Spatial autocorrelation of ndvi and gvi indices derived from landsat/tm images for soybean crops in the western of the state of Paraná in 2004/2005 crop season

Abstract

ABSTRACT:This research aims at studying spatial autocorrelation of Landsat/TM based on normalized difference vegetation index (NDVI) and green vegetation index (GVI) of soybean of the western region of the State of Paraná. The images were collected during the 2004/2005 crop season. The data were grouped into five vegetation index classes of equal amplitude, to create a temporal map of soybean within the crop cycle. Moran I and Local Indicators of Spatial Autocorrelation (LISA) indices were applied to study the spatial correlation at the global and local levels, respectively. According to these indices, it was possible to understand the municipality-based profiles of tillage as well as to identify different sowing periods, providing important information to producers who use soybean yield data in their planning.KEYWORDS: spatial statistics of areas, spatial correlation, vegetation index. AUTOCORRELAÇÃO ESPACIAL DOS ÍNDICES NDVI E GVI DERIVADOS DE

Spatial and Multivariate Analysis of Soybean Yield in the State of Paraná-Brazil

“…Studies using these indicators have shown for the state of Paraná : the soybean crop profile at different seeding dates (Dalposso et al, 2013, Cima et al, 2018; how municipalities relate spatially to soybean production; which are the main municipalities producing soy (Prudente et al, 2014); and the analysis of the spatial relationship of soybean yield with agrometeorological characteristics (Grzegozewski et al, 2017) In this context, regarding the simultaneous analysis of a set of variables, the multivariate analysis techniques can be helpful in finding patterns generated by the set of variables. In the Western region of Paraná , Araújo et al (2013) carried out a cluster analysis using information on the local Moran index (LISA) applied to agrometeorological and soybean yield data in crop year 2005/2006, and the formation of groups of similar municipalities was identified regarding their spatial distribution in relation to soybean yield and all agrometeorological elements analyzed.…”

Uso de imagens do sensor orbital modis na estimação de datas do ciclo de desenvolvimento da cultura da soja para o estado do Paraná – Brasil

“…Atrás da região Centro-Oeste, a região Sul é a segunda maior produtora de soja do País. Apenas o Estado do Paraná foi responsável por 20,2% da produção de soja no Brasil (CONAB, 2013;SEAB/Deral, 2013;IBGE, 2014), sendo objeto de diversos estudos (ADAMI, 2010;JOHANN et al, 2012;DALPOSSO et al, 2013;SOUZA et al, 2015;GRZEGOZEWSKI et al, 2016), evidenciando a importância econômica da cultura para o Estado.…”

Evolution of Cerrado Vegetal Cover on a River Island Based on Orbital Imaging Data

“…Among the geo-technologies used for identification and evaluation of changes in structure, physiognomy and dynamics of vegetal coverage across different dates, it is noteworthy mention spectral change detection by vegetation indices (JUNGES et al, 2013;SEXTON et al, 2013;DALPOSSO et al, 2013;HILL et al, 2012). Normalized Difference Vegetation Index (NDVI) is one of the vegetation indices most used in studies of plant coverage, since it allows evaluating vegetation conditions and respective spatiotemporal changes (SOUTHWORT et al, 2013;GIRI et al, 2013;TOWNSHEND et al, 2012).…”