共查询到19条相似文献，搜索用时 218 毫秒
1.
基于地学信息的土壤属性高精度曲面建模 总被引：5，自引：1，他引：4
目前土壤属性的曲面建模面临两大问题,一是缺乏足够多的采样点进行模拟,二是采样点的土壤属性与环境变量间存在非线性关系。高精度曲面建模(HASM)方法在如何融合地学信息对土壤属性进行空间插值,尚需深入研究。本文提出高精度曲面建模与地学信息相结合的土壤属性空间插值方法(High accuracy surface modeling for soil properties, HASM-SP),分别基于研究区的土壤类型、土地利用类型和母岩类型,模拟了江西省典型红壤丘陵区土壤的速效磷(AP)、锂(Li)、pH、碱解氮(AN)、全钾(K) 和铬(Cr) 6 种土壤属性的空间分布。将HASM-SP与普通克立格(OK)、OK与地学信息相结合的方法(OK-Geo) 和分层克立格(SK) 相对比,结果表明：结合地学信息可以使插值方法(HASM-SP和OK-Geo) 模拟结果的平均误差更趋近于0;相对于其他3 种方法,HASM-SP具有较小的平均绝对误差和均方根误差。从模拟的空间分布图上来看,HASM-SP获得了由于地学要素类型突变导致的土壤属性空间变异的细节信息。因此,基于地学信息的土壤属性高精度曲面建模方法(HASM-SP) 与传统插值方法相比,不仅提高了土壤属性空间分布的模拟精度,还能更好地刻画突变边界处土壤属性的空间变异,使土壤属性分布图更好地符合地学规律和实际情况。HASM-SP的提出对于丰富土壤属性的高精度曲面建模理论具有重要意义,并为土壤管理、精准农业的实施以及区域环境规划等提供科学依据。 相似文献
2.
喀斯特地区春季土壤水分空间插值方法对比 总被引：1，自引：0，他引：1
以杨眉河小流域为研究区,通过土壤水分采样,选取辅助变量,采用普通克里金、协同克里金、回归克里金3种地统计学方法对土壤水分数据进行空间插值。结果表明：1）回归克里金对研究区土壤水分估算误差最小,其次为协克里金,普通克里金的误差最大;2）普通克里金生成的土壤水分表面最为平滑,而回归克里金最大程度反映了研究区实际的土壤水分空间变化;3）对于协同克里金,以湿度指数（WI）样点数据作为辅助变量的估算误差小于将WI栅格数据作为辅助变量的估算误差。总之,在可获得有效辅助变量的条件下,回归克里金对研究区土壤水分估算的效果优于协同克里金与普通克里金。 相似文献
3.
癌症已成为危害全球居民健康的重大民生问题,选取合适的空间插值方法分析小区域癌症数据的空间特征可对区域性癌症防控工作的有效开展提供依据。本研究以湖南省苏仙区2012和2016年以村为单位的肺癌死亡率数据为研究对象,以平均误差和均方根误差为评价指标,对反距离加权（IDW）、普通克里金（OK）、趋势面分析（TSA）、多元线性回归（MLR）与协同克里金（CK）五种典型空间插值方法进行精度效果对比及参数优选,并结合不同插值方法的优缺点,确定癌症数据的最优插值方法。结果表明：插值精度方面,CK法的均方根误差最小、插值精度最高,OK、IDW（幂值=1）和MLR次之,TSA（阶数=5）最低;插值效果方面,五种插值方法的实测值和预测值均显著相关,除CK外,其它四种方法均对死亡率低估程度较大,CK和OK插值结果的空间分布效果更好。同时考虑空间因素和影响因子的CK方法是小区域苏仙区2012年、2016年肺癌死亡率最优插值方法,应用该方法可对区域性癌症防控工作的有效开展提供最优的技术支撑。本论文的研究思路也可为小区域癌症数据空间插值方法及参数优选提供参考。 相似文献
4.
以松花江干流哈尔滨段水体中悬浮物为研究对象,2012年7月14~15日,设置了11个采样断面,共33个采样点,测量得到总悬浮物含量和江面高光谱反射率数据;选用时间上较为接近的TM影像,分别用遥感反演模型(PSO-LSSVM模型)和克里格空间插值方法,对总悬浮物含量进行预测,并对使用两种方法的结果进行比较。结果表明,使用两种方法的结果的预测精度较为接近,遥感反演模型预测值的平均绝对百分误差为11.21%,均方根误差为10.05 mg/L;克里格空间插值预测结果的平均绝对百分误差为11.32%,均方根误差为10.93 mg/L;遥感反演模型预测值能较好的反映出松花江干流哈尔滨段总悬浮物含量的总体分布特征和变异特征;克里格空间插值对空间自相关小范围内具有较好的预测能力,超出自相关范围不能预测。 相似文献
5.
