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1.
Estimates of mean values of soil properties within small rectangular blocks of land can be obtained by kriging provided the semi-variogram is known. This paper describes optimal rectangular grid sampling configurations whereby estimation variances can be minimized. For linear semi-variograms square blocks are best estimated by sampling at the nodes of a centrally placed grid with its interval equal to the block side divided by the square root of the sample size. For spherical semi-variograms the same configuration is almost optimal. The estimation variance of a bulked sample can be identical with that of a kriged estimate where the semi-variogram is linear and equal portions of soil are taken from each node on the optimally configured grid and provided the soil property is additive. For spherical semi-variograms the above is approximately true. Comparisons with estimates that take no account of known spatial dependence show that the true variances can be much less than those apparent using classical theory, and the necessary sampling effort much less. Within block-variances are often needed for planning, and an appendix gives two-dimensional auxiliary functions from which they can be calculated for linear and spherical semi-variograms. 相似文献
2.
Kriging is a means of spatial prediction that can be used for soil properties. It is a form of weighted local averaging. It is optimal in the sense that it provides estimates of values at unrecorded places without bias and with minimum and known variance. Isarithmic maps made by kriging are alternatives to conventional soil maps where properties can be measured at close spacings. Kriging depends on first computing an accurate semi-variogram, which measures the nature of spatial dependence for the property. Estimates of semi-variance are then used to determine the weights applied to the data when computing the averages, and are presented in the kriging equations. The method is applied to three sets of data from detailed soil surveys in Central Wales and Norfolk. Sodium content at Plas Gogerddan was shown to vary isotropically with a linear semi-variogram. Simple punctual kriging produced a map with intricate isarithms and fairly large estimation variance, attributed to a large nugget effect. Sloniness on the same land varied anisotropically with a linear semi-variogram. and again the estimation error of punctual kriging was fairly large. At Hole Farm. Norfolk, the thickness of cover loam varied isotropically, but with a spherical semi-variogram. Its parameters were estimated and used to krige point values and produce a map showing substantial short-range variation. 相似文献
3.
Soil testing is used to help make fertilizer recommendations for greater yields and profits. But the increase of soil‐sampling density raises costs of sample collection and analyses. The aim of this study was to compare grid‐cell sampling densities (1, 2, and 4 ha) in terms of the estimation accuracy of macronutrients (P, K, Mg) availability and pH and to investigate how sampling density affects the amount of fertilizers and lime recommended and correctly applied to winter wheat (Triticum aestivum L.). The distribution of liming requirements and available nutrients were quite similar for the 1‐ and 2‐ha grids but notably different for the 4‐ha grid. However, the whole‐field average values of pH and P, K, and Mg concentrations in soil obtained for different sampling densities were very similar, thus placing, respectively, the soil of the studied area in the same class of liming needs and nutrient availability. The range and estimation errors of these parameters decreased with sampling‐grid size increase. The amount of lime and fertilizers to be applied on the field and the portion of a field correctly limed or fertilized depended on the soil chemical property considered. If one treats the 1‐ha grid as the reference and the most correct soil‐sampling approach, 2‐ha grid offered the greatest part of the field to be adequately fertilized with lime, P, and K. However, fertilization with Mg was much more appropriate if the recommendation was based on 4‐ha, than on a 2‐ha soil‐sampling grid. To gain an insight into soil variation and soil process occurring at small scale, laboratory and geostatistical analyses on individual soil samples may be necessary in some cases. Possibly, such costly research can deliver relevant information which could be then applied into farmer's practice. 相似文献
4.
