9 resultados para INTERPOLATION METHODS
em Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho"
Resumo:
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
Resumo:
The application of agricultural fertilizers using variable rates along the field can be made through fertility maps previously elaborated or through real-time sensors. In most of the cases applies maps previously elaborated. These maps are identified from analyzes done in soil samples collected regularly (a sample for each field cell) or irregularly along the field. At the moment, mathematical interpolation methods such as nearest neighbor, local average, weighted inverse distance, contouring and kriging are used for predicting the variables involved with elaboration of fertility maps. However, some of these methods present deficiencies that can generate different fertility maps for a same data set. Moreover, such methods can generate inprecise maps to be used in precision farming. In this paper, artificial neural networks have been applied for elaboration and identification of precise fertility maps which can reduce the production costs and environmental impacts.
Resumo:
The obtaining of the correct space distribution for attributes of the soil is relevant in the agricultural planning, in what concerns to the installation and maintenance of the cultures. The objective of that work was to compare statistical interpolation methods (ordinary krigagem) and deterministic methods (inverse square distance) in the estimate of CTC and V% in a distrophic yellow-red Latossolo. The study was accomplished in the State of Experimental Hands on of the Instituto Capixaba de Pesquisa, Assistência Técnica e Extensão Rural (INCAPER), in an irregular grading with 109 points. The data were collected in the layer of 0 - 0,20 m in the projection of the cup of the plants, in the superior part of the slope. The performance of the interpolators was obtained and compared using the criterion of the medium mistake. The observations are dependent in space until a maximum reach of 14,1 m, considering the isotropy. IDW presented larger mistake in the estimate of the data; however its difference in relation to KRIG was small for both variables.
Resumo:
There are many methods used to estimate values in places no sampled for construction of contours maps. The aim of this study was to use the methods of interpolation kriging, inverse of the square of the distance and polynomial in the representation of the spatial variability of the pH of the soil in the organic and conventional management in the culture of the coffee plantation. For that, irregular meshes were built for soil sampling in the depth of 0-0,10 meters, totaling 40 points sampling in each area. For gauging of the interpolation methods they were solitary 10% of the total of points, for each area. Initially, the data were appraised through the classic statistics (descriptive and exploratory) and spatial analysis. The method inverse square of the distance and kriging has low error in estimating dados. The method of kriging presented low variation around the average in different managements.
Resumo:
Traditional methods of submerged aquatic vegetation (SAV) survey last long and then, they are high cost. Optical remote sensing is an alternative, but it has some limitations in the aquatic environment. The use of echosounder techniques is efficient to detect submerged targets. Therefore, the aim of this study is to evaluate different kinds of interpolation approach applied on SAV sample data collected by echosounder. This study case was performed in a region of Uberaba River - Brazil. The interpolation methods evaluated in this work follow: Nearest Neighbor, Weighted Average, Triangular Irregular Network (TIN) and ordinary kriging. Better results were carried out with kriging interpolation. Thus, it is recommend the use of geostatistics for spatial inference of SAV from sample data surveyed with echosounder techniques. © 2012 IEEE.
Resumo:
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
Resumo:
Pós-graduação em Agronomia (Ciência do Solo) - FCAV
Resumo:
Pós-graduação em Agronomia (Irrigação e Drenagem) - FCA
Resumo:
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)