Application of fractal analysis in agriculture (original) (raw)
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Fractal approach in characterization of spatial pattern of soil properties
EURASIAN JOURNAL OF SOIL SCIENCE (EJSS), 2017
The objective of the study was to characterize spatial pattern of soil properties (CaCO3, soil organic carbon, P2O5, K2O, and clay content) using fractal concept. Total of 141 topsoil samples (0-30 cm) were collected on 1850 ha in karst polje (Petrovo polje, Croatia) and analyzed for listed soil properties. The semi-variogram method was used to estimate fractal dimension (D) value which was performed from both of isotropic and anisotropic perspective. The D value of soil properties ranged between 1.76 to 1.97, showing a domination of the short-range variations. The SOC and K2O fractal D values 1.79 and 1.76 respectively, exhibited a spatial continuity at the entire analysed range of the scale. The D value for P2O5 (1.97) showed a nearly total absence of the spatial structure at all scales. The CaCO3 and clay content indicated a multifractal behavior mainly attributed to effects of alluviation, differences in geology and its spatial changes and transitions. The results of anisotropic analysis of soil properties pattern have showed strong relations with directions and partial self-similarity over limited ranges of scales defined by scale-break. Finally, our results showed that fractal analysis can be used as a appropriate tool for the characterization of spatial pattern irregularities of soil properties and detection of soil forming factors that cause it.
Determination of the influence of tillage on the soil structure by fractal analysis
International Agrophysics
This contribution deals with an evaluation of soil structure by the unconventional method of fractal analysis. The soil is represented as a pore medium with statistically self-similar structure which represents a fractal structure. The fractal dimension is presented as decisive representative of the structural properties of soil. The fractal dimension is a non-integer number which expresses degradation of soil structure which was caused by pores. This number includes comprehensively the modification of structural properties of soil induced by arbitrary influence. The fractal dimension of clay-loam and sandy-clay soil was related to the activity of factors which represented the influence of exactly defined tillage practices (conventional, reduced and direct seeding) in the depths of 0-3 and 6-9 cm. The intensity and statistical significance of individual factors were determined by analysis of variance. The effects of tillage practices on the modification of surface soil structure rep...
Linear fractal analysis of three Mexican soils in different management systems
Soil Technology, 1997
The purpose of this study was to document the fractal nature of three soils of Mexico with contrasting genesis and marked differences in morphology and to estimate the fractal dimensions of their sets of aggregates and pores. These dimensions were estimated along lines and were called linear fractal dimensions. A single, 'ideal' fractal dimensionality was detected in the three soils studied. The soil linear fractal dimensions, calculated from macro and micromorphological data, had larger values than the dimension of the Cantor fractal dust model, but were less than unity. It was shown, that the fractal structure of the soil pore space could not be described by the same dimension as that of the aggregates. The linear fractal dimensions of soils of distinct genesis, were significantly different on all scales compared, but the differences fluctuated between 0.4% and 9.1%. 0 1997 Elsevier Science B.V.
Evaluation of Soil-Water Characteristic Curves for Different Textural Soils Using Fractal Analysis
Water
The soil-water characteristic curve (SWCC) is an essential tool to determine hydraulic and mechanical properties of unsaturated soils. As an inherent influencing factor, soil texture controls the characteristics of SWCCs. Fractal theory can quantitatively describe the physical characteristics of soil. This study used particle size distribution data and water content data contained in the UNSODA2.0 database to explore the fractal characteristics of 12 soil types with different textures under different matrix suctions. The SWCC fractal model was adopted to characterize the hydraulic properties of soil with various soil textures. The findings revealed that the mass fractal dimensions of particles from these 12 different soil types significantly differed and were closely related to the clay content. Fractal dimension increased with increasing clay content. The fractal dimension established a good relationship between soil structure and hydraulic properties. Fractal analysis can be used ...
2016
Fractal geometry and geostatistics have become effective tools for quantifying spatial variability of soil physical. In this research, fractal dimension (Dm) of Particle Size Distribution (PSD) was used to explain relationships between Dm and some physical properties of soils. Samples from 51 soil series with varying properties were collected from north of Iran. Sand fraction was determined by sieving and silt and clay fractions by the hydrometer methods. Fractal dimension of PSD was computed by Tyler & Wheatcraft model. Statistical analysis showed significant and positive correlations between Dm and clay (0.93) and silt (0.80) particles; and the correlation between Dm and sand (0.73) were significantly negative. Therefore, Dm had significant relations with soil textural fractions and textural classes, and might be used as an integrating index in modeling studies. Results also showed that greater Dm was associated with greater self-similarity in pore size distribution.