利用计算机模拟采样确定合理的土壤采样密度(英) 总被引：1，自引：1，他引：1
为了解决土壤采样中精度与经济性的平衡问题，利用计算机模拟采样研究了规则网格土壤采样时合理的采样点密度。首先构造了一个数学扩散模型，设置2～4个种子在一个100×100网格（1×1单位）的不同地方，根据扩散模型进行扩散和叠加，生成模拟的土壤属性分布地图，其结果可很好地模拟某些土壤属性的分布。利用计算机按照不同的网格单元尺寸（如3×3，5×5，7×7等）进行采样，之后利用采样值进行IDW插值处理，将数据点恢复到原始的10000个，并把插值结果与原始值进行比较即可得到采样误差。研究结果表明，当采样网格单元尺寸为属性地图输出栅格单元尺寸的11倍和17倍时，相对采样误差分别为10%和15%。合理的采样密度可以根据允许的采样误差及要求的属性地图输出栅格单元尺寸而定。 相似文献
5.
Optimal interpolation and isarithmic mapping of soil properties 总被引：3，自引：1，他引：3
The principle of optimal estimation using regionalized variable theory is extended from that of a single soil property to situations where there are two or more spatially interdependent ones. Auto and cross semi-variograms express the spatial relations among the properties concerned. They can be estimated from data and can then be used to interpolate the values of a variable by co-kriging from measurements of it plus data on one or more other properties that have been more intensively sampled. The technique of co-kriging is described and illustrated by a case study of the particle size distribution at Woburn experimental farm. There was a strong co-regionalization with common anisotropy between topsoil silt, subsoil silt and subsoil sand. This allowed topsoil silt to be estimated and mapped by co-kriging more precisely than by kriging from data on topsoil silt alone. When the auto and cross semi-variograms for a set of variables are known in advance or estimated from reconnaissance they can be used to plan an optimal sampling scheme. The main variable is sampled on a rectangular grid with finer grids for subsidiary variables. The maximum kriging variances are calculated for a range of sample spacings and relative sampling intensities. Those that match the maximum tolerable variance are potentially useful. The optimum scheme is the one that achieves the desired precision for least cost. For Woburn it is shown that measuring a main variable would need to cost at least 5 times that of a subsidiary variable to make a design for co-kriging economically sound. Such differences are unlikely for particle size fractions. Nevertheless there are many other instances in soil research where there are large differences in cost. If there is also a strong co-regionalization then savings should be possible by designing a sampling scheme that takes advantage of co-kriging. 相似文献
6.
This paper develops the concept of the quality of a soil map in terms of the proportion of soil boundaries that have remained undetected as a result of point sampling. This proportion is equated to the risk of omitting such boundaries during survey. A risk function is defined, and the optimal strategy is such that the risk is maintained at some predetermined acceptable level. In general the risk depends on the distribution of boundary spacings, the distance travelled from the last boundary and the projected sampling interval. Where the distribution is exponential, the position of the last encountered boundary is immaterial, and for a constant risk the sampling interval is also constant. The optimal strategy is a regular grid. The same principles enable the total sampling effort for a survey of constant risk to be forecast once the distributions of boundary spacings have been estimated from reconnaissance. The sampling effort for a risk of 0.1 is shown to be within the range of traditional practice. 相似文献
7.
不同采样设计会对土壤呼吸空间变异特征的预测精度产生重要影响。本研究选取黄淮海平原北部潮土区1 km×1 km夏玉米样地,在7×7单元规则格网(样点间距167 m)、完全随机(样点平均间距433 m)以及3×3单元规则格网+完全随机(样点平均间距405m)3种布点方式的基础上,保持样本总量(49)不变,以占总样点2%～14%的短距离样点(样点间距4m)随机替换原方案相应样点个数的方法优化布点方式,应用普通克里金法插值,以均方根误差(RMSE)和确定系数(R2)作为验证指标,检验基于3种布点方式设置的短距离样点对土壤呼吸空间变异预测精度的影响。结果表明:研究区土壤呼吸平均速率为2.65μmol·m?2·s?1,空间分布均呈西高东低,表现出中等程度变异。采样设计对土壤呼吸空间分布的预测精度影响显著,基于3种布点方式设置短距离样点可提高预测精度7%～13%。无短距离样点替换时,规则格网+完全随机的布点方式最优,比完全随机布点和规则格网布点的空间插值预测精度分别提高10%和22%;设置短距离样点替换后,在最优布点方式(规则格网+完全随机)中,对土壤呼吸空间变异的预测精度可再提高4%～7%,其中短距离样点个数占样本总量10%对土壤呼吸空间变异预测精度的提高最为明显。研究发现,基于相同的样本数量设置短距离样点可增加区域范围内样点密度,提高土壤呼吸空间变异预测精度及试验结果的可靠性。因此,在黄淮海平原北部潮土区100 hm2尺度的夏玉米样地中,规则格网+完全随机+10%短距离样点的布点方式是预测土壤呼吸空间变异最适宜的采样布点方式。 相似文献
8.