《干旱区地理》2021,44(4):1114-1124
协同环境变量与机器学习回归模型构建土壤有机质空间预测组合模型对养分精准管理具有重要意义,而多维变量间的信息冗余和相关性会导致模型训练时间过长、预测精度降低等问题。以陕西省咸阳市农耕区为例,选取高程、坡向、坡度、剖面曲率、平面曲率、地形起伏度、地形湿度指数、年均降水量、年均气温、归一化植被指数共10个环境变量,在主成分分析(Principal compo-nent analysis,PCA)、核主成分分析(Kernel principal component analysis,KPCA)方法特征提取基础上,组合随机森林(Random forest,RF)、支持向量回归机(Support vector regression,SVR)、K最近邻(K-nearest neighbor,KNN)机器学习模型进行土壤有机质含量空间预测。以单一模型作为对照,通过计算模型决定系数(Coefficient of determination,R~2)、均方根误差(Root mean square error,RMSE)和相对绝对误差(Relative absolute error,RAE),对不同模型的预测结果进行精度评价。结果表明:利用主成分提取方法和机器学习算法构建组合模型能消除变量间相关性,一定程度上提高土壤有机质含量预测模型精度。KPCA-RF模型对SOM含量预测精度高于其他模型,R~2、RMSE、RAE分别为0.791、1.970 g·kg~(-1)、50.100%,该模型良好的预测能力可以为土壤有机质含量的空间预测与制图提供科学依据。 相似文献
6.
耕地土壤速效钾含量的空间预测方法研究 总被引：1，自引：0，他引：1
利用插值方法进行土壤属性的空间预测是土壤学科的研究热点之一,以土壤发生学相关信息作为辅助变量的克里格空间插值方法则少有研究。该文以成土母质多样的湖南省石门县为例,基于GS+、ArcGIS和Matlab,结合成土母质信息的克里格(PMK)插值方法,对研究区土壤速效钾空间分布进行了预测。结果表明,PMK法较好地解决了因成土母质间速效钾含量差异给预测带来的误差,预测精度较反距离权重(IDW)、普通克里格(OK)法分别提高了21.68%、16.43%;PMK法制作的空间预测图中速效钾分布突变而非渐变,较IDW、OK预测结果接近研究区实际情况,进而证明在成土母质较为复杂的地区,PMK法适合对土壤速效钾含量的预测。 相似文献
7.
TRMM3B42降水产品在鄱阳湖流域梅川江子流域的精度评价(英文) 总被引：1，自引：0，他引：1
在鄱阳湖流域的梅川江子流域,利用52个站点9年(2001-2005及2007-2010)的日降水数据对V6和V7两个版本的TRMM 3B42降水产品进行了精度评价。该评价针对多个时空尺度进行,包括栅格和流域两个空间尺度,日、月和年三个时间尺度。为避免尺度不匹配问题,本文利用泰森多边形方法将点尺度的站点观测数据转换到与TRMM数据相同的栅格尺度。评价结果表明,V6和V7两个版本的TRMM3B42降水产品差别较小,整体上均轻微高估了降水量(偏差均为0.04)。在日尺度,栅格和流域空间尺度上V6和V7TRMM3B42降水产品的精度均较差,相对均方根误差在135%-199%之间。因此,在该地区利用3B42数据进行日尺度的水文分析前需要对其进行校正。在月和年尺度,栅格和流域两个空间尺度上V6和V7两个版本的TRMM 3B42降水产品精度均较高,决定系数达到0.91-0.99,相对均方根误差在4%-23%之间。这表明TRMM 3B42降水产品在该地区月和年尺度的水文分析方面具有很好的应用前景。 相似文献
8.
通过引入土壤水分可供率因子修正双层遥感蒸散模型中的植被剩余阻抗,以改进表层土壤含水量较小时的植被显热通量估算,并与美国Walnut Gulch流域两个地表通量站的观测值进行比较。实验结果表明:土壤水分可供率遥感估算值与实测波文比换算值的相关系数R2均大于0.84;引入土壤水分可供率改进后的显热通量估算值与实测值的相关系数R提高了0.34;均方根误差在两个通量站分别减少73.5W/m2和97.2W/m2,相对均方根误差均减小15%以上。结合土壤水分可供率的显热通量估算方法能够有效提高估算精度。 相似文献
9.
