Estimating the spatial pattern of human-caused forest fires using a generalized linear mixed model with spatial autocorrelation in South Korea

Most forest fires in Korea are spatially concentrated in certain areas and are highly related to human activities. These site-specific characteristics of forest fires are analyzed by spatial regression analysis using the R-module generalized linear mixed model (GLMM), which can consider spatial autocorrelation. We examined the quantitative effect of topology, human accessibility, and forest cover without and with spatial autocorrelation. Under the assumption that slope, elevation, aspect, population density, distance from road, and forest cover are related to forest fire occurrence, the explanatory variables of each of these factors were prepared using a Geographic Information System-based process. First, we tried to test the influence of fixed effects on the occurrence of forest fires using a generalized linear model (GLM) with Poisson distribution. In addition, the overdispersion of the response data was also detected, and variogram analysis was performed using the standardized residuals of GLM. Second, GLMM was applied to consider the obvious residual autocorrelation structure. The fitted models were validated and compared using the multiple correlation and root mean square error (RMSE). Results showed that slope, elevation, aspect index, population density, and distance from road were significant factors capable of explaining the forest fire occurrence. Positive spatial autocorrelation was estimated up to a distance of 32 km. The kriging predictions based on GLMM were smoother than those of the GLM. Finally, a forest fire occurrence map was prepared using the results from both models. The fire risk decreases with increasing distance to areas with high population densities, and increasing elevation showed a suppressing effect on fire occurrence. Both variables are in accordance with the significance tests.     

随机反演在陆丰13-1油田储层预测中的应用

这里以陆丰13-1油田为例,研究发现井上波阻抗曲线并不能有效区分砂岩储层和泥岩非储层,故对孔隙度数据体进行了反演.首先对井上孔隙度曲线进行直方图统计分析,变差函数分析及孔隙度和波阻抗的相关性分析,然后用高斯模拟加模拟退火的随机反演方法对研究区进行了孔隙度体的反演.经反演发现,较其它反演方法孔隙度体反演剖面分辨率有了很大提高,对薄砂体也能很好地识别,且与井上吻合较好,能很好地刻画出砂体的横向变化情况,平面上砂体的展布也符合该区的沉积相分布.     

随机地震反演关键参数优选和效果分析(英文)

随机地震反演技术是将地质统计理论和地震反演相结合的反演方法,它将地震资料、测井资料和地质统计学信息融合为地下模型的后验概率分布,利用马尔科夫链蒙特卡洛(MCMC)方法对该后验概率分布采样,通过综合分析多个采样结果来研究后验概率分布的性质,进而认识地下情况。本文首先介绍了随机地震反演的原理,然后对影响随机地震反演效果的四个关键参数,即地震资料信噪比、变差函数、后验概率分布的样本个数和井网密度进行分析并给出其优化原则。资料分析表明地震资料信噪比控制地震资料和地质统计规律对反演结果的约束程度,变差函数影响反演结果的平滑程度,后验概率分布的样本个数决定样本统计特征的可靠性,而参与反演的井网密度则影响反演的不确定性。最后通过对比试验工区随机地震反演和基于模型的确定性地震反演结果,指出随机地震反演可以给出更符合地下实际情况的模型。     

地质统计学在东天山化探信息提取中的应用

地球化学场和地球物理场都具有一定的空间结构性和空间自相关性,而揭示这种空间相关性的有力工具是变差函数。利用变差函数对东天山的1∶20万区域地球化学数据Cu和Au进行了结构分析。结果表明：两元素在东西方向有着较好的稳定性和连续性,南北方向有较大的变化性并具有一定的线性漂移,总体呈现带状异常,与东天山EW方向大断裂具有很好的一致性。利用泛克里格法对Cu、Au进行了异常信息的提取和评价,泛克里格法提取的剩余异常不仅能突出高异常区,也较清晰地反映了部分低缓异常带,为研究区域化探异常分布特征提供了丰富的信息。     

基于多尺度最小二乘支持向量机优化的克里金插值方法

克里金插值方法根据待估位置点、已知样本数据点的位置关系和区域化变量的空间相关性,实现空间加权估计,满足估计的无偏性和最优性。传统方法理论模型形状固定且选择具有人为主观性,无法反映空间数据的变化趋势及其空间多尺度特征。本文为解决上述问题,提出了一种基于多尺度最小二乘支持向量机优化的克里金插值方法,此方法为拟合实验变异函数提供了一种新的思路。从实际样本数据的变化趋势出发,采用最小二乘支持向量机拟合实验变异函数,并利用不同尺度小波核反映不同尺度下的空间变化。最后,实验环节包括模拟和应用,模拟主要验证经多尺度最小二乘支持向量机优化后插值方法的科学有效性以及准确性,应用主要研究青岛市PM_2.5浓度时空分布特征,为城市生态科学防护及控制提供理论依据。结果表明,基于多尺度最小二乘支持向量机优化的克里金插值方法能够更好地刻画变异函数,反映不同尺度下的空间变化细节,从而在一定程度上提高插值的精度,是一种可选的克里金插值方法。     

