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All publications of “Luis Fernando Chimelo Ruiz”

5 results

AlradSpectra: a Quantification Tool for Soil Properties Using Spectroscopic Data in R

André Carnieletto Dotto ORCID logo , Ricardo Simão Diniz Dalmolin ORCID logo , Alexandre ten Caten ORCID logo , Diego José Gris ORCID logo , Luis Fernando Chimelo Ruiz ORCID logo

23/Jul/2019

ABSTRACT Soil reflectance spectroscopy has become an innovative method for soil property quantification supplying data for studies in soil fertility, soil classification, digital soil mapping, while reducing laboratory time and applying a clean technology. This paper describes the implementation of a Graphical User Interface (GUI) using R named AlradSpectra. It contains several tools to process spectroscopic data and generate models to predict soil properties. The GUI was developed to accomplish tasks such as perform a large range of spectral preprocessing […]

Visual Abstract

Assessment of Digital Elevation Model for Digital Soil Mapping in a Watershed with Gently Undulating Topography

Jean Michel Moura-Bueno, Ricardo Simão Diniz Dalmolin, Alexandre ten Caten, Luis Fernando Chimelo Ruiz, Priscila Vogelei Ramos, André Carnieletto Dotto

06/Jun/2016

ABSTRACT Terrain attributes (TAs) derived from digital elevation models (DEMs) are frequently used in digital soil mapping (DSM) as auxiliary covariates in the construction of prediction models. The DEMs and information extracted from it may be limited with regard to the spatial resolution and error magnitude, and can differ in the behavior of terrain features. The objective of this study was to evaluate the quality and limitations of free DEM data and to evaluate a topographic survey (TS) underlying the […]

Digital mapping of soil properties: particle size and soil organic matter by diffuse reflectance spectroscopy

André Carnieletto Dotto, Ricardo Simão Diniz Dalmolin, Fabrício de Araújo Pedron, Alexandre ten Caten, Luis Fernando Chimelo Ruiz

01/Dec/2014

Diffuse reflectance spectroscopy (DRS) can be used as an alternative in identifying and quantifying some soil properties such as particle size and soil organic matter (SOM). This technique may be an alternative to quantifying those properties in a large volume of soil samples since it is faster and less costly and does not produce chemical residues. The aim of this study was to develop models using multiple linear regression analysis to predict the content of clay, sand, silt, and SOM […]

An appropriate data set size for digital soil mapping in Erechim, Rio Grande do Sul, Brazil

Alexandre ten Caten, Ricardo Simão Diniz Dalmolin, Fabrício de Araújo Pedron, Luis Fernando Chimelo Ruiz, Carlos Antônio da Silva

01/Apr/2013

Digital information generates the possibility of a high degree of redundancy in the data available for fitting predictive models used for Digital Soil Mapping (DSM). Among these models, the Decision Tree (DT) technique has been increasingly applied due to its capacity of dealing with large datasets. The purpose of this study was to evaluate the impact of the data volume used to generate the DT models on the quality of soil maps. An area of 889.33 km² was chosen in […]

Digital soil mapping: strategy for data pre-processing

Alexandre ten Caten, Ricardo Simão Diniz Dalmolin, Luis Fernando Chimelo Ruiz

01/Aug/2012

The region of greatest variability on soil maps is along the edge of their polygons, causing disagreement among pedologists about the appropriate description of soil classes at these locations. The objective of this work was to propose a strategy for data pre-processing applied to digital soil mapping (DSM). Soil polygons on a training map were shrunk by 100 and 160 m. This strategy prevented the use of covariates located near the edge of the soil classes for the Decision Tree […]