Visible–NIR reflectance: a new approach on soil evaluation (original) (raw)
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Spectral reflectance for the mineralogical evaluation of Brazilian low clay activity soils
International Journal of Remote Sensing, 2007
Highly weathered tropical soils are very important in terms of agricultural production but there are only a few spectral studies that have evaluated them in detail. Measurements of electromagnetic radiation (EMR) interactions with soil samples can provide useful information regarding mineralogy, organic matter content, granulometry as well as other important soil parameters. The objective of this study was to evaluate the relationship between analytical and spectral parameters of six important classes of tropical Brazilian soils. Spectral data were obtained under laboratory conditions using an IRIS (400-2500 nm) spectroradiometer. Soil chemical analyses were conducted as performed for pedological surveys. Spectral curves provided useful pedological information. Diagnostic mineralogical features were found for ''absorption bands'' that are well-defined ''valleys'' centred in some wavelengths of the spectral curve. The main absorption bands were centred at 450 and 850 nm and were attributed to interactions between EMR and the content of iron oxide in the soil. Water and hydroxyl absorption bands at 1450, 1950 and 2200 nm were also enhanced, and allowed a correlation with the presence of either 2 : 1 or kaolinitic mineralogy. Important pedological characteristics such as granulometry, quartz and the presence of magnetite could also be inferred. Reflectance increased as the iron content decreased and the soil's texture changed from clay to sandy. Iron forms differentially influenced the spectral data: crystalline forms were responsible for concavities in the 450 and 1100 nm spectral range and amorphous forms reduced the intensity of reflectance, but did not alter the concavities. Rich quartz soils reflected more than soils rich in iron and magnetite. The 1 : 1 mineralogy presented spectral contours that differed from the 2 : 1 mineralogy when evaluated with the bands at 1950 and 2200 nm. In conclusion, laboratory EMR analysis of soil samples collected in the field can provide a great deal of pedological information and assist traditional methods of soil evaluation.
The Open Remote Sensing Journal, 2009
Wet chemistry methods to extract soil properties such as Fe 2 O 3 , TiO 2 , MnO and clay are cost effective, time consuming and environmental polluter. Moreover, a large set of samples has to be collected for precise spatial mapping. Ordinary surface soil mapping is a problematic method. Accordingly, non destructive technologies, such as remote sensing methods can provide important vantages. The objective of the present work was to estimate soil attributes by laboratory and orbital sensors and compare these results with soil classification. The study area is a 473 ha bare soil field located in the region of Barra Bonita, Brazil. A sampling grid of 100 by 100 m was established and the exact position of each point was georeferenced, and sent to traditional (wet) laboratory analyses. The soil samples reflectance were also acquired by a laboratory sensor using artificial illumination (450 to 2500 nm). Over the same selected ground area reflectance data were extracted from the TM-Landsat-5 image. Prediction equations between the satellite and laboratory reflectance data and the wet chemistry were generated for each attribute. Most of the generated equations presented high and significant R 2 such as for the Fe 2 O 3 with 0.82 for laboratory and 0.67 for the orbital reflectance data. The comparison between reflectance estimates and laboratory wet measurements for iron presented 92.2% success for the laboratory and 91.3% for the orbital sensors. The comparison for the texture intervals, showed 65% and 50% success for laboratory and orbital data respectively. The iron contents obtained by the sensors allowed to better remotely classify soil classes. Soil extractions to determine these attributes can be substitute by spectral reflectance models based on the present methodology.
Bi-directional reflectance factor of 14 soil classes from Brazil
International Journal of Remote Sensing, 1995
The spectral reflectance of soils is required for ,effective use of remote sensing products. The absence of studies concerned with spectral reflectance of the soils from the tropical region in the 400 to 2500 nm spectral range is the main motivation of this research. The objective of this study was to present spectral reflectance data from different tropical sou l types. This spectral characterization was done through measurements of the bi-directional reflectance factor of 111 selected sou l samples, grouped in 14 tropical sou l classes, taken from 53 sites (São Paulo State, Brazil). The measurements were made with a spectroradiometer operating in the 400 to 2500 nm region of the electromagnetic spectrum. Each soul sample is associated to a set of physical and chemical analyses data, with part of these published in descriptive reports of sou l surveys.
Spectral analysis as an extra method to soil type discrimination
Agricultural Science and Technology, 2020
The purpose of the study was to test near infrared soil spectra as an extra method for three soil types (Fluvisols, Vertisols and Solonchaks) discrimination from different regions of South Bulgaria. The diffuse reflectance spectra of 177 soil samples (from the 0-20cm layers): 50 samples of Fluvisols soil type, 78 samples of Vertisols soil type and 48 samples of Solonchaks soil type were obtained using a Spectrum NIRQuest (OceanOptics, Inc.) working within the range from 900 to 1700 nm. Soft independent modelling of class analogy (SIMCA) was performed to classify samples according to their taxonomic classes. The results obtained showed that the soil samples are separated accurately according to their soil type based on their spectral information. All this could be used in the future studies related to the application of the NIRS method as a qualitative or quantitative method for soil analysis and also for the purposes of precision farming.
