Brazilian Soil Classification System Research Articles

A new frontier of archaeological dark earth at the northern Amazonia headwaters of Roraima state: Soil attributes and landscape interplays

Despite the existence of various studies on Archaeological Dark Earth - ADE, there is still a very large gap concerning the Amazon region, with many areas remaining unexplored scientifically. The aim of this study, therefore, was to characterize and classify areas of Archaeological Dark Earth located on rural properties and in one riverside community in the southern mesoregion of the state of Roraima. At these locations, trenches were dug in a total of 13 areas, and the profiles morphologically characterized and sampled for soil classification and Carbon-14 dating. The areas were georeferenced and measured, and the history of land use was described, together with the predominant vegetation in the region. The following physical analyses were carried out: texture and bulk density. The chemical analysis consisted of pH in water and KCl, exchangeable cations, exchangeable Al, available P, titratable acidity (H + Al), total N and organic matter. To produce the maps, computational processing was used in a Geographic Information System - GIS, employing geoprocessing tools with the aid of the ArcGIS v10.6 software; the attributes prepared from SRTM images were drainage network and terrain. Using the Brazilian System of Soil Classification (SiBCS), the profiles were classified as: Argissolos Amarelos, Cambissolo Háplico, Latossolos Amarelos, Argissolo Vermelho Amarelo, and Nitossolo Vermelho. It is suggested that the anthropogenic subgroup be included in the SiBCS. With the exception of 3 horizons, the anthropogenic horizon of each of the profiles sampled in the region has a eutrophic character, with ages that range from 1120 to 1864 years before present (YBP). Each of the areas of ADE is associated with a drainage network ranging from a small creek, approximately 6m wide, to a fast-flowing river, such as the Branco River, which is over 1,700m wide. The 13 areas are located in places away from the flood area that show little variation in relief, with a predominance of flat to gently undulating terrain.

Rapid Determination of Soil Horizons and Suborders Based on VIS-NIR-SWIR Spectroscopy and Machine Learning Models

In an effort to improve the efficiency of soil classification, traditional methods are being combined with analytical and computational techniques. This integration has strengthened the connection between conventional classification and the application of machine-learning (ML) models to interpret soil spectral reflectance data. Due to the time and computational cost, several studies are limited to testing the classification performance of a few algorithms and do not always explore the best parameters for model optimization. The study aims to assess the efficiency of combining soil spectral reflectance with prevalent ML models for classifying pedogenetic horizons and soil suborders, enhancing traditional classification methods. We collected seven soil monoliths, previously classified according to the Brazilian Soil Classification System (SiBCS) and soil taxonomy. Using the ASD Fieldspec spectroradiometer, we obtained spectral reflectance samples along each monolith (n = 800 per monolith) to classify horizons and n = 5600 for suborder classification. Spectral fingerprints were obtained and explored by Principal Component Analysis (PCA). The spectral data were subdivided into training (70%) and test (30%) sets and submitted to the Logistic Regression (LR), Artificial Neural Network (NN), Support Vector Machine (SVM), Random Forest (RF), and Gradient Boosting (GB) models for the classification of horizons and suborders, considering the model’s adjustment parameters. Accuracy and F-Score were used to verify the performance of the models. There was a significant influence of particle size and soil organic carbon on the spectral fingerprint of the soils. The PCA indicated that topsoil horizons clustered in most of the monoliths analyzed, while most of the subsoil horizons showed data overlap. The NN model showed the highest accuracy in the classification of horizons (97%), while the SVM showed the lowest performance (52% accuracy). The classification of soil suborders presented accuracies between 95% and 98%. Therefore, our study concludes that spectral data combined with ML models can enhance the discrimination and classification of soil horizons and suborders, improving upon traditional methods.

