Italia. Universita degli Studi di Pavia; ItaliaFil: Gamba, Paolo. Universita degli Studi di Pavia; ItaliaFil: Carranza, Maria Laura. Università degli Studi del Molise; Italia. Universita Degli Studi Di Pavia; ItaliaMultidisciplinary Digital Publishing Institute2025-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/272038Alaggia, Francisco Guillermo; Innangi, Michele; Cavallero, Laura; López, Dardo Rubén; Pontieri, Federica; et al.; Multi-Temporal Remote Sensing for Forest Conservation and Management: A Case Study of the Gran Chaco in Central Argentina; Multidisciplinary Digital Publishing Institute; Remote Sensing; 17; 5; 3-2025; 1-262072-4292CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.mdpi.com/2072-4292/17/5/748info:eu-repo/semantics/altIdentifier/doi/10.3390/rs17050748info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:32:40Zoai:ri.conicet.gov.ar:11336/272038instacron: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:34982025-09-29 09:32:40.902CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Multi-Temporal Remote Sensing for Forest Conservation and Management: A Case Study of the Gran Chaco in Central Argentina
title Multi-Temporal Remote Sensing for Forest Conservation and Management: A Case Study of the Gran Chaco in Central Argentina
spellingShingle Multi-Temporal Remote Sensing for Forest Conservation and Management: A Case Study of the Gran Chaco in Central Argentina
Alaggia, Francisco Guillermo
ECOSYSTEM MONITORING
STRUCTURAL ALTERATION INDEX
INDEXES PHENOLOGY
RANDOM FOREST
title_short Multi-Temporal Remote Sensing for Forest Conservation and Management: A Case Study of the Gran Chaco in Central Argentina
title_full Multi-Temporal Remote Sensing for Forest Conservation and Management: A Case Study of the Gran Chaco in Central Argentina
title_fullStr Multi-Temporal Remote Sensing for Forest Conservation and Management: A Case Study of the Gran Chaco in Central Argentina
title_full_unstemmed Multi-Temporal Remote Sensing for Forest Conservation and Management: A Case Study of the Gran Chaco in Central Argentina
title_sort Multi-Temporal Remote Sensing for Forest Conservation and Management: A Case Study of the Gran Chaco in Central Argentina
dc.creator.none.fl_str_mv Alaggia, Francisco Guillermo
Innangi, Michele
Cavallero, Laura
López, Dardo Rubén
Pontieri, Federica
Marzialetti, Flavio
Riera Tatché, Ramon
Gamba, Paolo
Carranza, Maria Laura
author Alaggia, Francisco Guillermo
author_facet Alaggia, Francisco Guillermo
Innangi, Michele
Cavallero, Laura
López, Dardo Rubén
Pontieri, Federica
Marzialetti, Flavio
Riera Tatché, Ramon
Gamba, Paolo
Carranza, Maria Laura
author_role author
author2 Innangi, Michele
Cavallero, Laura
López, Dardo Rubén
Pontieri, Federica
Marzialetti, Flavio
Riera Tatché, Ramon
Gamba, Paolo
Carranza, Maria Laura
author2_role author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv ECOSYSTEM MONITORING
STRUCTURAL ALTERATION INDEX
INDEXES PHENOLOGY
RANDOM FOREST
topic ECOSYSTEM MONITORING
STRUCTURAL ALTERATION INDEX
INDEXES PHENOLOGY
RANDOM FOREST
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.5
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Anthropogenic alteration of tropical and subtropical forests is a major driver of biodi-versity loss, with the Chaco forest, the largest dry forest in the Americas, among the most impacted regions. Sustainable forest management, a key objective of the UN´s 15th Sustainable Development Goal (SDG), underscores the need for advanced moni-toring tools. This study integrates Sentinel-2 remote sensing (RS) spectral indices with field data to analyze forests under varying management regimes and levels of altera-tion in a representative area of the Chaco region (Chancaní Provincial Reserve and surrounding areas of the West Arid Chaco). Forest structure types and conservation levels were linked to monthly spectral index behavior using Linear Mixed Models and Random Forest analysis. Spectral indices such as BI (Brightness Index), NDWI (Normalized Difference Water Index), and MCARI (Modified Chlorophyll Absorption in Reflectance Index) effectively differentiated forest stands by conservation status and structural alteration. This combined RS and field data approach proved highly effective for detecting and characterizing forests with diverse conservation and sustainability conditions. The methodology demonstrates significant potential as a reliable RS-based tool for monitoring forest health and supporting progress toward SDG targets, particularly in regions like the Chaco forest, which faces extensive anthropogenic pressures.