Spectral behavior of some modal soil profiles from São Paulo State, Brazil
Bragantia, 2012
Remote sensing has a high potential for environmental evaluation. However, a necessity exists for a better understanding of the relations between the soil attributes and spectral data. The objective of this work was to analyze the spectral behavior of some soil profiles from the region of Piracicaba, São Paulo State, using a laboratory spectroradiometer (400 to 2500 nm). The relations between the reflected electromagnetic energy and the soil physical, chemical and mineralogical attributes were analyzed, verifying the spectral variations of soil samples in depth along the profiles with their classification and discrimination. Sandy soil reflected more, presenting a spectral curve with an ascendant form, opposite to clayey soils. The 1900 nm band discriminated soil with 2:1 mineralogy from the 1:1 and oxidic soils. It was possible to detect the presence of kaolinite, gibbsite, hematite and goethite in the soils through the descriptive aspects of curves, absorption features and reflect...
Digital Soil Mapping of Soil Properties in the “Mar de Morros” Environment Using Spectral Data
Revista Brasileira de Ciência do Solo, 2019
Quantification of soil properties is essential for better understanding of the environment and better soil management. The conventional techniques of laboratory analysis are sometimes costly and detrimental to the environment. Thus, development of new techniques for soil analysis that do not generate residues, such as spectroscopy, is increasingly necessary as a viable way to estimate a wide range of soil properties. The objective of this study was to predict the levels of organic carbon (OC), clay, and extractable phosphorus (P), from the spectral responses of soil samples in the visible and near infrared (Vis-NIR), medium infrared (MIR), and Vis-NIR-MIR using different preprocessing methods combined with five prediction models. Soil samples were collected in Iconha, Espírito Santo State, Brazil, in the Ribeirão Inhaúma basin. A total of 184 samples were collected from 92 sites at two depths (0.00-0.10 and 0.10-0.30 m). Physical, chemical, and spectral analyses were performed according to routine soil laboratory methods. Random selection was made of 70 % of total samples for training and 30 % for validation of the models. The coefficient of determination (R 2) and root mean square error (RMSE) were calculated in order to assess model performance. The standardized indexes of prediction error RPD and RPIQ were also calculated. For clay and OC, the best R 2 was found in the MIR spectrum, at 0.69 and 0.65, respectively, and for P, it was 0.57 in Vis-NIR. The MSC (Multiplicative Scatter Correction), CR (Continuum removal), and SNV (Standard Normal Variate) preprocesses were most efficient for predicting clay, OC, and P, respectively, while the PLSR-Partial Least Squares Regression (OC and P) and SVM-Support Vector Machine (clay) gave the best predictions and are therefore recommended for modeling these properties in the study area. The models identified in this study can be used to discriminate soils according to a critical test value for clay, OC, and P.
Variations in Reflectance of Tropical Soils
Remote Sensing of Environment, 2001
The relationships between Airborne Visible/Infrared faces. In comparison with the light and loamy sand S AQ , the dark-red clay S TE and S LE presented higher contents Imaging Spectrometer (AVIRIS) surface reflectance values and constituents (total iron, organic matter, TiO 2 , of Fe 2 O 3 , Al 2 O 3 , and TiO 2 , and consequently lower overall Al 2 O 3 , and SiO 2) of samples representative of three imreflectance in the scene, because of the presence of portant soil types from central Brazil [Terra Roxa Estrugreater amounts of opaque minerals. The prediction of turada (S TE), Latossolo Vermelho-Escuro (S LE), and Areia these constituents from remote sensing data and their Quartzosa (S AQ)] were analyzed. End member spectra for close association with the spatial distribution of the difgreen vegetation (GV), nonphotosynthetic vegetation ferent soil types demonstrate the importance of the pres-(NPV), water (W), and the three soil types were selected ent investigation for soil mapping and soil erosion studby inspecting scatter plots derived from the principal ies. ©Elsevier Science Inc., 2001. All Rights Reserved. components analysis (PCA) of 140 AVIRIS bands. They were then used to compose a six end member unmixing model to characterize the spectral reflectance variations
Development of Reflectance Spectral Libraries for Characterization of Soil Properties
Soil Science Society of America Journal, 2002
