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

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorUniversidade Estadual de Maringá (UEM)-
Autor(es): dc.creatorSilva, Jéssica Alves da[UNESP]-
Autor(es): dc.creatorGalvanin, Edinéia Aparecida dos Santos[UNESP]-
Autor(es): dc.creatorFuzzo, Daniela Fernanda da Silva-
Data de aceite: dc.date.accessioned2025-08-21T16:00:01Z-
Data de disponibilização: dc.date.available2025-08-21T16:00:01Z-
Data de envio: dc.date.issued2023-03-01-
Data de envio: dc.date.issued2023-03-01-
Data de envio: dc.date.issued2021-12-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1007/978-3-030-84152-2_12-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/240010-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/240010-
Descrição: dc.descriptionStudies 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.-
Descrição: dc.descriptionFaculty of Agronomic Sciences Mestranda pela Paulista State University – UNESP-
Descrição: dc.descriptionSão Paulo State University – UNESP-
Descrição: dc.descriptionState University of Minas Gerais – UEMG-
Descrição: dc.descriptionFaculty of Agronomic Sciences Mestranda pela Paulista State University – UNESP-
Descrição: dc.descriptionSão Paulo State University – UNESP-
Formato: dc.format251-264-
Idioma: dc.languageen-
Relação: dc.relationSpringer Optimization and Its Applications-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectAgriculture-
Palavras-chave: dc.subjectRemote sensing-
Palavras-chave: dc.subjectStatistical modeling-
Título: dc.titleMonitoring and Estimation of Sugarcane Burning in the Middle Paranapanema Basin, Brazil, Using Linear Mixed Models-
Tipo de arquivo: dc.typelivro digital-
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