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基于模糊集理论提取土壤—地形定量关系及制图应用 总被引：8，自引：1，他引：8
通过对研究区地形因子的模糊聚类,提取了地形因子组合与特定土壤属性的定量隶属度关系,然后对隶属度高值区土壤进行目的性采样为隶属度函数赋值,制作研究区土层厚度连续分布图。通过野外实地验证,将观测值与图中预测值比较,结果显示该方法制图精度在82%左右,具有一定的可靠性。进一步考察认为该模型在地形部位较低,地势较为平坦,土壤发育较好,土层较厚,成土环境相对稳定的地区预测效果更好,适用性更强。该方法能提高土壤制图效率,降低制图成本,提高制图精度,对土壤微域变异的表现更为详细,图面信息负载量更高。应用该方法制作大比例尺土壤详图不失为土壤调查与制图领域一种可行的新方法。 相似文献
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基于54个土壤表层样品重金属全量浓度实验室测定数据,应用模糊c-均值算法对南京城市边缘带化工园附近20km^2样区内土壤重金属浓度进行了连续分类,对样点土壤的隶属度进行空间普通克里格插值,实现样区土壤重金属浓度和污染状况的空间预测.结果表明,样区土壤中重金属Cu、Zn、Cr、As和Cd的浓度均低于国家土壤环境质量标准,未发生污染;受工业、交通排放的影响,样区左侧和南部Cu、Zn、Cr、As较高,个别区域有Zn、Cr富集现象.Hg为样区主要的土壤重金属污染元素,土壤Hg污染主要发生在蔬菜基地及滁河流经区,较为严重的Hg污染土壤集中分布在样区中部的蔬菜基地.与利用样点测定数据直接插值的空间预测方法相比,基于模糊集理论的土壤污染空间预测方法可获得较好的预测效果. 相似文献
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Fuzzy classification methods for determining land suitability from soil profile observations and topography 总被引：6，自引：0，他引：6
Because conventional Boolean retrieval of soil survey data and logical models for assessing land suitability treat both spatial units and attribute value ranges as exactly specifiable quantities, they ignore the continuous nature of soil and landscape variation and uncertainties in measurement which can result in the misclassification of sites that just fail to match strictly defined requirements. This paper uses fuzzy classification to determine land suitability from (i) multivariate point observations of soil attributes, (ii) topographically controlled site drainage conditions, and (iii) minimum contiguous areas, and compares the results obtained with conventional Boolean methods. The methods are illustrated using data from the Alberta Agricultural Department experimental farm at Lacombe in Alberta, Canada. Data on site elevation and soil chemical and physical properties measured at 154 soil profiles were interpolated by ordinary block kriging to 15 m × 15 m cells on a 50 × 50 grid. The soil property data for each cell were classified by Boolean and fuzzy methods. The digital elevation model created by interpolating the elevation data was used to determine the surface drainage network and map it in terms of the numbers of cells draining through each cell on the grid. This map was reclassified to yield Boolean and fuzzy maps of surface wetness which were then intersected with the soil profile classes. The resulting classification maps were examined for contiguity to locate areas where a block of minimum size (45m × 45m) could be located successfully. In this study Boolean methods reject larger numbers of cells than fuzzy classification, and select cells that are insufficiently contiguous to meet the aims of the land classification. Fuzzy methods produce contiguous areas and reject less information at all stages of the analyses than Boolean methods. They are much better than Boolean methods for classification of continuous variation, such as the results of the drainage analysis. 相似文献
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Quantitative mapping of soil types based on regression kriging of taxonomic distances with landform and land cover attributes 总被引：4，自引：0，他引：4
