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%0 Conference Proceedings
%4 dpi.inpe.br/marte/2011/07.22.16.57
%2 dpi.inpe.br/marte/2011/07.22.16.57.57
%@isbn 978-85-17-00056-0 (Internet)
%@isbn 978-85-17-00057-7 (DVD)
%T Avaliação de interpoladores para a espacialização de variáveis de precipitação na bacia hidrográfica do rio Ivaí
%D 2011
%A Alves, Fabio Corrêa,
%@affiliation Universidade Estadual de Maringá - UEM
%@electronicmailaddress fabinho_netz@hotmail.com
%E Epiphanio, José Carlos Neves,
%E Galvão, Lênio Soares,
%B Simpósio Brasileiro de Sensoriamento Remoto, 15 (SBSR).
%C Curitiba
%8 30 abr. - 5 maio 2011
%I Instituto Nacional de Pesquisas Espaciais (INPE)
%J São José dos Campos
%P 4070-4077
%S Anais
%1 Instituto Nacional de Pesquisas Espaciais (INPE)
%K GIS, Spatial analysis, Interpolator, Accuracy, SIG, análise espacial, interpolador, acurácia.
%X A greater care with data handling in softwares using GIS also requires a greater knowledge and dedication to better represent and visualize the real surface. The use of a GIS for spatial analysis by the interpolation process with the precipitation variable is useful where values which are not sampled in a given region are estimated, favoring a better land use planning, associated with different environmental factors. Improper handling of a given interpolator may hide the expected outcome, underestimating or overestimating the final results, requiring further knowledge for better treating the data. The aim of this study is to evaluate the interpolators performance: quadrant Weighted average, weighted average, simple average and nearest neighbor, used in the regular grids generation with the version 5.0.6 SPRING software. The research was carried out based on 111 weather station samples with precipitation information distributed along the Ivaí river basin. The analysis was done visually by the thematic maps generated, accuracy verification and interpolators performance, using methods of cross validation and root mean squared error. The best results in accuracy and performance were obtained by the simple average interpolator, thus a better investigation is recommended with multiple variables at different sampling arrangements. For both methods, the weighted average interpolator showed the worst results.
%9 Geoprocessamento
%@language pt
%3 p0248.pdf


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