Semiautomatic and quantification identification of deforestation by Remote Sensing

Detalhes bibliográficos
Autor(a) principal: Lima, Diego Lanza
Data de Publicação: 2020
Outros Autores: Alves, Teodorico Sobrinho, Oliveira, Ana Paula Garcia, Catalani, Thais Gisele Torres, Dalmas, Fabrício Bau, Paranhos Filho, Antonio Conceição
Tipo de documento: Artigo
Idioma: por
Título da fonte: Research, Society and Development
Texto Completo: https://rsdjournal.org/index.php/rsd/article/view/2721
Resumo: Deforestation has followed population’s growth and development for thousands of years. Climate, culture, technology and commerce have influence on the acceleration or deceleration of the pace of deforestation. It is estimated that approximately 50% of the Cerrado (savanna) biome area has already been cleared to make way for agricultural fields, pasturelands and urban areas. Aiming to disseminate the current simplified deforestation detection procedures, generally performed manually by photointerpretation of satellite images, this study presents, tests and validates the hypothesis that it is possible to perform the monitoring by mathematical operations between thematic maps of remnant vegetation. A case study performed in a 3,865Km2 area, where the variation of vegetation cover was studied using satellite imagery Landsat 5 TM and Geographic Information Systems (GIS), showed that it is possible to carry out the proposed procedure with accurate results and in less time than the one needed for photointerpretation technique. The objective of this research was to quantitatively evaluate the area covered with vegetation in the municipality of São Gabriel do Oeste, for the years 1999 and 2009, through the elaboration of Remaining Vegetation Maps, a product of remote sensing techniques in the PCI Geomatica Focus software.
id UNIFEI_220a1ae5acf8ca9cf659d65468a03f56
oai_identifier_str oai:ojs.pkp.sfu.ca:article/2721
network_acronym_str UNIFEI
network_name_str Research, Society and Development
repository_id_str
spelling Semiautomatic and quantification identification of deforestation by Remote SensingIdentificación y cuantificación semiautomática de la deforestación por las Técnicas de TeledetecciónIdentificação e quantificação semiautomática de desmatamento por Sensoriamento RemotoDeforestationEnvironmental MonitoringGeographic Information Systems.Supresión de VegetalesMonitoreo AmbientalSistemas de Información Geográfica.Supressão VegetalMonitoramento AmbientalSistemas de Informações Geográficas.Deforestation has followed population’s growth and development for thousands of years. Climate, culture, technology and commerce have influence on the acceleration or deceleration of the pace of deforestation. It is estimated that approximately 50% of the Cerrado (savanna) biome area has already been cleared to make way for agricultural fields, pasturelands and urban areas. Aiming to disseminate the current simplified deforestation detection procedures, generally performed manually by photointerpretation of satellite images, this study presents, tests and validates the hypothesis that it is possible to perform the monitoring by mathematical operations between thematic maps of remnant vegetation. A case study performed in a 3,865Km2 area, where the variation of vegetation cover was studied using satellite imagery Landsat 5 TM and Geographic Information Systems (GIS), showed that it is possible to carry out the proposed procedure with accurate results and in less time than the one needed for photointerpretation technique. The objective of this research was to quantitatively evaluate the area covered with vegetation in the municipality of São Gabriel do Oeste, for the years 1999 and 2009, through the elaboration of Remaining Vegetation Maps, a product of remote sensing techniques in the PCI Geomatica Focus software.La deforestación ha acompañado el crecimiento y desarrollo de la población durante miles de años. El clima, la cultura, la tecnología y el comercio influyen en la aceleración o desaceleración de la tasa de deforestación. Se estima que aproximadamente el 50% del área del Bioma Cerrado ya ha sido deforestada para dar paso