RESUMO

Data Mining techniques play an important role in the prediction of soil spatial distribution in systematic soil surveying, though existing methodologies still lack standardization and a full understanding of their capabilities. The aim of this work was to evaluate the performance of preprocessing procedures and supervised classification approaches for predicting map units from 1:100,000-scale conventional semi-detailed soil surveys. Sheets of the Brazilian National Cartographic System on the 1:50,000 scale, Dois Córregos (Brotas 1:100,000-scale sheet), São Pedro and Laras (Piracicaba 1:100,000-scale sheet) were used for developing models. Soil map information and predictive environmental covariates for the dataset were obtained from the semi-detailed soil survey of the state of São Paulo, from the Brazilian Institute of Geography and Statistics (IBGE) 1:50,000-scale topographic sheets and from the 1:750,000-scale geological map of the state of São Paulo. The target variable was a soil map unit of four types: local soil unit name and soil class at three hierarchical levels of the Brazilian System of Soil Classification (SiBCS). Different data preprocessing treatments and four algorithms all having different approaches were also tested. Results showed that composite soil map units were not adequate for the machine learning process. Class balance did not contribute to improving the performance of classifiers. Accuracy values of 78 % and a Kappa index of 0.67 were obtained after preprocessing procedures with Random Forest, the algorithm that performed best. Information from conventional map units of semi-detailed (4th order) 1:100,000 soil survey generated models with values for accuracy, precision, sensitivity, specificity and Kappa indexes that support their use in programs for systematic soil surveying.(AU)

Assuntos

RESUMO

Data Mining techniques play an important role in the prediction of soil spatial distribution in systematic soil surveying, though existing methodologies still lack standardization and a full understanding of their capabilities. The aim of this work was to evaluate the performance of preprocessing procedures and supervised classification approaches for predicting map units from 1:100,000-scale conventional semi-detailed soil surveys. Sheets of the Brazilian National Cartographic System on the 1:50,000 scale, Dois Córregos (Brotas 1:100,000-scale sheet), São Pedro and Laras (Piracicaba 1:100,000-scale sheet) were used for developing models. Soil map information and predictive environmental covariates for the dataset were obtained from the semi-detailed soil survey of the state of São Paulo, from the Brazilian Institute of Geography and Statistics (IBGE) 1:50,000-scale topographic sheets and from the 1:750,000-scale geological map of the state of São Paulo. The target variable was a soil map unit of four types: local soil unit name and soil class at three hierarchical levels of the Brazilian System of Soil Classification (SiBCS). Different data preprocessing treatments and four algorithms all having different approaches were also tested. Results showed that composite soil map units were not adequate for the machine learning process. Class balance did not contribute to improving the performance of classifiers. Accuracy values of 78 % and a Kappa index of 0.67 were obtained after preprocessing procedures with Random Forest, the algorithm that performed best. Information from conventional map units of semi-detailed (4th order) 1:100,000 soil survey generated models with values for accuracy, precision, sensitivity, specificity and Kappa indexes that support their use in programs for systematic soil surveying.

Assuntos

RESUMO

The application of quantitative methods to digital soil and geomorphological mapping is becoming an increasing trend. One of these methods, Geomorphons, was developed to identify the ten most common landforms based on digital elevation models. This study aimed to make a quantitative assessment of the relationships between Geomorphons units, determined at three spatial resolutions and nine radii, and soil types and properties of two watersheds with different soil-landscape relationships in Brazil to help soil surveying and mapping under tropical conditions. The study was conducted at Lavrinha Creek (LCW) and Marcela Creek (MCW) watersheds, located in the state of Minas Gerais, Brazil. Spatial resolutions of 10, 20 and 30 m were the basis for generating Geomorphons at 9 radii of calculation for the watersheds. They were overlapped to detailed soil maps of the watersheds and a chi-square test was carried out to assess their relationship with soil types. Observation points were compared with the most highly correlated Geomorphons to also assess relationships with soil properties. Geomorphons with resolution of 30-m and radii of 20 and 50 cells, respectively for LCW and MCW, were more highly correlated with the variability of soil types, in accordance with the terrain features of these watersheds. The majority of observation points for each soil type was located in the same Geomorphon unit that was dominant when analyzing soil maps. There was less variability in soil properties between Geomorphon units, which was probably due to the highly weathered-leached stage of soils. Geomorphons can help to improve soil maps in tropical conditions when assessing soil variability due to its high correlation with tropical soil types variability.(AU)

Assuntos

RESUMO

The application of quantitative methods to digital soil and geomorphological mapping is becoming an increasing trend. One of these methods, Geomorphons, was developed to identify the ten most common landforms based on digital elevation models. This study aimed to make a quantitative assessment of the relationships between Geomorphons units, determined at three spatial resolutions and nine radii, and soil types and properties of two watersheds with different soil-landscape relationships in Brazil to help soil surveying and mapping under tropical conditions. The study was conducted at Lavrinha Creek (LCW) and Marcela Creek (MCW) watersheds, located in the state of Minas Gerais, Brazil. Spatial resolutions of 10, 20 and 30 m were the basis for generating Geomorphons at 9 radii of calculation for the watersheds. They were overlapped to detailed soil maps of the watersheds and a chi-square test was carried out to assess their relationship with soil types. Observation points were compared with the most highly correlated Geomorphons to also assess relationships with soil properties. Geomorphons with resolution of 30-m and radii of 20 and 50 cells, respectively for LCW and MCW, were more highly correlated with the variability of soil types, in accordance with the terrain features of these watersheds. The majority of observation points for each soil type was located in the same Geomorphon unit that was dominant when analyzing soil maps. There was less variability in soil properties between Geomorphon units, which was probably due to the highly weathered-leached stage of soils. Geomorphons can help to improve soil maps in tropical conditions when assessing soil variability due to its high correlation with tropical soil types variability.

