土壤图像孔隙轮廓线分形特征及其应用

孔隙轮廓线分形维数是用来描述孔隙本身所具有的分形特征，它反映了土壤孔隙与固体颗粒接触界限的不规则性。该文采用数字图像处理技术研究了中国科学院封丘农业生态实验站内3种不同质地土壤样本图像的孔隙轮廓线分形特征。结果表明：土壤孔隙轮廓线分形特征与土壤质地之间存在着一定的相关关系，即土壤质地越细(黏粒含量越高)分形维数取值越大。同时，根据这3种土壤的孔隙轮廓线分形维数，结合不同分形方法分别预测了它们的水分特征曲线，并与实测的土壤水分特征曲线进行了比较。     

基于CT数字图像的土壤孔隙分形特征研究

通过CT扫描获得了河南封丘地区3种不同质地潮土样本的高精度图像,利用数字图像分析方法识别出土壤孔隙及其轮廓线,然后用计盒法确定了表征土壤孔隙形态不规则性的分形维数.在此基础上,通过不同形式的分形模型预测了土壤水分特征曲线.结果表明,河南封丘地区不同质地潮土的孔隙分形维数(包括面积和轮廓线分维)差异不明显;预测水分特征曲线时,针对不同质地的土壤选择适宜的分形模型才能得到较好的模拟结果.     

中国封颗粒组成的分形特征研究

以土壤颗粒组成数据为基础,分析了我国土壤颗粒组成的分形维数。结果表明,不同质地的分形维数存在一定的差异,分形维数随土壤质地的变细而增大;由北至南、由西向东和由西南至东北,我国主要地带性土壤的分形维数逐渐递增;成土母质对土壤质地分形维数有很大影响,易风化母质上发育的土壤质地分形维数高于难风化母质上发育的土壤。     

土壤颗粒的分形特征及其应用

本文应用土壤颗粒的质量分布原理来描述土壤颗粒的分形特征。通过对10种土壤颗粒的机械组成进行分析,分别计算出它们的分形维数（D=2.489～2.896）,并分析了其与土壤质地之间的关系。同时对土壤颗粒分形维数与所对应土壤的幂函数型水分特征曲线的拟合分形维数进行比较分析,建立了二者之间的相关关系。结果表明:分形维数的大小反映了土壤质地中粘粒、粉粒和砂粒含量的变化,随粘粒含量的增多分形维数增大,随砂粒含量的增多分形维数减小;同时土壤颗粒分形维数与所对应的水分特征曲线的拟合分形维数呈现出良好的一致性,因而对所研究的土壤而言,可应用土壤颗粒的质量分形维数结合幂函数模型来估算土壤水分特性曲线。     

云南宣威市烟田耕作层土壤颗粒分形特征研究

在宣威市烟田耕作层土壤属性数据的基础上,研究了土壤颗粒分形维数与土壤机械组成、土壤质地和土壤养分间的关系,建立了植烟土壤颗粒分形维数的预测函数。结果表明:除了1.0 mm颗粒含量外,土壤颗粒分形维数与低于一定粒径的颗粒含量呈极显著正相关,且测定的粒径越小,直线斜率和相关系数越大,这表明随着土粒直径减小,分形维数增加。土壤颗粒分形维数重点反映黏粒含量,其次是粉粒含量。宣威市植烟土壤质地以壤土为主,适合优质烟的种植,土壤颗粒分形维数介于2.4889~3.8905之间,土壤颗粒分形维数可作为描述土壤质地的综合性定量指标,但土壤有机质、全氮、全磷、全钾含量与土壤颗粒分形维数的单相关性均不显著。建立的植烟土壤颗粒分形维数估算函数预测准确度和精确度高,分别为0.9714和0.9617,且相对误差较低(-0.8236%~0.8208%),能很好地用于模拟植烟土壤分形维数。     

汉中荒草地整治后耕作层土壤颗粒分形特征

运用分形模型,结合野外调查和室内试验分析汉中市荒草地整治后耕作层土壤颗粒分形特征,探讨土壤颗粒分形维数与土壤质地、粒径组成以及养分含量的关系,建立整治后耕作层土壤分形维数预测函数。结果表明:(1)整治后土壤颗粒分形维数D介于2.55~2.95之间,均值为2.77,标准差为0.134,土壤颗粒分形维数与土壤质地有一定的关系,表现为土壤质地越细,分形维数越大。(2)土壤颗粒分形维数主要是由黏粒含量决定,分形维数与黏粒含量呈显著线性正相关(R2=0.978 0);利用分形维数与土壤黏粒(≤0.002mm)建立的预测模型精确度高(R2=0.982 7),能够很好的预测土壤颗粒分形维数。(3)土壤分形维数与土壤全氮、有效磷和有机质含量的相关关系分别为0.914,0.580,0.513,分形维数与全氮、有效磷、速效钾含量均呈显著正相关关系,分形维数可作为衡量土壤肥力状况的有效指标。研究结论表明土壤分形维数D能够很好的表征土壤质地、粒径组成以及土壤养分状况,可为土地整治工程开展后土壤质量评价以及土地资源的永续利用提供一定的参考。     

