TENDENTIAL MODELING OF DEFORESTATION IN CAATINGA BIOME IN PIAUÍ STATE

Detalhes bibliográficos
Autor(a) principal: dos Santos, Raianara Andrade
Data de Publicação: 2022
Outros Autores: Juvanhol, Ronie Silva, Aguiar, Adriano Saraiva
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Caminhos de Geografia
Texto Completo: https://seer.ufu.br/index.php/caminhosdegeografia/article/view/59039
Resumo: The work aims to simulate the dynamics of deforestation in the area that covers the caatinga biome in the state of Piauí for the next five decades. In the simulation, the program Dinamica EGO was used. Were acquired deforestation data for 2002 and 2008 and spatial data of the explanatory variables of deforestation in the area. Five steps were performed: calculating the transition matrices, determining the weights of evidence, adjusting, validating and projecting the model in the trend scenario. Transition rates for total and annual deforestation resulted in 4.6% and 0.8%, respectively. The weights of evidence revealed that distances up to 600 m from deforested areas influence in the process of transition to deforestation. The variables with the highest weights were altitude, up to 100 meters; areas closer to urban patch and sustainable use units, in addition to land use and cover classes: urban influence, agriculture, livestock. With the simulated images it was observed a reduction of the forest remnants of caatinga area in the state, from 69% in 2008 to 43% in 2070. These results serve as a warning to the public authorities and the population. The proposed methodology can be applied to other Brazilian biomes with different approaches.
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spelling TENDENTIAL MODELING OF DEFORESTATION IN CAATINGA BIOME IN PIAUÍ STATESpatial-temporal dynamicsDeforestation rateSimulationThe work aims to simulate the dynamics of deforestation in the area that covers the caatinga biome in the state of Piauí for the next five decades. In the simulation, the program Dinamica EGO was used. Were acquired deforestation data for 2002 and 2008 and spatial data of the explanatory variables of deforestation in the area. Five steps were performed: calculating the transition matrices, determining the weights of evidence, adjusting, validating and projecting the model in the trend scenario. Transition rates for total and annual deforestation resulted in 4.6% and 0.8%, respectively. The weights of evidence revealed that distances up to 600 m from deforested areas influence in the process of transition to deforestation. The variables with the highest weights were altitude, up to 100 meters; areas closer to urban patch and sustainable use units, in addition to land use and cover classes: urban influence, agriculture, livestock. With the simulated images it was observed a reduction of the forest remnants of caatinga area in the state, from 69% in 2008 to 43% in 2070. These results serve as a warning to the public authorities and the population. The proposed methodology can be applied to other Brazilian biomes with different approaches.EDUFU - Editora da Universidade Federal de Uberlândia2022-08-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionAvaliado pelos paresapplication/pdfhttps://seer.ufu.br/index.php/caminhosdegeografia/article/view/5903910.14393/RCG238859039Caminhos de Geografia; Vol. 23 No. 88 (2022): Agosto; 103-118Caminhos de Geografia; Vol. 23 Núm. 88 (2022): Agosto; 103-118Caminhos de Geografia; v. 23 n. 88 (2022): Agosto; 103-1181678-6343reponame:Caminhos de Geografiainstname:Universidade Federal de Uberlândia (UFU)instacron:UFUenghttps://seer.ufu.br/index.php/caminhosdegeografia/article/view/59039/34396Copyright (c) 2022 Raianara Andrade dos Santos, Ronie Juvanhol, Adriano Saraiva Aguiarhttp://creativecommons.org/licenses/by-nc-nd/4.0info:eu-repo/semantics/openAccessdos Santos, Raianara AndradeJuvanhol, Ronie SilvaAguiar, Adriano Saraiva2022-08-04T15:50:50Zoai:ojs.www.seer.ufu.br:article/59039Revistahttps://seer.ufu.br/index.php/caminhosdegeografia/indexPUBhttp://www.seer.ufu.br/index.php/caminhosdegeografia/oaiflaviasantosgeo@gmail.com1678-63431678-6343opendoar:2022-08-04T15:50:50Caminhos de Geografia - Universidade Federal de Uberlândia (UFU)false
