共查询到20条相似文献，搜索用时 390 毫秒
1.
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
2.
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
3.
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
4.
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
5.
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
6.
Positional Accuracy of Spatial Data: Non-Normal Distributions and a Critique of the National Standard for Spatial Data Accuracy 总被引：5，自引：0，他引：5
Paul A Zandbergen 《Transactions in GIS》2008,12(1):103-130
Spatial data quality is a paramount concern in all GIS applications. Existing spatial data accuracy standards, including the National Standard for Spatial Data Accuracy (NSSDA) used in the United States, commonly assume the positional error of spatial data is normally distributed. This research has characterized the distribution of the positional error in four types of spatial data: GPS locations, street geocoding, TIGER roads, and LIDAR elevation data. The positional error in GPS locations can be approximated with a Rayleigh distribution, the positional error in street geocoding and TIGER roads can be approximated with a log‐normal distribution, and the positional error in LIDAR elevation data can be approximated with a normal distribution of the original vertical error values after removal of a small number of outliers. For all four data types considered, however, these solutions are only approximations, and some evidence of non‐stationary behavior resulting in lack of normality was observed in all four datasets. Monte‐Carlo simulation of the robustness of accuracy statistics revealed that the conventional 100% Root Mean Square Error (RMSE) statistic is not reliable for non‐normal distributions. Some degree of data trimming is recommended through the use of 90% and 95% RMSE statistics. Percentiles, however, are not very robust as single positional accuracy statistics. The non‐normal distribution of positional errors in spatial data has implications for spatial data accuracy standards and error propagation modeling. Specific recommendations are formulated for revisions of the NSSDA. 相似文献
7.
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
8.
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
9.
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
10.
Impacts of Positional Error on Spatial Regression Analysis: A Case Study of Address Locations in Syracuse, New York 总被引：1，自引：0，他引：1
Daniel A Griffith Marco Millones Matthew Vincent David L Johnson Andrew Hunt 《Transactions in GIS》2007,11(5):655-679
Positional error is the error produced by the discrepancy between reference and recorded locations. In urban landscapes, locations typically are obtained from global positioning systems or geocoding software. Although these technologies have improved the locational accuracy of georeferenced data, they are not error free. This error affects results of any spatial statistical analysis performed with a georeferenced dataset. In this paper we discuss the properties of positional error in an address matching exercise and the allocation of point locations to census geography units. We focus on the error's spatial structure, and more particularly on impacts of error propagation in spatial regression analysis. For this purpose we use two geocoding sources, we briefly describe the magnitude and the nature of their discrepancies, and we evaluate the consequences that this type of locational error has on a spatial regression analysis of pediatric blood lead data for Syracuse, NY. Our findings include: (1) the confirmation of the recurrence of spatial clustering in positional error at various geographic resolutions; and, (2) the identification of a noticeable but not shockingly large impact from positional error propagation in spatial auto‐binomial regression analysis results for the dataset analyzed. 相似文献
11.
《International Journal of Digital Earth》2013,6(10):825-839
With the increased use of locational information, spatial location referencing and coding methods have become much more important to the mining of both geographical and nongeographical data in digital earth system. Unfortunately, current methods of geocoding, based on reverse lookup of coordinates for a given address, have proven too lossy with respect to administrative and socioeconomic data. This paper proposes a spatial subdivision and geocoding model based on spatial address regional tessellation (SART). Given a hierarchical address object definition, and based on the ‘region of influence’ characteristics of an address, SART creates multiresolution spatial subdivisions by irregular and continuous address regions. This model reflects most of the geographical features and many of the social and economic implications for a given address. It also better reflects the way people understand addresses and spatial locations. We also propose an appropriate method of geocoding for standard addresses (SART-GC). The codes generated by this method can record address footprints, hierarchical relationships, and spatial scales in a single data structure. Finally, by applying our methods to the Shibei District of Qingdao, we demonstrate the suitability of SART-GC for multi-scale spatial information representation in digital earth systems. 相似文献
12.