a áreas agrícolas, pastos y áreas urbanas. Con el fin de difundir procedimientos simplificados para detectar la deforestación, generalmente realizados por fotointerpretación de imágenes de satélite, este estudio presenta, prueba y valida la hipótesis de que es posible llevar a cabo el monitoreo mediante operaciones matemáticas entre mapas temáticos de la vegetación restante. El estudio de caso llevado a cabo en un área de 3,865 Km², donde se estudió la variación de la cubierta vegetal usando imágenes del satélite Landsat 5 TM y los Sistemas de Información Geográfica (SIG), mostró que es posible llevar a cabo el procedimiento propuesto con resultados precisos y en menos tiempo que necesario para la técnica convencional de fotointerpretación. El objetivo de esta investigación fue evaluar cuantitativamente el área cubierta de vegetación en el municipio de São Gabriel do Oeste, para los años 1999 y 2009, a través de la elaboración de Mapas de Vegetación Restante, un producto de técnicas de teledetección en el software PCI Geomatica Focus.O desmatamento a companha o crescimento da população e seu desenvolvimento há milhares de anos. Clima, cultura, tecnologia e comércio têm influência sobre a aceleração ou desaceleração do ritmo de desmatamento. Estima-se que aproximadamente 50% da área do Bioma Cerrado já tenha sido desmatada para dar lugar a áreas agrícolas, pastos e áreas urbanas. Visando difundir procedimentos simplificados de detecção de desmatamentos, geralmente realizados por fotointerpretação de imagens de satélite, este estudo apresenta, testa e valida a hipótese de que é possível realizar o monitoramento por operações matemáticas entre mapas temáticos de vegetação remanescente. Estudo de caso realizado em área de 3.865 Km², onde a variação da cobertura vegetal foi estudada utilizando imagens do satélite Landsat 5 TM e Sistemas de Informações Geográficas (GIS), mostrou que é possível realizar o procedimento proposto com resultados precisos e em tempo inferior ao necessário para a técnica de fotointerpretação convencional. O objetivo desta pesquisa foi avaliar quantitativamente a área coberta com vegetação do Município de São Gabriel do Oeste, para os anos de 1999 e 2009, através da elaboração de Cartas de Vegetação Remanescente, produto de técnicas de sensoriamento remoto no software PCI Geomatica Focus.Research, Society and Development2020-03-20info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://rsdjournal.org/index.php/rsd/article/view/272110.33448/rsd-v9i4.2721Research, Society and Development; Vol. 9 No. 4; e30942721Research, Society and Development; Vol. 9 Núm. 4; e30942721Research, Society and Development; v. 9 n. 4; e309427212525-3409reponame:Research, Society and Developmentinstname:Universidade Federal de Itajubá (UNIFEI)instacron:UNIFEIporhttps://rsdjournal.org/index.php/rsd/article/view/2721/2724Copyright (c) 2020 Thais Gisele Torres Catalani, Ana Paula Garcia Oliveira, Teodorico Sobrinho Alves, Diego Lanza Lima, Fabricio Bau Dalmas, Antonio Conceição Paranhos Filhoinfo:eu-repo/semantics/openAccessLima, Diego LanzaAlves, Teodorico SobrinhoOliveira, Ana Paula GarciaCatalani, Thais Gisele TorresDalmas, Fabrício BauParanhos Filho, Antonio Conceição2020-08-20T18:07:16Zoai:ojs.pkp.sfu.ca:article/2721Revistahttps://rsdjournal.org/index.php/rsd/indexPUBhttps://rsdjournal.org/index.php/rsd/oairsd.articles@gmail.com2525-34092525-3409opendoar:2024-01-17T09:27:12.104323Research, Society and Development - Universidade Federal de Itajubá (UNIFEI)false
dc.title.none.fl_str_mv Semiautomatic and quantification identification of deforestation by Remote Sensing
Identificación y cuantificación semiautomática de la deforestación por las Técnicas de Teledetección
Identificação e quantificação semiautomática de desmatamento por Sensoriamento Remoto
title Semiautomatic and quantification identification of deforestation by Remote Sensing
spellingShingle Semiautomatic and quantification identification of deforestation by Remote Sensing
Lima, Diego Lanza
Deforestation
Environmental Monitoring
Geographic Information Systems.
Supresión de Vegetales
Monitoreo Ambiental
Sistemas de Información Geográfica.
