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

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Pubblicato in:Remote Sensing vol. 17, no. 5 (2025), p. 748
Autore principale: Alaggia, Francisco G
Altri autori: Innangi, Michele, Cavallero, Laura, López, Dardo Rubén, Pontieri, Federica, Marzialetti, Flavio, Riera-Tatché, Ramon, Gamba, Paolo, Carranza, Maria Laura
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100 1 |a Alaggia, Francisco G  |u Instituto Nacional de Tecnología Agropecuaria, Estación Forestal Villa Dolores (EEA Manfredi), Las Encrucijadas, Camino Viejo a San José, Km 1 Villa Dolores, Córdoba 5870, Argentina; <email>franciscoalaggia@gmail.com</email> (F.G.A.); <email>cavallero.lauri@gmail.com</email> (L.C.); <email>lopez.dardor@inta.gob.ar</email> (D.R.L.) 
245 1 |a Multi-Temporal Remote Sensing for Forest Conservation and Management: A Case Study of the Gran Chaco in Central Argentina 
260 |b MDPI AG  |c 2025 
513 |a Case Study Journal Article 
520 3 |a Anthropogenic alteration of tropical and subtropical forests is a major driver of biodiversity loss; notably, the Chaco Forest, which is the largest dry forest in the Americas, is 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 monitoring tools. This study integrates Sentinel-2 remote sensing (RS) spectral indices with field data to analyze forests under varying management regimes and levels of alteration 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. Spectral indices such as the BI (Brightness Index), NDWIGao (Normalized Difference Water Index), and MCARISent (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 face extensive anthropogenic pressures. 
651 4 |a Argentina 
651 4 |a Chaco region 
653 |a Forest management 
653 |a Desertification 
653 |a Sustainability management 
653 |a Conservation status 
653 |a Biodiversity 
653 |a Remote sensing 
653 |a Phenology 
653 |a Biomass 
653 |a Forest conservation 
653 |a Land degradation 
653 |a Ecosystems 
653 |a Dry forests 
653 |a Vegetation 
653 |a Tropical forests 
653 |a Sustainable forestry 
653 |a Biodiversity loss 
653 |a Hypotheses 
653 |a Sustainable development 
653 |a Conservation 
700 1 |a Innangi, Michele  |u EnviXLab, Department of Biosciences and Territory, University of Molise, Contrada Fonte Lappone, 86090 Pesche, Italy; <email>f.pontieri@studenti.unimol.it</email> (F.P.); <email>rrierat@gmail.com</email> (R.R.-T.); <email>carranza@unimol.it</email> (M.L.C.) 
700 1 |a Cavallero, Laura  |u Instituto Nacional de Tecnología Agropecuaria, Estación Forestal Villa Dolores (EEA Manfredi), Las Encrucijadas, Camino Viejo a San José, Km 1 Villa Dolores, Córdoba 5870, Argentina; <email>franciscoalaggia@gmail.com</email> (F.G.A.); <email>cavallero.lauri@gmail.com</email> (L.C.); <email>lopez.dardor@inta.gob.ar</email> (D.R.L.); Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), CCT Córdoba, Av. Ciudad de Valparaíso S/N, Córdoba 5000, Argentina 
700 1 |a López, Dardo Rubén  |u Instituto Nacional de Tecnología Agropecuaria, Estación Forestal Villa Dolores (EEA Manfredi), Las Encrucijadas, Camino Viejo a San José, Km 1 Villa Dolores, Córdoba 5870, Argentina; <email>franciscoalaggia@gmail.com</email> (F.G.A.); <email>cavallero.lauri@gmail.com</email> (L.C.); <email>lopez.dardor@inta.gob.ar</email> (D.R.L.); Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), CCT Córdoba, Av. Ciudad de Valparaíso S/N, Córdoba 5000, Argentina 
700 1 |a Pontieri, Federica  |u EnviXLab, Department of Biosciences and Territory, University of Molise, Contrada Fonte Lappone, 86090 Pesche, Italy; <email>f.pontieri@studenti.unimol.it</email> (F.P.); <email>rrierat@gmail.com</email> (R.R.-T.); <email>carranza@unimol.it</email> (M.L.C.) 
700 1 |a Marzialetti, Flavio  |u National Biodiversity Future Center (NBFC), 90133 Palermo, Italy; <email>fmarzialetti@uniss.it</email>; Department of Agricultural Sciences, University of Sassari, Viale Italia 39/a, 07100 Sassari, Italy 
700 1 |a Riera-Tatché, Ramon  |u EnviXLab, Department of Biosciences and Territory, University of Molise, Contrada Fonte Lappone, 86090 Pesche, Italy; <email>f.pontieri@studenti.unimol.it</email> (F.P.); <email>rrierat@gmail.com</email> (R.R.-T.); <email>carranza@unimol.it</email> (M.L.C.); Department of Electrical, Biomedical and Computer Engineering, University of Pavia, Via Ferrata 5, 27100 Pavia, Italy; <email>paolo.gamba@unipv.it</email> 
700 1 |a Gamba, Paolo  |u Department of Electrical, Biomedical and Computer Engineering, University of Pavia, Via Ferrata 5, 27100 Pavia, Italy; <email>paolo.gamba@unipv.it</email> 
700 1 |a Carranza, Maria Laura  |u EnviXLab, Department of Biosciences and Territory, University of Molise, Contrada Fonte Lappone, 86090 Pesche, Italy; <email>f.pontieri@studenti.unimol.it</email> (F.P.); <email>rrierat@gmail.com</email> (R.R.-T.); <email>carranza@unimol.it</email> (M.L.C.); National Biodiversity Future Center (NBFC), 90133 Palermo, Italy; <email>fmarzialetti@uniss.it</email> 
773 0 |t Remote Sensing  |g vol. 17, no. 5 (2025), p. 748 
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