松嫩平原西部典型盐生景观土壤分形维数及盐碱化特征

为探究松嫩平原西部典型盐生景观土壤颗粒粒度组成及分形特征与土壤盐碱化之间的关系,采用体积分形维数模型计算了6种典型盐生景观土壤表层0—30 cm颗粒组成及分形维数,结合相关分析法分析了土壤分形维数与质地、盐碱特征之间的相关性。结果表明:(1)6种典型盐生景观中农田土壤分形维数值最小(2.35),碱蓬群落土壤最大(2.61),分形维数均值为2.48,分形维数随盐生景观土壤碱化程度增加而增大。(2)土壤质地越粗,砂粒含量越高,分形维数值越小;土壤质地越细,黏粒和粉粒含量越高,分形维数越大。(3)分形维数与盐分含量呈显著正相关(r=0.87,P0.05),尤其与盐分组成中HCO_3~-含量呈极显著正相关(r=0.89,P0.01),与养分中总磷含量呈极显著正相关(r=0.90,P0.01)。(4)土壤颗粒组成中砂粒、粉粒和黏粒与盐分、HCO_3~-及总磷含量也存在极显著相关性。不同盐生景观土壤分形维数与土壤颗粒组成和土壤盐分之间存在显著的相关性,因此可以用分形维数来反映土壤质地和指示土壤盐碱化特征。     

基于扫描电镜图像分析的菜籽仁饼孔隙结构分形研究

以冷态压榨条件下菜籽仁饼为对象,研究油料饼孔隙结构,探讨油料饼孔隙结构的分形特性以及压榨压力对油料饼孔隙结构的影响.运用扫描电镜和Image-pro图像分析技术分别测试分析6种压榨压力下的菜籽仁饼孔隙的微观结构,采用小岛法对图片进行了孔隙截面边界和孔隙尺寸分布分形维数的测定,并采用回归分析方法建立了孔隙截面边界和孔隙尺寸分布分形维数与压榨压力的经验公式.结果表明,菜籽仁饼的孔隙结构存在明显的分形特征,分形维数越大,孔隙截面边界越不规则、孔隙尺寸分布越大;压榨压力越大,分形维数越大,压榨压力与分形维数满足明显的线性关系.     

北京地区表层土壤分形特征研究

土壤是一种具有分形特征的复杂系统.分形维数可以反映很多土壤特性.本研究考虑了7种土壤类型、4种土地利用类型,在北京地区选取了30个典型样点,对复杂地理环境表层土壤的分形特征进行了分析,探讨了分形维数与土壤质地、土壤理化性质等方面的关系.研究结果表明,在复杂地理环境条件下,土壤颗粒分形维数总体变异性较弱;分形维数与黏粒含量呈显著正相关,与(砂粒含量+粉粒含量)和黏粒含量的比值呈显著负相关.分形维数可以反映土壤质地,但仅可指示部分重要土壤的理化性质.     

河塘底泥与岸边土壤粒径分形维数及与其性状关系——以海南岛南渡江下游塘柳塘为例

以海南省南渡江下游塘柳塘为研究对象,采集52个河塘底泥和6个沿岸农田土壤样品,依据美国制土壤粒级分组与土壤质地分类标准,应用分形理论计算了58个样品的质量分形维数,探讨河塘底泥与邻近农田土壤在粒级组成上的差异,并揭示底泥粒径分形维数与粒级组成及有机质含量之间的相互关系。结果表明:(1)河塘底泥与沿岸农田土壤各粒级组成非常相似,均以极细砂、粉砂为主,土壤质地类型多为壤土;底泥粒径分形维数略高于沿岸农田分形维数,前者均值为2.662,后者为2.591。(2)底泥粒径分形维数与其黏粒和粉粒含量呈显著正相关关系,而与其砂粒含量呈显著负相关关系;底泥粒径分形维数与其有机质含量呈显著正相关关系。(3)塘柳塘底泥理化性状表明,南渡江下游河塘清淤底泥可用于周边土壤改良。     