Supressão Vegetal
Monitoramento Ambiental
Sistemas de Informações Geográficas.
title_short Semiautomatic and quantification identification of deforestation by Remote Sensing
title_full Semiautomatic and quantification identification of deforestation by Remote Sensing
title_fullStr Semiautomatic and quantification identification of deforestation by Remote Sensing
title_full_unstemmed Semiautomatic and quantification identification of deforestation by Remote Sensing
title_sort Semiautomatic and quantification identification of deforestation by Remote Sensing
author Lima, Diego Lanza
author_facet Lima, Diego Lanza
Alves, Teodorico Sobrinho
Oliveira, Ana Paula Garcia
Catalani, Thais Gisele Torres
Dalmas, Fabrício Bau
Paranhos Filho, Antonio Conceição
author_role author
author2 Alves, Teodorico Sobrinho
Oliveira, Ana Paula Garcia
Catalani, Thais Gisele Torres
Dalmas, Fabrício Bau
Paranhos Filho, Antonio Conceição
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Lima, Diego Lanza
Alves, Teodorico Sobrinho
Oliveira, Ana Paula Garcia
Catalani, Thais Gisele Torres
Dalmas, Fabrício Bau
Paranhos Filho, Antonio Conceição
dc.subject.por.fl_str_mv Deforestation
Environmental Monitoring
Geographic Information Systems.
Supresión de Vegetales
Monitoreo Ambiental
Sistemas de Información Geográfica.
Supressão Vegetal
Monitoramento Ambiental
Sistemas de Informações Geográficas.
topic Deforestation
Environmental Monitoring
Geographic Information Systems.
Supresión de Vegetales
Monitoreo Ambiental
Sistemas de Información Geográfica.
Supressão Vegetal
Monitoramento Ambiental
Sistemas de Informações Geográficas.
description Deforestation has followed population’s growth and development for thousands of years. Climate, culture, technology and commerce have influence on the acceleration or deceleration of the pace of deforestation. It is estimated that approximately 50% of the Cerrado (savanna) biome area has already been cleared to make way for agricultural fields, pasturelands and urban areas. Aiming to disseminate the current simplified deforestation detection procedures, generally performed manually by photointerpretation of satellite images, this study presents, tests and validates the hypothesis that it is possible to perform the monitoring by mathematical operations between thematic maps of remnant vegetation. A case study performed in a 3,865Km2 area, where the variation of vegetation cover was studied using satellite imagery Landsat 5 TM and Geographic Information Systems (GIS), showed that it is possible to carry out the proposed procedure with accurate results and in less time than the one needed for photointerpretation technique. The objective of this research was to quantitatively evaluate the area covered with vegetation in the municipality of São Gabriel do Oeste, for the years 1999 and 2009, through the elaboration of Remaining Vegetation Maps, a product of remote sensing techniques in the PCI Geomatica Focus software.
publishDate 2020
dc.date.none.fl_str_mv 2020-03-20
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://rsdjournal.org/index.php/rsd/article/view/2721
10.33448/rsd-v9i4.2721
url https://rsdjournal.org/index.php/rsd/article/view/2721
identifier_str_mv 10.33448/rsd-v9i4.2721
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://rsdjournal.org/index.php/rsd/article/view/2721/2724
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Research, Society and Development
publisher.none.fl_str_mv Research, Society and Development
dc.source.none.fl_str_mv Research, Society and Development; Vol. 9 No. 4; e30942721
Research, Society and Development; Vol. 9 Núm. 4; e30942721
Research, Society and Development; v. 9 n. 4; e30942721
2525-3409
reponame:Research, Society and Development
instname:Universidade Federal de Itajubá (UNIFEI)
instacron:UNIFEI
instname_str Universidade Federal de Itajubá (UNIFEI)
instacron_str UNIFEI
institution UNIFEI
reponame_str Research, Society and Development
collection Research, Society and Development
repository.name.fl_str_mv Research, Society and Development - Universidade Federal de Itajubá (UNIFEI)
repository.mail.fl_str_mv rsd.articles@gmail.com
_version_ 1797052646290358272