Multitemporal analysis of the ground usage and coverage in Faxinal do Soturno-RS town in the years of 1986, 1996, 2006 and 2011.
DOI:
https://doi.org/10.5902/223611709155Keywords:
remote sensing, Landsat-5, digital classification, thematic mapping.Abstract
http://dx.doi.org/10.5902/223611709155
The objective of this study was to evaluate changes in land use and cover in the municipality of Faxinal Soturno, Rio Grande do Sul, in the years 1986, 1996, 2006 and 2011. The images from the Landsat TM sensor 5, four classes were classified use and land cover: “Forest” “Field”, “Bare Soil” and “Water. Classification was supervised manner, using the algorithm MaxVer (maximum likelihood), and for processing the data we used the application SPRING 5.1.8. The results showed an increase of 8.64 km2 in forest area 1986-2011. In areas of the field, there was an increase of 43.4 km2 between 1986 and 2006, but between 2006 and 2011 were reduced 7.31 km2. The areas of exposed soil 44.52 km² decreased over the study period. Areas occupied by water are very common in the region, remained virtually unchanged. It was also used in the programming language Spatial GIS algebraic (LEGAL) to quantify the transition between classes use and land cover, which was observed throughout the study period of forest regeneration and 28.20 km² 19.54 km² of deforestation. We conclude that there was an increase of forest and a reduction in agricultural areas. This fact may be related to the growth of native forests in an area that was previously occupied by agriculture and livestock and increasing rural exodus and environmental inspections.
Downloads
References
BRIASSOULIS, H. Analysis of Land Use Change: Theoretical and Modeling Approaches. In: Regional
Research Institute. West Virginia University, 1999. Disponível em: <http://www.rri.wvu.edu/WebBook/Briassoulis/contents.htm>. Acesso em: 25 out. 2012.
CÂMARA, G. Modelos, Linguagens e Arquiteturas para Bancos de Dados Geográficos. 1995. 282f.
Tese (Doutorado em Computação Aplicada) – Instituto Nacional de Pesquisas Espaciais, São José dos Campos, 1995.
IBGE – Instituto Brasileiro de Geografia e Estatística. Disponível em: <http://www.ibge.gov.br>.
Acesso em: 26 out. 2012.
INPE – Instituto Nacional de Pesquisas Espaciais. Disponível em: <http://www.inpe.br>. Acesso em: 08 set. 2012.
LANDIS, J.; KOCH, G. G.The measurements of agreement for categorical data. Biometrics, Washington, v. 33, n. 3, p. 159-179, 1977. INPE – Instituto Nacional de Pesquisas Espaciais. Disponível em: <http://www.inpe.br>.Acesso em: 10 set. 2012.
MARTINS, S. V. Recuperação de Mata Ciliar. Viçosa: Aprenda Fácil, 2001. 146p.
MORENO, J. A. Clima do Rio Grande do Sul. Porto Alegre: Secretaria da Agricultura, 1961. 42 p.
NOVO, E. M. L. M. Sensoriamento Remoto: princípios e aplicações. São Paulo, SP: Editora Blucher, 2008. 333p.
PEDRON, F.A.; POELKING, E.L.; DALMOLIN, R.S.D.; AZEVEDO, A.C.; KLANT, E. A aptidão de uso da terra como base para o planejamento da utilização dos recursos naturais no município de São João do Polêsine - RS. Ciência Rural [online]. 2006, vol.36, n.1, p. 105-112. ISSN 0103-8478.
STRECK, E.V.; KAMPF, N.; DALMOLIN, R.S.D.; KLAMT, E.; NASCIMENTO, P.C.; SCHNEIDER, P. Solos do Rio Grande do Sul. Porto Alegre: EMATER-RS/UFRGS, 2008. 222 p.
VENTURIERI, A.; SANTOS, J.R. DOS. Técnicas de classificação de imagens para análise da cobertura vegetal. In: ASSAD, E. D. & SANO, E. E. (Org.). Sistemas de Informações Geográficas: Aplicações na Agricultura. 2. ed. Brasília: EMBRAPA, 1998. p. 351- 371.