Carbon Biomass Estimation Using Vegetation Indices in Agriculture–Pasture Mosaics in the Brazilian Caatinga Dry Tropical Forest

Autores
Sousa Júnior, Vicente de Paula; Sparacino, Javier; Espindola, Giovana Mira de; Assis, Raimundo Jucier Sousa de
Año de publicación
2023
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Remote sensing is valuable for estimating aboveground biomass (AGB) stocks. However, its application in agricultural and pasture areas is limited compared with forest areas. This study quantifies AGB in agriculture–pasture mosaics within Brazil’s Campo Maior Complex (CMC). The methodology employs remote sensing cloud processing and utilizes an estimator to incorporate vegetation indices. The results reveal significant changes in biomass values among land use and land cover classes over the past ten years, with notable variations observed in forest plantation, pasture, sugar cane, and soybean areas. The estimated AGB values range from 0 to 20 Mg.ha−1 (minimum), 53 to 419 Mg.ha−1 (maximum), and 19 to 57 Mg.ha−1 (mean). In Forest formation areas, AGB values range from approximately 0 to 278 Mg.ha−1, with an average annual value of 56.44 Mg.ha−1. This study provides valuable insights for rural landowners and government officials in managing the semiarid territory and environment. It aids in decision making regarding agricultural management, irrigation and fertilization practices, agricultural productivity, land use and land cover changes, biodiversity loss, soil degradation, conservation strategies, the identification of priority areas for environmental restoration, and the optimization of resource utilization.
Fil: Sousa Júnior, Vicente de Paula. Universidade Federal Do Piaui.; Brasil
Fil: Sparacino, Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones Biológicas y Tecnológicas. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Instituto de Investigaciones Biológicas y Tecnológicas; Argentina. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Centro de Ecología y Recursos Naturales Renovables; Argentina
Fil: Espindola, Giovana Mira de. Universidade Federal Do Piaui.; Brasil
Fil: Assis, Raimundo Jucier Sousa de. Universidade Federal Do Piaui.; Brasil
Materia
SEMIARID
ABOVEGROUND BIOMASS
REMOTE SENSING
LANDSAT
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/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:11336/242024
Acceder
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network_acronym_str CONICETDig
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network_name_str CONICET Digital (CONICET)
spelling Carbon Biomass Estimation Using Vegetation Indices in Agriculture–Pasture Mosaics in the Brazilian Caatinga Dry Tropical ForestSousa Júnior, Vicente de PaulaSparacino, JavierEspindola, Giovana Mira deAssis, Raimundo Jucier Sousa deSEMIARIDABOVEGROUND BIOMASSREMOTE SENSINGLANDSAThttps://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1https://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1https://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1Remote sensing is valuable for estimating aboveground biomass (AGB) stocks. However, its application in agricultural and pasture areas is limited compared with forest areas. This study quantifies AGB in agriculture–pasture mosaics within Brazil’s Campo Maior Complex (CMC). The methodology employs remote sensing cloud processing and utilizes an estimator to incorporate vegetation indices. The results reveal significant changes in biomass values among land use and land cover classes over the past ten years, with notable variations observed in forest plantation, pasture, sugar cane, and soybean areas. The estimated AGB values range from 0 to 20 Mg.ha−1 (minimum), 53 to 419 Mg.ha−1 (maximum), and 19 to 57 Mg.ha−1 (mean). In Forest formation areas, AGB values range from approximately 0 to 278 Mg.ha−1, with an average annual value of 56.44 Mg.ha−1. This study provides valuable insights for rural landowners and government officials in managing the semiarid territory and environment. It aids in decision making regarding agricultural management, irrigation and fertilization practices, agricultural productivity, land use and land cover changes, biodiversity loss, soil degradation, conservation strategies, the identification of priority areas for environmental restoration, and the optimization of resource utilization.Fil: Sousa Júnior, Vicente de Paula. Universidade Federal Do Piaui.; BrasilFil: Sparacino, Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones Biológicas y Tecnológicas. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Instituto de Investigaciones Biológicas y Tecnológicas; Argentina. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Centro de Ecología y Recursos Naturales Renovables; ArgentinaFil: Espindola, Giovana Mira de. Universidade Federal Do Piaui.; BrasilFil: Assis, Raimundo Jucier Sousa de. Universidade Federal Do Piaui.; BrasilMultidisciplinary Digital Publishing Institute2023-08-27info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/242024Sousa Júnior, Vicente de Paula; Sparacino, Javier; Espindola, Giovana Mira de; Assis, Raimundo Jucier Sousa de; Carbon Biomass Estimation Using Vegetation Indices in Agriculture–Pasture Mosaics in the Brazilian Caatinga Dry Tropical Forest; Multidisciplinary Digital Publishing Institute; ISPRS International Journal of Geo-Information; 12; 9; 27-8-2023; 354-3732220-9964CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.3390/ijgi12090354info:eu-repo/semantics/altIdentifier/url/https://www.mdpi.com/2220-9964/12/9/354info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:17:38Zoai:ri.conicet.gov.ar:11336/242024instacron: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 10:17:39.303CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Carbon Biomass Estimation Using Vegetation Indices in Agriculture–Pasture Mosaics in the Brazilian Caatinga Dry Tropical Forest
title Carbon Biomass Estimation Using Vegetation Indices in Agriculture–Pasture Mosaics in the Brazilian Caatinga Dry Tropical Forest
spellingShingle Carbon Biomass Estimation Using Vegetation Indices in Agriculture–Pasture Mosaics in the Brazilian Caatinga Dry Tropical Forest
