人为干扰下海岸沙丘表面粒度分布变异实证研究——以河北昌黎黄金海岸横向沙脊为例

选择我国海岸沙丘尤其是横向沙脊最为典型的河北昌黎黄金海岸,分别在人为干扰剧烈和人为干扰较少的区段,按垂直于横向沙脊走向各选择一个典型的横向沙脊断面,采集其表面沙质沉积物粒度样品,通过对样品粒度及其参数的分析与计算,对比分析人为干扰对海岸沙丘表面粒度分布的可能影响。结果表明,在滑沙和迎风坡脚沙质地表翻动与堆积沙堆等人为影响下,横向沙脊表面粒度分布发生了明显变异,由近自然状态下自沙脊两侧坡脚向脊顶粒径变细和分选变好、向陆背风坡的细化与分选优于向海迎风坡、脊顶沙粒最细及向陆背风坡脚最粗的自然分布模式转变为人为干扰下自两侧坡脚向沙脊坡部粒径变细与分选变好、向海迎风坡的细化与分选优于向陆背风坡、向海迎风坡粒径最细及迎风坡脚最粗的人为分布模式。     

河北昌黎黄金海岸横向沙脊表面的粒度分布模式

河北昌黎黄金海岸自然保护区内的横向沙脊规模高大、形态典型,对其表面采集的47个沙丘表面沉积物粒度样品的分析结果,该海岸横向沙脊表面粒度总体上是中砂、分选好、对称和中等峰态,但脊顶、坡部及坡脚的粒度分异明显,自沙脊两侧坡脚向脊顶粒径变细、分选变好,向陆背风坡的细化与分选优于向海迎风坡,脊顶粒径最细,向陆背风坡脚最粗,是一种新型的沙丘表面粒度分布模式。该粒度分布模式是该区域主风向与强风向交替变化及其风速差异、沙脊高大且两侧不对称等组合作用的结果。     

长江口表层沉积物分布特征及动力响应

基于长江口2003 年2 月采集的58 个表层沉积物样品及以同步水动力资料的分析表明, 表层沉积物中值粒径自江阴-口外逐渐变细, 由江阴附近的217.8 μm 减少到南槽口外的12.1 μm; 浑浊带海域表层沉积物中值粒径北港最大, 平均为126.2 μm, 北槽其次, 平均为48.4 μm, 南槽最小, 平均为14.2 μm; 口外海域则北槽最大, 为22.4 μm, 北港其次, 为16.5 μm, 南槽最小, 为12.1 μm。沉积物分选性大多为中等-很差, 中值粒径越大, 分选系数越 小; 沉积物偏度大多是近对称-极正偏; 峭度表现为中等峭度-很窄尖。横沙以上区域表层 沉积物类型以砂为主, 口外海域沉积物类型以粘土质粉砂为主, 浑浊带海域表层沉积物类型复杂多样。长江口主槽表层沉积物中值粒径与落潮历时、V_e/V_f 值和余流值等动力参数呈正相 关关系, 落潮动力条件是决定长江口表层沉积物中值粒径大小的主要动力因素。     

罗布泊地区红柳沙包纹层沙粒度特征与环境指示意义

通过对罗布泊西南缘一个红柳沙包的132个清晰沉积纹层沙物质特征分析表明:所有沉积纹层沙物质均以细砂为主,占42.54～91.82%,其中1871-1874年纹层砂粒最细,1903-1910年纹层砂粒最粗;沙物质粒径分布在0.044～0.283mm之间,平均值0.095mm,中值粒径0.083mm;所有纹层沙物质的分选性都很好,分选系数分布在0.04～0.06之间,平均值0.05;偏态值分布在0.14～0.35之间,平均值0.19;峰态值分布在1.03～1.17之间,平均值1.13;沙物质粒度分维值分布在1.39～2.88之间,平均值2.80。除沙层厚度外,粒级组成、粒度特征参数、粒级分布曲线以及粒度累计概率曲线等也有较明确的环境指示意义。     

