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Geocoding has become a routine task for many research investigations to conduct spatial analysis. However, the output quality of geocoding systems is found to impact the conclusions of subsequent studies that employ this workflow. The published development of geocoding systems has been limited to the same set of interpolation methods and reference data sets for quite some time. We introduce a novel geocoding approach utilizing object detection on remotely sensed imagery based on a deep learning framework to generate rooftop geocoding output. This allows geocoding systems to use and output exact building locations without employing typical geocoding interpolation methods or being completely limited by the availability of reference data sets. The utility of the proposed approach is demonstrated over a sample of 22,481 addresses resulting in significant spatial error reduction and match rates comparable to typical geocoding methods. For different land‐use types, our approach performs better on low‐density residential and commercial addresses than on high‐density residential addresses. With appropriate model setup and training, the proposed approach can be extended to search different object locations and to generate new address and point‐of‐interest reference data sets. 相似文献
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Exposure to traffic‐related pollutants is associated with both morbidity and mortality. Because vehicle‐exhaust are highly localized, within a few hundred meters of heavily traveled roadways, highly accurate spatial data are critical in studies concerned with exposure to vehicle emissions. We compared the positional accuracy of a widely used U.S. Geological Survey (USGS) roadway network containing traffic activity data versus a global positioning system (GPS)‐validated road network without traffic information; developed a geographical information system (GIS)‐based methodology for producing improved roadway data associated with traffic activities; evaluated errors from geocoding processes; and used the CALINE4 dispersion model to demonstrate potential exposure misclassifications due to inaccurate roadway data or incorrectly geocoded addresses. The GIS‐based algorithm we developed was effective in transferring vehicle activity information from the less accurate USGS roadway network to a GPS‐accurate road network, with a match rate exceeding 95%. Large discrepancies, up to hundreds of meters, were found between the two roadway networks, with the GPS‐validated network having higher spatial accuracy. In addition, identifying and correcting errors associated with geocoding resulted in improved address matching. We demonstrated that discrepancies in roadway geometry and geocoding errors, can lead to serious exposure misclassifications, up to an order of magnitude in assigned pollutant concentrations. 相似文献
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基于空间信息网格的数字地图分幅(块)方法 总被引：2，自引：0，他引：2
针对传统地图分幅方法的缺陷,本文提出了一种既适合数字环境又充分考虑到地球空间的自然特征和社会属性特点的地图分幅新方法。它以不破坏地物和区域的完整性为划分原则,根据分辨率和区域内地理信息的数量决定图块大小,块内每个地理实体都有一个行政区划代码属性和标识码。这种数字地图分块方法将地理区按行政体系或自然区划划分为地理空间单元,对每个空间单元记录和存储各种基础地理要素,建立空间单元地理数据文件。这种地理空间的划分和空间数据的组织方法为空间索引提供了方便,更为空间统计提供了便利。它既是空间位置的划分方法,也是特定空间位置范围内自然、社会、经济属性的信息载体,同时也是适合时空坐标系变化的空间信息的一种新的表示方法,是为了更方便地在网格计算环境下实现对空间信息资源的整合、共享与利用。 相似文献
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在分析人类认识自然界过程的基础上,建立了地理信息共享的理论研究框架,将支撑地理信息共享的理论划分成以空间认知理论和信息传输理论、空间概念研究、地理数据模型研究和地理信息标准化研究为主要研究内容的三层次结构,并对各理论基础进行了详细阐述。 相似文献
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OpenStreetMap (OSM), a widely-used open-source geographic information system platform, provides a vast geographic dataset in which users contribute both geometric information (nodes, ways, and relations) and semantic information (tags). This method of voluntary contributions is governed by the collective effort of the users. It is widely acknowledged that the quantity of tag information is substantial, but its quality is often poor. Researchers are therefore trying to assess the quality of the tags and enhance the data through various integration experiments. This article investigates the validity of the tags for geographical objects in metropolitan areas using municipal data and a reverse geocoding technique. The proposed method evaluates the data quality and the matching process carried out by reverse geocoding, using municipal points of interest as a reference. The accuracy of the tag and address information and road network centrality metrics were assessed for the OSM objects that were matched to the locations of interest. The tags were found to match the points of interest with an accuracy of 88%. Furthermore, the tag values were categorized and analyzed based on their similarity. It is concluded that in metropolitan settings where centers of interest are closely located, the accuracy of tags and addresses tends to decrease. 相似文献
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Machine learning innovations in address matching: A practical comparison of word2vec and CRFs 总被引：1，自引：0，他引：1