Nowadays, French soil scientists tend to gather new and existing soil data into a common database. The use of this database potentially allows for resolving environmental issues, largely through soil mapping. The purpose of this study is to present a methodology for mapping soil types illustrated by typical observations in the soil database, in this case from the La Rochelle area on the French Mid-Atlantic Coast. The main hypothesis underlying the method is that soil types result from environmental factors such as landform, parent material, and land cover. The method can be divided into four stages. The first step is to construct a local soil type classification from the database by a two-stage continuous classification procedure. The result of this procedure is that at each observation point, the soil is described by a vector of taxonomic distances to each of k centroidal soil types. In the example given, k=18. The second step involves fitting soil–environment equations, one for each centroidal soil type, by regressing taxonomic distances on layers of multivariate environmental data observed on a fine 20-m grid, by multiple linear regression. In this case, the layers are terrain attributes derived from a digital elevation model and land cover attributes derived from three bands of a SPOT image. The third step is to predict k maps or raster GIS layers representing taxonomic distances to soil types on the 20-m grid, using the soil–environment equations and the kriging of the residuals from the regressions. This results in many potential maps: a summary map depicting the nearest centroidal soil type (the soil type for which the taxonomic distance is least) at each location is possibly the most useful, and another one representing the minimum taxonomic distance which, if considered too large, might suggest locations for further field survey to refine the soil types. A map of standard errors of the kriged taxonomic distance residuals to the nearest centroidal soil type can be made to indicate spatial uncertainty. Continuous fuzzy membership maps can also be constructed from the distances. The fourth step involves validation with an independent soil data set allowing discovery of the nature of the actual prediction errors. Thirty-eight percent of sites in a validation sample of 1234 sites was unequivocally validated, 23% was equivocally validated, and the remainder was predicted wrongly by the method. 相似文献
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基于RAGA的PPE模型在土壤质量等级评价中的应用研究 总被引：17，自引：0，他引：17
以往的土壤分类与等级综合评价多是建立在模糊数学 (Fuzzy)基础上的模糊聚类分析与模糊综合评判 ,因此不可避免的涉及权重矩阵人为干扰 ,导致分类与评价结果的人为倾向。本文将高维降维技术——投影寻踪评价模型 (PPE)应用到土壤学科领域 ,利用改进的加速遗传算法 (RAGA)优化投影方向 ,将多维数据指标转换到低维子空间 ,通过寻求最优投影方向及投影函数值来实现对土壤的分类与等级评价 ,避免了主观赋权的人为干扰 ,取得了较好效果 ,可为土壤分类与等级评价研究提供一条新思路 相似文献
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D. Zhu T. W. Wang C. F. Cai L. Li Z. H. Shi 《Land Degradation \u0026amp; Development》2009,20(6):654-666
Reliable and cost‐effective soil erosion assessment is an important precondition for soil conservation measures, which remains a major challenge at large scale. Considering that the neuro‐fuzzy model has the special advantage in multi‐index comprehensive assessment and GIS technology is adept at geo‐spatial information processing, through the combination of them, it is possible to provide an effective approach for this difficult problem. Taking Hubei Province as a case study area, five evaluating indicators were selected for the large‐scale assessment, in which the GIS technology was used to construct the classification maps of evaluating indicators and to divide basic assessment units, and the neuro‐fuzzy model was adopted to extract fuzzy rules