REPRESENTATION IN 3D MESHES FROM THE INTERPOLATED SOIL TEXTURE DATA BY ARTIFICIAL NEURAL NETWORK: CASE STUDY FESCON - PONTA GROSSA - PR
DOI:
https://doi.org/10.12957/geouerj.2016.12310Keywords:
Interpolates soil texture, artificial neural network, 3D meshes representation.Abstract
doi: 10.12957/geouerj.2016.12310
The physical properties of the soil have great impact on their behavior, and these characteristics result in classification of the profile and soil suitability. In the case of Precision Agriculture is important to identify in the soil particle size space distribution or texture. Thus, from granulometric georeferenced data (sand, silt and clay) soils collected from a farmland Farm School Capão-da-Onça (FESCON Ponta Grossa - PR), was performed interpolation using Radial Basis Function (RBF) and supervised training for Artificial Neural Network (ANN), comparing the results obtained on a 3D model in order to verify the performance of the RNA used. It was found that especially the representations of RNA with the sand attribute was smoothed when interpolated the granulometric data in realation to RBF. The attributes clain and silt had some variations between ANN and RBF, it doesn’t always smoothed.
Downloads
Downloads
Published
How to Cite
Issue
Section
License
The copyright of articles published in Geo UERJ belongs to their respective authors with rights to first publication conceded to the journal. Every time that the article is cited and reproduced in institutional repositories or personal and professional web pages the link to the journal web page must be provided Geo UERJ.
The articles are simultaneously licensed under theCreative Commons Atribuição-Não Comercial-Compartilha Igual 4.0 Internacional.