Geocoding Method Research Articles

Turkish street addressing system and geocoding challenges

A street address system is one of the most basic techniques used by government and others for service delivery. It enables emergency services, security, taxation, health services, delivery and mail services and it also monitors the spatial whereabouts of individuals within a population. The effective management of urban areas can only be achieved if an accurate street address infrastructure is formed. The present study investigated the problems related to street addressing in Turkey and was conducted in three stages. First, the effectiveness of the existing street addressing system was examined. The problems caused by organisations and individuals that use non-standard formats were addressed in the second stage. In the third and final stage, statistical analyses of various geocoding methods, including dual-range, one-range, single field and the zoning improvement plan, were carried out and the most appropriate geocoding method was found.

Comparing Methodologies for Imputing Ethnicity in an Urban Ophthalmology Clinic

Purpose: To compare methodologies for imputing ethnicity in an urban ophthalmology clinic.Methods: Using data from 19,165 patients with self-reported ethnicity, surname, and home address, we compared the accuracy of three methodologies for imputing ethnicity: (1) a surname method based on tabulation from the 2000 US Census; (2) a geocoding method based on tract data from the 2010 US Census; and (3) a combined surname geocoding method using Bayes’ theorem.Results: The combined surname geocoding model had the highest accuracy of the three methodologies, imputing black ethnicity with a sensitivity of 84% and positive predictive value (PPV) of 94%, white ethnicity with a sensitivity of 92% and PPV of 82%, Hispanic ethnicity with a sensitivity of 77% and PPV of 71%, and Asian ethnicity with a sensitivity of 83% and PPV of 79%. Overall agreement of imputed and self-reported ethnicity was fair for the surname method (κ 0.23), moderate for the geocoding method (κ 0.58), and strong for the combined method (κ 0.76).Conclusion: A methodology combining surname analysis and Census tract data using Bayes’ theorem to determine ethnicity is superior to other methods tested and is ideally suited for research purposes of clinical and administrative data.

Accessible and Practical Geocoding Method for Traffic Collision Record Mapping

Numerous studies of geocoding systems have been used to assign geographical coordinates to incident reports identified simply with textual address references. These studies have typically focused on the level of accuracy achieved by various geocoding systems and found that acceptable results can be achieved. Depending on the quality of the input data, a match rate between 70% and 83% can be expected, with varying levels of accuracy. However, few studies have looked at the potential of freely available online geocoding services to spatially locate traffic crash records. It is proposed that although limitations currently exist, services such as the Google Maps API provide sufficient functionality and adequate accuracy for use with a wide variety of geocoding applications. A case study used traffic crash records from a municipality in the province of Quebec, Canada, with the goal of quantifying the geo coding results. It was found that although a competitive match rate was obtained, manual revision was required to ensure that the results returned by the geocoder referred to the same intersection that existed in the input address field.

Topological Analysis in Indoor Shopping Mall using Ontology

Recently, human activities have expanded from outdoor spaces to indoor spaces since a lot of complex buildings were constructed over the world. Especially, visitors in a shopping mall would like to receive specific information of interest regarding various shopping-related activities as well as shopping itself. However, when it comes to providing the information, existing guide services have some drawbacks. Firstly, the existing services cannot provide visitors with the information of other stores simply and promptly on the current location. Secondly, the services have difficulties in representation and share of the shopping-related knowledge, and in providing inferred information. Thus, the purpose of this study is to develop a method that allows topological analysis utilizing ontology technique around the current position in such shopping mall in order to provide shopping-related information. For this, the shopping activity ontology model is designed, and based on the ontology model, inferencing rules are defined in order to extract the information of interest efficiently through semantic queries. Also, a geocoding method in indoor spaces is used regarding the current location, and optimal routing analysis, which is one of topological analysis, is applied with the result from the semantic queries. As a result, an Android application is developed for 3D visualization and user interface.

