Monitoring and Estimation of Sugarcane Burning in the Middle Paranapanema Basin, Brazil, Using Linear Mixed Models

Detalhes bibliográficos
Autor(a) principal: Silva, Jéssica Alves da[UNESP]
Data de Publicação: 2022
Outros Autores: Galvanin, Edinéia Aparecida dos Santos[UNESP], Fuzzo, Daniela Fernanda da Silva
Tipo de documento: Capítulo de livro
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1007/978-3-030-84152-2_12
http://hdl.handle.net/11449/240010
Resumo: Studies on sugarcane burning demonstrate that the use of fire in agriculture has been condemned for centuries by soil conservation manuals since it increases the temperature and decreases the natural moisture of the soil, leading to greater compaction, loss of porosity, erosion, and consequently soil infertility. The objective of research was to evaluate the spatial and temporal distribution of fire incidences in the period from 2000 to 2018 in the Water Resources Management Unit of the Middle Paranapanema, located in the state of São Paulo—Brazil, and to carry out the future estimate of this activity through mixed linear models. For this purpose, images from the Landsat 5/TM (year 2000), 7/TM (years 2006 and 2012), and 8/OLI (year 2018) satellites and 2018 were used. Numerical data (regarding area and fire incidences) and categorical data (terrain slope) were also employed. Statistical model was used to evaluate data and was possible to identify a decrease in fires in smooth undulating terrains, corresponding to 99.9% per year, and characterized by the increase in agricultural machinery in these areas. In these lands, the model made it possible to carry out the forecast for the next 6 years, in which timeframe, considering causes/effects, there would be a decrease over 100%. On the other hand, in strong undulating terrain there was an increase of 2.07% per year, which in the next 6 years represents an increase of 12.45%, a result contrary to what the established laws provide.
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spelling Monitoring and Estimation of Sugarcane Burning in the Middle Paranapanema Basin, Brazil, Using Linear Mixed ModelsAgricultureRemote sensingStatistical modelingStudies on sugarcane burning demonstrate that the use of fire in agriculture has been condemned for centuries by soil conservation manuals since it increases the temperature and decreases the natural moisture of the soil, leading to greater compaction, loss of porosity, erosion, and consequently soil infertility. The objective of research was to evaluate the spatial and temporal distribution of fire incidences in the period from 2000 to 2018 in the Water Resources Management Unit of the Middle Paranapanema, located in the state of São Paulo—Brazil, and to carry out the future estimate of this activity through mixed linear models. For this purpose, images from the Landsat 5/TM (year 2000), 7/TM (years 2006 and 2012), and 8/OLI (year 2018) satellites and 2018 were used. Numerical data (regarding area and fire incidences) and categorical data (terrain slope) were also employed. Statistical model was used to evaluate data and was possible to identify a decrease in fires in smooth undulating terrains, corresponding to 99.9% per year, and characterized by the increase in agricultural machinery in these areas. In these lands, the model made it possible to carry out the forecast for the next 6 years, in which timeframe, considering causes/effects, there would be a decrease over 100%. On the other hand, in strong undulating terrain there was an increase of 2.07% per year, which in the next 6 years represents an increase of 12.45%, a result contrary to what the established laws provide.Faculty of Agronomic Sciences Mestranda pela Paulista State University – UNESPSão Paulo State University – UNESPState University of Minas Gerais – UEMGFaculty of Agronomic Sciences Mestranda pela Paulista State University – UNESPSão Paulo State University – UNESPUniversidade Estadual Paulista (UNESP)Universidade Estadual de Maringá (UEM)Silva, Jéssica Alves da[UNESP]Galvanin, Edinéia Aparecida dos Santos[UNESP]Fuzzo, Daniela Fernanda da Silva2023-03-01T19:57:30Z2023-03-01T19:57:30Z2022-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/bookPart251-264http://dx.doi.org/10.1007/978-3-030-84152-2_12Springer Optimization and Its Applications, v. 184, p. 251-264.1931-68361931-6828http://hdl.handle.net/11449/24001010.1007/978-3-030-84152-2_122-s2.0-85129595079Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengSpringer Optimization and Its Applicationsinfo:eu-repo/semantics/openAccess2023-03-01T19:57:30Zoai:repositorio.unesp.br:11449/240010Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T14:41:16.935540Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Monitoring and Estimation of Sugarcane Burning in the Middle Paranapanema Basin, Brazil, Using Linear Mixed Models