for individual units assessment from available ground truth data. According to the optimized assessment criteria generated by the neuro‐fuzzy model, the soil erosion state of the entire study area was then assessed. To represent the spatial distribution of soil erosion, a detailed map was produced by statistical mapping, which was represented with six erosion levels (from slight to severe) at a map scale of 1:250 000. The resulting map showed that about 30.1% of the total land area in Hubei was affected by different levels of soil erosion problem. Western high mountains and eastern low mountains suffered from the most serious erosion damage, a strong level of soil erosion was widely observed in these mountains. Large areas of moderate level erosion occurred in the northern hills. In contrast, most of the central plains were characterized as slight level erosion effect. The validation indicated that an overall accuracy of 88% and a κ of 0.89 were achieved, proving that the resulting map was in conformity with actual conditions, which indicates this assessment approach was reasonable and applicable. Copyright © 2009 John Wiley & Sons, Ltd. 相似文献
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基于GIS技术的红壤资源划分与评估 总被引：18，自引：0，他引：18
A small scale red soil resources information system(RSRIS) with applied mathematical models was developed and applied in red soil resources(RSR) classification and evaluation,taking Zhejiang Province,a typical distribution area of red soil,as the study area.Computer-aided overlay was conductied to classifty RSR types.The evaluation was carried out by using three methods,i.e.,index summation,square root of index multiplication and fuzzy comprehensive assessment,with almost identical results,The result of index summation could represent the basic qualitatie condition of RSR,that of square root of index miltiplication reflected the real condition of RSR qualitative rank,while fuzzy comprehensive assessment could satisfactorily handle the relationship between the evaluation factors and the qualitative rank of RSR,and therefore it is a feasible method for RSR evaluation. 相似文献
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基于GIS和多种土壤属性的烟田养分分区管理研究 总被引：1，自引：0，他引：1
以平顶山典型烟区烟田土壤为研究对象,用111个样点耕层土壤（0 ~ 20 cm）的pH、有机质、总N、碱解N、速效P、速效K、活性有机质、阳离子交换量等数据对烟田进行管理分区研究。利用主成分分析从繁杂的数据中提取3个主成分,利用MZA软件进行模糊聚类分析从而实现分区,采用FPI和NCE来确定最佳分区数。结果表明研究区的最佳分区数为3,模糊指数为1.5。各分区内土壤养分的变异系数都较整个研究区有所降低,而分区间土壤养分差异显著。研究区的平均混乱度指数为0.37,不同模糊类别交叠程度较小,地理空间上土壤的隶属关系相对明确。通过模糊聚类分析法可以较好地进行管理分区的划分,分区结果可以作为变量施肥的单独作业单元进行肥料管理。 相似文献
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基于多源数据的盐碱地精确农作管理分区研究 总被引：3，自引：5，他引：3
为了便于对盐碱地实施变量管理和精确农作，以海涂围垦区盐碱土为研究对象，以NDVI数据、盐分数据以及作物产量数据作为分区变量，对一面积为15 hm2的盐碱地农田进行了基于多个数据源的精确农作管理分区研究。利用模糊c均值聚类方法进行分类分区，引入了模糊聚类指数(FPI)和归一化分类熵(NCE)作为最佳分区数目的判断标准，通过单项方差分析对分区结果进行比较和评价。研究发现，对本研究区，最佳的分区数目为三个。不同管理分区之间土壤化学性质(EC1:5,有机质，速效磷，速效钾，全氮，碱解氮以及阳离子交换量)的均值都存在着统计意义上的显著差异性，其中子区3具有最高的肥力水平和作物生产能力而子区1最低。利用所选取的三个变量，模糊c均值聚类算法可以较好地进行精确农作管理分区划分。分区结果不但可以指导采样, 而且可以作为变量管理的决策单元用于田间变量管理作业中,为精确农业变量投入的实施提供有效手段和决策依据。 相似文献
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《Communications in Soil Science and Plant Analysis》2012,43(12):1452-1464
