Influência da densidade amostral e do tipo de interpolador na elaboração de mapas temáticos

• Autor(a) principal: Coelho, Edy Célia
• Data de Publicação: 2006
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Biblioteca Digital de Teses e Dissertações do UNIOESTE
• Texto Completo: http://tede.unioeste.br:8080/tede/handle/tede/2781
• topic: Agricultura de Precisão; Geoestatística; Amostragem; precision agriculture; geostatistics; sampling; CNPQ::CIENCIAS AGRARIAS::ENGENHARIA AGRICOLA

The general objective of this research was to evaluate the influence of the amostral density (five sampling grids) and of the type of interpolator (kriging, inverse of the square, inverse of the distance and polynomial) in the elaboration of thematic maps of the soybean yield in an area of Latossolo Vermelho Distroférrico soil, in a period five year for a research area under Precision Agriculture pertaining to the Research Center Eloy Gomes, of the Cooperativa Agropecuária de Desenvolvimento Tecnológico e Econômico LTDA (COODETEC). The data of this research had been raised during a period five year (from 1998 to 2002) for a project developed for the Technological Innovation Center (NIT) of the Universidade Estadual Oeste do Paraná (UNIOESTE). The selected grids had 128, 64 and 32 units using Stratified Systematic Aligned Sampling (AASE) and grids with 64 and 32 units using Nestled Systematic Aligned Sampling (AASA). From each amostral grid and using each one of the selected interpolators the thematic maps of the soybean yield had been generated in each year. To be analyzed the cited maps the Relative Deviation Coefficient (CDR) was proposed that express the average difference in module of the values interpolated in each grid in relation to the considered standard grid, the grid AASE 128 with Kriging. Thus it allowed to verify and to calculate which type of sampling more was recommended. For the area in study it was the grid AASE 128 that presented the best results. The CDR revealed to be efficient for thematic maps comparisons and allowed the conclusion that to really use all the potential of the kriging and for this method to be really recommended it is necessary to have many points so that a good semivariogram can be created, on the other hand, other interpolars analysed such as the inverse of the square distance or the inverse of the distance can be used. Besides that, the AASE 128 inverse of distance grid was the closest from the reference method, AASE 128 kriging.