Positional error and time-activity patterns in near-highway proximity studies: an exposure misclassification analysis

BackgroundThe growing interest in research on the health effects of near-highway air pollutants requires an assessment of potential sources of error in exposure assignment techniques that rely on residential proximity to roadways.MethodsWe compared the amount of positional error in the geocoding process for three different data sources (parcels, TIGER and StreetMap USA) to a “gold standard” residential geocoding process that used ortho-photos, large multi-building parcel layouts or large multi-unit building floor plans. The potential effect of positional error for each geocoding method was assessed as part of a proximity to highway epidemiological study in the Boston area, using all participants with complete address information (N = 703). Hourly time-activity data for the most recent workday/weekday and non-workday/weekend were collected to examine time spent in five different micro-environments (inside of home, outside of home, school/work, travel on highway, and other). Analysis included examination of whether time-activity patterns were differentially distributed either by proximity to highway or across demographic groups.ResultsMedian positional error was significantly higher in street network geocoding (StreetMap USA = 23 m; TIGER = 22 m) than parcel geocoding (8 m). When restricted to multi-building parcels and large multi-unit building parcels, all three geocoding methods had substantial positional error (parcels = 24 m; StreetMap USA = 28 m; TIGER = 37 m). Street network geocoding also differentially introduced greater amounts of positional error in the proximity to highway study in the 0–50 m proximity category. Time spent inside home on workdays/weekdays differed significantly by demographic variables (age, employment status, educational attainment, income and race). Time-activity patterns were also significantly different when stratified by proximity to highway, with those participants residing in the 0–50 m proximity category reporting significantly more time in the school/work micro-environment on workdays/weekdays than all other distance groups.ConclusionsThese findings indicate the potential for both differential and non-differential exposure misclassification due to geocoding error and time-activity patterns in studies of highway proximity. We also propose a multi-stage manual correction process to minimize positional error. Additional research is needed in other populations and geographic settings.

Mosaic method of side‐scan sonar strip images using corresponding features

The towing operation mode of side-scan sonar system (SSS) easily results in dislocations and distortions of targets in the SSS strip image, brings difficulty to the mosaic of these strip images by the geocoding method or the tessellation-line method and affects the recognition and understanding for seabed relief. Therefore this study proposes a new method, namely the segment-image mosaic method based on corresponding features of the two adjacent SSS strip images. Through SSS image preprocessing, segment match based on corresponding features and image fusion in the common coverage area based on wavelet transformation, this new method overcomes the drawbacks of the traditional methods of image mosaic, fulfils well the mosaic of SSS strip images and finally a whole-area SSS image is formed. Experiments have verified that the mosaic image formed by the new method can correctly reflect the position, shape and distribution of seabed targets, which is helpful to understand seabed relief.

Using the Bayesian Improved Surname Geocoding Method (BISG) to Create a Working Classification of Race and Ethnicity in a Diverse Managed Care Population: A Validation Study

To validate classification of race/ethnicity based on the Bayesian Improved Surname Geocoding method (BISG) and assess variations in validity by gender and age. Secondary data on members of Kaiser Permanente Georgia, an integrated managed care organization, through 2010. For 191,494 members with self-reported race/ethnicity, probabilities for belonging to each of six race/ethnicity categories predicted from the BISG algorithm were used to assign individuals to a race/ethnicity category over a range of cutoffs greater than a probability of 0.50. Overall as well as gender- and age-stratified sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. Receiver operating characteristic (ROC) curves were generated and used to identify optimal cutoffs for race/ethnicity assignment. The overall cutoffs for assignment that optimized sensitivity and specificity ranged from 0.50 to 0.57 for the four main racial/ethnic categories (White, Black, Asian/Pacific Islander, Hispanic). Corresponding sensitivity, specificity, PPV, and NPV ranged from 64.4 to 81.4 percent, 80.8 to 99.7 percent, 75.0 to 91.6 percent, and 79.4 to 98.0 percent, respectively. Accuracy of assignment was better among males and individuals of 65years or older. BISG may be useful for classifying race/ethnicity of health plan members when needed for health care studies.

Study on Block Segmenting Method of House Number

House number is one important city geocoding method, which has the most fundamental positioning role and also is the main information carrier in digital city construction. Because traditional house number system has faultiness and city spatial layout has changed a lot with urbanization process in china, house numbers are chaotic in many cities. It is very inconvenient for city management and information construction. It is urgent to reconstruct scientific house number system. First, the authors introduce the advantages and disadvantages of main domestic and foreign house number systems, analyzed the spatial characters of house number, and compared the merits and demerits of block geocoding and street geocoding method. Then, they point out that street is the appropriate spatial framework for house number system of our country. Next they analyzed the spatial localization characters of the house number geocoding within street framework, and pointed out the shortages of traditional serial number and distance number. Then, they put forward and elaborate the block segmenting method of house number. At last, on the assumption that each block has 100 numbers, the figures of block segmenting are displayed. The block segmenting method can ensure the robustness of house number system. It further strengthens the order and localization role of house number and realizes binding house numbers to street block segment. House numbers will not become chaos with the increases and decreases or changing hands of the buildings in the system.