title Monitoring and Estimation of Sugarcane Burning in the Middle Paranapanema Basin, Brazil, Using Linear Mixed Models
spellingShingle Monitoring and Estimation of Sugarcane Burning in the Middle Paranapanema Basin, Brazil, Using Linear Mixed Models
Silva, Jéssica Alves da[UNESP]
Agriculture
Remote sensing
Statistical modeling
title_short Monitoring and Estimation of Sugarcane Burning in the Middle Paranapanema Basin, Brazil, Using Linear Mixed Models
title_full Monitoring and Estimation of Sugarcane Burning in the Middle Paranapanema Basin, Brazil, Using Linear Mixed Models
title_fullStr Monitoring and Estimation of Sugarcane Burning in the Middle Paranapanema Basin, Brazil, Using Linear Mixed Models
title_full_unstemmed Monitoring and Estimation of Sugarcane Burning in the Middle Paranapanema Basin, Brazil, Using Linear Mixed Models
title_sort Monitoring and Estimation of Sugarcane Burning in the Middle Paranapanema Basin, Brazil, Using Linear Mixed Models
author Silva, Jéssica Alves da[UNESP]
author_facet Silva, Jéssica Alves da[UNESP]
Galvanin, Edinéia Aparecida dos Santos[UNESP]
Fuzzo, Daniela Fernanda da Silva
author_role author
author2 Galvanin, Edinéia Aparecida dos Santos[UNESP]
Fuzzo, Daniela Fernanda da Silva
author2_role author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (UNESP)
Universidade Estadual de Maringá (UEM)
dc.contributor.author.fl_str_mv Silva, Jéssica Alves da[UNESP]
Galvanin, Edinéia Aparecida dos Santos[UNESP]
Fuzzo, Daniela Fernanda da Silva
dc.subject.por.fl_str_mv Agriculture
Remote sensing
Statistical modeling
topic Agriculture
Remote sensing
Statistical modeling
description Studies on sugarcane burning demonstrate that the use of fire in agriculture has been condemned for centuries by soil conservation manuals since it increases the temperature and decreases the natural moisture of the soil, leading to greater compaction, loss of porosity, erosion, and consequently soil infertility. The objective of research was to evaluate the spatial and temporal distribution of fire incidences in the period from 2000 to 2018 in the Water Resources Management Unit of the Middle Paranapanema, located in the state of São Paulo—Brazil, and to carry out the future estimate of this activity through mixed linear models. For this purpose, images from the Landsat 5/TM (year 2000), 7/TM (years 2006 and 2012), and 8/OLI (year 2018) satellites and 2018 were used. Numerical data (regarding area and fire incidences) and categorical data (terrain slope) were also employed. Statistical model was used to evaluate data and was possible to identify a decrease in fires in smooth undulating terrains, corresponding to 99.9% per year, and characterized by the increase in agricultural machinery in these areas. In these lands, the model made it possible to carry out the forecast for the next 6 years, in which timeframe, considering causes/effects, there would be a decrease over 100%. On the other hand, in strong undulating terrain there was an increase of 2.07% per year, which in the next 6 years represents an increase of 12.45%, a result contrary to what the established laws provide.
publishDate 2022
dc.date.none.fl_str_mv 2022-01-01
2023-03-01T19:57:30Z
2023-03-01T19:57:30Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/bookPart
format bookPart
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1007/978-3-030-84152-2_12
Springer Optimization and Its Applications, v. 184, p. 251-264.
1931-6836
1931-6828
http://hdl.handle.net/11449/240010
10.1007/978-3-030-84152-2_12
2-s2.0-85129595079
url http://dx.doi.org/10.1007/978-3-030-84152-2_12
http://hdl.handle.net/11449/240010
identifier_str_mv Springer Optimization and Its Applications, v. 184, p. 251-264.
1931-6836
1931-6828
10.1007/978-3-030-84152-2_12
2-s2.0-85129595079
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Springer Optimization and Its Applications
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 251-264
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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