Gustavo Henrique Dalposso

Comparação de mapas de variabilidade espacial da resistência do solo à penetração construídos com e sem covariáveis usando um modelo espacial linear

A study about the spatial variability of data of soil resistance to penetration (RSP) was conducted at layers 0.0-0.1 m, 0.1-0.2 m and 0.2-0.3 m depth, using the statistical methods in univariate forms, i.e., using traditional geostatistics, forming thematic maps by ordinary kriging for each layer of the study. It was analyzed the RSP in layer 0.2-0.3 m depth through a spatial linear model (SLM), which considered the layers 0.0-0.1 m and 0.1-0.2 m in depth as covariable, obtaining an estimation model and a thematic map by universal kriging. The thematic maps of the RSP at layer 0.2-0.3 m depth, constructed by both methods, were compared using measures of accuracy obtained from the construction of the matrix of errors and confusion matrix. There are similarities between the thematic maps. All maps showed that the RSP is higher in the north region.

Variabilidade espacial da rentabilidade, perdas na colheita e produtividade do feijoeiro

Common bean is grown in all regions of Brazil and has an economic and social importance. It is a subsistente crop on small farms, however, there are some problems affecting its marketing, such as fluctuation of prices paid to producers. The harvesting methods are diverse and currently the most widely used in Brazil is the semi-mechanized one. In order to evaluate productivity, profitability, manual and mechanical losses of Juriti beans cultivar, it was carried out a survey of georeferenced data in an area of 10.50 ha, with a 50 x 50 m grid of regular sampling. To study the spatial variability, geostatistics techniques were used to draw thematic maps by kriging techniques. It was found out that for the 2005/2006 crop, the average productivity in this area was 6.77% higher than the regional average, reported by the SEAB in Parana. At harvest, the manual losses were lower (1.49%) than the mechanical (8.73%), and these, when added together, represented a total loss of 10.22% of average productivity. According to the maps, it was possible to identify the spatial distribution of variables across the studied area and register that there was a loss in 35.91% of cultivated area, which means that the beans sale profitability was less than the production cost, caused mainly by the low yield of this crop. Such information is important so that farmers know their acreage, as well as evaluate, by the profitability map, if eventually, any other crop would have a better return per area.

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

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 Parana. 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.

Comparison measures of maps generated by geostatistical methods

This study uses several measures derived from the error matrix for comparing two thematic maps generated with the same sample set. The reference map was generated with all the sample elements and the map set as the model was generated without the two points detected as influential by the analysis of local influence diagnostics. The data analyzed refer to the wheat productivity in an agricultural area of 13.55 ha considering a sampling grid of 50 x 50 m comprising 50 georeferenced sample elements. The comparison measures derived from the error matrix indicated that despite some similarity on the maps, they are different. The difference between the estimated production by the reference map and the actual production was of 350 kilograms. The same difference calculated with the mode map was of 50 kilograms, indicating that the study of influential points is of fundamental importance to obtain a more reliable estimative and use of measures obtained from the error matrix is a good option to make comparisons between thematic maps.