Spectral behavior of some modal soil profiles from São Paulo State, Brazil.

O sensoriamento remoto representa um importante potencial na avaliação do ambiente, contudo, ainda existe a necessidade de entender melhor as relações entre atributos do solo e dados espectrais. O objetivo do trabalho foi analisar descritivamente o comportamento espectral de alguns perfis de solos da região de Piracicaba, Estado de São Paulo, utilizando o espectrorradiômetro de laboratório (400 a 2500 nm). Procurou-se ainda, avaliar as relações entre energia eletromagnética refletida com atributos químicos, físicos e mineralógicos dos solos, verificando as variações espectrais das amostras ao longo dos perfis e suas relações com classificação e discriminação dos solos. Observou-se que solos mais arenosos refletiram mais, com curvas espectrais de aspecto ascendente, ao contrário dos solos argilosos. A banda centrada em 1900 nm discriminou solos com mineralogia 2:1 dos de 1:1 e oxídicos. Foi possível detectar a presença de caulinita, gibbsita e dos óxidos de ferro (hematita e goethita) presentes nos solos pelos aspectos descritivos das curvas, feições de absorção e intensidade de reflectância; e que existe uma relação entre níveis de intemperismo e informações espectrais. A avaliação dos dados espectrais de amostras dos horizontes superficiais e subsuperficiais permitiu caracterizar e discernir a variabilidade analítica do perfil, auxiliando na discriminação e classificação dos solos

Determinação da cor do solo a partir de dados radiométricos e sua relação com teores de hematita.

Color is widely recognized as a primary identifying parameter of soil. The physical, mineralogical, and chemical properties can be derived from assessing the subsurface color characteristics. The present research aimed to estimating the hematite content clay fraction, in laboratory, from data related to soil color obtained by using automatic devices. Fifteen subsurface soil samples from São Paulo State had their clay fraction hematite contents semiquantitavely determined by the association of chemical and physical methods and their colors evaluated in laboratory through measurements made with a spectro-radiometer. The radiometric data were used to the determination of soil color in L*a*b* and Munsell systems and to the calculation of reddish indexes (RI). The RI values show functional dependence of hematite contents and the best relation is verified with RI values derived from color determined in the L*a*b* system. Exponential models, developed from remote sensors, show themselves adequate in predicting the soil hematite contents

Características físicas, químicas e mineralógicas de uma catena de solos sobre folhelho

Four soils on a shale catena were studied in Sete Lagoas region, Minas Gerais State and theirs physical, chemical and mineralogical properties were studied. The soils belongs to the following great soil groups: Soils Bruns Acids (Oxic Humitropepts), Profile 1 located in upland Profile 2 (Typic Paleustult) located in pediment backslope and Dark Red Latosols (Typic Haplorthox) Profiles 3 and 4, located in pediment footslope. The silt content is high and it decreaces from Pedon 1 through Pedon 4, and it was inherited from parent material. There is a relationship between soil properties and the position of the soils on the landscape. The contents of base saturation, silt and 2:1 clay minerals are higher in soils located on upland and pediment blackslope than soils located on pediment footslope. Soils Bruns Acids are mineralogicaly younger than Dark Red Latosols. Mica, ikaolinite and montmorillonite were probably inherited from parente material. Gibbsite and vermiculite were formed during pedogenesis. According to mica content the following weathering sequence is suggested, going from the least to the most weathered soils: Soils Bruns Acid (Profiles 1 and 2) < Dark Red Latosol (Profile 3) < Dark Red Latosol (Profile 4). In relation to genetic implication in the studied area a general conclution is drown that all soils have been developed from reworked parent material.Foram selecionados quatro perfis de solos localizados em uma catena sobre folhelho na região de Sete Lagoas, Estado de Minas Gerais. Os solos pertencem aos seguintes, grandes grupos: Bruno Avermelhado (Oxic Humitropept), Perfil 1 localizado na posição de terras altas, Perfil 2 (Typic Paleustult) localizado na posição de pedimento de encosta e Latossol Vermelho Escuro (Typic Haplortox), Perfis 3 e 4, localizados na posição de pedimento de sopé. O teor de silte é elevado e decresce dos Perfis 1 e 2 em direção aos Perfis 3 e 4, valores estes atribuídos a herança do material orginário. Existe relação entre a posição que os solos ocupam na paisagem e as características estudadas. Solos mais férteis e com maior teores de silte e minerais de argila de grade 2:1 estão localizados na posição de terras altas e pedimentos de encosta enquanto que os menos férteis, de menores teores de silte e minerais de grade 2:1 estão localizados na posição de pedimento de sopé. Os Bruno Ácidos são portanto mineralogicamente mais jovens do que os Latossois Vermelho Escuro. A mica, parte da caulinita e montmorilonita são minerais provavelmente herdados do material de origem enquanto que a gibbsita, parte da vermiculita e minerais interestratificados foram formados por pedogenese. A seguinte seqüência de intemperismo foi obtida, indo do solo menos evoluído ao mais evoluído: Bruno Ácido (Perfis 1 e 2) < Latossol Vermelho Escuro (Perfil 3) < Latossol Vermelho Escuro (Perfil 4). Todos os perfis estudados são provenientes de material retrabalhado com contribuição de folhelho

Enhancing digital soil mapping in southeastern Brazil: incorporating stream density and soil reflectance from multiple depths.