不同布点密度条件下土壤有机碳的空间变异特性 总被引：1，自引：0，他引：1
选择福建省漳州市三个不同尺度的典型区,在格网法采样的基础上设计6种不同分类方法和4种格网密度,研究不同尺度下高效表征耕地土壤有机碳空间变异的样点布设方式。研究结果表明:市级尺度(漳州市)高效的样点布设方法为结合地貌类型和土壤类型信息的分类格网法,样点密度以接近6 km×6 km为最节省的采样方法。县级(龙海市)尺度按土壤类型与格网法相结合的方法是高效的布点方式,土壤类型若仅划分到土类,格网密度需接近1 km×1 km;若土壤类型划分到亚类或土属,格网密度可放宽到2 km×2 km。乡镇级(程溪镇)最适合的样点布设方法是未分类格网法。由于土壤类型信息是表征土壤有机碳空间变异最重要的影响因素,因此建议在县级以上尺度进行土壤有机碳空间变异研究时应考虑到土壤类型的影响。 相似文献
9.
土壤参数的时空变异是实施精细农业时要考虑的重要因素，在土壤检测的栅格采样中有必要确定最优样本量。本研究的试验田是一块生长中的玉米地块，试验区的面积为4.2 m×4.2 m，该试验区被假定为土壤采样中的一个栅格，该栅格又被细分为49个0.6 m×0.6 m的子栅格。采样时，所分析的土壤参数为土壤硝态氮含量，从播种到收获共进行了7次采样。通过对土壤样本土壤硝态氮时空变异的分析，揭示了样本量和土壤硝态氮含量预测误差之间的相关关系。土壤硝态氮含量呈非正态分布，通过对玉米各个生长期获得的数据分析表明：含量水平的预测误差随深度的增加而增大；当从一个栅格只采集1个土壤样本时(样本量为1)，预测误差基本在50％左右(显著水平：α≈0.10)，而当从一个栅格采集5个土壤样本时(样本量为5)，预测误差将降至25％左右。另一方面，当要求预测误差低于30％时，对于普通生长条件下的土壤需要从1个栅格至少采集3个样本，而对于追肥后的土壤则至少需采集15个样本。 相似文献
10.
基于Kriging估计误差的县域耕地等级监测布样方法 总被引：7，自引：2，他引：5
为了监测耕地的质量等级,通常采取抽样调查的方法.由于空间样本间存在不独立性等原因,传统抽样方法效率低、精度不高.为此,该文提出基于Kriging估计误差的布样方法,定义了反映Kriging估计情况的统计量作为评估监测网的标准,通过分析样本量与抽样精度的变化趋势确定最优样本容量,将调整过的方形格网作为监测网的基础,在泰森多边形限制下对监测网优化增密,并选用部分标准样地作为监测点.以北京市大兴区为例对该方法进行验证,结果表明,当监测点数同为48时,该文方法均方根误差小于简单随机抽样、分层抽样以及单一使用格网布样的方法,预测总体均值的相对误差为0.07%.因此,该文方法使用较少的监测点反映县域耕地等级的分布状况和变化趋势,能够满足县域耕地等级监测的需求. 相似文献
11.