FRACTAL ANALYSIS OF SOIL STRUCTURE AS INFLUENCED BY TILLAGE TREATMENT
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EURASIAN JOURNAL OF SOIL SCIENCE (EJSS), 2018
The present study was conducted to explore the fractal behavior and establish fractal dimensions of soil physical and chemical properties (i.e., sand, silt, and clay contents, bulk density, degree of moisture saturation, pH, organic carbon content, total nitrogen, available phosphorus, and available potassium) to characterize their spatial patterns. Soil samples were collected from 0-30 (surface) and 30-60 cm (subsurface) depths from an agricultural field, Mashhad Plain, Northeast Iran. Descriptive statistics and fractal analysis were used to describe the extent and form of variability. Spatial patterns of the soil properties were estimated using GS+ 10.0 software. Soil properties showed low to high variations in both surface and subsurface layers across the field, where bulk density and pH being the most reliable soil physical and chemical properties in the study area. The variability was high (CV > 35%) for total N, available P, available K and organic carbon in both surface and subsurface soils and it could be attributed to management practices and micro-topographical variations as these are the dynamic properties of soil. The fractal dimension (D) values of soil physical properties ranged from 1.398 to 1.913 at the surface, and from 1.874 to 1.934 at the subsurface indicating both short and long range variations. The D values for the chemical properties ranged from 1.331 to 1.975, and 1.148 to 1.990 in the surface and subsurface layers, respectively. The results showed that fractal analysis could be employed to effectively describe the structure of soil heterogeneity in spatial scale for effective agricultural and environmental management of soil.
Fractal analysis of microstructure of peat soil
This study discusses fractal analysis on the microscopic structure of the peat soil. The main objective is to investigate the distribution of pores in the rock samples. The results of fractal analysis using the Minkowski-Bouligand method indicates that the SEM images of microscopic structures of peat soil behave as a fractal with dimension value 1.8965. These values confirm that the distribution of pores in the peat soil is very irregular at the microscale levels.
From fractal analysis along a line to fractals on the plane
Soil and Tillage Research, 1998
Self-similar fractals are useful models for soil solid and pore sets. The scaling properties of these fractals along a line and across an area can be described by the fractal dimensions. One method, for estimating the soil areal fractal dimension from the solid and pore set distributions along the lines, was proposed and tested with real macro-and micromorphological data on three Ž. soils of Mexico. The soil areal fractal dimension D was compared with the soil mass fractal a Ž. dimension D estimated by two-dimensional binary image analysis, separately for solids and m pores. Both methods are based on the box-counting technique and are suitable for determining the soil 'box' or 'capacity' fractal dimension, that seems to be apt to estimate the alternative filling of an area by a fractal set of solids and pores. This paper examines the relations between the fractal dimensions obtained along a line, across an area and directly from the image. Analysis of D and a D data seems to suggest that both soil genesis and management practice can contribute to areal m fractal dimension dynamics. It was shown that fractal dimensions are useful parameters able to monitor tillage influence on soil properties and to estimate the degree of soil compaction.
Fractal Behaviour of Soil Physical and Hydraulic Properties
Physical and hydraulic properties of soils show spatial and temporal variability at different scales. The measurement and understanding of soil properties is essential to describe dominant hydrologic processes/parameters at various scales. Due to self - similar (or scale invariant) properties of fractals and their representation by a single parameter, fractal dimension, they have potential as a descriptive tool for scaling up various parameters. The objectives of this study was to illustrate fractal depiction of spatial behaviour of soil physical and hydraulic properties on a field scale, and to describe their anisotropic feature and possible impact on fractal dimension. The variogram plotted on a log - log scale was used to estimate fractal dimension of data collected from soil core samples and in-situ field measurements. The results indicate that soil properties show fractal behaviour and cannot capture anisotropic variability of soil properties on a field scale. There is a furthe...