Pedogenesis and landscape evolution of Calcisols on Quaternary carbonatic sediments of Fernando de Noronha and Trindade volcanic islands, South Atlantic

Carbonate-rich soils are found in different materials, climates, and environments, and are generally characterized by alkaline pH values and high base saturation, dominated by exchangeable Ca2+. Fernando de Noronha and Trindade volcanic islands, in South Atlantic, register carbonate-rich soils on bioclastic sediments at coastal areas. This study aims to investigate the pedogenic evolution of these soils associated with landscape processes. Six profiles were described and sampled, four of which located on bioclastic sediments (PN1, PN2, PT1, and PT2), one on Quaternary fluvial sediments (PN3), and one developed on calcarenites overlying ankaratrite flows (PN4). Morphological, physical, chemical, mineralogical, micromorphological and microchemical investigations were carried out, and principal component (PCA) and statistical analyses were applied to all data. The soils were classified as Calcisols, Fluvisol, and Cambisol and the results suggest that the carbonatic parent material and local climate are the main drivers of soil genesis, subordinated by biogenic and landform processes. All profiles have high exchangeable Ca2+, base saturation, pH, CaCO3 equivalent, and total Ca content, with calcite and aragonite minerals. Pedogenic carbonates features occur in all soil, being more developed in Fernando de Noronha Calcisols, and partially dissolved in Trindade Calcisols. The contrasting landscape and climate evolution between these islands explain these differences. Hence, these insular Calcisols are products of varying pedological evolution, with Holocene paleoclimates as the main factor of differentiation. Our results indicate the adoption of “bioclástico-carbonático” sub-group for Calcisols and Fluvisols from Fernando de Noronha, proposing the inclusion of “bioclástico-chernossólico” sub-group in the Brazilian Soil Classification System.

Atributos físicos, químicos e caracterização morfológica de solos na cidade de Cáceres - Mato Grosso

As crescentes intervenções no solo em decorrência da ocupação e atividades humanas, tem gerado impactos e alterações nas dinâmicas naturais a partir de processos de degradação ambiental que, potencialmente, podem ser irreversíveis. Nesse sentido, o presente estudo objetivou caracterizar os atributos físicos, químicos e morfológicos de perfis de solo em Cáceres – Mato Grosso tendo em vista importantes transformações em seus sistemas ambientais com a expansão do perímetro urbano e tipologias de uso ao longo dos anos. Para tanto, foram caracterizados nove perfis distribuídos nas áreas central, intermediárias e periféricas do perímetro urbano bem como a coleta de amostras de seus respectivos horizontes e/ou camadas. Foram realizadas análises laboratoriais dos aspectos químicos e físicos e a descrição morfológica de acordo com a Embrapa e o Sistema Brasileiro de Classificação de Solos. Os solos analisados são pertencentes as classes dos Latossolos, Gleissolos e Plintossolos. Contudo, ressalta-se a presença de materiais exógenos e notáveis alterações em alguns perfis, fruto da ocupação antrópica associado a remobilização de materiais e a expansão urbana. Na maioria dos perfis estudados foi possível verificar as diferenciações entre as camadas de origem antrópica e os horizontes dos solos a quais estas estão dispostas. Dessa forma, considera-se a efetiva participação do homem nos processos ambientais com impactos na pedogênese local. O presente estudo possibilitou discussões iniciais a respeito dos solos urbanos considerando que a mesma ainda é escassa no estado de Mato Grosso, ao revelar uma carência desse tipo de abordagem. Portanto, destaca-se a necessidade de conhecer minunciosamente a distribuição e os atributos físicos, químicos e morfológicos dos solos urbanos juntamente com os possíveis efeitos das dinâmicas ambientais e sociais sobre o ambiente e na organização das cidades no que diz respeito a infraestrutura, expansão e tipologias de uso.Palavras-chave: Classificação de solos, Solos Urbanos, Intervenções, Alterações. Physical-chemical attributes of soils in the city of Cáceres - Mato Grosso A B S T R A C TIncreasing soil interventions due to occupation have generated impacts and changes leading to changes in the natural profile of soils. This research aims to identify and analyze the physical, chemical and morphological attributes in the city of Cáceres – Mato Grosso. The study was conducted in the urban perimeter of the city, where samples were collected in nine representative profiles distributed in the central, intermediate and peripheral areas of the center. Laboratory analyzes of chemical and physical aspects and morphological description were performed according to Embrapa and the Brazilian Soil Classification System. The soils found belong to the classes of Latossolos, Gleissolos and Plintossolos. We highlight the presence of exogenous materials and notable alterations resulting from anthropic occupation.Keywords: Soil Classification, Urban Soils, Interventions and Alterations.