利用2010-2014年6~8月MOD10A1、MOD10A2及HJ-1/CCD数据,以天山北坡为研究区,对比分析了积雪持续时间比率法及最大值合成法在雪线高程提取中的精度和适用性。结果表明:当MOD10A1以旬合成,积雪持续时间比率阈值为40%时,提取的雪线高程与"真值"最为接近;基于混淆矩阵法,以目视解译得到的HJ-1/CCD积雪面积为"真值",分析得出,积雪持续时间比率法提取积雪面积的总体精度较高,为98.59%,khat系数为0.90,最大值合成法的总体精度仅为85.29%,khat系数为0.70;基于统计学的方法,计算得出,积雪持续时间比率法提取的雪线高程与"真值"的相关系数较高,为0.77,其平均误差、正、负误差、绝对平均误差以及均方根误差相对较低;最大值合成法提取的雪线高程与"真值"的相关系数较低,仅为0.54,其平均误差、正、负误差、绝对平均误差以及均方根误差相对较高;积雪持续时间比率法提取的雪线高程结果优于最大值合成法。 相似文献
10.
由于光学遥感穿透性差,不能穿透林冠层识别林下植被,基于单一光学遥感提取的植被覆盖度,难以反映林下植被信息,从而无法为土壤侵蚀评价提供有效植被覆盖因子。针对此问题,本文以白洋淀–大清河流域为研究对象,结合实测数据,探究不同光子点分类下光子计数ICESat-2/ATLAS植被覆盖度采样的能力,并实现了研究区内星地协同植被覆盖度采样。在此基础上,联合Sentinel-2和Sentinel-1以及DEM等多源数据,基于随机森林回归模型方法实现植被覆盖度反演,并与传统常用的NDVI像元二分法提取结果进行对比。结果表明：相比于传统的NDVI像元二分法提取的反演结果,利用本研究中构建的随机森林回归模型估算的植被覆盖度精度更高,一定程度上可以对茂密森林的林下植被进行监测,避免了光学遥感存在的林下植被信号缺失的问题。在0.05、0.1和0.15不同的植被覆盖度误差容忍范围内,精度分别提升–4.1%、5.3%和9.4%,分别达到55.6%、71.1%和94.3%。 相似文献
11.
利用不同方法估测土壤有机质及其对采样数的敏感性分析 总被引：7，自引：5，他引：2
用随机方法从262个采样点中抽取200个点作为已知有机质含量的数据集,将所有采样点的碱解氮作为辅助数据预测有机质的空间分布。利用有机质信息的普通克立格法的方差解释量和预测精度最低,而回归克立格法因在预测过程中加入了回归残差而使方差解释量最大、预测精度最高。为了分析采样数对不同方法预测精度的影响,从上述已知有机质含量的200个点中分别随机抽取40、80、120、160个点构成4个数据集,分别利用它们的有机质信息和不同方法预测了有机质的空间分布,结果表明:对于每个数据集,4种方法的预测精度顺序均为RGK>COK>RG>OK,线性回归法的预测精度随采样点的增加基本不变,而其它三种方法的预测精度却逐渐提高。 相似文献
12.
Several alternative estimation and interpolation methods for making annual precipitation maps of Asturias are analysed. The
data series in this study corresponds to the year 2003. There exists an evident relationship between precipitation and altitude,
with a high correlation coefficient of 0.70, that reflects the hillside effect; that is, the increase in the amount of precipitation
in more mountainous areas. The direct spatial variability of precipitation and of altitude and the cross variability of precipitation–altitude
are defined by two exponential variogram models: one with a short-range structure (15–30 km) that reflects the control exerted
by the lesser, local mountain ranges over the amount of precipitation; and another with a long-range structure (80 km) that
supposes the influence over precipitation of the major mountainous alignments of the inland areas of the Cantabrian Mountain
Range (Cordillera Cantábrica) situated between 60 and 90 km from the coastline. These variogram models had to be validated for coregionalization by the
Pardo-Igúzquiza and Dowd method so as to be able to make the cokriging map. The geometric estimation methods employed were
triangulation and inverse distance. The geostatistical estimation methods developed were simple kriging, ordinary kriging,
kriging with a trend model (universal kriging), lognormal kriging, and cokriging. In all of these methods, a 3 × 3 km2 grid was selected with a total of 2580 points to estimate, a circular search window of 60 km, and a relatively small number
of samples with the aim of highlighting the local features and variations on isohyet maps. The kriging methods were implemented
using the WinGslib software, incorporating two specific programs, Prog2 and Fichsurf, so as to be able then to make isohyet
maps using the Surfer software. All the methods employed, apart from triangulation, rendered realistic maps with good fits
to the values of the original data (precipitation) of the sample maps. The problem with triangulation lies not in the reliability
of the estimates but in the fact that it gives rise to contrived maps because of the tendency of isohyets to present abundant
triangular facets. The reliability of the methods was based on cross-validation analysis and on evaluation of the different
types of errors, both in their values and in their graphical representations. Substantial differences were not found in the
values of the errors that might discriminate some methods from others in an evident way. Bearing the aforesaid in mind, should
we have to make an evaluation of the different estimation methods in decreasing order of acceptance, this would be: kriging
with a trend model, inverse distance, cokriging, lognormal kriging, ordinary kriging, simple kriging, and triangulation. The
application of other estimation methods such as colocated cokriging, kriging with an external drift, and kriging of variable
local means (residual kriging) is dependent on the availability of a digital model of the terrain with an altitude grid of
the region. 相似文献
13.