Random encounters in probabilistic time geography

Probabilistic time geography considers the encounter of moving agents to be random; therefore, a quantitative time geography analysis must consider the actual encounter probability. The existing algorithm of encounter probability is oriented over a discrete space and is sensitive to the unit definition of a virtual grid; thus, it is not suitable for continuous space. For this reason, a new method is presented in this paper for the encounter of two moving agents in continuous space. When the encounters are less than a specified distance threshold apart, an encounter event occurs based on the probability of the product, which is calculated by their respective probability density functions over their respective potential location areas. This probability provides a quantitative basis for predicting the likelihood of two agents meeting, as well as the location of this meeting point. Finally, the validity of the proposed model is verified by an experiment, which uses tracking data to calculate the encounter probabilities of three zebras and analyse the distribution characteristics of these probabilities over time and space.     

库姆塔格沙漠北部三垄沙地区风成沉积物粒度特征

对位于库姆塔格沙漠北部的三垄沙地区,迄今尚未开展详细的风沙地貌研究。对该区域地表沉积物样品进行粒度分析,旨在探讨不同区域、不同沙丘类型以及沙丘不同地貌部位的沉积物特征差异。结果表明:三垄沙地区地表沉积物以中沙和细沙为主,二者平均含量之和为63.20%,平均粒径为0.95~1.89Φ,分选系数为0.55~1.55,粗于库姆塔格沙漠和塔克拉玛干沙漠,与世界其他沙海沙物质相比属于偏粗粒径。三垄沙地区的主要沙丘类型为新月形沙丘或沙丘链,其北部发育有线形沙丘;这两种沙丘表层沉积物平均粒径均属于中沙范围,且从沙丘底部到丘顶平均粒径变大、分选变好,最粗的沙粒出现在沙丘顶部,平均粒径分别为1.64Φ和0.71Φ,不同于其他地区沙丘顶部沉积物最细的分布模式。从概率累积曲线来看,流动沙丘多为二段或三段式,风成沙砾浪和剥蚀残丘多为三段或四段式,表明后者经历的分选过程较短。本区地表沉积物的平均粒径沿主导风向有变小的趋势,其中,新月形沙丘和线形沙丘的这一特征最为明显。     

Uncertainty in the effects of the modifiable areal unit problem under different levels of spatial autocorrelation: a simulation study

ABSTRACT

The objective of this paper is to investigate uncertainties surrounding relationships between spatial autocorrelation (SA) and the modifiable areal unit problem (MAUP) with an extensive simulation experiment. Especially, this paper aims to explore how differently the MAUP behaves for the level of SA focusing on how the initial level of SA at the finest spatial scale makes a significant difference to the MAUP effects on the sample statistics such as means, variances, and Moran coefficients (MCs). The simulation experiment utilizes a random spatial aggregation (RSA) procedure and adopts Moran spatial eigenvectors to simulate different SA levels. The main findings are as follows. First, there are no substantive MAUP effects for means. However, the initial level of SA plays a role for the zoning effect, especially when extreme positive SA is present. Second, there is a clear and strong scale effect for the variances. However, the initial SA level plays a non-negligible role in how this scale effect deploys. Third, the initial SA level plays a crucial role in the nature and extent of the MAUP effects on MCs. A regression analysis confirms that the initial SA level makes a substantial difference to the variability of the MAUP effects.     

Solving land-use suitability analysis and planning problem by a hybrid meta-heuristic algorithm