ABSTRACTSoil texture is a key controlling factor of soil properties and its functions include water and nutrient holding capacity, retention of pollutants, root development, soil biodiversity, and biogeochemical cycling. From the geotechnical standpoint, it is interesting to analyze the soil texture in regions due to its relation with the infiltration and runoff processes and, consequently, the effect on erosion processes. The purpose of this study is to present a methodology that provides the soil texture spatial variation by using Fuzzy logic theory and geostatistical technique in Geographic Information System (GIS) platform. A total of 140 soil samples were taken from topsoil (0–30 cm) in the study area located in the north of Guilan Province, the southern coast of Caspian Sea, Northern Iran. The soil textural classes were converted to numerical values (fuzzy values) using the fuzzy logic concept. The fuzzy values were spatially interpolated by ordinary kriging method such that the fitted model on experimental semi-variogram was exponential with moderate structure. The results showed the accuracy of soil texture predictive map was acceptable according to the values of normalized root-mean-square error for train data set (0.182) and test data set (0.179). The knowledge of the spatial variability of soil properties such as the soil texture can be an important tool for land-use planning in order to reduce the potential soil losses during rainy seasons. The results indicated that the integration of fuzzy logic, geostatistics, and GIS can improve the interpolation process. 相似文献
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基于分类树方法的土壤有机质空间制图研究 总被引：6，自引：0，他引：6
以浙江省龙游县研究区为例 ,提供了一种推断和表达土壤有机质 (OM)含量空间分布信息的方法 ,通过一种数据挖掘方法———分类树建模方法将土壤OM含量与一些易于广泛观测的景观属性 ,包括地形、地质、土地利用和遥感影像建立联系 ,从而将有关土壤OM含量分布的知识转入一种清楚的、定量的、与景观因子相关联的规则系统中 ,并以此来预测研究区土壤OM水平的连续空间分布。树分析选取了高程、岩石类型、土属类型、PC4 、PC2 、土地利用类型、PC3、PC1、上坡贡献面积、坡度、坡向、平面曲率和剖面曲率来预测研究区土壤OM等级的分布。其中 ,高程、岩石类型、土属类型和反映植被覆盖度的PC4 、PC2 以及土地利用类型对于研究区土壤OM等级预测更为重要。从分析结果来看 ,依据分类树所划分出的景观类型与土壤OM含量有着较好的关联性 相似文献
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变量施肥对改善土壤养分空间差异性的综合评价 总被引：7，自引：4，他引：3
精准农业中一个非常重要的环节就是变量施肥,其核心思想是根据土壤中养分含量的多少来决定施肥量,以达到土壤养分平衡。目前通常对土壤养分情况评价的做法是分别考察每种土壤养分的变异情况,不能综合分析。因此,该文提出利用一种加权模糊聚类算法,综合评价经过变量施肥作业后土壤养分空间差异性的变化情况。通过对榆树市弓棚镇十三号村3号地未变量施肥、连续变量施肥2年和连续变量施肥5年的土壤养分进行综合分析比较,可知经过连续变量作业后土壤养分空间差异明显减小。 相似文献
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Colluvial soils are considered to be the direct result of accelerated soil erosion, resulting in accumulation of humus-rich soil material in terrain depressions and base parts of slopes. The organic carbon concentration in these soils and their depth make them an important organic carbon storage. Mapping the Colluvial soils, therefore, represents an important contribution in total carbon stock estimation. A method of delineating Colluvial soils is proposed by applying a combination of high resolution digital elevation model analysis and detailed field survey. Two models based on fuzzy classification of soil units were created using different topographic derivatives as the only input parameters to predict the Colluvial soil area on a morphologically diverse study site in the Southern Moravia, Czech Republic. The model that considers only the derivatives with a strong relationship to Colluvial soil occurrence reached 71% accuracy in Colluvial area delineation, while the model combining six commonly used derivatives showed less favorable results. The main advantage of the method lies in a low demand of input soil data and its relatively high accuracy. 相似文献
