基于空间变异修正普通克里金的矿区复杂地形高精度建模     

于广婷  刘同文  王琦  潘懋  李涛  宋冠涵  刘善伟 《测绘通报》2022,(11):106-111

普通克里金法是构建矿区三维地形模型并揭示地表沉陷形变场动态变化规律的有效方法。但普通克里金法存在平滑效应的问题,导致估计值的空间变异程度小于实际,无法真实反映矿区复杂地表形态的空间变化特征。本文结合矿区实际地形采样数据,提出了一种空间变异修正的普通克里金法,并将其应用于矿区复杂地形的高精度建模,并与已有方法在建模精度和空间变异性复现方面进行了对比分析。研究结果表明,空间变异修正的普通克里金法能够很好地处理平滑效应对建模的影响,具有更高的建模精度和空间变异性复现能力,在矿区复杂地形高精度建模应用中具有较强的适用性,可以作为一种可靠的建模工具用于矿区复杂地形沉陷形变场动态变化规律分析。  相似文献   

实验变差函数计算方法的研究与运用   总被引：1，自引：0，他引：1  

李章林  王平  李冬梅 《国土资源信息化》2008,(2):10-14

本文系统、详尽地分析讨论了不同样品数据条件下实验变差函数的计算方法。在实验变差函数计算流程的设计和有效样品搜索域的确定方面提出了自己独特的见解。最后用一个矿山的控矿工程教据对文中介绍的方法进行了测试。结果表明,利用本文的方法,容易得到稳健、准确、信息量高的实验变差函数。  相似文献   

Spatial Variability of Rock Depth in Bangalore Using Geostatistical, Neural Network and Support Vector Machine Models     

T. G. Sitharam  Pijush Samui  P. Anbazhagan 《Geotechnical and Geological Engineering》2008,26(5):503-517

Geospatial technology is increasing in demand for many applications in geosciences. Spatial variability of the bed/hard rock is vital for many applications in geotechnical and earthquake engineering problems such as design of deep foundations, site amplification, ground response studies, liquefaction, microzonation etc. In this paper, reduced level of rock at Bangalore, India is arrived from the 652 boreholes data in the area covering 220 km². In the context of prediction of reduced level of rock in the subsurface of Bangalore and to study the spatial variability of the rock depth, Geostatistical model based on Ordinary Kriging technique, Artificial Neural Network (ANN) and Support Vector Machine (SVM) models have been developed. In Ordinary Kriging, the knowledge of the semi-variogram of the reduced level of rock from 652 points in Bangalore is used to predict the reduced level of rock at any point in the subsurface of the Bangalore, where field measurements are not available. A new type of cross-validation analysis developed proves the robustness of the Ordinary Kriging model. ANN model based on multi layer perceptrons (MLPs) that are trained with Levenberg–Marquardt backpropagation algorithm has been adopted to train the model with 90% of the data available. The SVM is a novel type of learning machine based on statistical learning theory, uses regression technique by introducing loss function has been used to predict the reduced level of rock from a large set of data. In this study, a comparative study of three numerical models to predict reduced level of rock has been presented and discussed.  相似文献   

Geostatistical estimation of chemical contamination in stream sediments: The case study of Vale das Gatas mine (northern Portugal)     

A.R. Salgueiro  P. Freire vila  H. Garcia Pereira  J.M. Santos Oliveira 《Journal of Geochemical Exploration》2008,98(1-2):15

Based on an environmental geochemistry case study carried out in the neighbourhood of a W–Sn abandoned mine, the pollution in stream sediments was modelled through a Global Contamination Index. Such an index permits one to summarize the combination of deleterious elements in a single variable, obtained by the projection of samples onto the first axis of a PCASD (Principal Components Analysis of Standardized Data) applied to the entire n × p matrix containing the available concentrations of p = 16 elements in the set of n = 220 collected samples.In order to provide a sound basis for a coherent planning of the remediation process which will be put in operation in the affected area, it is necessary to balance the costs of reclaiming with the probabilities of exceeding the upper limits accepted for concentrations of environmentally harmful elements in sediments. Given these limits, they are back-transformed in the index values, providing a practical threshold between ‘clean’ and ‘contaminated’ samples. On the other hand, the minimum dimension of the cell to be reclaimed is restrained by the selected remediation process to be applied in the affected area. Hence, to meet the constraints of such a remediation process, it is required to estimate the probabilities of exceeding the index threshold in technologically meaningful sub-areas. For this end, the Indicator Block Kriging technique was applied, producing a series of maps where sub-areas to be reclaimed can be spotted for different probability levels. These maps, on which the decision making remediation agency can rely for its cost-benefit analysis, take into account both the spatial structure of ‘clean’ vs. ‘contaminated’ samples and the constraints of the reclaiming process.  相似文献   

Triple diagram method for the prediction of wave height and period   总被引：1，自引：0，他引：1  

