Change in forest cover of the northwest region of Amazon in Mato Grosso state
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.31413/nativa.v7i5.7248 http://hdl.handle.net/11449/196179 |
Resumo: | In the past few years, the intensification of anthropic activities that modify the soil-vegetation cover in Brazil's land has been occurring on a large scale. To monitor the forest cover changes, the techniques of Remote Sensing of vegetation are essential tools, especially in large areas and with difficult access, as is the case of the Brazilian Amazon. The aim of this work was to identify the changes in land use and land cover, over the past 20 years, in the municipalities of Aripuana and Rondolandia, Northwest of Mato Grosso State, in order to quantify the effective altered areas. Landsat 5 TM and Landsat 8 OLI digital classification images techniques were used in three different dates (1995, 2005 and 2015) and, later, the detection to the land use and land cover changes. The digital classification showed excellent results, with kappa index above 0.80 for the generated maps, indicating the digital classification as a potential tool for land use and land cover. Results reflect the conversion of forest areas mainly for agricultural activities, in the order of 472 km(2), representing a loss of 1.3% of Amazon forest surface in the study region. |
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Repositório Institucional da UNESP |
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Change in forest cover of the northwest region of Amazon in Mato Grosso stateforest conversionland use and land coverdigital classificationmultitemporal analysisIn the past few years, the intensification of anthropic activities that modify the soil-vegetation cover in Brazil's land has been occurring on a large scale. To monitor the forest cover changes, the techniques of Remote Sensing of vegetation are essential tools, especially in large areas and with difficult access, as is the case of the Brazilian Amazon. The aim of this work was to identify the changes in land use and land cover, over the past 20 years, in the municipalities of Aripuana and Rondolandia, Northwest of Mato Grosso State, in order to quantify the effective altered areas. Landsat 5 TM and Landsat 8 OLI digital classification images techniques were used in three different dates (1995, 2005 and 2015) and, later, the detection to the land use and land cover changes. The digital classification showed excellent results, with kappa index above 0.80 for the generated maps, indicating the digital classification as a potential tool for land use and land cover. Results reflect the conversion of forest areas mainly for agricultural activities, in the order of 472 km(2), representing a loss of 1.3% of Amazon forest surface in the study region.Univ Fed Parana, Programa Posgrad Engn Florestal, Curitiba, Parana, BrazilUniv Estadual Paulista, Programa Posgrad Ciencias Cartog, Presidente Prudente, SP, BrazilUniv Estadual Paulista, Programa Posgrad Ciencias Cartog, Presidente Prudente, SP, BrazilUniv Federal Mato GrossoUniv Fed ParanaUniversidade Estadual Paulista (Unesp)Oliveira Piva, Luani Rosa deMartins Neto, Rorai Pereira [UNESP]2020-12-10T19:36:03Z2020-12-10T19:36:03Z2019-09-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article520-526http://dx.doi.org/10.31413/nativa.v7i5.7248Nativa. Sinop: Univ Federal Mato Grosso, v. 7, n. 5, p. 520-526, 2019.2318-7670http://hdl.handle.net/11449/19617910.31413/nativa.v7i5.7248WOS:000485808600009Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPporNativainfo:eu-repo/semantics/openAccess2024-06-18T15:01:27Zoai:repositorio.unesp.br:11449/196179Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T17:28:46.958251Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Change in forest cover of the northwest region of Amazon in Mato Grosso state |
title |
Change in forest cover of the northwest region of Amazon in Mato Grosso state |
spellingShingle |
Change in forest cover of the northwest region of Amazon in Mato Grosso state Oliveira Piva, Luani Rosa de forest conversion land use and land cover digital classification multitemporal analysis |
title_short |
Change in forest cover of the northwest region of Amazon in Mato Grosso state |
title_full |
Change in forest cover of the northwest region of Amazon in Mato Grosso state |
title_fullStr |
Change in forest cover of the northwest region of Amazon in Mato Grosso state |
title_full_unstemmed |
Change in forest cover of the northwest region of Amazon in Mato Grosso state |
title_sort |
Change in forest cover of the northwest region of Amazon in Mato Grosso state |
author |
Oliveira Piva, Luani Rosa de |
author_facet |
Oliveira Piva, Luani Rosa de Martins Neto, Rorai Pereira [UNESP] |
author_role |
author |
author2 |
Martins Neto, Rorai Pereira [UNESP] |
author2_role |
author |
dc.contributor.none.fl_str_mv |
Univ Fed Parana Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Oliveira Piva, Luani Rosa de Martins Neto, Rorai Pereira [UNESP] |
dc.subject.por.fl_str_mv |
forest conversion land use and land cover digital classification multitemporal analysis |
topic |
forest conversion land use and land cover digital classification multitemporal analysis |
description |
In the past few years, the intensification of anthropic activities that modify the soil-vegetation cover in Brazil's land has been occurring on a large scale. To monitor the forest cover changes, the techniques of Remote Sensing of vegetation are essential tools, especially in large areas and with difficult access, as is the case of the Brazilian Amazon. The aim of this work was to identify the changes in land use and land cover, over the past 20 years, in the municipalities of Aripuana and Rondolandia, Northwest of Mato Grosso State, in order to quantify the effective altered areas. Landsat 5 TM and Landsat 8 OLI digital classification images techniques were used in three different dates (1995, 2005 and 2015) and, later, the detection to the land use and land cover changes. The digital classification showed excellent results, with kappa index above 0.80 for the generated maps, indicating the digital classification as a potential tool for land use and land cover. Results reflect the conversion of forest areas mainly for agricultural activities, in the order of 472 km(2), representing a loss of 1.3% of Amazon forest surface in the study region. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-09-01 2020-12-10T19:36:03Z 2020-12-10T19:36:03Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.31413/nativa.v7i5.7248 Nativa. Sinop: Univ Federal Mato Grosso, v. 7, n. 5, p. 520-526, 2019. 2318-7670 http://hdl.handle.net/11449/196179 10.31413/nativa.v7i5.7248 WOS:000485808600009 |
url |
http://dx.doi.org/10.31413/nativa.v7i5.7248 http://hdl.handle.net/11449/196179 |
identifier_str_mv |
Nativa. Sinop: Univ Federal Mato Grosso, v. 7, n. 5, p. 520-526, 2019. 2318-7670 10.31413/nativa.v7i5.7248 WOS:000485808600009 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
Nativa |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
520-526 |
dc.publisher.none.fl_str_mv |
Univ Federal Mato Grosso |
publisher.none.fl_str_mv |
Univ Federal Mato Grosso |
dc.source.none.fl_str_mv |
Web of Science 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 |
|
_version_ |
1808128816389816320 |