실내 공간에서의 문자매칭 기반 지오코딩 기법

최근 위치 정보의 이용이 여러 분야에 걸쳐 급격하게 증가하고 있다. 실외에서는 위치 정보의 획득을 위해 일반적으로 GPS 기술을 사용하였으나, 복잡한 실내 공간에서는 벽, 기둥과 같은 물리적인 장애물들로 인해 발생한 다중경로 간섭으로 무선 근거리통신망, RFID, 블루투스 등의 무선 네트워크 기술을 적용한 연구가 진행되었다. 그러나 이러한 위치 측정 기술들은 센싱 인프라스트럭쳐 구축비용이 많이 들며, 측위에 있어 계산 집약적이고, 실내 구조에 따른 정확도의 변화가 발생하는 한계가 존재한다. 본 연구에서는 이러한 한계점을 보완하고자 복합용도건물 내에서 쉽게 획득 및 식별이 가능한 상가, 컨벤션 센터 및 오피스의 전화번호, 방 번호, 상호명과 같은 서술 데이터를 이용하여 위치를 추출한다. 이 과정에서 문자 매칭을 활용하며, 위치 추정에 있어 신속한 계산과 실내 환경에 따른 정확도 변화를 배제하기 위해 지오코딩 방법을 적용한다. 본 연구에서 제안된 방법을 아키텍쳐로 설계하며, 구현을 위해 3차원 가시화 프로그램을 개발한다. 또한 제한된 기법에서의 매칭률, 프로세싱 시간을 통하여 정략적으로 평가한다. Recently, the use of locational information is growing rapidly. GPS technology has been adopted generally for obtaining locational information in outdoor spaces. In the other hand, the researches on indoor positioning have been carried out applying WLAN, RFID or Bluetooth technology because of the multi-path interference of GPS signal caused by the physical obstacles such as walls or columns in buildings. However, such technologies for indoor positioning cost too much to build sensing infrastructure and compute-intensive processes are involved. Furthermore, the accuracy of location estimation is variable caused by interior structures in buildings. In this study, to make up for the limitations, descriptive data such as phone number, unique room numbers, or business names readily available in mixed-use buildings is used for extracting location information. Furthermore, during the process, a geocoding method using character matching is applied to this study enabling prompt location estimation and sublating the fluctuation of accuracy caused by interior structures. Based on the proposed method in this study, an architecture is designed, and three-dimensional viewer program is developed for the implementation of this study. Also, this research is quantitatively analyzed through match rate and processing time of proposed method.

Race and ethnicity data quality and imputation using U.S. Census data in an integrated health system: the Kaiser Permanente Southern California experience.

Research on racial and ethnic disparities using health system databases can shed light on the usual health care and outcomes of large numbers of individuals so that health inequities can be better understood and addressed. Such research often suffers from limitations in race/ethnicity data quality. We examined the quality of race/ethnicity data in a large, diverse, integrated health system that repeatedly collects these data on utilization of services. We tested the accuracy of Bayesian Improved Surname Geocoding for imputation of race/ethnicity data. Administrative race/ethnicity data were accurate as judged by comparison with self-report in adults. The Bayesian Improved Surname Geocoding method produced imputation results far better than chance assignment for the four most common race/ethnicity groups in the health system: Whites, Hispanics, Blacks, and Asians. These results support renewed efforts to conduct studies of racial and ethnic disparities in large health systems.

A unified location sharing service with end user privacy control

With the rapid development of the Global Positioning System (GPS), Wi-Fi, and cell ID based positioning technologies, location based applications are becoming popular. In the development and deployment of location based applications, it is usually necessary to have common location platforms or location enablers which can collect and store the end user's location and then share it with the applications. This paper presents a location sharing service prototype which can transmit an end user location gathered from different sources (GPS location, physical address, Internet Protocol (IP) address, and cell ID) to location applications. The service is provided to end users and applications through open and simple Web service interfaces. In addition, it enables end users to set rules around how their location may be distributed. The paper describes the overall architecture of the service, focusing on its geocoding method and privacy control mechanism.