Geostatistics and its application to soil science 总被引：7，自引：0，他引：7
M.A. Oliver 《Soil Use and Management》1987,3(1):8-20
Abstract. Geostatistics is principally the application of regionalized variable theory. The methods it embodies are applicable throughout the earth sciences for investigating the spatial variation of, and for estimating continuous random variables. The semi-variogram is the central tool of geostatistics. It can quantify the scale and intensity of spatial variation and it provides the essential spatial information for local estimation by kriging and for optimizing sample intensity. It can also be used in an exploratory manner to try to discover underlying causes of the variation. Geostatistical methods have been widely applied in the mining industry and there are many examples of their application in soil science. Their use is illustrated by a case study of soil spatial variation in the Wyre Forest of England. 相似文献
12.
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
13.
We propose a general model for soil pH measurement that includes instrumental drift, random measurement error, and random and correlated spatial variation. Methods for estimating these four components are described in detail. For soil pH in water, instrumental drift, random measurement error and random spatial variation (nugget effect) were greater than the corresponding quantities for soil pH in CaCl2. For both pH measurements, instrumental drift was quite marked. Measurement error and nugget effect were of a similar size. A modified kriging method is presented that takes into account the four-component model proposed here. It is concluded that, for measuring soil chemical attributes, grid layouts should be supplemented by additional sites for the estimation of short-range variation, that laboratory sampling designs should include controls, and that field measurements should be adjusted for instrumental drift prior to being used for spatial contouring or kriging. 相似文献
14.
R. Earl J. C. Taylor G. A. Wood I. Bradley I. T. James T. Waine J. P. Welsh R. J. Godwin S. M. Knight 《Biosystems Engineering》2003,84(4):425-440
A fundamental component of adopting the concept of precision farming in practice is the ability to measure spatial variation in soil factors and assess the influence of this on crop variability in order to apply appropriate management strategies. The aim of this study was to appraise potential methods for measuring spatial variability in soil type, nutrient status and physical properties in practical farming situations. Five fields that are representative of more than 30% of soils used for arable production in England and Wales were selected for use as case studies. Maps of soil type were generated from a conventional hand-auger survey on a 100 m grid and the excavation of targeted soil profile pits. These were compared with those refined using a mechanised soil coring device and scans of electromagnetic inductance (EMI) carried out while the soil could reasonably be considered to be at, or near, field-capacity moisture content. In addition, soil sampling for nutrient analyses was conducted on a 50 m grid to examine the spatial variation in nutrient status. Conventional methods for sampling soil were found to be appropriate for identifying soil types at specific locations within the field sites, however, they were time-consuming to perform which placed an economic and therefore a practical limitation on the sampling density possible. The resulting data were considered to be too sparse for demarcating soil-type boundaries for use in the context of precision farming. The location of soil boundaries were refined by using the mechanised soil corer, however, the limitation of this was found to be the time required to analyse the soil cores produced. Maps of soil variation generated from EMI scans conducted at field capacity appear to reflect the underlying variation in soil type observed in maps generated using the mechanised soil corer and, therefore, this approach has potential as a cost-effective, data-rich, surrogate for measures of soil variability. Results from analyses of soil samples for measurement of nutrient status indicated that whilst there was considerable variation in macro- and micro-nutrient levels in each field, with the exception of pH, these levels were above commonly accepted agronomic limits. Results, however, did demonstrate the potential for addressing variation in critical factors such as pH at specific locations, however, there is a need to develop protocols for targeting sampling in order to reduce costs. 相似文献
15.
