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All publications of “Alexandre ten Caten”

7 results

Edaphic and Topographic Factors and their Relationship with Dendrometric Variation of Pinus Taeda L. in a High Altitude Subtropical Climate

Taciara Zborowski Horst, Ricardo Simão Diniz Dalmolin, Alexandre ten Caten, Jean Michel Moura-Bueno, Luciano Campos Cancian, Fabrício de Araújo Pedron, [...]


ABSTRACT The study of the relationships between the yield potential of forest stands and the conditions offered for plant development is fundamental for the adequate management of the forest when aiming at sustainable high yields. However, these relations are not clear, especially in commercial forests, on rugged terrain where relationships between the landscape, soil, and plants are more complex. Considering this, we tested the hypothesis that the morphological aspects of the soil conditioned by topography are the main limiting factors […]

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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


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 […]

Potential of Spectroradiometry to Classify Soil Clay Content

André Carnieletto Dotto, Ricardo Simão Diniz Dalmolin, Alexandre ten Caten, Jean Michel Moura-Bueno


ABSTRACT Diffuse reflectance spectroscopy (DRS) is a fast and cheap alternative for soil clay, but needs further investigation to assess the scope of application. The purpose of the study was to develop a linear regression model to predict clay content from DRS data, to classify the soils into three textural classes, similar to those defined by a regulation of the Brazilian Ministry of Agriculture, Livestock and Food Supply. The DRS data of 412 soil samples, from the 0.0-0.5 m layer, […]

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


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


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


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 […]

Multiple Logistic Regressions: controlling factors in applications to soil class prediction

Alexandre ten Caten, Ricardo Simão Diniz Dalmolin, Fabrício Araújo Pedron, Maria de Lourdes Mendonça-Santos


More effective methodologies to determine the soil class distribution must be evaluated in order to meet the demand for soil maps at regional and global scales. In this study, logistic regressions were used as predictive models in an application of Digital Soil Mapping. The models were derived from an existing soil map as dependent variable and terrain attributes as independent variables. The probability of finding soil classes in the landscape at the 1st and 2nd Categorical Level of the Brazilian […]