TENDENTIAL MODELING OF DEFORESTATION IN CAATINGA BIOME IN PIAUÍ STATE
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , |
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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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 |
_version_ |
1797067018733617152 |