SPATIAL AUTOCORRELATION OF PHYSICAL ATTRIBUTES OF AN OXISOL

Studies that seek to identify a smaller number of soil attributes that represent others can generate less expenditure of time and financial resources for monitoring cultivated areas. Thus, this study aimed to analyze the spatial distribution and spatial autocorrelation of physical attributes of an Oxisol (Latossolo Vermelho Amarelo, Brazilian Soil Classification System). The evaluated attributes consisted of soil density (SD), total porosity (TP), free porosity (FP), field capacity (FC), permanent wilt point (PW), and total water availability (TW). Semivariogram adjustments and semivariance estimates were performed to characterize the structure and magnitude of the spatial dependence of soil attributes. The attributes were distributed on thematic maps and the spatial autocorrelation was estimated by the Moran index, which quantifies the degree of autocorrelation. TP showed a high positive correlation with PWP. Soil TW showed a high positive correlation with SD and a high negative correlation with FP. In turn, FP showed a high negative correlation with SD. The results showed spatial dependence for all attributes, standing out the apparent soil density and permanent wilt point, which were good evaluators of strong spatial dependence.

Characterization and classification of soils from an Amazonic Biome in western Pará

Despite its great soil diversity, the Amazon Biome still lacks pedological studies that would also contributes to the Brazilian Soil Classification System. Based on this, this study aimed to characterize and classify the soils from an area in western Pará state. Six soil profiles were described and collected, characterized both physically and chemically, and then classified according to the Brazilian Soil Classification System. There were soils with anthropic influence with thick superficial horizons, with high levels of organic carbon, Ca2+, Mg2+ and P, differing from the observed pattern concerning non-anthropized soils. A great variability of texture was also observed due to the nature of parental material. A high weathering degree was found in the Entisols located in the floodplain area, with low activity clays and low base saturation. Due to observing a superficial diagnostic anthropic horizon A in “Cambissolos Háplicos” and “Húmicos” profiles, it is suggested to create the “antrópico” (anthropic) subgroup for these soil classes in the Brazilian Soil Classification System.

Suscetibilidade à erosão hídrica do solo: bacia hidrográfica do rio Capim (MA-PA)

The objective of this study was to analyze the sustainability to water erosion in the Capim river/PA-MA. Acquired precipitation (GPCC), slope (TOPODATA project), land use and land cover data (MapBiomas) and pedology (Brazilian Soil Classification System) were obtained. Based on these variables, in a Geographic Information System environment, the product representing the sustainability to soil water erosion was generated. A sustainability gradient for soil water erosion was observed in the SE-NW direction, where it was higher near the mouth of the Capim River. The other variables were: clinical component presenting predominance of stability and high sustainability in the south of the basin; land use influences the entire axis of the basin, indicating instability in the medium-low Capim and in the extreme southeast. It was observed that the sustainability to erosion in the Capim watershed is motivated by intensified land use near the mouth. The zoning carried out in the basin is a warning sign for the municipalities of São Domingos do Capim, Rondon do Pará and Goianésia do Pará.

Biogenic structures in soils under a primary Atlantic Rain Forest in SE-Brazil

As minhocas desempenham papeis importantes na formação do solo, contudo pouca atenção é dada à bioturbação pelos pedólogos. A descrição morfológica tradicional, assim como os procedimentos de caracterização física e química do solo, não contemplam as estruturas biogênicas, que nem mesmo são consideradas pelo Sistema Brasileiro de Classificação de Solos. O objetivo deste trabalho foi caracterizar as feições biogênicas como canais, câmaras e dejeções, produzidas pela atividade de minhocas no solo da Estação Biológica de Boracéia, em São Paulo. As bioestruturas foram coletadas, medidas, fotografadas e organizadas por tipo (cilíndricos e blocos irregulares) e tamanho (muito pequeno, pequeno, médio, grande e muito grande). Foram realizadas análises físicas e químicas destes materiais e do solo: granulometria, carbono orgânico, bases trocáveis (Ca2+, Mg2+, K+, P). Alguns canais biogênicos encontravam-se preenchidos por solo revolvido (as crotovinas) e outros não. As características redoximórficas são muito comuns nas paredes dos canais, porque esses dutos biogênicos contribuem para a difusão de O2 do solo e a remoção de CO2 no perfil. As dejeções têm textura arenosa, o conteúdo de carbono orgânico nelas é três vezes superior comparado ao da matriz do solo, indicando a eficiência de certos grupos ecológicos de anelídeos na incorporação de matéria orgânica em subsuperfície. Os coprólitos também apresentaram maiores quantidades de fósforo, cálcio e magnésio do que o solo. As minhocas cumprem funções fundamentais no solo, como aeração, agregação, incorporação de matéria orgânica e aumento de sua fertilidade. Portanto, os agregados biogênicos influenciam fortemente na pedogênese, especialmente na zona tropical.