GIS-based geocoding methods for area-based addresses and 3D addresses in urban areas

For more than four decades, two address-matching methods, the street-based address geocoding method and address-point-matching method, have been used to identify geographical coordinates from postal addresses. However, street-based address geocoding methods developed for the US addressing system are not universally applicable in developing a single-portal geocoding middleware for worldwide Internet-based geographic information systems applications. Problems also exist with address-point matching especially in its capability to identify features and incorporate 3D locational data from 3D addresses for analysis of large public buildings, shopping centers or metro-subways, that exist in urban environments. To alleviate these problems, this paper details two alternative address-matching methods, an area-based address geocoding method and a 3D address geocoding method. The area-based address geocoding method is a 2D positioning method based on a 2D area-based address-matching technique. The 3D address geocodin...

Applying InSAR technique to accurately relocate the epicentre for the 1999Ms= 5.6 Kuqa earthquake in Xinjiang province, China

SUMMARY The 1999 M s = 5.6 Kuqa earthquake occurred in a seismically active belt between the Tianshan Mountain and the Traim basin. Because of the sparse seismic network and complex crustal structure, it is very difficult to accurately locate the epicentre for this event using seismic waves. The epicentres located by different research groups vary over a spatial range of 20– 40 km. Interferometric synthetic aperture radar (InSAR) is a geodetic technique with fine spatial resolution, good precision and wide coverage. An interferometric map of the epicentral region constrains the epicentre of this event. The arid climate and sparsely vegetation in the Kuqa region provide excellent conditions for InSAR studies. In this paper, we firstly construct a interferogram to map the coseismic deformation field due to the 1999 Kuqa earthquake using a coseismic interferometric pair of radar images acquired by the ESA ERS-2 satellite. Then, we develop a new geocoding method and apply it to the interferogram. Next, we infer the geometry of the seismogenic fault according to its focal mechanism and tectonic setting. To model the interferogram, we assume a dislocation buried in a uniform elastic half-space. Finally, we infer the epicentre of this earthquake to be located at (82.80 ◦ E, 41.92 ◦ N), which is close to the results of the National Earthquake Information Center of USGS and China Earthquake Administration. The epicentre location inferred from InSAR falls in the six-level isoseismal contour described by Xinjiang earthquake administration using the field investigations.

A new method for estimating race/ethnicity and associated disparities where administrative records lack self-reported race/ethnicity.

To efficiently estimate race/ethnicity using administrative records to facilitate health care organizations' efforts to address disparities when self-reported race/ethnicity data are unavailable. Surname, geocoded residential address, and self-reported race/ethnicity from 1,973,362 enrollees of a national health plan. We compare the accuracy of a Bayesian approach to combining surname and geocoded information to estimate race/ethnicity to two other indirect methods: a non-Bayesian method that combines surname and geocoded information and geocoded information alone. We assess accuracy with respect to estimating (1) individual race/ethnicity and (2) overall racial/ethnic prevalence in a population. The Bayesian approach was 74 percent more efficient than geocoding alone in estimating individual race/ethnicity and 56 percent more efficient in estimating the prevalence of racial/ethnic groups, outperforming the non-Bayesian hybrid on both measures. The non-Bayesian hybrid was more efficient than geocoding alone in estimating individual race/ethnicity but less efficient with respect to prevalence (p<.05 for all differences). The Bayesian Surname and Geocoding (BSG) method presented here efficiently integrates administrative data, substantially improving upon what is possible with a single source or from other hybrid methods; it offers a powerful tool that can help health care organizations address disparities until self-reported race/ethnicity data are available.

A Three-Dimensional Navigable Data Model to Support Emergency Response in Microspatial Built-Environments

Since the 11 September 2001 attacks in the United States and the 7 July 2005 London bombings, geospatial researchers have attempted to utilize GIScience technologies in response to disasters occurring in the microspace of multilevel structures (such as the interior of buildings) in urban areas. Such applications require 3D geographic information systems (GIS) functionalities to represent the three-dimensional structures of urban environments and to conduct 3D GIS-based spatial analyses. These requirements motivate this study to represent the complex internal structure of buildings at a three-dimensional subunit level so as to analyze human behavior in an emergency situation. This article discusses the development of a 3D Navigable Data Model (3D NDM) based on the 3D Geometric Network Data Model and representing pedestrian access within buildings or urban built-environments, which can be modeled as a network of walkway sections and connections. Additionally, this article discusses the design of a geospatial database created to manage the physical and environmental factors of disaster sites that are essential for emergency response. To improve planning and facilitate rescue operations in a decision support system, this article presents (1) a 3D geo-coding method to locate rescue personnel and disaster sites within the reference data (a network representation of a building), (2) a 3D map matching method to define the correlation between the location of bottlenecks or disaster sites and the nearest location on the 3D NDM, which represents the internal structure of the built-environment as a network representation, and (3) an indoor navigation model, based on the Dijkstra algorithm, to identify optimal routes within a multilevel structure by measuring relative pedestrian accessibility and to provide navigation guidance for rescue personnel. Lastly, this article presents the results of an experimental implementation of the 3D NDM using GIS data for a section of the University of North Carolina at Charlotte campus.

