Avaliação da dinâmica espectro-temporal visando o mapeamento dos principais cultivos de verão no Rio Grande do Sul

Abstract

This study aimed to develop a low-cost method for mapping summer crops in the Rio Grande do Sul State, from the spectraltemporal behavior of vegetation indices and the HAND Model. The study was conducted in the Rio Grande do Sul State in the 2011/2012 harvest. It was used EVI images from the MODIS sensor and SRTM data. To evaluate the results, we used field data and IBGE data and a reference map elaborated with RapidEye images. The results of the MODIS classification and the IBGE data generated a correlation coefficient (r) of 0.98 for rice and 0.89 for soybeans. Validation with data collected in the field, irrigated rice obtained a Kappa coefficient of 0.66 and soybean, 0.61. In the Fuzzy similarity analysis, the irrigated rice achieved a similarity of 87% and soybean, 81%. Therefore, multi-temporal MODIS data, combined with the delineation of flood areas, using the HAND model, allow to estimate the area planted with the main summer crops in the Rio Grande do Sul State.

Potential distribution ofPythium insidiosumin Rio Grande do Sul, Brazil, and projections to neighbour countries

“…Overall, we found pythiosis suitability in geographic areas that either have swamps or that correspond to areas with artificially irrigated rice fields (Mengue & Fontana, ). Thus, rice farmers may be particularly exposed to this pathogen.…”

“…The regions predicted to be at risk of pythiosis transmission correlated with areas of similar ecological characteristics found in Thailand (Supporting Information Figure S3) including agricultural fields, irrigation ditches, damp soil located within one metre of irrigation ditches (Supabandhu, Fisher, Mendoza, & Vanittanakom, ; Vanittanakom et al., ), and areas that are extremely wet during the summer due an increase in irrigation and an association with a rainy season (Mengue & Fontana, ). Another relevant finding of the environmental sampling was that P. insidiosum was mostly from lakes with dark muddy water and dark soil with large amounts of decaying organic matter.…”

NDVI and meteorological data as indicators of the Pampa biome natural grasslands growth

“…Therefore, VI shows potential to obtain inferences about growth and development of the vegetation in general (Soudani et al 2012). They also have had, in RS, a significant use in monitoring, either for annual agricultural crops (Junges et al 2013;Santos et al 2014;Mengue and Fontana 2015), for grasslands (Fonseca et al 2007;Soudani et al 2012;Wagner et al 2013;Scottá and Fonseca 2015;Junges et al 2016) or forests (Berra et al 2014).…”

Métodos para análise de concordância: estudo de simulação e aplicação a dados de evapotranspiração

“…O coeciente de correlação de Pearson é utilizado em diferentes estudos de concordância entre métodos ou modelos nas mais diversas áreas (CUNHA et al,2015;MENGUE & FONTANA, 2015;SOUZA et al, 2014;XIMENES et al, 2014;RAMOS et al, 2014a;RAMOS et al, 2014b;CUNHA et al, 2013;FENG et al, 2013;GIONGO et al, 2013;ALENCAR et al, 2011;FERNANDES et al, 2011;PEREIRA et al, 2009;PICOLI et al, 2009;ANDRADE JÚNIOR et al, 2003), e usualmente a variável X assume os valores de referência e a variável Y os valores do novo método/modelo a ser testado.…”

“…O índice d é utilizado em diferentes áreas do conhecimento para estudar a concordância entre modelos/métodos (CUNHA et al,2015;MENGUE & FONTANA, 2015;MIRANDA et al, 2014;SOUZA et al, 2014;XIMENES et al, 2014;RAMOS et al, 2014a;CARVALHO et al, 2013;CUNHA et al, 2013;GIONGO et al, 2013;ALENCAR et al, 2011;FERNANDES et al, 2011;PEREIRA et al, 2009;HALLOCK et al, 2014;ANDRADE JÚNIOR et al, 2003). O índice d r , mais recente, também vem ganhando espaço no estudo de concordância (MENGUE & FONTANA, 2015;El MASRI et al, 2015;GAITAN et al 2014;HALLOCK et al, 2014;FENG et al, 2013;SONG et al 2013).…”