dc.title.none.fl_str_mv TENDENTIAL MODELING OF DEFORESTATION IN CAATINGA BIOME IN PIAUÍ STATE
title TENDENTIAL MODELING OF DEFORESTATION IN CAATINGA BIOME IN PIAUÍ STATE
spellingShingle TENDENTIAL MODELING OF DEFORESTATION IN CAATINGA BIOME IN PIAUÍ STATE
dos Santos, Raianara Andrade
Spatial-temporal dynamics
Deforestation rate
Simulation
title_short TENDENTIAL MODELING OF DEFORESTATION IN CAATINGA BIOME IN PIAUÍ STATE
title_full TENDENTIAL MODELING OF DEFORESTATION IN CAATINGA BIOME IN PIAUÍ STATE
title_fullStr TENDENTIAL MODELING OF DEFORESTATION IN CAATINGA BIOME IN PIAUÍ STATE
title_full_unstemmed TENDENTIAL MODELING OF DEFORESTATION IN CAATINGA BIOME IN PIAUÍ STATE
title_sort TENDENTIAL MODELING OF DEFORESTATION IN CAATINGA BIOME IN PIAUÍ STATE
author dos Santos, Raianara Andrade
author_facet dos Santos, Raianara Andrade
Juvanhol, Ronie Silva
Aguiar, Adriano Saraiva
author_role author
author2 Juvanhol, Ronie Silva
Aguiar, Adriano Saraiva
author2_role author
author
dc.contributor.author.fl_str_mv dos Santos, Raianara Andrade
Juvanhol, Ronie Silva
Aguiar, Adriano Saraiva
dc.subject.por.fl_str_mv Spatial-temporal dynamics
Deforestation rate
Simulation
topic Spatial-temporal dynamics
Deforestation rate
Simulation
description The work aims to simulate the dynamics of deforestation in the area that covers the caatinga biome in the state of Piauí for the next five decades. In the simulation, the program Dinamica EGO was used. Were acquired deforestation data for 2002 and 2008 and spatial data of the explanatory variables of deforestation in the area. Five steps were performed: calculating the transition matrices, determining the weights of evidence, adjusting, validating and projecting the model in the trend scenario. Transition rates for total and annual deforestation resulted in 4.6% and 0.8%, respectively. The weights of evidence revealed that distances up to 600 m from deforested areas influence in the process of transition to deforestation. The variables with the highest weights were altitude, up to 100 meters; areas closer to urban patch and sustainable use units, in addition to land use and cover classes: urban influence, agriculture, livestock. With the simulated images it was observed a reduction of the forest remnants of caatinga area in the state, from 69% in 2008 to 43% in 2070. These results serve as a warning to the public authorities and the population. The proposed methodology can be applied to other Brazilian biomes with different approaches.
publishDate 2022
dc.date.none.fl_str_mv 2022-08-04
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Avaliado pelos pares
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://seer.ufu.br/index.php/caminhosdegeografia/article/view/59039
10.14393/RCG238859039
url https://seer.ufu.br/index.php/caminhosdegeografia/article/view/59039
identifier_str_mv 10.14393/RCG238859039
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://seer.ufu.br/index.php/caminhosdegeografia/article/view/59039/34396
dc.rights.driver.fl_str_mv Copyright (c) 2022 Raianara Andrade dos Santos, Ronie Juvanhol, Adriano Saraiva Aguiar
http://creativecommons.org/licenses/by-nc-nd/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2022 Raianara Andrade dos Santos, Ronie Juvanhol, Adriano Saraiva Aguiar
http://creativecommons.org/licenses/by-nc-nd/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv EDUFU - Editora da Universidade Federal de Uberlândia
publisher.none.fl_str_mv EDUFU - Editora da Universidade Federal de Uberlândia
dc.source.none.fl_str_mv Caminhos de Geografia; Vol. 23 No. 88 (2022): Agosto; 103-118
Caminhos de Geografia; Vol. 23 Núm. 88 (2022): Agosto; 103-118
Caminhos de Geografia; v. 23 n. 88 (2022): Agosto; 103-118
1678-6343
reponame:Caminhos de Geografia
instname:Universidade Federal de Uberlândia (UFU)
instacron:UFU
instname_str Universidade Federal de Uberlândia (UFU)
instacron_str UFU
institution UFU
reponame_str Caminhos de Geografia
collection Caminhos de Geografia
repository.name.fl_str_mv Caminhos de Geografia - Universidade Federal de Uberlândia (UFU)
repository.mail.fl_str_mv flaviasantosgeo@gmail.com
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