Numerical examination of a field classification of some red, yellow and grey earth profiles

Soil Research ◽  
1983 ◽  
Vol 21 (4) ◽  
pp. 343 ◽  
Author(s):  
RJ Coventry ◽  
WT Williams

Numerical methods have been used to examine an existing and accepted field classification of 48 profiles of red, yellow, and grey earths (mainly Alfisols) from central north Queensland. The three-dimensional soils data (sites by depths by descriptors, which may be mixed in type) were converted to a form which appeared to the computer as a two-dimensional set of profiles by attributes. The soils data were from independent depth intervals, and no assumptions were made about the inter-relationships among soil layers tvithin a profile; nor were the values of any of the soil attributes weighted. In order to consider shallow profiles on the same total depth basis as the deep profiles, the absence of a soil horizon or sampling interval at depth has been regarded as a positive attribute in the numerical classification. Comparison of the traditional field classification and a numerical classification of the same soils dataset showed that certain soil attributes played an important role in both classifications. The most striking difference between them was the relative importance of soil colour attributes, from which it might be argued that field pedologists have assigned to colour a weight out of proportion to its real importance in soil classification. However, this attribute carries additional information about the mineral constituents and hydrological regimes of the soils, and represents information known to, and used by, the field pedologist but not revealed to the computer. The essential subjectivity in the choice of attributes for soil classification is demonstrated.

2014 ◽  
Vol 38 (2) ◽  
pp. 372-385 ◽  
Author(s):  
Rodnei Rizzo ◽  
José A. M. Demattê ◽  
Fabrício da Silva Terra

Considering that information from soil reflectance spectra is underutilized in soil classification, this paper aimed to evaluate the relationship of soil physical, chemical properties and their spectra, to identify spectral patterns for soil classes, evaluate the use of numerical classification of profiles combined with spectral data for soil classification. We studied 20 soil profiles from the municipality of Piracicaba, State of São Paulo, Brazil, which were morphologically described and classified up to the 3rd category level of the Brazilian Soil Classification System (SiBCS). Subsequently, soil samples were collected from pedogenetic horizons and subjected to soil particle size and chemical analyses. Their Vis-NIR spectra were measured, followed by principal component analysis. Pearson's linear correlation coefficients were determined among the four principal components and the following soil properties: pH, organic matter, P, K, Ca, Mg, Al, CEC, base saturation, and Al saturation. We also carried out interpretation of the first three principal components and their relationships with soil classes defined by SiBCS. In addition, numerical classification of the profiles based on the OSACA algorithm was performed using spectral data as a basis. We determined the Normalized Mutual Information (NMI) and Uncertainty Coefficient (U). These coefficients represent the similarity between the numerical classification and the soil classes from SiBCS. Pearson's correlation coefficients were significant for the principal components when compared to sand, clay, Al content and soil color. Visual analysis of the principal component scores showed differences in the spectral behavior of the soil classes, mainly among Argissolos and the others soils. The NMI and U similarity coefficients showed values of 0.74 and 0.64, respectively, suggesting good similarity between the numerical and SiBCS classes. For example, numerical classification correctly distinguished Argissolos from Latossolos and Nitossolos. However, this mathematical technique was not able to distinguish Latossolos from Nitossolos Vermelho férricos, but the Cambissolos were well differentiated from other soil classes. The numerical technique proved to be effective and applicable to the soil classification process.


1987 ◽  
Vol 67 (3) ◽  
pp. 417-432 ◽  
Author(s):  
L. LAMONTAGNE ◽  
C. CAMIRE

Analysis and numerical classification of Lanoraie Delta soils were performed as part of an ecological study. After stratification, using detailed soil maps, 84 forest sites were randomly sampled. Eighteen soil descriptors, mainly morphologic, were retained for numerical analysis. Gower's similarity coefficient between profiles was used for the principal coordinate analysis (PCA) which brought out the most probable factors governing soil distribution. The first two axes of the PCA represented 15.5 and 6.2% of the total variance. Soil distribution was along two gradients: soil water regime (Xeric-Hydric) and genetic development (Gleysolic-Podzolic). Cluster analysis by complete linkage created five soil groups which were composed of 23, 9, 17, 25 and 10 soil individuals, respectively. The interpretation of these soil groups utilized the superposition of clusters onto the first two axes of the PCA. Each group was classified into a taxonomic subgroup (Canadian System of Soil Classification) and defined by a typical humus form. Key words: Lanoraie Delta, multivariate analysis, soil classification


2004 ◽  
Vol 61 (6) ◽  
pp. 615-625 ◽  
Author(s):  
Lindomário Barros de Oliveira ◽  
Maria da Graça de Vasconcelos Xavier Ferreira ◽  
Flávio Adriano Marques

Geomorphic surfaces that present soils derived from basic rocks under warm and humid climate are unique scenarios for studying tropical soils. This paper aimed to characterize and classify two pedons derived from basalt at the Atlantic Forest Zone, Pernambuco State, Northeastern coast of Brazil. Two representative pedons (P1 and P2) were selected on a hillslope at the Cabo de Santo Agostinho municipality. Field macromorphological descriptions were carried out and soil horizon were sampled for physical, chemical, mineralogical and micromorphological characterization. The soils were classified, according to the Brazilian System of Soil Classification (and US Soil Taxonomy) as: "Latossolo Vermelho-Amarelo distroférrico argissólico" (Typic Hapludox) (P1) and "Nitossolo Vermelho distroférrico típico" (Rhodic Paleudult) (P2). Pedon 1 differs from Pedon 2 in some aspects. For instance, P1 presents more yellowish colors, absence of clay illuviation, more friable consistence and the prismatic structure undergoes transformation to angular and subangular blocks. Pedon 2 presents ferri-argilans and leptocutans which indicate that vertical and lateral illuviation of clay is an active process in their formation. These chemically poor and mineralogically uniform soils are a result of the high temperature and rainfall of the studied area.


