Hydrograph and unit hydrograph derivation in arid regions

Arid and semi‐arid regions expose special hydrological features that are distinctive from humid areas. Unfortunately, humid‐region hydrological empirical formulations are used directly in the arid and semi‐arid regions without care about the basic assumptions. During any storm rainfall in arid regions, rainfall, infiltration and runoff components of the hydrological cycle have impacts on water resources. The basis of the methodology presented in this paper is the ratio of runoff increment to rainfall increment during an infinitesimally small time duration. This is the definition of runoff coefficient for the same infinitesimal time duration. The ratio is obtained through rational, physical and mathematical combination of hydrological thinking and then integrated with the classical infiltration equation for the hydrograph determination. The parameters of the methodology are explained and their empirical estimations are presented. The methodology works for rainfall and runoff from ungauged watersheds where infiltration measurement can be performed. The comparison of the new approach with different classical approaches, such as the rational formula and Soil Conservation Service method, are presented in detail. Its application is performed for two wadis within the Kingdom of Saudi Arabia. Copyright © 2006 John Wiley & Sons, Ltd.     

Approaches to Semantic Similarity Measurement for Geo-Spatial Data: A Survey

Semantic similarity is central for the functioning of semantically enabled processing of geospatial data. It is used to measure the degree of potential semantic interoperability between data or different geographic information systems (GIS). Similarity is essential for dealing with vague data queries, vague concepts or natural language and is the basis for semantic information retrieval and integration. The choice of similarity measurement influences strongly the conceptual design and the functionality of a GIS. The goal of this article is to provide a survey presentation on theories of semantic similarity measurement and review how these approaches – originally developed as psychological models to explain human similarity judgment – can be used in geographic information science. According to their knowledge representation and notion of similarity we classify existing similarity measures in geometric, feature, network, alignment and transformational models. The article reviews each of these models and outlines its notion of similarity and metric properties. Afterwards, we evaluate the semantic similarity models with respect to the requirements for semantic similarity measurement between geospatial data. The article concludes by comparing the similarity measures and giving general advice how to choose an appropriate semantic similarity measure. Advantages and disadvantages point to their suitability for different tasks.     

Determining Semantic Similarity of Behaviour Using Natural Semantic Metalanguage to Match User Objectives to Available Web Services

Natural Semantic Metalanguage specifies a set of semantic primitives identified by linguists since the 1970s as being present in all analysed languages and not capable of further reduction. In this article, the 63 semantic primitives are used to define the semantics of user objectives and web services in the form of semantic explications, which are then compared to determine whether the web services are likely to be helpful in meeting the user objective. The comparison of the user objectives and web services is a two stage process. Firstly, the content is compared by classifying the semantic primitives from the candidate web service and user objective on the basis of whether the primitives are common or similar. On the basis of these classifications, the percentage match and semantic relationship (subset, superset, overlaps, disjoint, identical) are determined. Secondly, the order of the semantic primitives is compared and the edit distance determined as a measure of semantic similarity. The method is tested using two examples: a comparison of spatial relations and a comparison of a user objective and three geospatial web services. The results show that the method is able to determine which concepts are broadly semantically similar and which are not.     

Context-awareness in similarity measures and pattern discoveries of trajectories: a context-based dynamic time warping method

Analyzing the spatial behaviors of moving-point objects (MPOs) and discovering their movement patterns have been of great interest to the geographic information science community recently. These interests can be explored through analyzing similarities in the MPO trajectories. Because movements of objects take place in various contexts, their trajectories are also highly influenced by such contexts. Therefore, it is essential to fully understand the contexts and to realize how they can be incorporated into movement analysis. This article first proposes a taxonomy for contexts. Then, a modified version of dynamic time warping called context-based dynamic time warping (CDTW) is introduced, to contextually assess the multidimensional weighted similarities of trajectories. Ultimately, the results of similarity searches are utilized in discovering the relative movement patterns of the MPOs. To evaluate the performance and effectiveness of our proposed CDTW method, we run several experiments on real datasets that were obtained from commercial airplanes in a constrained Euclidean space, taking into account contextual information. Specifically, these experiments were conducted to explore the role of contexts and their interactions in similarity measures of trajectories. The results yielded the robustness of CDTW method in quantifying the commonalities of trajectories and discovering movement patterns with 80% accuracy. Moreover, the results revealed the importance of exploiting contextual information because it can enhance and restrict movements.     