Calcination as an alternative method to classify Spodosols on the second categorical level

The classification of Spodosols on the second categorical level (suborder), according to the Brazilian Soil Classification System (SiBCS), is done by observing the colors of genetic horizons in the field. The presence or absence of iron oxides is the main factor for this classification, and the color of the horizon is the criterion currently adopted. However, the simple observation of color in the field can be mistaken and cause an error in the definition of the second categorical level. [...]

Identification and quantification of iron oxides by diffuse reflectance spectroscopy with Praying Mantis accessory and integration sphere

Soil color is one of the main attributes used in the Brazilian System of Soil Classification and is related to the presence and concentration of iron oxides. This work aimed to identify and quantify the iron oxides (hematite, goethite and maghemite) present in soils and synthetic minerals and compare the diffuse reflectance spectroscopy (DRS) data equipped with the Integration Sphere (DRS-IS) or the Praying Mantis (DRS-PM) accessories with reference values obtained by XRD. Four samples of synthetic iron oxides (hematite, goethite, maghemite, magnetite) and two samples of aluminosilicates (kaolinite and smectite) were selected along with the A and Bw Horizons from 6 Oxisols of the State of Paraná-Brazil. The soils were characterized on their physical and mineralogical attributes and organic carbon content. All minerals, soil samples, soils clay fractions treated and not treated with the boiling 5 M NaOH procedure and with 1.8 M H2SO4 were analyzed using the integration sphere, the Praying Mantis accessory and color determined in the Munsell scale using a Minolta CR 400 spectroradiometer. The DRS-PM, by means of the second derivative of Kubelka-Munk function was very promising for identification and quantification of hematite for presenting results close to those obtained by XRD. Otherwise, the quantification of goethite was overestimated in both DRS's measurements due to the presence of organic matter. It was not possible to identify and quantify the presence of maghemite in soils and mixture minerals samples using both DRSs accessories due to the superposition of secondary bands of goethite, hematite, and the magnetite on the maghemite spectrum. The presence of maghemite in the soil material induces an overestimation of hematite content by DRS. The estimation of the Hm/(Hm + Gt) and Gt/(Gt + Hm) ratios by both accessories presented good correlation with data obtained by XRD.

Tropical soil order and suborder prediction combining optical and X-ray approaches

Proper soil taxonomic classification makes a significant contribution toward sustainable soil management, decision making, and soil conservation. For that, a quick, environmentally-friendly, non-invasive, cost-effective and reliable method for soil class assessment is desirable. As such, this study used NixPro color and portable X-ray fluorescence (pXRF) data to characterize seven different soil orders in Brazilian tropical soils, exploring the ability of three machine learning algorithms [Support Vector Machine with Linear Kernel (SVMLK), Artificial Neural Network (ANN), and Random Forest (RF)] with and without Principal Component Analysis (PCA) pretreatment for prediction of different soils at the order and suborder taxonomic levels under both dry and moist conditions. In total, 734 soil samples were collected from surface and subsurface horizons encompassing twelve suborders. The soil profiles were morphologically described and taxonomy classified per the Brazilian Soil Classification System and the approximate correspondence was made with the US Soil Taxonomy. Soil samples were separated into modeling (70%) and validation (30%) sub-datasets, overall accuracy and Cohen's Kappa coefficient evaluated model quality. Models generated from B horizon sample with pXRF and NixPro (moist samples) data combined delivered the best accuracy for order (81.19% overall accuracy and 0.71 Kappa index) and suborder predictions (74.35% overall accuracy and 0.65 Kappa index) through RF algorithm without PCA pretreatment. Summarily, the use of these two portable sensor systems was shown effective at accurately predicting different soil orders and suborders in tropical soils. Future works should extend the results of this study to temperate regions to corroborate the conclusions presented herein.