Sousa Júnior, Vicente de Paula
SEMIARID
ABOVEGROUND BIOMASS
REMOTE SENSING
LANDSAT
title_short Carbon Biomass Estimation Using Vegetation Indices in Agriculture–Pasture Mosaics in the Brazilian Caatinga Dry Tropical Forest
title_full Carbon Biomass Estimation Using Vegetation Indices in Agriculture–Pasture Mosaics in the Brazilian Caatinga Dry Tropical Forest
title_fullStr Carbon Biomass Estimation Using Vegetation Indices in Agriculture–Pasture Mosaics in the Brazilian Caatinga Dry Tropical Forest
title_full_unstemmed Carbon Biomass Estimation Using Vegetation Indices in Agriculture–Pasture Mosaics in the Brazilian Caatinga Dry Tropical Forest
title_sort Carbon Biomass Estimation Using Vegetation Indices in Agriculture–Pasture Mosaics in the Brazilian Caatinga Dry Tropical Forest
dc.creator.none.fl_str_mv Sousa Júnior, Vicente de Paula
Sparacino, Javier
Espindola, Giovana Mira de
Assis, Raimundo Jucier Sousa de
author Sousa Júnior, Vicente de Paula
author_facet Sousa Júnior, Vicente de Paula
Sparacino, Javier
Espindola, Giovana Mira de
Assis, Raimundo Jucier Sousa de
author_role author
author2 Sparacino, Javier
Espindola, Giovana Mira de
Assis, Raimundo Jucier Sousa de
author2_role author
author
author
dc.subject.none.fl_str_mv SEMIARID
ABOVEGROUND BIOMASS
REMOTE SENSING
LANDSAT
topic SEMIARID
ABOVEGROUND BIOMASS
REMOTE SENSING
LANDSAT
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.5
https://purl.org/becyt/ford/1
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
dc.description.none.fl_txt_mv Remote sensing is valuable for estimating aboveground biomass (AGB) stocks. However, its application in agricultural and pasture areas is limited compared with forest areas. This study quantifies AGB in agriculture–pasture mosaics within Brazil’s Campo Maior Complex (CMC). The methodology employs remote sensing cloud processing and utilizes an estimator to incorporate vegetation indices. The results reveal significant changes in biomass values among land use and land cover classes over the past ten years, with notable variations observed in forest plantation, pasture, sugar cane, and soybean areas. The estimated AGB values range from 0 to 20 Mg.ha−1 (minimum), 53 to 419 Mg.ha−1 (maximum), and 19 to 57 Mg.ha−1 (mean). In Forest formation areas, AGB values range from approximately 0 to 278 Mg.ha−1, with an average annual value of 56.44 Mg.ha−1. This study provides valuable insights for rural landowners and government officials in managing the semiarid territory and environment. It aids in decision making regarding agricultural management, irrigation and fertilization practices, agricultural productivity, land use and land cover changes, biodiversity loss, soil degradation, conservation strategies, the identification of priority areas for environmental restoration, and the optimization of resource utilization.
Fil: Sousa Júnior, Vicente de Paula. Universidade Federal Do Piaui.; Brasil
Fil: Sparacino, Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones Biológicas y Tecnológicas. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Instituto de Investigaciones Biológicas y Tecnológicas; Argentina. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Centro de Ecología y Recursos Naturales Renovables; Argentina
Fil: Espindola, Giovana Mira de. Universidade Federal Do Piaui.; Brasil
Fil: Assis, Raimundo Jucier Sousa de. Universidade Federal Do Piaui.; Brasil
description Remote sensing is valuable for estimating aboveground biomass (AGB) stocks. However, its application in agricultural and pasture areas is limited compared with forest areas. This study quantifies AGB in agriculture–pasture mosaics within Brazil’s Campo Maior Complex (CMC). The methodology employs remote sensing cloud processing and utilizes an estimator to incorporate vegetation indices. The results reveal significant changes in biomass values among land use and land cover classes over the past ten years, with notable variations observed in forest plantation, pasture, sugar cane, and soybean areas. The estimated AGB values range from 0 to 20 Mg.ha−1 (minimum), 53 to 419 Mg.ha−1 (maximum), and 19 to 57 Mg.ha−1 (mean). In Forest formation areas, AGB values range from approximately 0 to 278 Mg.ha−1, with an average annual value of 56.44 Mg.ha−1. This study provides valuable insights for rural landowners and government officials in managing the semiarid territory and environment. It aids in decision making regarding agricultural management, irrigation and fertilization practices, agricultural productivity, land use and land cover changes, biodiversity loss, soil degradation, conservation strategies, the identification of priority areas for environmental restoration, and the optimization of resource utilization.
publishDate 2023
dc.date.none.fl_str_mv 2023-08-27
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/11336/242024
Sousa Júnior, Vicente de Paula; Sparacino, Javier; Espindola, Giovana Mira de; Assis, Raimundo Jucier Sousa de; Carbon Biomass Estimation Using Vegetation Indices in Agriculture–Pasture Mosaics in the Brazilian Caatinga Dry Tropical Forest; Multidisciplinary Digital Publishing Institute; ISPRS International Journal of Geo-Information; 12; 9; 27-8-2023; 354-373
2220-9964
CONICET Digital
CONICET
url http://hdl.handle.net/11336/242024
identifier_str_mv Sousa Júnior, Vicente de Paula; Sparacino, Javier; Espindola, Giovana Mira de; Assis, Raimundo Jucier Sousa de; Carbon Biomass Estimation Using Vegetation Indices in Agriculture–Pasture Mosaics in the Brazilian Caatinga Dry Tropical Forest; Multidisciplinary Digital Publishing Institute; ISPRS International Journal of Geo-Information; 12; 9; 27-8-2023; 354-373
2220-9964
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.3390/ijgi12090354
info:eu-repo/semantics/altIdentifier/url/https://www.mdpi.com/2220-9964/12/9/354
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv 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 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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score 13.070432

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