顾及框架点坐标误差的三维基准转换严密模型

框架点坐标是由观测数据通过平差得到的,不可避免地受到观测误差的影响。针对原框架和目标框架坐标均存在误差、非公共点与公共点间存在相关性,以及转换系数矩阵中仅部分元素存在误差的实际情况,提出了同时考虑框架内误差以及转换点间相关性的基准转换严密模型,该模型将公共点和非公共点联合处理,同时计算坐标转换参数和所有点的坐标转换值,推导出了新的严格坐标转换公式,该公式为传统坐标转换公式基础上增加一改正量的形式;进一步,推导了原框架和目标框架坐标的方差不一致情况下的坐标转换模型的自适应解法;最后,利用"陆态网络工程"2000个区域站的实测坐标进行坐标转换验证,结果表明,这种严密模型较传统坐标转换模型具有更高的坐标转换精度。     

一种基于地理环境相似度的滑坡负样本可信度度量方法

滑坡负样本在统计型滑坡危险度制图中具有重要作用,能抑制统计模型对滑坡危险度的高估。当前滑坡负样本采样方法采集的负样本可信度未知,在负样本采样过程中,极有可能将那些潜在滑坡点错选为负样本,这些假的负样本会降低负样本集的质量和训练样本集的质量,进而影响统计模型的精度。本文基于“地理环境越相似、地理特征越相似”的地理学常识,认为与正样本有着相似地理环境的点极有可能是未来发生滑坡的点;与正样本的地理环境越不相似的点,则越有可能是负样本。基于此假设提出一种基于地理环境相似度的负样本可信度度量方法,将该方法应用于滑坡灾害频发的陇南山区油房沟流域,对油房沟进行滑坡负样本可信度评价制图;使用油房沟流域的滑坡发生初始面来验证该方法的有效性。结果发现：滑坡发生初始面上所有栅格点的负样本可信度平均值为0.26,超过95%的栅格点的负样本可信度都小于0.5,说明本文提出的负样本可信度度量方法合理。     

基于经济户口匹配的语料库建设

经济户口数据匹配是将经济户口中包含的企业名称和驻址等基本信息通过地名地址的规范化和一系列匹配算法,得到最佳匹配坐标并定位到电子地图上的过程,是我国推行全面数字化建设的重要举措。本文系统分析了经济户口数据的组织形式,深入研究了中文匹配的原理特点,并以潍坊市奎文区9 000多条经济户口数据作为训练集,设计构建了基于双字哈希和数组三层数据结构的经济户口语料库,总结制定了涵盖500种行业类型的三级编码规则,并根据中文词条的文字相似性和行业之间的相关关系,设置文字和类型相似度值,采用动态加权方法求得复合相似度指标,建立了基于经济户口语料库的相似度匹配方法。文章最后以潍坊市潍城区8 000多条经济户口数据作为测试集,对本文提出的匹配方法进行实验验证。试验结果表明,利用本文设计的经济户口语料库和相似度匹配方法能够高效地完成经济户口数据的唯一性匹配和相似度匹配,极大地提高了检索效率和匹配成功率,具有良好的实际可操作性。     

基于用户轨迹的POI个性化推荐算法研究

为了实现兴趣点(POI)的个性化推荐,本文针对用户轨迹中的含有大量冗余点的问题,探讨了利用POI和公交数据对用户轨迹数据进行压缩的算法。研究了传统的协调过滤推荐算法后,提出一种基于用户轨迹的加权Top N推荐算法(User TN)。实验结果表明,推荐结果的准确率、召回率和个性化程度都优于传统的协同过滤推荐算法,证明了本文方法的有效性。     

一种基于复杂网络的道路匹配方法

为了满足用户对数据现势性的要求,应当保证道路数据的及时准确更新,其关键是对同名道路数据进行匹配。鉴于对道路进行整体分析,道路的形状特征变得尤为重要,因此提出了基于复杂网络的道路匹配方法。该方法利用复杂网络理论分析每条道路的形状特性,得到相关的形状参数,再结合距离、方向等指标的参数计算得到总的相似度,从而选出最佳的匹配道路。这种方法计算简单,对道路的形状特征能很好地描述,并能很快地从候选匹配道路中识别出匹配道路。实验结果表明,将该方法用于道路匹配具有较高的准确率和可靠性。