Pedon Characterization in the Caatinga Biome Area in Chapada Apodi, RN, Brazil

The Apodi Plateau is a Brazilian with important agricultural activity, which is located between the states of Ceará and Rio Grande do Norte, in an area of the Caatinga biome. Therefore, this work was developed to characterize the morphological, physical, chemical and mineralogical attributes of soil profiles of this region. For this purpose, trenches were open in three areas in the Tabuleiro Grande Settlement Project, in the municipality of Apodi, RN, Brazil. The profiles were described in the field and samples of the horizons were collected for physical, chemical and mineralogical analyzes. The profiles were classified up to the fourth categorical level and correlated with Soil Taxonomy.According to the Brazilian Soil Classification System, the soils studied were Vertissolo Háplico Órtico chernossólico (Mollisols), Chernossolo Rêndzico Petrocálcico típico (Mollisols) e Vertissolo Háplico Órtico chernossólico (Vertisols).

Physical Indicators of Cambisols Under Agricultural Uses in Chapada do Apodi, Semiarid Region of Brazil

Soil physical structure is related to porous space dynamics, which is affected by pedogenetic conditions, land uses, and agricultural practices. Thus, the objective of this work was to evaluate physical and structural attributes of Cambissolos under different uses in the Terra de Esperança Settlement Project, in Chapada do Apodi, Governor Dix-Sept Rosado, Rio Grande do Norte, Brazil, and detect the most sensitive attributes for the distinction of environments using multivariate analysis. The study areas with different land uses were: Native Forest Area 1 (NFA1), Native Forest Area 2 (NFA2), Native Forest Area 3 (NFA3) (reference areas), Conventional Management Area (CMA) Agroecological Area (AEA), and Cajaraneira (Spondia sp.) Orchard Area (COA). Areas with agricultural uses were characterized through physical and structural analyses, using disturbed and undisturbed soil samples collected from their 0.00-0.10, 0.10-0.20, and 0.20-0.30 m soil layers. The soil classes of the areas, according to the Brazilian Soil Classification System (SiBCS) were Cambissolo Haplico Carbonatico vertissolico (NFA1); Cambissolo Haplico Ta Eutrofico tipico (NFA2 and COA); Cambissolo Haplico Ta Eutrofico vertissolico (NFA3); and Cambissolo Haplico Carbonático tipico (CMA and AEA). The results of the attributes analyzed were expressed as mean of three replications per soil layer of each area, using multivariate analysis. Soil textures varied from sandy clay loam to clay. The total sand fraction presented negative correlations with clay dispersed in water, gravimetric moisture (GM), volumetric moisture (VM), total porosity determined (TPd) and microporosity (MiP); and positive correlations with soil density (SD), and basic infiltration rate (BIR), denoting pedogenetic influence. The SD presented significant correlation with GM, VM, TPd, MiP, macroporosity (MaP), aeration porosity (AP) and BIR, denoting its importance for the physical structure of the soil, and its dynamics. The most relevant attributes for the discrimination of the soil physical structure were the inorganic fractions clay and sand, porosity, degree of flocculation, aggregates, and soil mechanical resistance to penetration. The physical and structural attributes of the Cambissolos Haplicos were generally preserved, when compared to the current conditions of the NFAs, despite the different land use and managements. However, the soils of NFA1 (0.20-0.30 m layer), CMA, and AEA areas indicate fragility in aggregate stability and degree of flocculation due to the predominance of the sand fraction. The COA presented more favorable physical and structural conditions to the development of agricultural crops, especially on the surface layers, mostly influenced by their clay, TPd, AP, GM, VM, and soil mechanical resistance to penetration.

