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Building predictive models of soil particle-size distribution Rev. Bras. Ciênc. Solo
Samuel-Rosa,Alessandro; Dalmolin,Ricardo Simão Diniz; Miguel,Pablo.
Is it possible to build predictive models (PMs) of soil particle-size distribution (psd) in a region with complex geology and a young and unstable land-surface? The main objective of this study was to answer this question. A set of 339 soil samples from a small slope catchment in Southern Brazil was used to build PMs of psd in the surface soil layer. Multiple linear regression models were constructed using terrain attributes (elevation, slope, catchment area, convergence index, and topographic wetness index). The PMs explained more than half of the data variance. This performance is similar to (or even better than) that of the conventional soil mapping approach. For some size fractions, the PM performance can reach 70 %. Largest uncertainties were observed...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Digital soil mapping; Terrain attributes; Multiple linear regression; Cross-validation; Additive log-ratio.
Ano: 2013 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06832013000200013
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Digital elevation model quality on digital soil mapping prediction accuracy Ciência e Agrotecnologia
Costa,Elias Mendes; Samuel-Rosa,Alessandro; Anjos,Lúcia Helena Cunha dos.
ABSTRACT Digital elevation models (DEM) used in digital soil mapping (DSM) are commonly selected based on measures and indicators (quality criteria) that are thought to reflect how well a given DEM represents the terrain surface. The hypothesis is that the more accurate a DEM, the more accurate will be the DSM predictions. The objective of this study was to assess different criteria to identify the DEM that delivers the most accurate DSM predictions. A set of 10 criteria were used to evaluate the quality of nine DEMs constructed with different data sources, processing routines and three resolutions (5, 20, and 30 m). Multinomial logistic regression models were calibrated using 157 soil observations and terrain attributes derived from each DEM. Soil class...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Multinomial logistic regression; Predictor variables; Collinearity; Shannon entropy.
Ano: 2018 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1413-70542018000600608
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How is the learning process of digital soil mapping in a diverse group of land use planners? Rev. Bras. Ciênc. Solo
Dalmolin,Ricardo Simão Diniz; Moura-Bueno,Jean Michel; Samuel-Rosa,Alessandro; Flores,Carlos Alberto.
ABSTRACT The use of new technologies, the development of new software, and the advances in the machines ability to process data have brought a new perspective to soil science and especially to pedology, with the advent of digital soil mapping (DSM). To meet the demand for soil surveys in Brazil, it will be necessary to popularize the techniques used in DSM. To identify and map the soil to generate maps of land use capability, we proposed a theoretical and practical course focused on the training in DSM for professionals involved in the management of land resources. The methodology was divided into five modules: I. Introduction to pedology, soil-landscape relationship, soil survey and soil classification (theory); II. Identification of soils in the field...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Expert knowledge; Pedometry; PronaSolos; Soil education; Soil survey.
Ano: 2020 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06832020000100600
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Open legacy soil survey data in Brazil: geospatial data quality and how to improve it Scientia Agricola
Samuel-Rosa,Alessandro; Dalmolin,Ricardo Simão Diniz; Moura-Bueno,Jean Michel; Teixeira,Wenceslau Geraldes; Alba,José Maria Filippini.
ABSTRACT: Spatial soil data applications require sound geospatial data including coordinates and a coordinate reference system. However, when it comes to legacy soil data we frequently find them to be missing or incorrect. This paper assesses the quality of the geospatial data of legacy soil observations in Brazil, and evaluates geospatial data sources (survey reports, maps, spatial data infrastructures, web mapping services) and expert knowledge as a means to fix inconsistencies. The analyses included several consistency checks performed on 6,195 observations from the Brazilian Soil Information System. The positional accuracy of geospatial data sources was estimated so as to obtain an indication of the quality for fixing inconsistencies. The coordinates...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Free Brazilian Repository for Open Soil Data; PronaSolos; Pedometrics; Soil data recovery; Digital soil mapping.
Ano: 2020 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162020000101401
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Replacing the (inefficient) manual runoff sampling method used in Brazil – a prototype sample splitter Scientia Agricola
Samuel-Rosa,Alessandro; Moura-Bueno,Jean Michel; Dalmolin,Ricardo Simão Diniz.
ABSTRACT The method used to sample the runoff collected from soil erosion plots can be a significant source of error. In this study, we performed a laboratory experiment to evaluate the efficiency of the runoff sampling method most commonly used in Brazil. It is based on the manual homogenization and sampling of the collected runoff. Using soil material with 583 g kg–1 of sand and 89 g kg–1 of clay, the manual sampling method was tested for its ability to produce representative samples of artificial suspensions with a concentration of 2, 10 and 50 g L–1 of total solids. An underestimation of 30 % or more of the concentration of total solids was observed, with a variation of the same magnitude (CV between 20 and 45 %). We then developed a prototype sample...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Erosion monitoring; Soil loss; Sandy soil; Uncertainty.
Ano: 2021 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162021000401402
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The effect of intrinsic soil properties on soil quality assessments Rev. Bras. Ciênc. Solo
Samuel-Rosa,Alessandro; Dalmolin,Ricardo Simão Diniz; Miguel,Pablo; Zalamena,Jovani; Dick,Deborah Pinheiro.
The assessment of soil quality is based on indicators and indices derived from soil properties. However, intrinsic soil properties may interfere with other soil properties that vary under different land uses and are used to calculate the indices. The aim of this study was to assess the extent to which intrinsic soil properties (clay and iron oxide contents) explain variable soil properties (sum of bases, potential acidity, organic carbon, total porosity, and bulk density) under different land uses (native forest, no-tillage and conventional agriculture) on small family farms in Southern Brazil. The results showed that the five properties evaluated can be included in soil quality assessments and are not influenced by the clay and iron oxide contents. It was...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Soil quality; Family farms; ANCOVA; Spurious correlation.
Ano: 2013 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06832013000500013
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Variação das características pedológicas e classificação taxonômica de argissolos derivados de rochas sedimentares Rev. Bras. Ciênc. Solo
Pedron,Fabrício de Araújo; Samuel-Rosa,Alessandro; Dalmolin,Ricardo Simão Diniz.
Trabalhos têm apontado demandas em relação ao conhecimento da variação pedológica de Argissolos. Essa variação pode ser analisada pela estatística multivariada - também responsável pela classificação numérica dos dados. A comparação entre a classificação numérica e a classificação hierárquica pode contribuir para a evolução do Sistema Brasileiro de Classificação de Solos (SiBCS). Os objetivos deste trabalho foram analisar a variação pedológica de Argissolos derivados de materiais sedimentares na Depressão Central do Rio Grande do Sul e validar a estrutura da ordem dos Argissolos do SiBCS por meio da interpretação da classificação numérica. Foram considerados 42 perfis de Argissolos derivados da Formação Santa Maria e da Formação Caturrita, na região...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Solos arenosos; Morfologia; Classificação numérica; Análise multivariada; SiBCS.
Ano: 2012 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06832012000100001
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