Record linkage is a frequent obstacle to unlocking the benefits of integrated (spatial) data sources. In the absence of unique identifiers to directly join records, practitioners often rely on text‐based approaches for resolving candidate pairs of records to a match. In geographic information science, spatial record linkage is a form of geocoding that pertains to the resolution of text‐based linkage between pairs of addresses into matches and non‐matches. These approaches link text‐based address sequences, integrating sources of data that would otherwise remain in isolation. While recent innovations in machine learning have been introduced in the wider record linkage literature, there is significant potential to apply machine learning to the address matching sub‐field of geographic information science. As a response, this paper introduces two recent developments in text‐based machine learning—conditional random fields and word2vec—that have not been applied to address matching, evaluating their comparative strengths and drawbacks. 相似文献
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Daniel W. Goldberg 《Transactions in GIS》2011,15(6):829-850
Address ranges used in linear interpolation geocoding often have errors and omissions that result in input address numbers falling outside of known address ranges. Geocoding systems may match these input addresses to the closest available nearby address range and assign low confidence values (match scores) to increase match rates, but little is published describing the matching or scoring techniques used in these systems. This article sheds light on these practices by investigating the need for, technical approaches to, and utility of nearby matching methods used to increase match rates in geocode data. The scope of the problem is motivated by an analysis of a commonly used health dataset. The technical approach of a geocoding system that includes a nearby matching approach is described along with a method for scoring candidates based on spatially‐varying neighborhoods. This method, termed dynamic nearby reference feature scoring, identifies, scores, ranks, and returns the most probable candidate to which the input address feature belongs or is spatially near. This approach is evaluated against commercial systems to assess its effectiveness and resulting spatial accuracy. Results indicate this approach is viable for improving match rates while maintaining acceptable levels of spatial accuracy. 相似文献
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Using geographic information systems to link administrative databases with demographic, social, and environmental data allows researchers to use spatial approaches to explore relationships between exposures and health. Traditionally, spatial analysis in public health has focused on the county, ZIP code, or tract level because of limitations to geocoding at highly resolved scales. Using 2005 birth and death data from North Carolina, we examine our ability to geocode population‐level datasets at three spatial resolutions – zip code, street, and parcel. We achieve high geocoding rates at all three resolutions, with statewide street geocoding rates of 88.0% for births and 93.2% for deaths. We observe differences in geocoding rates across demographics and health outcomes, with lower geocoding rates in disadvantaged populations and the most dramatic differences occurring across the urban‐rural spectrum. Our results suggest that highly resolved spatial data architectures for population‐level datasets are viable through geocoding individual street addresses. We recommend routinely geocoding administrative datasets to the highest spatial resolution feasible, allowing public health researchers to choose the spatial resolution used in analysis based on an understanding of the spatial dimensions of the health outcomes and exposures being investigated. Such research, however, must acknowledge how disparate geocoding success across subpopulations may affect findings. 相似文献
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ABSTRACT Spatial heterogeneity represents a general characteristic of the inequitable distributions of spatial issues. The spatial stratified heterogeneity analysis investigates the heterogeneity among various strata of explanatory variables by comparing the spatial variance within strata and that between strata. The geographical detector model is a widely used technique for spatial stratified heterogeneity analysis. In the model, the spatial data discretization and spatial scale effects are fundamental issues, but they are generally determined by experience and lack accurate quantitative assessment in previous studies. To address this issue, an optimal parameters-based geographical detector (OPGD) model is developed for more accurate spatial analysis. The optimal parameters are explored as the best combination of spatial data discretization method, break number of spatial strata, and spatial scale parameter. In the study, the OPGD model is applied in three example cases with different types of spatial data, including spatial raster data, spatial point or areal statistical data, and spatial line segment data, and an R “GD” package is developed for computation. Results show that the parameter optimization process can further extract geographical characteristics and information contained in spatial explanatory variables in the geographical detector model. The improved model can be flexibly applied in both global and regional spatial analysis for various types of spatial data. Thus, the OPGD model can improve the overall capacity of spatial stratified heterogeneity analysis. The OPGD model and its diverse solutions can contribute to more accurate, flexible, and efficient spatial heterogeneity analysis, such as spatial patterns investigation and spatial factor explorations. 相似文献