Revealing Tropical Technosols as an Alternative for Mine Reclamation and Waste Management

This study was based on the premise that Technosols constructed under tropical conditions are a valuable tool for inexpensive mine reclamation programs. These anthropogenic soils are still poorly studied in Brazil and are not recognized by the Brazilian Soil Classification System. Given the importance of mining to the Brazilian economy (the sector accounts for 20% of all products exported and 5% of the gross domestic product), there is an urgency to properly manage the large amount of waste produced. For this purpose, we suggest the use of Technosols as a strategy to overcome both land degradation and waste production by presenting a successful case of mine rehabilitation combining limestone wastes and tropical grasses. We show that Technosols constructed from the mine spoils can develop into soils suitable for agriculture in a few years, promoting land reclamation and producing food and energy. These soils are also valuable resources that can provide important ecosystem services, such as organic carbon storage.

Soil macrofauna associated with cover crops in an Oxisol from the southwest of Piauí state, Brazil

ABSTRACT: The soil macrofauna is fundamental for the maintenance of soil quality. The aim of this study was to characterize the soil macrofauna under different species of cover crops, including monoculture or intercropping associated to two types of soil management in the southwest region of Piauí state. The study was carried out in an Oxisol (Latossolo Amarelo, according to Brazilian Soil Classification System) in the municipality of Bom Jesus, Piauí, distributed in 30 m2 plots. Testing and evaluation of the soil macrofauna were conducted in a 9 × 2 strip factorial design, with combinations between cover crops/consortia and soil management (with or without tillage), with four replications. Soil monoliths (0.25 × 0.25 m) were randomly sampled in each plot for macrofauna at 0‒0.1, 0.1‒0.2, and 0.2‒0.3 m depth, including surface litter. After identification and counting of soil organims, the relative density of each taxon in each depth was determined. The total abundance of soil macrofauna quantified under cover crops in the conventional and no-tillage system was 2,408 ind. m-2, distributed in 6 classes, 16 orders, and 31 families. The results of multivariate analysis show that grass species in sole cropping systems and no-tillage presents higher macrofauna density, in particular the taxonomic group Isoptera. No-tillage also provided higher richness of families, where Coleoptera adult were the second more abundant group in no-tillage and Hemiptera in conventional tillage.

Semi-detailed survey of soils of Ceará’s semiarid region: Lavoura Seca Experimental Farm

The semiarid region of northeastern Brazil has more than 53 million inhabitants who depend, directly or indirectly, on the resources that the region offers. Among these resources, the soil is highlighted as one of the most important. Due to the importance attributed to the knowledge on the pedological and morphological characteristics of the soils of the Brazilian northeastern semiarid region, the aim of this study was to identify and characterize the different soil classes on the Lavoura Seca Experimental Farm, in the municipality of Quixada, Ceara, Brazil, through the traditional method of soil mapping. The selected site is located in the municipality of Quixada, Ceara, with a total extension of approximately 190 hectares. A regular grid of 200 m x 200 m was established to determine the sampling sites, totaling 47 collection points. The soil samples were collected with an auger at depths of 0-20, 40-60 and 80-100 cm, and the chemical and granulometric analyses were then carried out to select the pit opening sites and classify the units according to the Brazilian Soil Classification System (SIBCS). The predominant soil classes in the study area were: Neossolos Litolicos Eutroficos tipicos (59.4%), Planossolos Haplicos Eutroficos tipicos (20.4%), Argissolos Vermelhos Eutroficos tipicos and abrupticos (15.9%) and Luvissolos Cromicos Orticos tipicos (4.3%). Differences in parent material, relief and climate were the main influencing factors for the occurrence of a diversity of soil classes in the studied area, which shows large extensions of young and shallow soils, as well as evolved and deep soils.

Multi-temporal bare surface image associated with transfer functions to support soil classification and mapping in southeastern Brazil