Mehmet zger  Zekai en 《Ocean Engineering》2007,34(7):1060-1068

Many formulations have been developed so far to predict the wave height and period from fetch length and wind blowing duration for a constant wind speed. This study aimed to predict wave parameters from fetch length and meteorological factors by using triple diagram methodology based on Kriging principles. Proposed model results were compared with Joint North Sea Wave Project (JONSWAP) model which is used so commonly in the ocean and coastal engineering studies. For the implementation of the methodology hourly wave and wind data were obtained from a buoy located in Lake Ontario. Numerical and graphical comparisons demonstrated that the proposed method outperforms the classical formulation.  相似文献   

利用端元光谱内插的青海植被覆盖度估算研究     

杜英坤  燕琴  童李霞  王晓波 《测绘科学》2016,41(9):87-90,169

针对利用像元二分模型估算植被覆盖度的精度不高的问题,该文基于OSAVI,提出了选定模型参数(OSAVIs和OSAVIv)的方法,并将该方法应用于青海省植被覆盖度估算。该方法通过高分辨率影像在研究区内选取纯裸地和纯植被样点,并将纯裸地样点的OSAVI作为纯裸地样点像元的OSAVIs,将纯植被样点的OSAVI作为纯植被样点像元的OSAVIv,利用样点像元的OSAVIs和OSAVIv值,通过普通克里金内插法,求得研究区每个像元对应的OSAVIs和OSAVIv。经精度验证结果表明:此方法较常规的参数选取方法,RMSE由0.170降至0.156,MAE由0.137降至0.124。经进一步分析表明,此方法对边缘验证点和非边缘验证点的估算精度都有所提高,由于配准误差和周围地表漫反射的影响,边缘验证点的估算精度低于对非边缘验证点的估算精度。  相似文献   

Estimation of transit trip production using Factorial Kriging with External Drift: an aggregated data case study     

Anabele Lindner  Cira Souza Pitombo  Samille Santos Rocha  José Alberto Quintanilha 《地球空间信息科学学报》2016,19(4):245-254

Studies in transportation planning routinely use data in which location attributes are an important source of information. Thus, using spatial attributes in urban travel forecasting models seems reasonable. The main objective of this paper is to estimate transit trip production using Factorial Kriging with External Drift (FKED) through an aggregated data case study of Traffic Analysis Zones in São Paulo city, Brazil. The method consists of a sequential application of Principal Components Analysis (PCA) and Kriging with External Drift (KED). The traditional Linear Regression (LR) model was adopted with the aim of validating the proposed method. The results show that PCA summarizes and combines 23 socioeconomic variables using 4 components. The first component is introduced in KED, as secondary information, to estimate transit trip production by public transport in geographic coordinates where there is no prior knowledge of the values. Cross-validation for the FKED model presented high values of the correlation coefficient between estimated and observed values. Moreover, low error values were observed. The accuracy of the LR model was similar to FKED. However, the proposed method is able to map the transit trip production in several geographical coordinates of non-sampled values.  相似文献   

区域地下水动态观测网优化的组合克立金方法     

仵彦卿 《地球科学与环境学报》1995,(1)

本文推导出了普通二变量及泛二变量组合克立金方程式．同时，给出了两种方法的估计误差标准差求解方程，可用于地下水动态观测网的密度优化；该方法还可用于地下水位、水中离子浓度的最优估计．  相似文献   

基于改进的Kriging法区域似大地水准面精化分析     

候宗祥 《全球定位系统》2014,(6):94-96

区域似大地水准面精化研究主要是用于测绘学科,将精化结果应用到绘制地形图中,减少户外工作量,降低人力成本。传统采用的Kriging法在精化时会出现误差,精度值不达标。所以,改用了一种基于已知的拟合残差进行计算的改进方法重新精化研究。将改进的Kriging法与传统的Kriging法对比后,改进后的方法精化结果的拟合精度明显要高于传统方法。  相似文献   

基于块克里金的土壤水分点观测向像元尺度的尺度上推研究   总被引：3，自引：1，他引：2  

冉有华  李新 《冰川冻土》2009,31(2):275-283

土壤水分是陆面水文过程的一个重要分量,土壤水分的地面点观测与卫星观测的尺度是不匹配的,用点观测数据进行遥感反演结果的验证或者融合这两种观测都需要开展点观测数据向卫星像元尺度的尺度上推研究.土壤水分时空异质性的分析和描述是进行尺度上推的基础,地统计方法是描述连续随机变量空间结构的经典方法.应用块克里金法分别将黑河寒区遥感试验阿柔试验区2008年4月1日与L波段微波辐射计同步的地面液态含水量和含冰量点观测数据经过尺度转换,得到与遥感像元相匹配的像元平均估计值和标准差,可用于该天L波段微波辐射计土壤液态含水量和含冰量反演结果的真实性检验,估计结果充分利用了像元临近位置的观测,得到了比直接的采样平均更合理的块估计结果,对块克里金估计值与采样平均值进行比较,发现两种结果趋势是一致的,块克里金法提供了更为合理的块估计结果,土壤水分空间结构的时间变异、小尺度的土壤特性的变化和测量误差都会对估计结果带来一定的不确定性.  相似文献