Spatial prediction of river channel topography by kriging

Topographic information is fundamental to geomorphic inquiry, and spatial prediction of bed elevation from irregular survey data is an important component of many reach‐scale studies. Kriging is a geostatistical technique for obtaining these predictions along with measures of their reliability, and this paper outlines a specialized framework intended for application to river channels. Our modular approach includes an algorithm for transforming the coordinates of data and prediction locations to a channel‐centered coordinate system, several different methods of representing the trend component of topographic variation and search strategies that incorporate geomorphic information to determine which survey data are used to make a prediction at a specific location. For example, a relationship between curvature and the lateral position of maximum depth can be used to include cross‐sectional asymmetry in a two‐dimensional trend surface model, and topographic breaklines can be used to restrict which data are retained in a local neighborhood around each prediction location. Using survey data from a restored gravel‐bed river, we demonstrate how transformation to the channel‐centered coordinate system facilitates interpretation of the variogram, a statistical model of reach‐scale spatial structure used in kriging, and how the choice of a trend model affects the variogram of the residuals from that trend. Similarly, we show how decomposing kriging predictions into their trend and residual components can yield useful information on channel morphology. Cross‐validation analyses involving different data configurations and kriging variants indicate that kriging is quite robust and that survey density is the primary control on the accuracy of bed elevation predictions. The root mean‐square error of these predictions is directly proportional to the spacing between surveyed cross‐sections, even in a reconfigured channel with a relatively simple morphology; sophisticated methods of spatial prediction are no substitute for field data. Copyright © 2007 John Wiley & Sons, Ltd.     

支持向量机优化的克里金插值算法及其海洋资料对比试验

针对常规克里金插值方法中变异函数为有限确定函数,难以准确刻画实际数据分布（特别是复杂要素资料的空间结构）的不足,基于最小二乘支持向量机从实际资料场中拟合重构变异函数的研究思想,提出了一种改进的插值方法——支持向量机—克里金插值算法（SVM-Kriging）。采用常规的克里金方法和支持向量机—克里金插值方法（SVM-Kriging）进行插值试验和对比分析,结果表明：支持向量机—克里金方法（SVM-Kriging）的变异函数源自实际的数据场,它克服了常规克里金插值对变异函数选择的依赖性以及变异函数选择的主观性和人为性,表现出较好的针对性和客观性,较为有效地改善了插值效果。     

在储层建模中利用多点地质统计学整合地质概念模型及其解释

基于三维空间中稀疏的观测数据,地质学家和储层建模人员尝试预测井间的地质沉积相的空间非均质性时,地质概念模型和先验认识在其中扮演着重要的角色。这种整合先验模型或解释的过程有时是隐蔽或不易察觉的,正如在手工绘等值线图中的情形;它也能够被显式地运用到某种算法当中,比如数字绘图中的算法。新近兴起的多点地质统计学为地质学家和储层建模人员提供了一种有力工具,它强调使用训练图像把先验模型明确而定量地引入到储层建模当中。先验地质模型包含了被研究的真实储层中确信存在的样式,而训练图像则是该模型的定量化表达。通过再现高阶统计量,多点算法能够从训练图像中捕捉复杂的(非线性)特征样式并把它们锚定到观测的井位数据。文中描述了多点地质统计学原理,以突出训练图像概念重要性为主线,描述了多点地质统计学在建立三维储层模型中的应用。     

序贯模拟方法在储层建模中的应用研究

条件模拟方法是地质统计学发展的一个主要方向和研究热点。作者通过序贯模拟方法在储层建模中的应用，对模拟结果进行了参数统计和变异函数分析；并对克立格和序贯模拟方法进行了比较。应用研究的结果证明了该方法的各种特点，弥补了条件模拟方法在理论研究上的不足，为进一步的方法改进和拓宽其应用范围提供了理论依据和实例参考。     

利用分形参数进行地貌定量分区研究——以鄂尔多斯块体及周边为例

地貌分区是地学研究的基础内容之一.传统的地貌分区大多是定性的划分,随着数字地形技术以及分形分析方法的成熟,利用分形参数进行定量化的地貌分区成为可能.本文利用水平分辨率为90m的SRTM数据,采用元分维模型,通过变差函数法计算了鄂尔多斯块体及周边地形的分形参数.在65×65,129×129以及257×257等3种尺度滑动...