Comparing a single-stage geocoding method to a multi-stage geocoding method: how much and where do they disagree?

Comparing a single-stage geocoding method to a multi-stage geocoding method: how much and where do they disagree?

Assessing the Certainty of Locations Produced by an Address Geocoding System

Addresses are the most common georeferencing resource people use to communicate to others a location within a city. Urban GIS applications that receive data directly from citizens, or from legacy information systems, need to be able to quickly and efficiently obtain a spatial location from addresses. In this paper we understand addresses in a broader perspective, in which not only the conventional elements of postal addresses are considered, but other kinds of direct or indirect references to places, such as building names, postal codes, or telephone area codes, which are also valuable as locators to urban places. This broader view on addresses allows us to work with two perspectives. First, in the ontological definition, modeling, and implementation of an addressing database that is flexible enough to accommodate the variety of concepts and address formats used worldwide, along with direct and indirect references to places. Second, in the definition of an indicator that is able to quantify the degree of certainty that could be reached when a user-given, semi-structured address is geocoded into a spatial position, as a function of the type and completeness of the available addressing data and of the geocoding method that has been employed. This indicator, which we call Geocoding Certainty Indicator (GCI), can be used as a threshold, beyond which the geocoded event should be left out of any statistical analysis, or as a weight that allows spatial analysis methods to reduce the influence of events that have been less reliably located. In order to support geocoding activities and the determination of the GCI, we propose a conceptual schema for addressing databases. The schema is flexible enough to accommodate a variety of addressing systems, at various levels of detail, and in different countries. Our intention is to depart from the usual geocoding strategy employed in commercial GIS products, which is usually limited to the average American or British address format. The schema also extends the notion of postal address to something broader, including popular names for places, building names, reference places, and other concepts. This approach extends Simpson’s and Yu’s Comput. Environ. Urban Syst., 27: 283–307, 2003 work on postal codes to records of any kind, including place names and loosely formatted addresses.

Comparing a single-stage geocoding method to a multi-stage geocoding method: how much and where do they disagree?

BackgroundGeocoding methods vary among spatial epidemiology studies. Errors in the geocoding process and differential match rates may reduce study validity. We compared two geocoding methods using 8,157 Washington State addresses. The multi-stage geocoding method implemented by the state health department used a sequence of local and national reference files. The single-stage method used a single national reference file. For each address geocoded by both methods, we measured the distance between the locations assigned by each method. Area-level characteristics were collected from census data, and modeled as predictors of the discordance between geocoded address coordinates.ResultsThe multi-stage method had a higher match rate than the single-stage method: 99% versus 95%. Of 7,686 addresses were geocoded by both methods, 96% were geocoded to the same census tract by both methods and 98% were geocoded to locations within 1 km of each other by the two methods. The distance between geocoded coordinates for the same address was higher in sparsely populated and low poverty areas, and counties with local reference files.ConclusionThe multi-stage geocoding method had a higher match rate than the single-stage method. An examination of differences in the location assigned to the same address suggested that study results may be most sensitive to the choice of geocoding method in sparsely populated or low-poverty areas.

On the accuracy of TIGER-type geocoded address data in relation to cadastral and census areal units

In many applications of Geographical Information Systems (GIS) a common task is the conversion of addresses into grid coordinates. In many countries this is usually accomplished using address range TIGER-type files in conjunction with geocoding packages within a GIS. Improvements in GIS functionality and the storage capacity of large databases mean that the spatial investigation of data at the individual address level is now commonly performed. This process relies on the accuracy of the geocoding mechanism and this paper examines this accuracy in relation to cadastral records and census tracts. Results from a study of over 20 000 addresses in Sydney, Australia, using a TIGER-type geocoding process suggest that 5-7.5% (depending on geocoding method) of addresses may be misallocated to census tracts, and more than 50% may be given coordinates within the land parcel of a different property.