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26 results

Satellite Spectral Data on the Quantification of Soil Particle Size from Different Geographic Regions

José Alexandre Melo Demattê, Clécia Cristina Barbosa Guimarães, Caio Troula Fongaro, Emmily Larissa Felipe Vidoy, Veridiana Maria Sayão, André Carnieletto Dotto, [...]


ABSTRACT: The study of soils, including their physical and chemical properties, is essential for agricultural management. Soil quality must be maintained to ensure sustainable production of food and conservation of natural resources. In this context, soil mapping is important to provide spatial information, which can be performed using remote sensing (RS) techniques. Modeling through use of satellite data is uncertain regarding the amplitude of replicability of the models. The aim of this study was to develop a quantification model for […]

Multinomial Logistic Regression and Random Forest Classifiers in Digital Mapping of Soil Classes in Western Haiti

Wesly Jeune, Márcio Rocha Francelino, Eliana de Souza, Elpídio Inácio Fernandes Filho, Genelício Crusoé Rocha


ABSTRACT Digital soil mapping (DSM) has been increasingly used to provide quick and accurate spatial information to support decision-makers in agricultural and environmental planning programs. In this study, we used a DSM approach to map soils in western Haiti and compare the performance of the Multinomial Logistic Regression (MLR) with Random Forest (RF) to classify the soils. The study area of 4,300 km2 is mostly composed of diverse limestone rocks, alluvial deposits, and, to a lesser extent, basalt. A soil […]

Prediction of Topsoil Texture Through Regression Trees and Multiple Linear Regressions

Helena Saraiva Koenow Pinheiro, Waldir de Carvalho, César da Silva Chagas, Lúcia Helena Cunha dos Anjos, Phillip Ray Owens


ABSTRACT: Users of soil survey products are mostly interested in understanding how soil properties vary in space and time. The aim of digital soil mapping (DSM) is to represent the spatial variability of soil properties quantitatively to support decision-making. The goal of this study is to evaluate DSM techniques (Regression Trees – RT and Multiple Linear Regressions – MLR) and the ability of these tools to predict mineral fraction content under a wide variability of landscapes. The study site was […]

Spatial Disaggregation of Multi-Component Soil Map Units Using Legacy Data and a Tree-Based Algorithm in Southern Brazil

Israel Rosa Machado, Elvio Giasson, Alcinei Ribeiro Campos, José Janderson Ferreira Costa, Elisângela Benedet da Silva, Benito Roberto Bonfatti


ABSTRACT Soil surveys often contain multi-component map units comprising two or more soil classes, whose spatial distribution within the map unit is not represented. Digital Soil Mapping tools supported by information from soil surveys make it possible to predict where these classes are located. The aim of this study was to develop a methodology to increase the detail of conventional soil maps by means of spatial disaggregation of multi-component map units and to predict the spatial location of the derived […]

Slash Spatial Linear Modeling: Soybean Yield Variability as a Function of Soil Chemical Properties

Regiane Slongo Fagundes, Miguel Angel Uribe-Opazo, Luciana Pagliosa Carvalho Guedes, Manuel Galea


ABSTRACT: In geostatistical modeling of soil chemical properties, one or more influential observations in a dataset may impair the construction of interpolation maps and their accuracy. An alternative to avoid the problem would be to use most robust models, based on distributions that have heavier tails. Therefore, this study proposes a spatial linear model based on the slash distribution (SSLM) in order to characterize the spatial variability of soybean yields as a function of soil chemical properties. The likelihood ratio […]

Surface Spectroscopy of Oxisols, Entisols and Inceptisol and Relationships with Selected Soil Properties

Raúl Roberto Poppiel, Marilusa Pinto Coelho Lacerda, Manuel Pereira de Oliveira, José Alexandre Melo Demattê, Danilo Jefferson Romero, Marcus Vinicius Sato, [...]


ABSTRACT: Traditional method of soil survey is expensive, slow, and must be carried out by experienced researchers. Thus, advances in soil observation technologies and the need to obtain information quickly by modern techniques have intensified the use of proximal sensing. This study characterized surface reflectance spectra (A horizon) and related them to traditional soil classification, based on morphological, physical, and chemical properties of representative pedogenetic profiles, developed in two toposequences of the Distrito Federal, Brazil. In the toposequences, 15 soil […]

Environmental Correlation and Spatial Autocorrelation of Soil Properties in Keller Peninsula, Maritime Antarctica

André Geraldo de Lima Moraes, Marcio Rocha Francelino, Waldir de Carvalho, Marcos Gervasio Pereira, André Thomazini, Carlos Ernesto Gonçalves Reynaud Schaefer


ABSTRACT: The pattern of variation in soil and landform properties in relation to environmental covariates are closely related to soil type distribution. The aim of this study was to apply digital soil mapping techniques to analysis of the pattern of soil property variation in relation to environmental covariates under periglacial conditions at Keller Peninsula, Maritime Antarctica. We considered the hypothesis that covariates normally used for environmental correlation elsewhere can be adequately employed in periglacial areas in Maritime Antarctica. For that […]

Bulk Density Prediction for Histosols and Soil Horizons with High Organic Matter Content

Sidinei Julio Beutler, Marcos Gervasio Pereira, Wagner de Souza Tassinari, Michele Duarte de Menezes, Gustavo Souza Valladares, Lúcia Helena Cunha dos Anjos


ABSTRACT Bulk density (Bd) can easily be predicted from other data using pedotransfer functions (PTF). The present study developed two PTFs (PTF1 and PTF2) for Bd prediction in Brazilian organic soils and horizons and compared their performance with nine previously published equations. Samples of 280 organic soil horizons used to develop PTFs and containing at least 80 g kg-1 total carbon content (TOC) were obtained from different regions of Brazil. The multiple linear stepwise regression technique was applied to validate […]

Magnetic Susceptibility of Soil to Differentiate Soil Environments in Southern Brazil

Priscila Vogelei Ramos, Ricardo Simão Diniz Dalmolin, José Marques, Diego Silva Siqueira, Jaime Antonio de Almeida, Jean Michel Moura-Bueno


ABSTRACT The interest in new techniques to support digital soil mapping (DSM) is increasing. Numerous studies pointed out that the measure of magnetic susceptibility (MS) can be extremely useful in the identification of properties related with factors and processes of soil formation, applied to soil mapping. This study addressed the effectiveness of magnetic soil susceptibility to identify and facilitate the distinction of different pedogenic environments of a representative hillslope in the highland Planalto Médio in the state of Rio Grande […]

Cacao Crop Management Zones Determination Based on Soil Properties and Crop Yield

Perla Silva Matos de Carvalho, Laís Barreto Franco, Samuel de Assis Silva, George Andrade Sodré, Daniel Marçal de Queiroz, Julião Soares de Souza Lima


ABSTRACT: The use of management zones has ensured yield success for numerous agricultural crops. In spite of this potential, studies applying precision agricultural techniques to cacao plantations are scarce or almost nonexistent. The aim of the present study was to delineate management zones for cacao crop, create maps combining soil physical properties and cacao tree yield, and identify what combinations best fit within the soil chemical properties. The study was conducted in 2014 on a cacao plantation in a Nitossolo […]

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