The aim of Land-use Suitability Analysis and Planning Problem (LSAPP) is to identify the most suitable parcels of land for future land-uses considering several conflicting criteria. LSAPP can be modeled using a variant of a well-known combinatorial optimization problem called Quadratic Assignment Problem (QAP). In this paper, a multi-objective mathematical model is developed for LSAPP based on QAP modeling. The large-size instances of the proposed multi-objective mathematical model are difficult to solve in a reasonable CPU time using exact algorithms. So, an efficient three-phase hybrid solution procedure is proposed. In the first phase, the compensatory objectives are integrated using Analytic Hierarchy Process (AHP) and Decision-Making Trial and Evaluation Laboratory. Then, based on the aforementioned suitability objective function and other spatial objectives and constraints, a multi-objective LSAPP is constructed. Finally, a hybrid multiple objective meta-heuristic algorithm is proposed to solve the LSAPP. The core of the proposed algorithm is based on Scatter Search while Tabu Search and Variable Neighborhood Search are also utilized. The proposed algorithm is equipped with the concepts of Pareto optimality and Veto Threshold, which improve its efficacy. The proposed algorithm is applied on a real LSAPP case study, in ‘Persian Gulf Knowledge Village’, wherein its performance is compared with a well-known evolutionary computation algorithm called Vector Evaluated Genetic Algorithm (VEGA) using comprehensive statistical analysis. A survey on time complexity of the proposed algorithm is also accomplished. The results show that MOSVNS is significantly superior to VEGA both in single and in multi-objective modes. Furthermore, analysis of time complexity of the proposed algorithm shows that it is of polynomial time and can be applied to significantly larger problems with multiple compensatory and non-compensatory objectives.     

Use of Intelligent Methods to Design Effective Pattern Parameters of Mine Blasting to Minimize Flyrock Distance

Flyrock is one of the most important environmental issues in mine blasting, which can affect equipment, people and could cause fatal accidents. Therefore, minimization of this environmental issue of blasting must be considered as the ultimate objective of many rock removal projects. This paper describes a new minimization procedure of flyrock using intelligent approaches, i.e., artificial neural network (ANN) and particle swarm optimization (PSO) algorithms. The most effective factors of flyrock were used as model inputs while the output of the system was set as flyrock distance. In the initial stage, an ANN model was constructed and proposed with high degree of accuracy. Then, two different strategies according to ideal and engineering condition designs were considered and implemented using PSO algorithm. The two main parameters of PSO algorithm for optimal design were obtained as 50 for number of particle and 1000 for number of iteration. Flyrock values were reduced in ideal condition to 34 m; while in engineering condition, this value was reduced to 109 m. In addition, an appropriate blasting pattern was proposed. It can be concluded that using the proposed techniques and patterns, flyrock risks in the studied mine can be significantly minimized and controlled.

     

Unbiased Resource Evaluations with Kriging and Stochastic Models of Heterogeneous Rock Properties

This paper revisits the computation of product combinations for quantification of resources (e.g., pore volume for hydrocarbon reservoir formations). The explanations have been simplified by considering the exhaustive numerical model for properties that are multiplied first and then added or averaged for evaluation. The analysis starts without any probabilistic considerations. Abbreviated (up-scaled) computations in the sum of multiplications are proposed by substituting the individual values by averages for each rock property in the coarser cell resolution model. A result found is that averaged properties can be utilized for estimation at non-sampled locations, instead of individual values; however, covariances and cumulants must also be included in the abbreviated computations. The smoothing effect of kriging is found to be irrelevant if the kriging variance is also included in the up-scaled abbreviated pore volume computations. Thus, the equivalence between computation of resource volumes from kriging estimates and conditional stochastic simulations is established, with the condition that numerical estimation must incorporate the complete covariance and cumulant information as well. An example shows pore volume prediction from a kriging model matches the unbiased result from stochastic simulations.     

Automatic model for finding the one-dimensional magnetotelluric problem

Summary. A method is described for finding a resistivity model that fits given magnetotelluric data in the one-dimensional case. The procedure is automatic and objective in that no a priori model structure is imposed. Starting with a uniform half space derived directly from the data, the procedure gradually transforms the half space to one with a continuous and smooth resistivity distribution whose response fits the measured data. The method is illustrated by application to two magnetotelluric data sets.     

