一种基于边界搜索的栅格矢量化算法

栅格数据的矢量化是GIS领域重要的研究内容。针对栅格数据矢量化准确率低和效率低等问题,该文提出了一种基于边界搜索的矢量化算法,通过对栅格图像的一次遍历,提取结点和中间点,生成弧段,构建多边形;并在构建多边形中,提出了一种简单易行的最右侧方向判断方法,综合运用最小外接矩形和射线法判定逆时针多边形的归属。实验表明,该文提出的矢量化算法能够较准确矢量化复杂的栅格图像,具有较好的效率,可为多值栅格图像快速矢量化及相关研究提供借鉴。     

基于球面四元三角网剖分的层次空间关系推理

主要讨论了基于四元三角网（Quaternary Triangular Mesh,简称QTM）球面层次格网剖分的基础上，通过单元递归细化来确定2个球面实体的空间关系。传统确定空间关系的方法是通过二元经典剖分元－实体的内部（xi)和外部（xe)，通过对QTM球面层次特征的分析，增加了第3个剖分元－不定剖分元（xm)，利用三值逻辑－true(T)，false(F）,和maybe(M)快速准确地确定2球面实体的拓扑关系。其基本原理是：在球面四元三角网的根水平带有不确定空间关系开始，一层一层地递归细化，来排除不可能结果。当细化的信息满足一定的查询要求，递归分解过程就停止。特别在细化过程中，提出并应用了“继承推理”方法来提高系统效率。     

基于Voronoi图的空间方向关系形式化描述研究(一)

空间方向关系形式化描述模型是空间方向关系研究的难点和重点，目前尚无完善的模型出现。首先提出了影响空间方向关系的两个因素目标：一是两目标群凸壳的直径；二是目标的可视性。论述了运用平面目标Voronoi科作为两目标指向线的“替身”来描述方向关系在理论上的可行性。本文的结论是：Voronoi图是描述空间方向关系的良好工具。     

Rescaling of Access and Property Relations in a Frontier Landscape: Insights from Jambi,Indonesia

The recent expansion of protected areas and oil palm plantations in Jambi (Sumatra), Indonesia, has been notably disruptive. This article investigates the scalar dimensions of land conflicts within a privately managed conservation area. We built on qualitative research focusing on struggles related to the formation of two informal settlements within the conservation area. Results indicate that, especially in the context of rapid rescaling (e.g., decentralization), new power constellations emerge, thereby altering preexisting property relations. We argue that competing scales of meaning and regulation are structuring the ability of actors to access land and, consequently, reflect tensions between structure and agency.     

拓扑线性空间中存在非连续线性算子的充要条件

在拓扑线性空间中存在非连续线性泛函的基础上,给出了拓扑线性空间中存在非连续线性算子的充要条件,即拓扑线性空间中存在不闭的线性真子空间.     

基于二分图的温度网络拓扑性质研究

利用中国地区435个台站1961—2002年逐日平均温度序列,将温度变化发生在9天时间尺度上的特征编码在网络中,通过研究二分图温度网络(BGT网络)中节点与项目的关系,揭示出9天时间尺度上温度变化的特征及其在空间上的拓扑统计性质.网络中各节点RRRD, RrDD, eeed, DRRD, DDRR等所代表的温度波动模态在网络中异常频发,对9天尺度温度变化的预报有一定的指导意义.统计网络的节点度分布,集群系数等拓扑结构特征量,发现BGT网络服从正态分布特征.BGT网络项目内节点度的多样性大体上     

SOM拓扑保序机理的模拟弹性力分析

针对SOM内在原理和基本特性中一些未解决的重要问题,定义了输出阵列上神经元i承受的、正比于模式向量及权向量之间距离的2种模拟弹性力：输入模式向量对胜者i的拉力,以及阵列中胜者j对邻近i的牵动力;分析了弹性力的9个性质,对SOM学习过程中神经元权向量的演变过程及拓扑映射保序的机理给出了易于理解的、形象的解释。     

模糊化(拓扑)导算子的公理化

将模糊化(拓扑)导算子进行了公理化，并且给出了若干模糊化(拓扑)导算子的刻画；同时建立了模糊化(拓扑)导算子和模糊化(拓扑)闭包算子之间的关系。     

Resource partitioning by two large planktivorous fishes Micromesistius australis and Macruronus magellanicus in the Southwest Atlantic

The ontogenetic, seasonal, bathymetric and regional variations in the feeding spectrum of 922 specimens of southern blue whiting Micromesistius australis and 512 specimens of hoki Macruronus magellanicus were studied on the Falkland Islands’ shelf (Southwest Atlantic) between November 1999 and April 2003. A total of 49 different prey items were found in the stomach contents of the two species, with the hyperiid Themisto gaudichaudii and Euphausiacea being amongst the most important prey. Although the species composition did not change over fish size, the proportions of individual prey items in their diets did, with an increase in T. gaudichaudii and Euphausiacea with increasing fish size in southern blue whiting. The opposite occurred in hoki. Seasonal variations in the diet were found to mirror the seasonal abundance of prey around the Falkland Islands for the two species. Intra-specific differences in the diet of both predators reflected the distribution of prey, which in turn was determined by the water structure in the two regions sampled, leading to very different diets. In the limited time that the two species occupied the same space there was little or no competition resulting in almost total segregation of their trophic niches in space and time.     

Classifying natural-language spatial relation terms with random forest algorithm

The exponential growth of natural language text data in social media has contributed a rich data source for geographic information. However, incorporating such data source for GIS analysis faces tremendous challenges as existing GIS data tend to be geometry based while natural language text data tend to rely on natural language spatial relation (NLSR) terms. To alleviate this problem, one critical step is to translate geometric configurations into NLSR terms, but existing methods to date (e.g. mean value or decision tree algorithm) are insufficient to obtain a precise translation. This study addresses this issue by adopting the random forest (RF) algorithm to automatically learn a robust mapping model from a large number of samples and to evaluate the importance of each variable for each NLSR term. Because the semantic similarity of the collected terms reduces the classification accuracy, different grouping schemes of NLSR terms are used, with their influences on classification results being evaluated. The experiment results demonstrate that the learned model can accurately transform geometric configurations into NLSR terms, and that recognizing different groups of terms require different sets of variables. More importantly, the results of variable importance evaluation indicate that the importance of topology types determined by the 9-intersection model is weaker than metric variables in defining NLSR terms, which contrasts to the assertion of ‘topology matters, metric refines’ in existing studies.