Mapping and characterization of intensity in land use by pasture using remote sensing
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Revista Brasileira de Engenharia Agrícola e Ambiental (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662019000500352 |
Resumo: | ABSTRACT The current demand for food has been met through the exploitation of natural reserves. Brazil has 26% of its extension occupied by agricultural uses, 62% of which are pastures. Degraded pastures have greater land use intensity than well-managed pastures, leading to greater degradation of the environment. Land use classification systems consider that pastures are well managed, a misconception for the Brazilian reality. Based on this approach, it was aimed to develop a methodology for mapping the intensity of land use by pasture via remote sensing. The method of mapping was developed and validated in basins with different soil and climatic characteristics. Three calibrations were performed based on NDVI values to ascertain the influence on the results, being evaluated from the field campaigns and the kappa and weighted kappa indices. The kappa and weighted kappa indices presented reasonable and moderate agreement, respectively. The results were considered as satisfactory for the three calibrations, evidencing that the degree of degradation of the pastures can be estimated in a simple way by remote sensing. The Limoeiro River Basin has around 46.9% of pastures, at least, heavily degraded and 96.6% with some degree of degradation, which contributes to degradation of the natural resources and reduction of livestock farming and economic potential of the basin. |
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Mapping and characterization of intensity in land use by pasture using remote sensingsoil and water conservationGISkappa and weighted kappa indicesABSTRACT The current demand for food has been met through the exploitation of natural reserves. Brazil has 26% of its extension occupied by agricultural uses, 62% of which are pastures. Degraded pastures have greater land use intensity than well-managed pastures, leading to greater degradation of the environment. Land use classification systems consider that pastures are well managed, a misconception for the Brazilian reality. Based on this approach, it was aimed to develop a methodology for mapping the intensity of land use by pasture via remote sensing. The method of mapping was developed and validated in basins with different soil and climatic characteristics. Three calibrations were performed based on NDVI values to ascertain the influence on the results, being evaluated from the field campaigns and the kappa and weighted kappa indices. The kappa and weighted kappa indices presented reasonable and moderate agreement, respectively. The results were considered as satisfactory for the three calibrations, evidencing that the degree of degradation of the pastures can be estimated in a simple way by remote sensing. The Limoeiro River Basin has around 46.9% of pastures, at least, heavily degraded and 96.6% with some degree of degradation, which contributes to degradation of the natural resources and reduction of livestock farming and economic potential of the basin.Departamento de Engenharia Agrícola - UFCG2019-05-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662019000500352Revista Brasileira de Engenharia Agrícola e Ambiental v.23 n.5 2019reponame:Revista Brasileira de Engenharia Agrícola e Ambiental (Online)instname:Universidade Federal de Campina Grande (UFCG)instacron:UFCG10.1590/1807-1929/agriambi.v23n5p352-358info:eu-repo/semantics/openAccessCalegario,Arthur T.Pereira,Luis F.Pereira,Silvio B.Silva,Laksme N. O. daAraújo,Uriel L. deFernandes Filho,Elpídio I.eng2019-05-02T00:00:00Zoai:scielo:S1415-43662019000500352Revistahttp://www.scielo.br/rbeaaPUBhttps://old.scielo.br/oai/scielo-oai.php||agriambi@agriambi.com.br1807-19291415-4366opendoar:2019-05-02T00:00Revista Brasileira de Engenharia Agrícola e Ambiental (Online) - Universidade Federal de Campina Grande (UFCG)false |
dc.title.none.fl_str_mv |
Mapping and characterization of intensity in land use by pasture using remote sensing |
title |
Mapping and characterization of intensity in land use by pasture using remote sensing |
spellingShingle |
Mapping and characterization of intensity in land use by pasture using remote sensing Calegario,Arthur T. soil and water conservation GIS kappa and weighted kappa indices |
title_short |
Mapping and characterization of intensity in land use by pasture using remote sensing |
title_full |
Mapping and characterization of intensity in land use by pasture using remote sensing |
title_fullStr |
Mapping and characterization of intensity in land use by pasture using remote sensing |
title_full_unstemmed |
Mapping and characterization of intensity in land use by pasture using remote sensing |
title_sort |
Mapping and characterization of intensity in land use by pasture using remote sensing |
author |
Calegario,Arthur T. |
author_facet |
Calegario,Arthur T. Pereira,Luis F. Pereira,Silvio B. Silva,Laksme N. O. da Araújo,Uriel L. de Fernandes Filho,Elpídio I. |
author_role |
author |
author2 |
Pereira,Luis F. Pereira,Silvio B. Silva,Laksme N. O. da Araújo,Uriel L. de Fernandes Filho,Elpídio I. |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Calegario,Arthur T. Pereira,Luis F. Pereira,Silvio B. Silva,Laksme N. O. da Araújo,Uriel L. de Fernandes Filho,Elpídio I. |
dc.subject.por.fl_str_mv |
soil and water conservation GIS kappa and weighted kappa indices |
topic |
soil and water conservation GIS kappa and weighted kappa indices |
description |
ABSTRACT The current demand for food has been met through the exploitation of natural reserves. Brazil has 26% of its extension occupied by agricultural uses, 62% of which are pastures. Degraded pastures have greater land use intensity than well-managed pastures, leading to greater degradation of the environment. Land use classification systems consider that pastures are well managed, a misconception for the Brazilian reality. Based on this approach, it was aimed to develop a methodology for mapping the intensity of land use by pasture via remote sensing. The method of mapping was developed and validated in basins with different soil and climatic characteristics. Three calibrations were performed based on NDVI values to ascertain the influence on the results, being evaluated from the field campaigns and the kappa and weighted kappa indices. The kappa and weighted kappa indices presented reasonable and moderate agreement, respectively. The results were considered as satisfactory for the three calibrations, evidencing that the degree of degradation of the pastures can be estimated in a simple way by remote sensing. The Limoeiro River Basin has around 46.9% of pastures, at least, heavily degraded and 96.6% with some degree of degradation, which contributes to degradation of the natural resources and reduction of livestock farming and economic potential of the basin. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-05-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662019000500352 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662019000500352 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/1807-1929/agriambi.v23n5p352-358 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Departamento de Engenharia Agrícola - UFCG |
publisher.none.fl_str_mv |
Departamento de Engenharia Agrícola - UFCG |
dc.source.none.fl_str_mv |
Revista Brasileira de Engenharia Agrícola e Ambiental v.23 n.5 2019 reponame:Revista Brasileira de Engenharia Agrícola e Ambiental (Online) instname:Universidade Federal de Campina Grande (UFCG) instacron:UFCG |
instname_str |
Universidade Federal de Campina Grande (UFCG) |
instacron_str |
UFCG |
institution |
UFCG |
reponame_str |
Revista Brasileira de Engenharia Agrícola e Ambiental (Online) |
collection |
Revista Brasileira de Engenharia Agrícola e Ambiental (Online) |
repository.name.fl_str_mv |
Revista Brasileira de Engenharia Agrícola e Ambiental (Online) - Universidade Federal de Campina Grande (UFCG) |
repository.mail.fl_str_mv |
||agriambi@agriambi.com.br |
_version_ |
1750297686842540032 |