ABSTRACT: Increasingly, applications of machine learning techniques for digital soil mapping (DSM) are being used for different soil mapping purposes. Considering the variety of models available, it is important to know their performance in relation to soil data and environmental variables involved in soil mapping. This paper investigated the performance of eight machine learning algorithms for soil mapping in a tropical mountainous area of an official rural settlement in the Zona da Mata region in Brazil. Morphometric maps generated from […]

ABSTRACT: Planning sustainable use of land resources requires reliable information about spatial distribution of soil physical and chemical properties related to environmental processes and ecosystemic functions. In this context, cation exchange capacity (CEC) is a fundamental soil quality indicator; however, it takes money and time to obtain this data. Although many studies have been conducted to spatially quantify soil properties on various scales and in different environments, not much is known about interactions between soil properties and environmental covariates in […]

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 […]

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 […]

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 […]

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 […]

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 […]

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 […]

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 […]

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 […]