Comparison of fractal dimensions of soils estimated from adsorption isotherms,mercury intrusion,and particle size distribution

The values of the surface fractal dimensions were determined for several samples of Cambisols and Luvisols from analysis of nitrogen and water vapor adsorption isotherms and from mercury intrusion data. Moreover, the values of fractal dimension characterizing the particle size distributions of soil samples were calculated by using a number‐based method. For almost all investigated soils the values of the surface fractal dimension, obtained from water vapor isotherms were lower than those obtained from nitrogen isotherms. Largest were the surface fractal dimensions evaluated form mercury intrusion data. No significant correlations between different kinds of surface fractal dimensions were found, and the reasons of this finding are discussed. However, the values of the surface fractal dimensions calculated from mercury intrusion data correlate with those characterizing the texture of soils. The paper also reports on correlations between of the values of surface area, fractal dimensions and some selected physico‐chemical characteristics of soils.     

土壤粒径分布单重分形与孔隙单重分形

土壤颗粒大小的分布是重要的土壤物理性质,对土壤水、气、热传导特性有着显著的影响。鉴于土壤颗粒分形在分析和描述岩土介质多孔结构的优势,本文通过对5种不同质地的土样进行颗粒分析与水分特征曲线的测试。结果表明:土壤结构定量化表征的方法就是确定土壤结构的分形维数,针对不同地区的土壤,可以通过土壤粒径分布分形维数体现土壤粒径分布的情况,分形维数越大,颗粒粒径越小,细粒含量越高,质地越发呈现不均匀性;且可利用土壤粒径分形维数估算土壤孔隙分形维数。为建立土壤粒径分布模型提供数据支持,同时也为推进土壤结构的研究进展提供了新的方向。     

土壤孔隙质量分数维D_m二元图像分析及其影响因素研究

本文简要介绍了利用土壤切片的二元图像分析了土壤孔隙结构的质量分数维Dm 的方法 ,并研究比较了四类土壤类型的Dm 及其影响因素。结果表明Dm 可以较好地定量描述土壤孔隙的空间分布特征 ,Dm 与土壤孔隙面积、孔隙孔径分布、土壤深度以及土壤质地之间均具有一定的联系     

From fractal analysis along a line to fractals on the plane

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 soils of Mexico. The soil areal fractal dimension (D_a) was compared with the soil mass fractal dimension (D_m) estimated by two-dimensional binary image analysis, separately for solids and 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_a and D_m data seems to suggest that both soil genesis and management practice can contribute to areal 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.     

兴国县红壤颗粒分形及其与环境因子的关系

以土壤颗粒组成数据为基础，运用分形模型，分析了红壤丘陵山区林地土壤颗粒的分形维数。结果表明：84个耕层土壤颗粒的分形维数D为2．568～2．828，其中紫色土2．722，红壤2．700，棕红壤2．693，黄红壤2．670，黄壤2．713。D随土壤质地的变细而增大。从空间分布上看，研究区域的西部和东南部D值较大，而西南部和北部D值较小，D在2．7～2．8的面积最大，为1171km^2，占总面积的47．0％，D在2．8以上的面积最小，为48km。，占总面积的1．9％。土壤分维数和坡向、海拔之间呈显著正相关关系，而与坡度、平面曲率、剖面曲率之间无明显的相关关系。     

土壤水分特征曲线的分形模拟

Many empirical models have been developed to describe the soil water retention curve （SWRC）. In this study, a fractal model for SWRC was derived with a specially constructed Menger sponge to describe the fractal scaling behavior of soil; relationships were established among the fractal dimension of SWRC, the fractal dimension of soil mass, and soil texture; and the model was used to estimate SWRC with the estimated results being compared to experimental data for verification. The derived fractal model was in a power-law form, similar to the Brooks-Corey and Campbell empirical functions. Experimental data of particle size distribution （PSD）, texture, and soil water retention for 10 soils collected at different places in China were used to estimate the fractal dimension of SWRC and the mass fractal dimension. The fractal dimension of SWRC and the mass fractal dimension were linearly related. Also, both of the fractal dimensions were dependent on soil texture, i.e., clay and sand contents. Expressions were proposed to quantify the relationships. Based on the relationships, four methods were used to determine the fractal dimension of SWRC and the model was applied to estimate soil water content at a wide range of tension values. The estimated results compared well with the measured data having relative errors less than 10% for over 60% of the measurements. Thus, this model, estimating the fractal dimension using soil textural data, offered an alternative for predicting SWRC.