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Soil microbial properties are widely used as indicators of soil quality. The interpretation of soil microbial processes, however, is difficult because of their regional and seasonal heterogeneity as well as the lack of reference values. One possibility to overcome these limitations to apply the fuzzy set theory. This approach more realistically describes ecological systems because it considers natural ambiguity and complexity. The present study applies a fuzzy rule-based classification model to define soil quality based on soil microbial biomass, N-mineralisation, enzyme activity data (urease, xylanase, phosphatase, arylsulfatase) and soil organic matter. The data have been collected from different grassland sites in the European Union over a period of 20 years. The fuzzy model is based on a rule system derived from a training set using simulated annealing as an optimisation algorithm. For each variable, nine triangular fuzzy sets were defined for consideration as possible rule arguments. The model uses the t-norm for combination of arguments, product inference, the weighted sum as rule combination and the maximum method for defuzzification. The output is the assignment of membership of the object to a given soil quality class. The soil quality classes (very poor, poor, medium, high, very high) were defined by five heavy metal contamination levels (very high, high, medium, low, no). A predefined number of fuzzy rules were assessed using a simulated annealing algorithm. The fuzzy model was validated by a test file by assigning the soils to the quality class with the highest response value. The fuzzy model yielded an overall coincidence of 88.8% between observed and simulated results. The most sensitive index of soil quality was microbial biomass. N-mineralisation was a good indicator for the high-quality soils, while urease and arylsulfatase were important indicators for heavily contaminated, poor soil quality. Xylanase and phosphatase behaved ambivalently. Including soil organic carbon in the model decreased its effectiveness by 6.5%. We suggest that the presented fuzzy model based on soil microbial properties could be applied not only to soil degradation, upscaling and prediction, but also to judge the response of soils to environmental changes. 相似文献
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基于裸土期多时相遥感影像特征及最大似然法的土壤分类 总被引：6，自引：5，他引：1
运用单时相遥感数据进行土壤分类及制图,其数据本身易受到其他因素干扰而出现误差,存在一定的局限性,导致制图精度不高。为了提高制图精度,以松嫩平原林甸县为研究区,利用裸土时期多时相Landsat 8遥感影像、DEM数据和全国第二次土壤普查数据,从所有单时相遥感影像中提取出多种分类特征,按照分类特征类型进行压缩处理,得到新的多时相分类特征,将不同分类特征进行组合并分别进行最大似然法分类,得到不同分类特征组合下的土壤类型图,通过不同土壤类型图精度来判断各分类特征对于制图的影响。研究表明,该文所提取的分类特征均可以实现土壤制图,使用压缩处理后得到的多时相遥感数据分类特征完成制图的精度更高,总体精度达到91.0%,研究可为土壤精细制图提供依据。 相似文献
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运用分类树进行土壤类型自动制图的研究 总被引：1，自引：0，他引：1
提供了一种基于机器学习的方法来自动建立针对土壤资源制图的规则库。以浙江省龙游县研究区为例,将已有的土壤图与地质图、土地利用现状图、DEM及其派生属性、双时相的TM卫星数据相结合,使用分类树算法从训练数据中生成该地区土壤制图的规则知识,并进行了研究区土壤类型的知识分类。这种建立土壤自动制图知识库的方法要比传统的知识获取方法更为简便易行。精度评价结果表明,所建立的知识库对于研究区的大部分土壤类型的预测是可行的。 相似文献
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为了解决旋转式土槽试验台的槽体和槽内土壤质量较大带来速度不容易控制和调节的问题,建立轮胎摩擦驱动的旋转式土槽试验台的数学模型。根据旋转式土槽交流伺服驱动器的特点设计了模糊控制器,对模糊控制进行优化并进行MATLAB仿真、对比。当交流伺服驱动器初始输入转速为300 r/min时,优化前后土槽在模糊控制策略下输出转速最终都稳定在3 r/min;优化后模糊控制下的土槽输出转速超调量小,最大转速为3.4 r/min,比优化前的3.7减小0.3 r/min,土槽输出转速稳定在3 r/min的时间由优化前的9.0减少到8.0 s,后期无振荡。试验结果表明:当旋转式土槽交流伺服驱动器输入转速320 r/min时,土槽运行稳定性误差由模糊控制的0.034降低到优化模糊控制的0.029,土槽从启动到进入稳定运行的时间由10.1缩短到7.9 s。该研究可提升后续利用该种试验台进行移栽和播种等农业机械试验的精度。 相似文献