This study proposes a novel and simple method to incorporate laboratory soil spectral data in the production of digital soil maps

Caracterização espectral de solos utilizando espectrorradiômetro em laboratório e imagem de satélite hiperespectral.

Data obtained with hyperspectral remote sensors have the advantage of containing a great spectral resolution, offering more details about spectral behavior of a particular target. The use of these images show high potential to describe soil mineralogical attributes. The main objective of this study was to obtain the spectral and mineralogical attributes of soils using hyperspectral satellite imagery and with data acquired at ground level; evaluation of a supervised classification routine for determination of soils texture; and estimate clay using multivariate analysis. Soil samples were collected at a 0-20cm depth and spectral measurements, texture and mineralogy analysis were made. Using GIS software, image processing and statistical packages, the information obtained in the laboratory has been analyzed. The use of hyperspectral imagery enhanced the mineralogical characterization of the studied area. The maximum likelihood classification algorithm showed great skill in distinguishing between four textures class created with the aim of hyperspectral data. The statistical method PLSR provided a satisfactory prediction of clay and sand, using data collected in the laboratory, with high coefficients of determination and low error values (RMSE)

Digital Soil Mapping Using Multispectral Modeling with Landsat Time Series Cloud Computing Based.

Abstract: Geotechnologies allow natural resources to be surveyed more quickly and cheaply than traditional methods. This paper aimed to produce a digital soil map (DSM) based on Landsat time series data. The study area, located in the eastern part of the Brazilian Federal District (Rio Preto hydrographic basin), comprises a representative basin of the Central Brazil plateau in terms of pedodiversity. A spectral library was produced based on the soil spectroscopy (from the visible to shortwave infrared spectral range) of 42 soil samples from 0?15 cm depth using the Fieldspec Pro equipment in a laboratory. Pearson?s correlation and principal component analysis of the soil attributes revealed that the dataset could be grouped based on the texture content. Hierarchical clustering analysis allowed for the extraction of 13 reference spectra. We interpreted the spectra morphologically and resampled them to the Landsat 5 Thematic Mapper satellite bands. Afterward, we elaborated a synthetic soil/rock image (SySI) and a soil frequency image (number of times the bare soil was captured) from the Landsat time series (1984?2020) in the Google Earth Engine platform. Multiple Endmember Spectral Mixture Analysis (MESMA) was used to model the SySI, using the endmembers as the input and generating a DSM, which was validated by the Kappa index and the confusion matrix. MESMA successfully modeled 9 of the 13 endmembers: Dystric Rhodic Ferralsol (clayic); Dystric Rhodic Ferralsol (very clayic); Dystric Haplic Ferralsol (loam-clayic); Dystric Haplic Ferralsol (clayic); Dystric Petric Plinthosol (clayic); Dystric Petric Plinthosol (very clayic); Dystric Regosol (clayic); Dystric Regosol (very clayic); and Dystric, Haplic Cambisol (clayic). The root mean squared error (RMSE) varied from 0 to 1.3%. The accuracy of DSM achieved a Kappa index of 0.74, describing the methodology?s effectiveness to differentiate the studied soils

Prediction statistical model for soil organic carbon mapping in crop areas using the Landsat/OLI sensor.

Abstract: The quantification of soil organic carbon (SOC) is essential to agriculture and sustainable use of the land. However, there are difficulties to estimate it in large areas due to high cost of soil sample extraction, and laboratory preparations. There are approaches that may facilitate the estimation of SOC, such as the use of satellite imagery and the application of statistical models based on the spectral bands of the satellite under study. In July of 2017, this study proposed a prediction statistical model from optical-orbital data of the series Landsat, OLI sensor for estimating SOC content

Spectral patterns in the mid-ir of soils in the northeast of Brazil and their relation to the taxonomic classification.

Knowing particularities of soils allows the adoption of sustainable management practices. The most efficient method to obtain data on the soil is through its characterization, essential for planning land use and soil conservation. However, soil surveys conducted in the conventional methods are costly and time-consuming. This study aimed to identify spectral patterns in the mid-IR wavelengths for a quick and low cost characterization of soil classes. Soils from the Natuba river basin, Pernambuco State, Brazil, were used. These soils were mapped on a scale of 1:25,000, where the presence of Latossolos, Argissolos, Gleissolos and Neossolos were identified. The data of reflectance for profiles of each soil class were collected using the spectral range between 2,500 and 25,000 nm. In the mid-IR region, Latossolos and Argissolos presented spectral characteristics peculiar to classification criteria. The increased contents of organic matter and iron oxides reduced soil reflectance. The horizons with sand content above 80% showed strong absorption spectra and significant reflectance peaks of quartz in the mid-IR. The wavelengths 2,681, 2,600 and 2,495 cm-1 occurred only in these horizons. The spectral analysis presented as a high-potential method for the characterization and classification of soils