The Backus–Gilbert theory for piecewise continuous structures with variable discontinuity levels and its application to the magnetotelluric inverse problem

Summary. The Backus–Gilbert theory is extended to the case when the models are piecewise continuous vector functions of depth with variable discontinuity locations. In addition, some of the layers may be represented by linear combinations of known functions. For such layers only a finite number of discrete parameters is to be determined. The iterative process for obtaining a model satisfying the data is convergent, the numerical procedure by which the iterations are performed being equivalent to the method of spectral decomposition for continuous structures. The method of obtaining the Fréchet kernels by using the first perturbation of the differential system satisfied by the corresponding functionals is shown to be valid.
The theory is applied to the magnetotelluric problem, Fréchet kernels being calculated for isotropic and non-isotropic structures.
A few numerical examples are described.     

基于“双评价”集成的国土空间地域功能优化分区

“双评价”（资源环境承载能力和国土空间开发适宜性评价）作为构建国土空间的基本战略格局、实施功能分区的科学基础,为主体功能区降尺度传导、国土空间结构优化、国土开发强度管制等提供了一系列重要参数。以地域功能理论为基础,从人地关系演化出发,探索“双评价”的理论内涵,建立“双评价”到地域功能优化分区的科学逻辑,指出“双评价”集成实现综合效益最大化时所形成的主体功能分区方案为地域功能优化分区的最优方案。以福建省、六盘水市为案例,将人类生产生活的合理需求转化为用地需求参数,通过降尺度的参数分解与测算,结合上位规划及政府与专家系统研判,确定总量控制、结构化控制、空间结构或战略格局控制等目标参数,并在“双评价”基础上,通过不断调整指标、参数及阈值,逐步进行格网单元地域功能优化。着重考虑相邻区域功能冲突与协调、差异化的主体功能定位、土地利用现状及规划、区域发展战略格局以及海陆统筹等区域特征,不断校核与优化。从数据的可获取性、数据集满足理论模型及评估方法的适应程度、可使用的分析方法及模型的不确定性以及尺度效应等方面,探讨功能分区方案不确定性及其解决途径,增强优化结果的鲁棒性,以此作为“三区三线”划定等国土空间规划的科学基础。     

Hillslope-to-valley transition morphology: New opportunities from high resolution DTMs

The search for the optimal spatial scale for observing landforms to understand physical processes is a fundamental issue in geomorphology. Topographic attributes derived from Digital Terrain Models (DTMs) such as slope, curvature and drainage area provide a basis for topographic analyses. The slope–area relationship has been used to distinguish diffusive (hillslope) from linear (valley) processes, and to infer dominant sediment transport processes. In addition, curvature is also useful in distinguishing the dominant landform process. Recent topographic survey techniques such as LiDAR have permitted detailed topographic analysis by providing high-quality DTMs. This study uses LiDAR-derived DTMs with a spatial scale between 1 and 30 m in order to find the optimal scale for observation of dominant landform processes in a headwater basin in the eastern Italian Alps where shallow landsliding and debris flows are dominant. The analysis considered the scaling regimes of local slope versus drainage area, the spatial distribution of curvature, and field observations of channel head locations. The results indicate that: i) hillslope-to-valley transitions in slope–area diagrams become clearer as the DTM grid size decreases due to the better representation of hillslope morphology, and the topographic signature of valley incision by debris flows and landslides is also best displayed with finer DTMs; ii) regarding the channel head distribution in the slope–area diagrams, the scaling regimes of local slope versus drainage area obtained with grid sizes of 1, 3, and 5 m are more consistent with field data; and iii) the use of thresholds of standard deviation of curvature, particularly at the finest grid size, were proven as a useful and objective methodology for recognizing hollows and related channel heads.     