wide range of materials . Spectral signatures of materials are defined by their Methods for rapid estimation of soil properties are needed for reflectance or absorbance, as a function of wavelength quantitative assessments of land management problems. We develin the electromagnetic spectrum. Under controlled conoped a scheme for development and use of soil spectral libraries for rapid nondestructive estimation of soil properties based on analysis ditions, the signatures result from electronic transitions of diffuse reflectance spectroscopy. A diverse library of over 1000 of atoms and vibrational stretching and bending of strucarchived topsoils from eastern and southern Africa was used to test the tural groups of atoms that form molecules or crystals. approach. Air-dried soils were scanned using a portable spectrometer Fundamental features in reflectance spectra occur at (0.35-2.5 m) with an artificial light source. Soil properties were energy levels that allow molecules to rise to higher vibracalibrated to soil reflectance using multivariate adaptive regression tional states. For example, the fundamental features splines (MARS), and screening tests were developed for various soil related to various components of soil organic matter fertility constraints using classification trees. A random sample of generally occur in the mid-to thermal-infrared range one-third of the soils was withheld for validation purposes. Validation (2.5-25 m), but their overtones (at one half, one third, r 2 values for regressions were: exchangeable Ca, 0.88; effective cationone fourth etc. of the wavelength of the fundamental exchange capacity (ECEC), 0.88; exchangeable Mg, 0.81; organic C concentration, 0.80; clay content, 0.80; sand content, 0.76; and soil feature) occur in the near-infrared (0.7-1.0 m) and pH, 0.70. Validation likelihood ratios for diagnostic screening tests short-wave infrared (1.0-2.5 m) regions. Soil clay minwere: ECEC Ͻ4.0 cmol c kg Ϫ1 , 10.8; pH Ͻ5.5, 5.6; potential N mineralerals have very distinct spectral signatures in the shortization Ͼ4.1 mg kg Ϫ1 d Ϫ1 , 2.9; extractable P Ͻ7 mg kg Ϫ1 , 2.9; exchangewave infrared region because of strong absorption of able K Ͻ0.2 cmol c kg Ϫ1 , 2.6. We show the response of prediction the overtones of SO 2Ϫ 4 , CO 2Ϫ 3 , and OH Ϫ and combinaaccuracy to sample size and demonstrate how the predictive value of tions of fundamental features of, for example, H 2 O and spectral libraries can be iteratively increased through detection of CO 2 (Hunt, 1982; Clark, 1999). The visible (0.4-0.7 m) spectral outliers among new samples. The spectral library approach region has been widely used for color determinations opens up new possibilities for modeling, assessment and management in soil and geological applications as well as in the identiof risk in soil evaluations in agricultural, environmental, and engineering fication of Fe oxides and hydroxides (Ben-Dor et al., applications. Further research should test the use of soil reflectance in pedotransfer functions for prediction of soil functional attributes. 1998). Although geological spectral libraries exist that
Soil Spectral Mapping and Its Correlation with the Traditional Methodology
Boletim de Ciências Geodésicas, 2018
The use of remote sensing is increasing in agriculture and this raises questions about its efficiency over other usual methods. Thus, the purposes of this study were to compare methodologies for soil mapping, using field samplings and spectral data (from laboratory and from a simulated Landsat-TM), and to estimate their correlation. The soil samples were collected in a wetland with a great variety of soil classes. The distribution of soil classes in the maps was based on independence analysis by the Chi-square. Ten soil classes were determined in the study area, 6 in the first category level. The map of laboratory spectral data showed low correlation with conventional data. The map of spectral data that simulated wavelenghts corresponding the spectral bands of Landsat-TM sensor showed the same behavior of the previous map, with lower correlation with the conventional data. Thus, we verified that the mapping of paddy soils with spectral data shows low correlation with conventional data, however, still rather positive.
Geoderma, 2018
There are several methods to extract soil information by spectral sensing. For this reason, the database should be built including standards and protocols both in the lab and in field acquisitions. If we does not align the measurement one to each other, the models will have no merit in term of large-scale application and stay as an academic exercise only. The use of standard samples with known spectra is expected to allow parameterizing mathematically soil spectra collected by different equipment and with distinct geometries. This study was proposed for the reason that to date, the new methodology proposed has not been evaluated in Brazilian tropical soils (Oxisols) in visible, near and short infrared (VIS-NIR-SWIR-350 to 2500 nm) spectral regions from three spectrometers (FieldSpec 3) in three distinct protocols (Long Light, Near Light and Contact Probe). The current study compared the spectral intensity of each combination between spectrometers and protocols by ANOVA module and the clay prediction capacity by PLSR with cross-validation, before and after the internal soil standard (ISS) method application. The results showed that visual spectral variation is minimized by the ISS method and its correction enables better proxy modeling of clay content especially if the data are mixed from different protocols. The model for clay prediction was improved showing a favorable case to use the ISS technique in any soil spectral measurement in a better way to merge spectral libraries from different sources.