Detailed soil maps are essential for agricultural management, but they are scarce in many regions. Even with the recent development of digital soil mapping (DSM) strategies, providing an adequate spatial representation of soils is still a challenging task. Therefore, this work aims to define a DSM approach, which combines proximal and remote sensing data to describe the spatial variation of soil attributes and types. The study was carried out in a site at southeastern Brazil, where 326 sampling points were defined and collected at two depths. Soil Vis-NIR spectra and physico-chemical attributes were measured in laboratory. A bare surface synthetic image (SYSI) was created from multi-temporal Landsat images and later validated with lab. spectra. Geographically weighted regression was used to calibrate depth transfer functions, which were applied to SYSI, generating a subsurface soil synthetic image (SYSIsub). Soil attributes at both depths were mapped with SYSI, SYSIsub and terrain derivatives. A soil classification key was designed following the Brazilian Soil Classification System and boolean logic. Soils were classified based on the soil attributes maps and boolean key. Hence, Monte-Carlo simulation (MCS) was performed to evaluate the error propagation from predicted attribute maps to soil types map. Correlations between satellite and lab. spectra varied from 0.68 to 0.8, indicating good capacity of SYSI in retrieving bare soil reflectance. Depth transfer functions also had good performance, with R2 ranging from 0.62 to 0.72. The soil attribute maps with best performance were clay content (R2 = 0.63), iron concentration (R2 = 0.72) and soil color (hue R2 = 0.57; value R2 = 0.73; chroma R2 = 0.63). Soil organic matter and chemical attributes were poorly predicted, with R2 between 0.12 and 0.38. MCS indicated that uncertainties in attributes maps might result in confusion between Ferralsols and Acrisols, Regosols and Luvisols, as well as Luvisols and Acrisols. Comparison between digital and conventional maps of soil classes, presented satisfactory kappa (34.65%) and global accuracy (54.46%). The technique presents an improvement to DSM, as it integrates soil sensing and depth transfer functions into DSM.

Preprocessing procedures and supervised classification applied to a database of systematic soil survey

ABSTRACT: 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 Corregos” (“Brotas” 1:100,000-scale sheet), “Sao 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 Sao 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 Sao 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.

Soils characterization and classification in clean field, dirty field and forest areas in amazonian environments

The soil and vegetation characteristics of the southern Amazonas region include highly weathered soils, high aluminum content and some hydromorphic conditions, its vegetation is composed from grasslands to small isolated trees and forest galleries along the rivers streams. In this way, this work aims to characterize and classify the soil in areas of clean field, dirty field, and forest in Humaitá region AM. Soil trenches were opened in the clean field, dirty field, and forest environments, soil profiles were morphologically characterized, and samples were collected from their horizons. Physical analysis of texture, dispersed clay in water, flocculation, bulk density, particle density and porosity were performed. The chemical analyzes included pH and KCl in water; Ca, Mg, K, Al, and; available P; H+Al and organic C; SiO2, Al2O3 and Fe2O3 sulfuric attack. The soils were classified according to criteria established by the Brazilian System of Soil Classification and Soil Taxonomy. The forest, dirty field (high) and clean field (low) showed different soil types, Typic Dystrudept for the first two environments and Typic Fluvaquents for last. Multivariate techniques expressed the similarity relations presenting between the different environments studied, characterizing, which are of great importance in the relation landscape-soil studies.

PEDOGENESIS ON COASTAL TABLELANDS AREA WITH LOW RANGE ALTIMETRY IN PARAÍBA STATE

ABSTRACT Small variations of relief may change drainage and runoff and hence promote the formation of sandy surface horizons and hardened subsurface horizons (fragipans and/or duripans) in Coastal Tablelands soils. This study aimed to investigate the pedogenesis on Coastal Tablelands area with low range altimetry in Paraíba state; secondly, we also sought to contribute to the improvement of the Brazilian Soil Classification System (BSCS). Four soil profiles ware described and collected to be submitted to routine physical and chemical analysis, determination of Fe, Al and Si extracted by sulfuric acid digestion, sodium citrate-bicarbonate-dithionite and acid ammonium oxalate, sodium pyrophosphate, and mineralogical analysis in the sand and clay fractions by X-ray diffractometry. Optical density of the oxalate extract (ODOE) was also determined; the results were statistically evaluated using the R software. Microrelief variations conditioning differentiated water flows, along with the sandy texture of the surface horizons (A and E) and the lower coarse sand/fine sand ratio in the subsurface horizon, seem to promote clay accumulation in depth in the Spodosols developed on Coastal Tablelands environments. For this soils, the argilluvic (argissólico) character at the subgroup level of the BSCS should be incorporated. In addition, Al amorphous mineral phases and/or poorly crystalline play an important role in the formation of strongly cemented horizons (duripans) of the Spodosols, as also reported by other authors. Finally, the ODOE showed to be an efficient indicator of soils under podzolization process, being possible its use as a taxonomic criterion for classification of Spodosols by the BSCS.