An evaluation of ontology matching techniques on geospatial ontologies

Standardization is one of the pillars of interoperability. In this context, efforts promoted by the Open Geospatial Consortium, such as CityGML (Technical University, Berlin), a standard for exchanging three-dimensional models or urban city objects, are welcomed. However, information from other domains of interest (e.g. energy efficiency or building information modeling) is needed for tasks such as land planning, large-scale flooding analysis, or demand/supply energy simulations. CityGML allows extension in order to integrate information from other domains, but the development process is expensive because there is no way to perform it automatically. The discovery of correspondences between CityGML concepts and other domains concepts poses a significant challenge.

Ontology matching is the research field emerged from the Semantic Web to address automatic ontology integration. Using the ontology underlying CityGML and the ontologies which model other domains of interest, ontology matching would be able to find the correspondences that would permit the integration in a more automatic manner than it is done now.

In this paper, we evaluate if ontology matching techniques allow performing an automatic integration of geospatial information modeled from different viewpoints. In order to achieve this, an evaluation methodology was designed, and it was applied to the discovery of relationships between CityGML and ontologies coming from the building information modeling and Geospatial Semantic Web domains. The methodology and the results of the evaluation are presented. The best results have been achieved using string-based techniques, while matching systems give the worst precision and recall. Only in a few cases the values are over 50%, which shows the limitations when these techniques are applied to ontologies with a partial overlap.     

Machine learning for cross-gazetteer matching of natural features

ABSTRACT

Defining and identifying duplicate records in a dataset is a challenging task which grows more complex when the modeled entities themselves are hard to delineate. In the geospatial domain, it may not be clear where a mountain, stream, or valley ends and begins, a problem carried over when such entities are catalogued in gazetteers. In this paper, we take two gazetteers, GeoNames and SwissNames3D, and perform matching – identifying records in each that are about the same entity – across a sample of natural feature records. We first perform rule-based matching, establishing competitive results, then apply machine learning using Random Forests, a method well-suited to the matching task. We report on the performance of a wider array of matching features than has been previously studied, including domain-specific ones such as feature type, land cover class, and elevation. Our results show an increase in performance using machine learning over rules, with a notable performance gain from considering feature types, but negligible gains from other specialized matching features. We argue that future work in this area should strive to be more reproducible and report results on a realistic testing pipeline including candidate selection, feature extraction, and classification.     

A deep learning architecture for semantic address matching

ABSTRACT

Address matching is a crucial step in geocoding, which plays an important role in urban planning and management. To date, the unprecedented development of location-based services has generated a large amount of unstructured address data. Traditional address matching methods mainly focus on the literal similarity of address records and are therefore not applicable to the unstructured address data. In this study, we introduce an address matching method based on deep learning to identify the semantic similarity between address records. First, we train the word2vec model to transform the address records into their corresponding vector representations. Next, we apply the enhanced sequential inference model (ESIM), a deep text-matching model, to make local and global inferences to determine if two addresses match. To evaluate the accuracy of the proposed method, we fine-tune the model with real-world address data from the Shenzhen Address Database and compare the outputs with those of several popular address matching methods. The results indicate that the proposed method achieves a higher matching accuracy for unstructured address records, with its precision, recall, and F1 score (i.e., the harmonic mean of precision and recall) reaching 0.97 on the test set.     

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广西数字测震台网建设成果及效益分析

介绍了"十五"广西数字测震台网建设的基本情况,分析了台站布局、观测动态范围和台基环境地噪声水平对台网地震监测能力的影响。实现与邻省台网和地方社会台网的联网与数据共享后,台网监测能力得到进一步提高。以广西数字测震台网投入运行前后记录到的地震情况,阐述了广西数字测震台网技术成果及所取得的社会经济效益。     

多光谱遥感影像中云影区域的检测与修复

提出了一种有效针对多光谱遥感影像的云影检测与阴影区域修复方法。基于同一地区时相相近的两幅影像,充分利用碎云及阴影的光谱特性分别对云影区域进行融合增强,然后采用Otsu算法求解最佳阈值自动检测出云及阴影区域,根据云影的出现会引起两幅影像局部相应区域明显的亮度变化,可排除亮地物和水体的影响,建立归一化的云影密度图,在此基础上,采用线性加权组合与光谱直方图匹配相结合的方法对其加以修复,利用SPOT 4影像进行的实验表明其修复效果完全能够满足应用需要。     

局部单应约束的高精度图像自动配准方法

提出一种基于SIFT特征的抗差图像匹配算法。算法分为两个阶段:①初始匹配,综合利用SIFT特征匹配方法和基于SIFT特征尺度和方位信息的自适应归一化互相关(normalized cross correlation,NCC)方法建立初始相关,并基于几何关系一致性检测剔除误匹配;②匹配传播,在初始相关的基础上,利用自适应NCC和局部单应约束进行匹配传播,迭代产生更多的匹配点并采用几何关系一致性检测剔除可能的误匹配。初始单应采用最小二乘匹配方法估计得到,并采用自适应NCC为其提供良好的初始值。与现有的基于SIFT特征的图像配准方法相比,算法在抗几何变形和配准精度等方面具有优越性。     

层次分析综合法在地下水污染防治区划方面的应用——以南四湖平原区为例

阐述了南四湖平原区地下水类型及分布概况,选取地下水防污性能、地下水污染评价、地下水可开采资源分布、地下水开采程度和污染源荷载为防护区评价指标,利用层次分析综合法对评价指标进行叠加分析,进而对南四湖平原地区地下水污染做出区划,为政府部门制定地下水保护规划提供科学依据,有利于地下水资源的保护。     

土压力传感器在硬土介质中的非线性响应分析

为掌握土压力传感器置于硬土介质中呈现的非线性响应特性,建立了传感器与土介质的相互作用模型,运用有限元分析了满足匹配误差稳定所需的传感器与土介质的模量比条件。进行了传感器的单体标定和级配碎石土介质标定试验,探讨了传感器非线性响应的主要影响因素。计算与试验表明,目前国内主流的双膜土压力传感器在量测硬土介质中的土压力时,由于模量偏小标定曲线非线性显著;土压力传感器单体标定曲线线性度较高且其模量基本稳定,表明土介质的模量变化是引起标定曲线非线性的主要因素;通过将传感器置于与使用环境相近的土介质中进行标定,并采用非线性修正可明显提高硬土介质中土压力量测的准确性。     

断—盖时空匹配及其对油气聚集与分布的控制作用——以南堡凹陷中浅层东营组为例

为研究南堡凹陷中浅层东营组油气分布规律,根据油气输导断裂与盖层时空匹配与油气分布之间的关系,分析油气聚集与分布的控制作用.结果表明:南堡凹陷中浅层断—盖空间匹配关系对油气分布层位的控制作用表现:(1)如果东营组二段泥岩盖层有效厚度大于90～95m,无论馆陶组三段火山岩盖层有效厚度多大,则油气主要分布在东三、四段(简称东二段、馆三段);(2)如果东二段火山岩盖层有效厚度小于90～95m,馆三段火山岩盖层有效厚度大于130～150m,则油气除分布在东三、四段外,还可以分布在东一段和馆四段;(3)如果东三段泥岩盖层有效厚度小于90～95m,馆三段火山岩盖层有效厚度小于130～150m,明下段泥岩盖层有效厚度大于90～95m时,则油气从下至上均有分布.3套区域性盖层封闭能力形成时期早于断裂输导油气的大量时期,可有效封住断裂输导运移来的油气,这是导致3套区域性盖层之下油气相对富集的重要原因.