A series of five papers compares the cost-effectiveness of different procedures for soil survey at medium scale. The first three are presented here. The whole trial area of 120 km2 in Berkshire, in south-central England, was mapped in soil series by free survey at 1:25 000 for publication at 1:63 360. Three contrasting sample areas of 1.26 km2 were resurveyed to the same legend by free survey at 1:10 560, and by grid survey at a range of scales between 1:20 000 and 1:70 000, to both general purpose (soil series) and fifteen–twenty different single-property legends. The direct costs of producing each map were recorded. The study confirmed how much the free survey procedure depended on the external features of soil boundaries to locate them. The density of soil observations required to map soil series by free survey at the same map scale in different terrains was approximately proportional to the length of mapped boundary/km2, or to the number of separately mapped soil occurrences/km2. The density was least where the soil boundaries had the clearest external expression. Survey effort/km2 increased in proportion to the density of observations but was also affected by local differences in the ease of cross-country access, or in the effort necessary (by spade or auger) to identify the soil at a point. For soil series grid surveys there are approximately linear relations between log(cost) and log(map scale) with gradients between 1.3 and 1.7. A map of soil series by grid survey is more expensive than a map of the same units, based upon the same density of observations by the same surveyor, by free survey. But a series map by grid survey by a scientific assistant is cheaper than a series map based on the same density of soil observations by free survey by a scientific officer (diplomate or graduate). The cost of an isoline map of a single soil property depends very much upon the cost of determining the property mapped, and to some extent upon the number of different isoline maps produced from a single set of samples or observations. Even at the unusually low costs of chemical analyses assumed here, an isoline map of one chemical property costs nearly twice as much as a series map by grid survey. 相似文献
16.
考虑人为因素影响的重金属含量分析用土壤样品采集方法研究 总被引：1，自引：0，他引：1
合理布置土壤采样点是全面掌握重金属空间变异特征及变化趋势的重要环节。目前在土壤重金属相关研究中还是以网格化均匀采样为主的传统采样。然而,这些方法未能充分考虑采样的成本和代表性,无法满足高精度空间分析方法要求。本文基于人为影响因素进行重金属采样布局,通过筛选区域范围内影响土壤重金属的人为影响因素,利用核密度方法对影响因素进行指标量化,以半变异方差为目标函数,通过变程分析采样点的采样方案。本文以龙口北部平原区为典型研究区,选择了工矿企业密度（DI）和道路密度（DR）两种重要的人为因素指标,寻求土壤Hg元素的最佳采样点采集方案,最后通过基于不同间距的采样点分析来验证本文提出的采样方案的有效性。结果表明（1）DI与Hg在研究区南部和东北部区域具有相似的空间分布趋势,DR与Hg在研究区南部和东南部区域的空间分布趋势相似程度较大;（2）DI和DR的有效变程分别为5819 m、6079 m,与土壤数据Hg的变程（6000 m）也较为相近;（3）为了验证人为因素指标所求变程可以作为土壤Hg采样距离参考值,设置了不同采样间距的Hg实际采样方案（3000 m、4000 m、5000 m、6000 m和7000 m）,利用克里金插值精度（MSE、RMSDE）获取不同采样方案的重金属估测误差。对比不同采样间距发现,当采样间距 ≤ 6000 m时,不同采样间距之间的误差相差无几,而以7000 m作为采样间距时,误差却大幅增加。所以6000 m作为采样间距时,既能充分考虑采样的成本和代表性,也能满足高精度空间分析方法要求,而且这个数值与DI、DR所求变程（6000 m）相同,进一步证明了人为因素指标DI、DR所求变程具有Hg样本采集方案布局的参考价值。 相似文献
17.
18.
为研究土壤质地的合理取样方式,进而研究其空间变异情况,为田间施肥及灌溉提供依据,本试验利用地统计学方法和GIS技术,在重庆市彭水县重庆烟草试验站,利用289个表层土样,研究了16 m间距的栅格取样法(对照,253个土样,扣除36个验证样点)、34 m间距的栅格取样法(115个土样)和随机取样法(115个土样)3种取样方式下土壤质地的空间插值精度。3种土壤颗粒指标中粉粒占68.43%,砂粒含量最少,占12.68%,黏粒含量略高于砂粒。砂粒和黏粒具有中等强度的变异性,粉粒具弱变异性,且数据符合正态分布。地统计分析显示,在分析该区域土壤质地时,采用栅格取样方法应适当增大取样间距,而采用随机取样方法可适当缩小取样间距。交叉检验显示,土壤质地成分在3种取样方式下的插值精度均以对照最大,栅格取样次之,随机取样最小。综合考虑插值误差、样品采集和分析成本及时效性等因素,本研究建议在该区域进行土壤质地空间变异规律分析为生产服务时应采用随机取样。 相似文献
19.