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针对监控视频动态目标的空间定位问题,本文在考虑相机畸变的前提下,对监控相机、目标像素坐标和地理场景之间的映射关系进行了研究,提出了基于数字表面模型(DSM)和基于平面约束的目标定位算法。首先,完成相机的标定,确定相机的成像模型;然后,提取畸变校正后的目标像素坐标,并通过目标定位算法计算目标的三维地理坐标;最后,进行了定位精度评定,并分析了两种定位算法的应用特点。本文的定位算法将以像素坐标定位的目标数据解析为以三维坐标定位的空间地理信息,为多摄像头的目标跟踪提供了统一的地理参考框架。 相似文献
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提出了一种基于百度地图服务的地址解析方法,通过自动搜索和调用百度数据资源,实现了地名地址信息的快速、批量定位与上图,在武汉市第一次地理国情普查数据采集中取得了较好应用。 相似文献
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Geocoding urban addresses usually requires the use of an underlying address database. Under the influence of the format defined for TIGER files decades ago, most address databases and street geocoding algorithms are organized around street centerlines, associating numbering ranges to thoroughfare segments between two street crossings. While this method has been successfully employed in the USA for a long time, its transposition to other countries may lead to increased errors. This article presents an evaluation of the centerline‐geocoding resources provided by Google Maps, as compared to the point‐geocoding method used in the city of Belo Horizonte, Brazil, which we took as a baseline. We generated a textual address for each point object found in the city's point‐based address database, and submitted it to the Google Maps geocoding API. We then compared the resulting coordinates with the ones recorded in Belo Horizonte's GIS. We demonstrate that the centerline segment interpolation method, employed by the online resources following the American practice, has problems that can considerably influence the quality of the geocoding outcome. Completeness and accuracy have been found to be irregular, especially within lower income areas. Such errors in online services can have a significant impact on geocoding efforts related to social applications, such as public health and education, since the online service can be faulty and error‐prone in the most socially demanding areas of the city. In the conclusion, we point out that a volunteered geographic information (VGI) approach can help with the enrichment and enhancement of current geocoding resources, and can possibly lead to their transformation into more reliable point‐based geocoding services. 相似文献
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Accurately mapped locations within multi-unit properties are useful for several organizations in today's society. Published work on geocoding methods either require detailed location reference data or does not apply to multi-unit buildings. In this research, a generalizable method is realized to map apartment addresses to their explicit locations without access to indoor location reference data based on publicly available address- and geospatial-building information. The performance of this approach is measured by conducting a comparative study between a linear interpolation baseline and gradient-boosted decision trees model. The proposed method can successfully geocode addresses across different building shapes and sizes. Furthermore, the model significantly outperforms the baseline in terms of positional accuracy proving the feasibility of approximating apartment locations by their address- and geospatial-building information. 相似文献
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采用了Geodatabase空间数据模型，建立了地理信息数据库，设计了基于地理信息的人员疏散模型。 相似文献
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针对地理数据中空间对象概念模型,尝试利用对象-关系数据库(ORDB)的一些优势,对已有的地理数据中空间对象的M-L-E(S,A)分层模型进行了改进,实体之间可以通过类、继承等方式产生和关联,地图和图层之间、图层和实体之间采用引用方式实现连接,不再存在从属关系,实现了更大程度的共享,可以更好地体现ORDB相对于OODB或RDB对地理空间数据的表达。同时提出了该模型的形式化表达,并对空间实体、图层和地图各层次分别进行了分析讨论,提出基于ORDB的支持方式和特点,并设想了地图尺度转化从图层到实体向下层追溯的过程。 相似文献
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随着我国城市化和信息化的发展,地址编码已经成为建设数字城市的基础工作。地址匹配是地址编码的关键环节,但面临着中文地址分词困难的问题。本文基于Lucene检索引擎,结合三叉树分词词典机制和基于规则的地址分词技术,设计了具有地址分词和地址匹配功能的地址匹配引擎,并构建了Rest风格的在线地址匹配服务,取得了良好的应用效果。 相似文献
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Hassan A. Karimi Monir H. Sharker Duangduen Roongpiboonsopit 《Transactions in GIS》2011,15(6):869-886
Today, many services that can geocode addresses are available to domain scientists and researchers, software developers, and end‐users. For a number of reasons, including quality of reference database and interpolation technique, a given address geocoded by different services does not often result in the same location. Considering that there are many widely available and accessible geocoding services and that each geocoding service may utilize a different reference database and interpolation technique, selecting a suitable geocoding service that meets the requirements of any application or user is a challenging task. This is especially true for online geocoding services which are often used as black boxes and do not provide knowledge about the reference databases and the interpolation techniques they employ. In this article, we present a geocoding recommender algorithm that can recommend optimal online geocoding services by realizing the characteristics (positional accuracy and match rate) of the services and preferences of the user and/or their application. The algorithm is simulated and analyzed using six popular online geocoding services for different address types (agricultural, commercial, industrial, residential) and preferences (match rate, positional accuracy). 相似文献