空间尺度上推方法的精度评价——以内蒙古锡林郭勒盟土地利用数据为例

不同的空间尺度上推方法会导致不同程度的信息丢失、信息歪曲等后果;但目前少有研究在较长的尺度序列上、对不同尺度上推方法所得成果开展精度分析。本研究首先提出尺度上推方法精度评价的三个准则,即:保持土地类型构成特征、保持土地面积精度、保持土地空间分布格局和斑块形态;继而使用格点中心值、最大面积斑块、最大聚合面积斑块等3种尺度上推方法,配合100 m～50 km土地利用数据开展尺度转化实验;最后基于上述评价准则和尺度上推实验所得的系列输出结果,分析了不同尺度上推方法的精度。研究表明:(1)格点中心值上推方法能更好地保留区域土地类型构成、土地面积精度等特征;(2)锡林郭勒盟地区土地研究的适宜尺度应小于10 km,最大不应超过30 km;(3)在尺度上推过程中,土地斑块的平均面积、形态以及空间分布格局对尺度上推成果精度有着重要影响。     

Probabilistic methodology for estimation of undiscovered petroleum resources in play analysis of the United States

A geostochastic system called FASPF was developed by the U.S. Geological Survey for their 1989 assessment of undiscovered petroleum resources in the United States. FASPF is a fast appraisal system for petroleum play analysis using a field-size geological model and an analytic probabilistic methodology. The geological model is a particular type of probability model whereby the volumes of oil and gas accumulations are modeled as statistical distributions in the form of probability histograms, and the risk structure is bilevel (play and accumulation) in terms of conditional probability. The probabilistic methodology is an analytic method derived from probability theory rather than Monte Carlo simulation. The resource estimates of crude oil and natural gas are calculated and expressed in terms of probability distributions. The probabilistic methodology developed by the author is explained.The analytic system resulted in a probabilistic methodology for play analysis, subplay analysis, economic analysis, and aggregation analysis. Subplay analysis included the estimation of petroleum resources on non-Federal offshore areas. Economic analysis involved the truncation of the field size with a minimum economic cutoff value. Aggregation analysis was needed to aggregate individual play and subplay estimates of oil and gas, respectively, at the provincial, regional, and national levels.     

巴丹吉林沙漠地表沉积物粒度特征及区域差异

对巴丹吉林沙漠不同区域、不同类型沙丘、不同地貌部位的223个地表沉积物样品进行粒度分析表明,该沙漠的流动沙丘主要由细沙组成,其含量可达49.5%～66.1％;沙丘沙的平均粒径介于2.104～2.706 Φ之间,粗于塔克拉玛干沙漠和腾格里沙漠,与世界其他沙海中沙物质粒径相比处于中等粗细。粒径最细者为灌丛沙丘表面沙粒,最粗者为横向沙山迎风坡;分选度好至极好,均为正偏中等峰态。丘间地物质粗于沙丘沙,平均粒径为1.409 Φ,分选较好,正偏窄峰态。从频率曲线来看,沙丘沙为单峰,丘间地多为双峰或三峰。在典型横向沙山剖面上,自迎风坡坡脚至沙丘顶部平均粒径变细而分选性变好,最粗的沙粒出现在靠近迎风坡坡脚的丘间地,而最细和分选最好的沙粒出现在紧邻沙丘顶部的背风坡。尽管横向沙山与新月形沙丘和沙丘链的尺度不同,但二者同属横向沙丘系统,具有相似的沙丘动力机制,因而粒度参数之间关系的表现趋同。从区域上来看,在平行于主导风向的3条NW—SE向断面上,沙漠中北部高大沙山之间低矮“通道”上的沙粒平均粒径存在微弱的变细趋势,而高大沙山区则不存在明显的变化规律;在平行于雅布赖山的3条SW—NE向断面上,粒度参数沿断面方向无明显的变化规律,但断面越靠近雅布赖山平均粒径越粗。一般认为巴丹吉林沙漠是中国重要的沙尘源区之一,然而粒度分析结果表明,沙漠中北部几乎不含粉沙黏土（<0.0625 mm）组分,而东南部的横向沙山区含量则相对较高,这就需要进一步推断巴丹吉林沙漠具体的沙尘源区和沙尘释放过程。以上变化规律说明,除了物源和主导风向等宏观因素外,引起局地气流改变进而影响沙粒跃移过程的地形起伏、植被覆盖等微观因素也对沙粒分选过程起着重要的控制作用;宏观和微观因素共同作用,最终形成的粒度参数规律性在沙丘尺度上要好于区域尺度上。该粒度分析结果,对于分析巴丹吉林沙漠沙物质来源和形成演变过程、反演高大沙山形成机理、估算地表沙尘释放量等均具有重要参考意义。     