县域尺度土壤有机碳储量估算的样点密度优化 总被引：4，自引：0，他引：4
县域是我国国家尺度土壤碳库估算的基本地域单元,合理的土壤样品采集密度是保证估算精度要求的基础。以桃源县为例,设置4.70、0.90、0.60、0.40、0.25、0.15、0.10和0.05个km-2共8个样点密度梯度,利用经典统计学和地统计学方法,研究样点密度对县域尺度土壤有机碳库估算精度的影响。经典统计表明,随着样点密度的降低,重复抽样下土壤有机碳均值及其变异系数的波动逐渐增大,标准误差呈幂函数增加(Y=0.025X-0.47,R2=0.97,p0.01)。地统计学分析表明,随着样点密度的降低,块金值和基底效应逐渐增加,偏基台、变程和决定系数的波动幅度逐渐增大,拟合残差呈幂函数增加(Y=0.001 4X-1.66,R2=0.56,p0.05);土壤有机碳空间分布的局部差异逐渐被弱化,重复抽样下县域土壤有机碳库储量及其平均误差的波动逐渐增强,均方根误差呈幂函数增加(Y=0.77X-0.05,R2=0.59,p0.05)。从整体上看,样点密度小于0.15个km-2时,以上变化均急剧增强,土壤碳储量估算的精度快速降低。因此,综合科学、高效和经济方面的考虑,估算县域农田表层土壤有机碳储量的最佳样点密度为0.15个km-2。本研究结果可为开展区域尺度土壤有机碳野外调查提供辅助支持。 相似文献
20.
Weixia Sun Yongcun Zhao Biao Huang Xuezheng Shi Jeremy Landon Darilek Jinsong Yang Zhigang Wang Beier Zhang 《植物养料与土壤学杂志》2012,175(5):671-680
An extensive knowledge of how sampling density affects soil organic C (SOC) estimation at regional scale is imperative to reduce uncertainty to a meaningful confidence level and aid in the development of sampling schemes that are both rational and economical. Using kriging prediction, this paper examined the effect of sampling density on regional SOC‐concentration estimations in cultivated topsoils at six scales in a 990 km2 area of Yucheng County, a typical region in the N China Plain. Except the original data set (n = 394), five other sampling densities were recalculated using grids of 8 km × 8 km (n = 28), 8 km × 4 km (n = 44), 4 km × 4 km (n = 82), 4 km × 2 km (n = 142), and 2 km × 2 km (n = 257), respectively. Experimental SOC semivariances and kriging interpolations at six sampling density scales were calculated and modeled to estimate regional SOC variability. Accuracy of the effects of the five sampling densities on regional SOC estimations was assessed using the indices of mean error (ME) and root mean square error (RMSE) with 100 independent validation samples. By comparison with the kriged grid map derived from the 394 samples data set, the relative error (RE,%) was spatially calculated to highlight the spatial variability of prediction errors at five sampling‐density scales due to the intrinsic limitations of ME and RMSE in accuracy assessment. The results indicated that sampling density significantly affected the estimation of regional SOC concentration. Particularly when the sampling density was < 4 km × 4 km, the large spatial variation of SOC was concealed. Semivariance analysis indicated that different sampling density had significant effect on reasonable detection of the dominant factors which influenced SOC spatial variation. Greater sampling density could more exactly reveal regional SOC variation caused by human management. The prediction accuracy for regional SOC estimation increased with the increasing of sampling density. The critical areas with larger RE values should be intensified in the future sampling scheme, and the areas of lower RE values should be decreased relatively. A specific sampling scheme should be considered in accordance with the demand to the estimation accuracy of regional SOC stock at a certain confidence level. Our results will facilitate a better understanding of the effect of sampling density on regional SOC estimation for future sampling schemes by providing meaningful confidence levels. 相似文献