Fil: Alaggia, Francisco Guillermo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Córdoba. Estación Experimental Agropecuaria Manfredi. Estación Forestal Villa Dolores; Argentina
Fil: Innangi, Michele. Università degli Studi del Molise; Italia
Fil: Cavallero, Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Córdoba. Estación Experimental Agropecuaria Manfredi. Estación Forestal Villa Dolores; Argentina
Fil: López, Dardo Rubén. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Córdoba. Estación Experimental Agropecuaria Manfredi. Estación Forestal Villa Dolores; Argentina
Fil: Pontieri, Federica. Università degli Studi del Molise; Italia
Fil: Marzialetti, Flavio. National Biodiversity Future Center; Italia. University of Sassari; Italia
Fil: Riera Tatché, Ramon. Università degli Studi del Molise; Italia. Universita degli Studi di Pavia; Italia
Fil: Gamba, Paolo. Universita degli Studi di Pavia; Italia
Fil: Carranza, Maria Laura. Università degli Studi del Molise; Italia. Universita Degli Studi Di Pavia; Italia
description Anthropogenic alteration of tropical and subtropical forests is a major driver of biodi-versity loss, with the Chaco forest, the largest dry forest in the Americas, among the most impacted regions. Sustainable forest management, a key objective of the UN´s 15th Sustainable Development Goal (SDG), underscores the need for advanced moni-toring tools. This study integrates Sentinel-2 remote sensing (RS) spectral indices with field data to analyze forests under varying management regimes and levels of altera-tion in a representative area of the Chaco region (Chancaní Provincial Reserve and surrounding areas of the West Arid Chaco). Forest structure types and conservation levels were linked to monthly spectral index behavior using Linear Mixed Models and Random Forest analysis. Spectral indices such as BI (Brightness Index), NDWI (Normalized Difference Water Index), and MCARI (Modified Chlorophyll Absorption in Reflectance Index) effectively differentiated forest stands by conservation status and structural alteration. This combined RS and field data approach proved highly effective for detecting and characterizing forests with diverse conservation and sustainability conditions. The methodology demonstrates significant potential as a reliable RS-based tool for monitoring forest health and supporting progress toward SDG targets, particularly in regions like the Chaco forest, which faces extensive anthropogenic pressures.
publishDate 2025
dc.date.none.fl_str_mv 2025-03
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/11336/272038
Alaggia, Francisco Guillermo; Innangi, Michele; Cavallero, Laura; López, Dardo Rubén; Pontieri, Federica; et al.; Multi-Temporal Remote Sensing for Forest Conservation and Management: A Case Study of the Gran Chaco in Central Argentina; Multidisciplinary Digital Publishing Institute; Remote Sensing; 17; 5; 3-2025; 1-26
2072-4292
CONICET Digital
CONICET
url http://hdl.handle.net/11336/272038
identifier_str_mv Alaggia, Francisco Guillermo; Innangi, Michele; Cavallero, Laura; López, Dardo Rubén; Pontieri, Federica; et al.; Multi-Temporal Remote Sensing for Forest Conservation and Management: A Case Study of the Gran Chaco in Central Argentina; Multidisciplinary Digital Publishing Institute; Remote Sensing; 17; 5; 3-2025; 1-26
2072-4292
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.mdpi.com/2072-4292/17/5/748
info:eu-repo/semantics/altIdentifier/doi/10.3390/rs17050748
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute
publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute
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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