2010 ◽  
Vol 3 (2) ◽  
pp. 156-180 ◽  
Author(s):  
Renáta Gregová ◽  
Lívia Körtvélyessy ◽  
Július Zimmermann

Universals Archive (Universal #1926) indicates a universal tendency for sound symbolism in reference to the expression of diminutives and augmentatives. The research ( Štekauer et al. 2009 ) carried out on European languages has not proved the tendency at all. Therefore, our research was extended to cover three language families – Indo-European, Niger-Congo and Austronesian. A three-step analysis examining different aspects of phonetic symbolism was carried out on a core vocabulary of 35 lexical items. A research sample was selected out of 60 languages. The evaluative markers were analyzed according to both phonetic classification of vowels and consonants and Ultan's and Niewenhuis' conclusions on the dominance of palatal and post-alveolar consonants in diminutive markers. Finally, the data obtained in our sample languages was evaluated by means of a three-dimensional model illustrating the place of articulation of the individual segments.


i-com ◽  
2020 ◽  
Vol 19 (2) ◽  
pp. 67-85
Author(s):  
Matthias Weise ◽  
Raphael Zender ◽  
Ulrike Lucke

AbstractThe selection and manipulation of objects in Virtual Reality face application developers with a substantial challenge as they need to ensure a seamless interaction in three-dimensional space. Assessing the advantages and disadvantages of selection and manipulation techniques in specific scenarios and regarding usability and user experience is a mandatory task to find suitable forms of interaction. In this article, we take a look at the most common issues arising in the interaction with objects in VR. We present a taxonomy allowing the classification of techniques regarding multiple dimensions. The issues are then associated with these dimensions. Furthermore, we analyze the results of a study comparing multiple selection techniques and present a tool allowing developers of VR applications to search for appropriate selection and manipulation techniques and to get scenario dependent suggestions based on the data of the executed study.


2021 ◽  
Vol 40 (4) ◽  
pp. 8493-8500
Author(s):  
Yanwei Du ◽  
Feng Chen ◽  
Xiaoyi Fan ◽  
Lei Zhang ◽  
Henggang Liang

With the increase of the number of loaded goods, the number of optional loading schemes will increase exponentially. It is a long time and low efficiency to determine the loading scheme with experience. Genetic algorithm is a search heuristic algorithm used to solve optimization in the field of computer science artificial intelligence. Genetic algorithm can effectively select the optimal loading scheme but unable to utilize weight and volume capacity of cargo and truck. In this paper, we propose hybrid Genetic and fuzzy logic based cargo-loading decision making model that focus on achieving maximum profit with maximum utilization of weight and volume capacity of cargo and truck. In this paper, first of all, the components of the problem of goods stowage in the distribution center are analyzed systematically, which lays the foundation for the reasonable classification of the problem of goods stowage and the establishment of the mathematical model of the problem of goods stowage. Secondly, the paper abstracts and defines the problem of goods loading in distribution center, establishes the mathematical model for the optimization of single car three-dimensional goods loading, and designs the genetic algorithm for solving the model. Finally, Matlab is used to solve the optimization model of cargo loading, and the good performance of the algorithm is verified by an example. From the performance evaluation analysis, proposed the hybrid system achieve better outcomes than the standard SA model, GA method, and TS strategy.


Minerals ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 598
Author(s):  
Jose R. A. Godinho ◽  
Gabriel Westaway-Heaven ◽  
Marijn A. Boone ◽  
Axel D. Renno

This paper demonstrates the potential of a new 3D imaging technique, Spectral Computed Tomography (sp-CT), to identify heavy elements inside materials, which can be used to classify mineral phases. The method combines the total X-ray transmission measured by a normal polychromatic X-ray detector, and the transmitted X-ray energy spectrum measured by a detector that discriminates between X-rays with energies of about 1.1 keV resolution. An analysis of the energy spectrum allows to identify sudden changes of transmission at K-edge energies that are specific of each element. The additional information about the elements in a phase improves the classification of mineral phases from grey-scale 3D images that would be otherwise difficult due to artefacts or the lack of contrast between phases. The ability to identify the elements inside the minerals that compose ore particles and rocks is crucial to broaden the application of 3D imaging in Earth sciences research and mineral process engineering, which will represent an important complement to traditional 2D imaging mineral characterization methods. In this paper, the first applications of sp-CT to classify mineral phases are showcased and the limitations and further developments are discussed.


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