Assuntos

RESUMO

Hillslope curvatures are associated with specific environments that correlate to chemical and mineralogical attributes of soil, so determining specific management zones. Phosphorus is one of the main limiting factors to the development and longevity of sugarcane. The type and the mineralogical constitution of the clay fraction play an important role in the phosphorus (P) adsorption of soil. High proportion of gibbsite (Gb) in soil may be the major responsible for P adsorption. The relationships among spatial variability as a function of hillslope curvature, the proportion of kaolinite (Kt) and Gb, and phosphorus adsorption were evaluated in an Alfisol cultivated with sugarcane. Two plots of 1 ha of a concave and a convex hillslope area were selected and 121 samples were collected in each area. The maximum P adsorption was determined in six samples taken randomly in each area. Data were submitted to descriptive statistical and geostatistical analysis. The lowest average values of available phosphorus were found in the convex area. In this area, the proportion of gibbsite, expressed by the values of the ratio [Gb/(Gb + Ct)] and the values of maximum adsorption capacity of phosphorus were higher than in the concave area.

As curvaturas do relevo promovem pedoambientes específicos que condicionam os atributos químicos e mineralógicos do solo e podem auxiliar na definição de zonas específicas de manejo. O fósforo (P) é um dos principais elementos limitantes ao desenvolvimento e longevidade do canavial. O teor e a constituição mineralógica da fração argila assumem papel importante na disponibilidade do P, sendo que a gibbsita (Gb), quando presente em altas proporções no solo, pode ser a principal responsável pela sua adsorção e indisponibilidade. Investigaram-se as relações e a variabilidade espacial da adsorção de P e a ocorrência de caulinita (Ct) e gibbsita na fração argila de um Argissolo Vermelho-Amarelo eutrófico originado de rochas areníticas sob diferentes curvaturas do relevo em área sob cultivo de cana-de-açúcar. Duas malhas de 1 ha foram delimitadas numa área côncava e outra área convexa. Foram coletadas 121 amostras em cada área para realização das análises granulométricas, químicas e mineralógicas. A capacidade máxima de adsorção de P foi obtida em seis amostras escolhidas ao acaso em cada área. Os resultados foram submetidos às análises estatísticas descritiva e geoestatística. Os menores valores médios de P disponível encontraram-se na área convexa. Nesta área, a proporção de gibbsita, expressa pelos valores da razão [Gb/(Gb+Ct)] e os valores de capacidade máxima de adsorção de fósforo foram maiores do que na área côncava.

RESUMO

Hillslope curvatures are associated with specific environments that correlate to chemical and mineralogical attributes of soil, so determining specific management zones. Phosphorus is one of the main limiting factors to the development and longevity of sugarcane. The type and the mineralogical constitution of the clay fraction play an important role in the phosphorus (P) adsorption of soil. High proportion of gibbsite (Gb) in soil may be the major responsible for P adsorption. The relationships among spatial variability as a function of hillslope curvature, the proportion of kaolinite (Kt) and Gb, and phosphorus adsorption were evaluated in an Alfisol cultivated with sugarcane. Two plots of 1 ha of a concave and a convex hillslope area were selected and 121 samples were collected in each area. The maximum P adsorption was determined in six samples taken randomly in each area. Data were submitted to descriptive statistical and geostatistical analysis. The lowest average values of available phosphorus were found in the convex area. In this area, the proportion of gibbsite, expressed by the values of the ratio [Gb/(Gb + Ct)] and the values of maximum adsorption capacity of phosphorus were higher than in the concave area.

As curvaturas do relevo promovem pedoambientes específicos que condicionam os atributos químicos e mineralógicos do solo e podem auxiliar na definição de zonas específicas de manejo. O fósforo (P) é um dos principais elementos limitantes ao desenvolvimento e longevidade do canavial. O teor e a constituição mineralógica da fração argila assumem papel importante na disponibilidade do P, sendo que a gibbsita (Gb), quando presente em altas proporções no solo, pode ser a principal responsável pela sua adsorção e indisponibilidade. Investigaram-se as relações e a variabilidade espacial da adsorção de P e a ocorrência de caulinita (Ct) e gibbsita na fração argila de um Argissolo Vermelho-Amarelo eutrófico originado de rochas areníticas sob diferentes curvaturas do relevo em área sob cultivo de cana-de-açúcar. Duas malhas de 1 ha foram delimitadas numa área côncava e outra área convexa. Foram coletadas 121 amostras em cada área para realização das análises granulométricas, químicas e mineralógicas. A capacidade máxima de adsorção de P foi obtida em seis amostras escolhidas ao acaso em cada área. Os resultados foram submetidos às análises estatísticas descritiva e geoestatística. Os menores valores médios de P disponível encontraram-se na área convexa. Nesta área, a proporção de gibbsita, expressa pelos valores da razão [Gb/(Gb+Ct)] e os valores de capacidade máxima de adsorção de fósforo foram maiores do que na área côncava.