图形显示和比较古水流数据的一种软件(PC99):以青藏高原北部可可西里盆地新生代古水流数据为例

PC99是基于Windows 95 / 98/ 2 0 0 0版本操作系统的VisualBasic语言程序,以简单和友好界面图形显示、统计分析和比较古水流数据文件。这种软件支持的古水流数据显示方式包括玫瑰花图和环形图两种,玫瑰花图的花瓣宽度和半径比例尺的可调节性可以辅以解释古水流分布样式,环形图可以同时装载、显示和比较 10个单组或合成古水流数据文件。本文以青藏高原北部可可西里盆地新生代沉积的古水流数据为例,分析古水流方向的时空分布特征,表明PC99是图形显示和解释古水流数据的一种高效软件工具。     

Compositional Kriging: A Spatial Interpolation Method for Compositional Data

Compositional data are very common in the earth sciences. Nevertheless, little attention has been paid to the spatial interpolation of these data sets. Most interpolators do not necessarily satisfy the constant sum and nonnegativity constraints of compositional data, nor take spatial structure into account. Therefore, compositional kriging is introduced as a straightforward extension of ordinary kriging that complies with these constraints. In two case studies, the performance of compositional kriging is compared with that of the additive logratio-transform. In the first case study, compositional kriging yielded significantly more accurate predictions than the additive logratio-transform, while in the second case study the performances were comparable.     

顾及数据空间分布特性的模糊C-均值聚类算法研究

利用描述空间数据分布的Voronoi图的有关理论分析了样本空间数据分布特性，从理论上论述了样本集中各类样本数差异较大产生的根源，并在此基础上提出了一种顾及数据空间分布特性的模糊C—均值聚类算法。     

两种岩石地球化学图解在确定岩石同化,混染成因方面的应用

首先介绍了两种简易岩石地球化学图解，即元素，元素对比值混合方程和混染岩，混染端员元素浓度差相关性图解。进而应用这两种图解配合其它地质事实共同验证了冀东迁西上营－十八盘地区的云英闪长质片麻岩是由奥长花岩是由奥长花岗岩浆对角闪质岩石不同程度同化，混染形成的。     

利用自然伽马能谱确定地层岩性的方法

地层中的放射性核素Th、U和K的分布规律,与岩石的岩性、矿物成分、成岩环境和地下水活动有关。本文根据三肇地区27口探井的646个取心岩样的自然伽马能谱和室内分析出的岩性,通过自然伽马能谱数据库管理系统,给出Th-U交会图和Th-K交会图,从而找出自然伽马能谐与岩性的关系。     

基于线性四叉树结构的Voronoi图反向膨胀生成方法

提出一种基于线性四叉树结构并顾及矢量与栅格计算性质的Voronoi图生成方法,其核心思想是利用线性四又树结构以减小空间剖分所产生的空间复杂度,改变膨胀模拟操作的计算方向以减小时间复杂度。讨论了基于数学形态学的反向膨胀计算模型及推理出基于该计算模型的几个优化计算性质。实验验证,这种方法能够有效地平衡时空复杂度,并且易于求取邻元,其时间复杂度小于均匀格网结构与常规四叉树结构。一般情况下,空间复杂度小于均匀格网结构。     

Probabilistic mapping of flood-induced backscatter changes in SAR time series

The information content of flood extent maps can be increased considerably by including information on the uncertainty of the flood area delineation. This additional information can be of benefit in flood forecasting and monitoring. Furthermore, flood probability maps can be converted to binary maps showing flooded and non-flooded areas by applying a threshold probability value p_F = 0.5. In this study, a probabilistic change detection approach for flood mapping based on synthetic aperture radar (SAR) time series is proposed. For this purpose, conditional probability density functions (PDFs) for land and open water surfaces were estimated from ENVISAT ASAR Wide Swath (WS) time series containing >600 images using a reference mask of permanent water bodies. A pixel-wise harmonic model was used to account for seasonality in backscatter from land areas caused by soil moisture and vegetation dynamics. The approach was evaluated for a large-scale flood event along the River Severn, United Kingdom. The retrieved flood probability maps were compared to a reference flood mask derived from high-resolution aerial imagery by means of reliability diagrams. The obtained performance measures indicate both high reliability and confidence although there was a slight under-estimation of the flood extent, which may in part be attributed to topographically induced radar shadows along the edges of the floodplain. Furthermore, the results highlight the importance of local incidence angle for the separability between flooded and non-flooded areas as specular reflection properties of open water surfaces increase with a more oblique viewing geometry.     

A spatial co-location mining algorithm that includes adaptive proximity improvements and distant instance references

Spatial co-location pattern mining is employed to identify a group of spatial types whose instances are frequently located in spatial proximity. Current co-location mining methods have two limitations: (1) it is difficult to set an appropriate proximity threshold to identify close instances in an unknown region, and (2) such methods neglect the effects of the distance values between instances and long-distance instance effects on pattern significance. This paper proposes a novel maximal co-location algorithm to address these problems. To remove the first constraint, the algorithm uses Voronoi diagrams to extract the most related instance pairs of different types and their normalized distances, from which two distance-separating parameters are adaptively extracted using a statistical method. To remove the second constraint, the algorithm employs a reward-based verification based on distance-separating parameters to identify the prevalent patterns. Our experiments with both synthetic data and real data from Beijing, China, demonstrate that the algorithm can identify many interesting patterns that are neglected by traditional co-location methods.     

Old open clusters: the interesting case of Berkeley 21

We present CCD BVI photometry of the old open cluster Berkeley 21, one of the most distant clusters in the Galactic anticentre direction, and possibly the lowest metallicity object in the open clusters sample. Its position and metal abundance make it very important for the study of the Galactic disc. Using the synthetic colour–magnitude diagram method, we estimate values for the distance modulus ( m  − M )₀ = 13.4–13.6, reddening E ( B  −  V ) = 0.74–0.78 (with possible differential absorption), and age = 2.2–2.5 Gyr.