9 results

Soil legacy data: An opportunity for digital soil mapping

Beatriz Macêdo Medeiros ORCID logo , Letícia Sequinatto Rossi ORCID logo , Alexandre ten Caten ORCID logo , Gustavo Eduardo Pereira ORCID logo , Elisângela Benedet da Silva ORCID logo , Kelly Tamires Urbano Daboit ORCID logo

23/Jul/2024

ABSTRACT Soil legacy data is past information on soils available from various sources (e.g. survey reports and maps). When compiled and organized, data obtained through historical retrieval can be used as basic input or validation data for digital soil mapping. A bibliometric analysis of this topic can reveal research patterns, evolution, and scientific contribution, thus mapping the science produced in a specific period and determining the trend in research topics based on search terms. This article presents the characterization of […]

Visual Abstract

Reflectance spectroscopy in the prediction of soil organic carbon associated with humic substances

Sharon Gomes Ribeiro ORCID logo , Marcio Regys Rabelo de Oliveira ORCID logo , Letícia Machado Lopes ORCID logo , Mirian Cristina Gomes Costa ORCID logo , Raul Shiso Toma ORCID logo , Isabel Cristina da Silva Araújo ORCID logo , [...]

06/Jun/2023

ABSTRACT Understanding organic carbon and predominant humic fractions in the soil allows contributes to soil quality management. Conventional fractionation techniques require time, excessive sampling, and high maintenance costs. In this study, predictive models for organic carbon in humic substances (HS) were evaluated using hyperspectral data as an alternative to chemical fractionation and quantification by wet digestion. Twenty-nine samples of Neossolos Flúvicos (Fluvents) – A1, and 36 samples of Cambissolos (Inceptisols) – A2 were used. The samples were also analyzed jointly, […]

Visual Abstract

Fine-scale soil mapping with Earth Observation data: a multiple geographic level comparison

José Lucas Safanelli ORCID logo , José Alexandre Melo Demattê ORCID logo , Natasha Valadares dos Santos ORCID logo , Jorge Tadeu Fim Rosas ORCID logo , Nélida Elizabet Quiñonez Silvero ORCID logo , Benito Roberto Bonfatti ORCID logo , [...]

24/Nov/2021

ABSTRACT Multitemporal collections of satellite images and their products have recently been explored in digital soil mapping. This study aimed to produce a bare soil image (BSI) for the São Paulo State (Brazil) to perform a pedometric analysis for different geographical levels. First, we assessed the potential of the BSI for predicting the surface (0.00-0.20 m) and subsurface (0.80-1.00 m) clay, iron oxides (Fe 2 O 3 ), aluminum (m%) and bases saturation (V%) contents at the state level, which […]

Visual Abstract

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

Digital Soil Mapping Using Machine Learning Algorithms in a Tropical Mountainous Area

Martin Meier, Eliana de Souza, Marcio Rocha Francelino, Elpídio Inácio Fernandes Filho, Carlos Ernesto Gonçalves Reynaud Schaefer

02/Nov/2018

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 […]

Visual Abstract

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

11/Jan/2017

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 […]

Boundary between Soil and Saprolite in Alisols in the South of Brazil

Fabrício de Araújo Pedron, Rodrigo Bomicieli de Oliveira, Ricardo Simão Diniz Dalmolin, Antonio Carlos de Azevedo and, Ricardo Vargas Kilca

01/May/2015

Despite numerous studies conducted on the lower limit of soil and its contact with saprolite layers, a great deal of work is left to standardize identification and annotation of these variables in the field. In shallow soils, the appropriately noting these limits or contacts is essential for determining their behavior and potential use. The aims of this study were to identify and define the field contact and/or transition zone between soil and saprolite in profiles of an Alisol derived from […]

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 […]

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 […]