Michael Kuntz 《International journal of geographical information science》2014,28(9):1904-1921
Small-sized housing samples and price predictions at nonobserved locations require geostatistical approaches, particularly the kriging estimator. Nevertheless, geostatistics has thus far received little attention in real estate economics. The article’s objective is to empirically compare the prediction accuracy of univariate kriging variants, namely detrended kriging (DK) and universal kriging (UK), and multivariate extensions, including detrended cokriging (DCK) and universal cokriging (UCK). Both latter methods consider structural and neighborhood characteristics as auxiliary variables. While the price surfaces of DK and UK show nearly identical cross-validated accuracies, the cross-validation-based prediction accuracy of DCK and UCK differ in favor of the latter. If real estate agencies are faced with a univariate sample of property prices, either DK or UK can be used, while in the multivariate case, UCK is recommended, although numerically more complex. 相似文献
14.
A treatise on the use of geostatistics for the characterization of nonrenewable resources 总被引：1，自引：0，他引：1
James R. Carr 《Natural Resources Research》1992,1(1):61-73
Five decades of geostatistical development are reviewed to summarize the state of the art for spatial interpolation vis-à-vis kriging or a form thereof. Although a search of the literature reveals a variety of kriging methods, there are but two infrastructures for geostatistical interpolation: simple cokriging, for estimating a single variable using two variables, and generalized cokriging, for estimating one or more variables using the same number of variables that are estimated. The many forms of kriging are varieties of these two interpolation infrastructures. This notion is emphasized to aid the selection of an appropriate interpolation model for a nonrenewable resource. These models are discussed, and literature for the models and for applicable software is cited. Additionally, all aspects of spatial interpolation are discussed, including the adequacy of spatial sampling, distribution characteristics of spatial samples, semivariograms, search parameters, and selection of interpolation models in conformance with spatial data characteristics. Finally, the relationship between interpolation and raster-based geographic information systems is emphasized. 相似文献
15.
Generally, multiple variables are sampled in addition to the one used to quantify the main phenomenon under study. In some
situations, this secondary information is sampled exhaustively for the study area and can be incorporated for helping in estimating
the variable of interest. There are several methodologies available for incorporating densely sampled secondary information.
Collocated cokriging is one of these methodologies and has the advantage to other methodologies, of accounting for spatial
correlation. However, one drawback in its application comes from the difficulty in modeling the coregionalization. Simplified
models of coregionalization were developed specifically for the collocated cokriging case.
This paper presents, through a case study, the incorporation of dense secondary information using collocated cokriging. The
watertable above a coal underground mine is mapped using water-level readings at monitoring piezometers complemented by highly
correlated topographic data. The incorporation of dense secondary information through the utilization of a linear model of
coregionalization and Markov models is comparatively evaluated in various aspects such as mathematical quality, coherence
with the natural phenomena and the ease of utilization and modeling. Simple kriging with local varying means also is evaluated
as it accounts for nonstationarity and is easily implemented. All these methods that incorporate topography as secondary information
for mapping the watertable provided maps more in accordance with the natural phenomena than ordinary kriging using the principal
attribute solely. Among these methods, strictly collocated cokriging using a linear model of coregionalization showed overall
superior performance. 相似文献
16.