ROBUST PRINCIPAL COMPONENT ANALYSIS BY PROJECTION PURSUIT

Principal component analysis (PCA) is a widely used technique in chemometrics.The classical PCAmethod is,unfortunately,non-robust,since the variance is adopted as the objective function.In thispaper,projection pursuit (PP) is used to carry out PCA with a criterion which is more robust than thevariance.In addition,the generalized simulated annealing (GSA) algorithm is introduced as anoptimization procedure in the process of PP calculation to guarantee the global optimum.The resultsfor simulated data sets show that PCA via PP is resistant to the deviation of the error distribution fromthe normal one.The method is especially recommended for use in cases with possible outlier(s) existingin the data.     

Connectivity of the Coarsest Fraction in Headwater Channels: Imprints of Fluvial Processes and Debris‐Flow Activity

Some steep headwater streams of the mid‐mountains landscape of the flysch belt of the Western Carpathians are affected by debris flows. Connectivity of the largest boulder and cobble fractions has been evaluated in steep streams found in the transitional zones between the hillslopes and alluvial cones of similar lithology and watershed morphometry. Two longitudinal profiles affected by past debris‐flow activity and two longitudinal profiles void of such processes were selected. In the first case, active channels were characterised by the presence of the coarsest fraction, while a downstream trend of sediment coarsening or fining lacked any influence of contemporary fluvial processes and sediment supply. In addition, debris‐flow‐affected streams showed greater differences between the middle axis of the coarsest particle and the particle‐size index including the lengths of all three axes, which is most likely the result of limited active fluvial transport. All the studied streams demonstrated general downstream fining of the largest particles, which resulted from local flysch lithology containing more resistant sandstones in the upper parts of the watershed. The trend of sediment fining was more rapid in the longitudinal profiles unaffected by past debris flows. These types of streams also showed adjustment of the coarsest bed fraction to contemporary processes in channels by sediment coarsening in incised reaches and sediment fining in depositional reaches as well as by downstream response to some lateral sediment inputs. The index of the unit stream power showed no correlation with the considered coarsest fraction in both fluvial‐dominated channels and debris‐flow‐affected channels.     

Mineral Potential Mapping Using a Conjugate Gradient Logistic Regression Model

Mineral potential prediction is a process of establishing a statistical model that describes the relationship between evidence variables and mineral occurrences. In this study, evidence variables were constructed from geological, remote sensing, and geochemical data collected from the Lalingzaohuo district, Qinghai Province, China. Based on these evidence variables, a conjugate gradient logistic regression (CG-LR) model was established to predict exploration targets in the study area. The receiver operating characteristic (ROC) and prediction–area (P-A) curves were used to evaluate the effectiveness of the CG-LR model in mineral potential mapping. The difference between the vertical and horizontal coordinates of each point on the ROC curve was used to determine the optimal threshold for classifying the exploration targets. The optimal threshold corresponds to the point on the ROC curve where the difference between the vertical coordinate and the horizontal coordinate is the largest. In exploration target prediction in the study area, the CG algorithm was used to optimize iteratively the LR coefficients, and the prediction effectiveness was tested for different epochs. With increasing iterations, the prediction performance of the model becomes increasingly better. After 60 iterations, the LR model becomes stable and has the best performance in exploration target prediction. At this point, the exploration targets predicted by the CG-LR model occupy 14.39% of the study area and contain 93% of the known mineral deposits. The exploration targets predicted by the model are consistent with the metallogenic geological characteristics of the study area. Therefore, the CG-LR model can effectively integrate geological, remote sensing, and geochemical data for the study area to predict targets for mineral exploration.