针对目前在线专题图表达存在交互性差、使用不够灵活、表达不够美观等问题。该文分析了当前在线专题制图产品存在的不足之处,并基于NewMap Server软件提出了一套集在线专题数据服务和在线专题制图API为一体的解决方案,在此基础上研发了面向服务的在线专题制图系统。利用NewMap地名地址匹配技术实现专题数据与地名数据的快速准确匹配并且制定统一的服务标准与客户端交互。客户端采用自主的图形算法实现专题数据的可视化表达。最后对专题图系统进行了详细的设计,并对设计的7种统计专题图进行实例验证。实践表明,该专题图系统有交互性强、制图速度快等优点,具有很好应用前景。 相似文献
13.
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
14.
Zhengcong Yin Daniel W. Goldberg Tracy A. Hammond Chong Zhang Andong Ma Xiao Li 《Transactions in GIS》2020,24(3):656-680
Reverse geocoding, which transforms machine‐readable GPS coordinates into human‐readable location information, is widely used in a variety of location‐based services and analysis. The output quality of reverse geocoding is critical because it can greatly impact these services provided to end‐users. We argue that the output of reverse geocoding should be spatially close to and topologically correct with respect to the input coordinates, contain multiple suggestions ranked by a uniform standard, and incorporate GPS uncertainties. However, existing reverse geocoding systems often fail to fulfill these aims. To further improve the reverse geocoding process, we propose a probabilistic framework that includes: (1) a new workflow that can adapt all existing address models and unitizes distance and topology relations among retrieved reference data for candidate selections; (2) an advanced scoring mechanism that quantifies characteristics of the entire workflow and orders candidates according to their likelihood of being the best candidate; and (3) a novel algorithm that derives statistical surfaces for input GPS uncertainties and propagates such uncertainties into final output lists. The efficiency of the proposed approaches is demonstrated through comparisons to the four commercial reverse geocoding systems and through human judgments. We envision that more advanced reverse geocoding output ranking algorithms specific to different application scenarios can be built upon this work. 相似文献
15.
As tools for collecting data continue to evolve and improve, the information available for research is expanding rapidly. Increasingly, this information is of a spatio‐temporal nature, which enables tracking of phenomena through both space and time. Despite the increasing availability of spatio‐temporal data, however, the methods for processing and analyzing these data are lacking. Existing geocoding techniques are no exception. Geocoding enables the geographic location of people and events to be known and tracked. However, geocoded information is highly generalized and subject to various interpolation errors. In addition, geocoding for spatio‐temporal data is especially challenging because of the inherent dynamism of associated data. This article presents a methodology for geocoding spatio‐temporal data in ArcGIS that utilizes several additional supporting procedures to enhance spatial accuracy, including the use of supplementary land use information, aerial photographs and local knowledge. This hybrid methodology allows for the tracking of phenomenon through space and over time. It is also able to account for reporting inconsistencies, which is a common feature of spatio‐temporal data. The utility of this methodology is demonstrated using an application to spatio‐temporal address records for a highly mobile group of convicted felons in Hamilton County, Ohio. 相似文献
16.
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
17.
18.
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
19.
《制图学和地理信息科学》2013,40(4):285-301
How to effectively represent spatial information on handheld mobile devices is a key question, given the increasing use of personal digital assistants (PDAs) and cell phones concurrent with the development of location-based services. The mobile use of digital maps on small displays presents new capabilities and challenges that differ from using paper maps in a mobile setting or viewing digital maps on a desktop computer. This research addresses these issues through a study that evaluated maps on a mobile device used for a field-based navigation task. Map representations at two levels of generalization were compared by analyzing subject performance in a pedestrian route-following task, in which a handheld computer was used as a navigation aid. Subject time and accuracy as well as interaction with the mobile device during the task were measured. The results carry implications for map design for small, mobile displays and identify factors that affect the use of maps while moving. Maps are and will increasingly be used on small displays in mobile contexts for a variety of purposes and in many different environments. The requirements and preferences of mobile users, as well as how these maps are used in different contexts, must be understood in order to inform more effective designs. 相似文献