High accuracy surface modeling(HASM) is a method which can be applied to soil property interpolation.In this paper,we present a method of HASM combined geographic information for soil property interpolation(HASM-SP) to improve the accuracy.Based on soil types,land use types and parent rocks,HASM-SP was applied to interpolate soil available P,Li,pH,alkali-hydrolyzable N,total K and Cr in a typical red soil hilly region.To evaluate the performance of HASM-SP,we compared its performance with that of ordinary kriging(OK),ordinary kriging combined geographic information(OK-Geo) and stratified kriging(SK).The results showed that the methods combined with geographic information including HASM-SP and OK-Geo obtained a lower estimation bias.HASM-SP also showed less MAEs and RMSEs when it was compared with the other three methods(OK-Geo,OK and SK).Much more details were presented in the HASM-SP maps for soil properties due to the combination of different types of geographic information which gave abrupt boundary for the spatial varia-tion of soil properties.Therefore,HASM-SP can not only reduce prediction errors but also can be accordant with the distribution of geographic information,which make the spatial simula-tion of soil property more reasonable.HASM-SP has not only enriched the theory of high accuracy surface modeling of soil property,but also provided a scientific method for the ap-plication in resource management and environment planning. 相似文献
17.
空间软数据及其插值方法研究进展 总被引：7，自引：0，他引：7
由于对地观测技术的迅速发展,空间数据的种类和数量增长迅猛,由空间数据反演得到的各种信息日趋膨胀,这些反演结果中的信息不少以软数据的形式出现。在实际应用中,这些软数据往往与空间插值的目标变量具有一定的相关性,甚至成为控制目标变量空间分布特征的重要因素。然而,由于这些数据通常表示为非数值形式,在计算和处理上存在着一定困难,以致被传统的插值方法所忽视,从而造成信息浪费。近来出现的空间软插值方法是一种利用空间软数据作为辅助信息并以改善插值效果的方法,能够较好的处理并利用软数据所隐含的信息,具有较好的应用发展前景。本文根据空间软数据的特点及其分类,系统综述了空间软插值方法及其应用领域。首先分析了空间数据软硬性质的根本区别,论述了软数据的分类和“硬化”方法,然后介绍空间插值模型中对空间软数据的集成方法和原理,最后对空间软插值方法及其应用研究领域进行了展望。 相似文献
18.
In most modern coal mines, there are many coal quality parameters that are measured on samples taken from boreholes. These data are used to generate spatial models of the coal quality parameters, typically using inverse distance as an interpolation method. At the same time, downhole geophysical logging of numerous additional boreholes is used to measure various physical properties but no coal quality samples are taken. The work presented in this paper uses two of the most important coal quality variables—ash and volatile matter—and assesses the efficacy of using a number of geostatistical interpolation methods to improve the accuracy of the interpolated models, including the use of auxiliary variables from geophysical logs. A multivariate spatial statistical analysis of ash, volatile matter and several auxiliary variables is used to establish a co-regionalization model that relates all of the variables as manifestations of an underlying geological characteristic. A case study of a coal mine in Queensland, Australia, is used to compare the interpolation methods of inverse distance to ordinary kriging, universal kriging, co-kriging, regression kriging and kriging with an external drift. The relative merits of these six methods are compared using the mean error and the root mean square error as measures of bias and accuracy. The study demonstrates that there is significant opportunity to improve the estimations of coal quality when using kriging with an external drift. The results show that when using the depth of a sample as an external drift variable there is a significant improvement in the accuracy of estimation for volatile matter, and when using wireline density logs as the drift variable there is improvement in the estimation of the in situ ash. The economic benefit of these findings is that cheaper proxies for coal quality parameters can significantly increase data density and the quality of estimations.
相似文献19.
Oktay Erten Mehmet Siddik Kizil Erkan Topal Lachlan McAndrew 《Natural Resources Research》2013,22(3):207-227
Tropical laterite-type bauxite deposits often pose a unique challenge for resource modelling and mine planning due to the extreme lateral variability at the base of the bauxite ore unit within the regolith profile. An economically viable drilling grid is often rather sparse for traditional prediction techniques to precisely account for the lateral variability in the lower contact of a bauxite ore unit. However, ground-penetrating radar (GPR) offers an inexpensive and rapid method for delineating laterite profiles by acquiring fine-scale data from the ground. These numerous data (secondary variable) can be merged with sparsely spaced borehole data (primary variable) through various statistical and geostatistical techniques, provided that there is a linear relation between the primary and secondary variables. Four prediction techniques, including standard linear regression, simple kriging with varying local means, co-located cokriging and kriging with an external drift, were used in this study to incorporate exhaustive GPR data in predictive estimation the base of a bauxite ore unit within a lateritic bauxite deposit in Australia. Cross-validation was used to assess the performance of each technique. The most robust estimates are produced using ordinary co-located cokriging in accordance with the cross-validation analysis. Comparison of the estimates against the actual mine floor indicates that the inclusion of ancillary GPR data substantially improves the quality of the estimates representing the bauxite base surface. 相似文献