Mapping and characterization of intensity in land use by pasture using remote sensing/ Mapeamento e caracterizacao da intensidade de uso da terra pelas pastagens usando sensoriamento remoto

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 environ...

Full description

Saved in:
Bibliographic Details
Published inRevista brasileira de engenharia agrícola e ambiental Vol. 23; no. 5; p. 352
Main Authors Calegario, Arthur T, Pereira, Luis F, Pereira, Silvio B, da Silva, Laksme N.O, de Araujo, Uriel L, Filho, Elpidio I. Fernandes
Format Journal Article
LanguageEnglish
Published ATECEL--Associacao Tecnico Cientifica Ernesto Luiz de Oliveira Junior 01.05.2019
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary: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. Key words: soil and water conservation, GIS, kappa and weighted kappa indices A demanda atual por alimentos tem sido atendida por meio da exploracao das reservas naturais. O Brasil apresenta 26% da sua extensao ocupada por usos agropecuarios, sendo 62% desses, pastagens. Pastagens degradadas apresentam maior intensidade de uso da terra do que pastagens bem manejadas, levando a maior degradacao do meio ambiente. Os sistemas de classificacao da capacidade de uso de terra consideram que as pastagens se apresentam bem manejadas, consideracao equivocada para a realidade brasileira. Baseado nesse enfoque, objetivou-se apresentar e validar uma metodologia de mapeamento da intensidade de uso da terra exercida por pastagens via sensoriamento remoto. O metodo de mapeamento foi desenvolvido e validado em bacias com caracteristicas edafoclimaticas distintas. De posse da metodologia, tres calibracoes foram realizadas, com base nos valores de IVDN, para averiguar a influencia nos resultados, sendo avaliados a partir das campanhas de campo e dos indices kappa e kappa ponderado. Os indices kappa e kappa ponderado apresentaram concordancia razoavel e moderada, respectivamente. Os resultados foram considerados satisfatorios para as tres calibracoes, evidenciando que o grau de degradacao das pastagens pode ser estimado de maneira simples por sensoriamento remoto. A Bacia do Rio Limoeiro apresenta em torno de 46,9% das pastagens, no minimo, fortemente degradadas; e 96,6% com algum grau de degradacao, o que contribui para degradacao dos recursos naturais e reducao do potencial pecuario e economico da bacia. Palavras-chave: conservacao de solo e agua, SIG, indices kappa e kappa ponderado
ISSN:1415-4366
1807-1929
DOI:10.1590/1807-1929/agriambi.v23n5p352-358