7 results

Training pedologist for soil mapping: Contextualizing methods and its accuracy using the project pedagogy approach

Elias Mendes Costa ORCID logo , Marcos Bacis Ceddia ORCID logo , Felipe Nascimento dos Santos ORCID logo , Laiz de Oliveira Silva ORCID logo , Igor Prata Terra de Rezende ORCID logo , Douglath Alves Correa Fernandes ORCID logo

10/mar/2021

ABSTRACT There is a growing demand for more detailed knowledge about soils, their functions, and connections with human activities and environmental services. In Brazil, where soil survey and mapping have been scarce since the 1990s, there is a remarkable sense of urgency. Recently, a national soil program was created (PronaSolos) to attend to the massive demand for soil information. PronaSolos is an effort to return to the systematic soil mapping of the national territory, which requires many pedologists who master […]

Visual Abstract

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, [...]

12/set/2018

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

18/jun/2018

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

04/abr/2018

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

02/mar/2018

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 […]

Is It Possible to Classify Topsoil Texture Using a Sensor Located 800 km Away from the Surface?

José Alexandre Melo Demattê, Marcelo Rodrigo Alves, Fabricio da Silva Terra, Raoni Wainer Duarte Bosquilia, Caio Troula Fongaro, Pedro Paulo da Silva Barros

17/out/2016

ABSTRACT It is often difficult for pedologists to “see” topsoils indicating differences in properties such as soil particle size. Satellite images are important for obtaining quick information for large areas. However, mapping extensive areas of bare soil using a single image is difficult since most areas are usually covered by vegetation. Thus, the aim of this study was to develop a strategy to determine bare soil areas by fusing multi-temporal satellite images and classifying them according to soil textures. Three […]

Uso de regressões logísticas múltiplas para mapeamento digital de solos no Planalto Médio do RS

Samuel Ribeiro Figueiredo, Elvio Giasson, Carlos Gustavo Tornquist, Paulo César do Nascimento

01/dez/2008

Regressões nominais logísticas estabelecem relações matemáticas entre variáveis independentes contínuas ou discretas e variáveis dependentes discretas. Essas foram avaliadas quanto ao seu potencial em predizer a ocorrência e distribuição de classes de solos na região dos municípios de Ibirubá e Quinze de Novembro (RS). A partir de modelo numérico de terreno digital (MNT) com 90 m de resolução, foram calculadas variáveis de terreno topográficas (elevação, declividade e curvatura) e hidrográficas (distância dos rios, índice de umidade topográfica, comprimento de fluxo […]