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An Iterative Approach to the Parcel Level Address Geocoding of a Large Health Dataset to a Shifting Household Geography
210 Haag Hall 5100 Rockhill Road Kansas City, MO 64110 (816) 235‐1314 cei.umkc.edu Center for Economic Information Working Paper 1702-01 July 21, 2017 An Iterative Approach to the Parcel Level Address Geocoding of a Large Health Dataset to a Shifting Household Geography by Ben Wilson and Neal Wilson Abstract This article details an iterative process for the address geocoding of a large collection of health encounters (n = 242,804) gathered over a 13 year period to a parcel geography which varies by year. This procedure supports an investigation of the relationship between basic housing conditions and the corresponding health of occupants. Successful investigation of this relationship necessitated matching individuals, their health outcomes and their home environments. This match process may be useful to researchers in a variety of fields with particular emphasis on predictive modeling and up-stream medicine. An Iterative Application of Centerline and Parcel Geographies for Spatio-temporal Geocoding of Health and Housing Data Ben Wilson & Neal Wilson 1 Introduction This article explains an iterative geocoding process for matching address level health encounters (590,058 asthma and well child encounters ) to heterogeneous parcel geographies that maintains the spatio-temporal disaggregation of both datasets (243,260 surveyed parcels). The development of this procedure supports the objectives outlined in the U.S. Department of Housing and Urban Development funded Kansas City – Home Environment Research Taskforce (KC-Heart). The goal of KC-Heart is investigate the relationship between basic housing conditions and the health outcomes of child occupants. Successful investigation of this relationship necessitates matching individuals, their health outcomes and their home environments. -
A Comparison of Address Point and Street Geocoding Techniques
A COMPARISON OF ADDRESS POINT AND STREET GEOCODING TECHNIQUES IN A COMPUTER AIDED DISPATCH ENVIRONMENT by Jimmy Tuan Dao A Thesis Presented to the FACULTY OF THE USC GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Fulfillment of the Requirements for the Degree MASTER OF SCIENCE (GEOGRAPHIC INFORMATION SCIENCE AND TECHNOLOGY) August 2015 Copyright 2015 Jimmy Tuan Dao DEDICATION I dedicate this document to my mother, sister, and Marie Knudsen who have inspired and motivated me throughout this process. The encouragement that I received from my mother and sister (Kim and Vanna) give me the motivation to pursue this master's degree, so I can better myself. I also owe much of this success to my sweetheart and life-partner, Marie who is always available to help review my papers and offer support when I was frustrated and wanting to quit. Thank you and I love you! ii ACKNOWLEDGMENTS I will be forever grateful to the faculty and classmates at the Spatial Science Institute for their support throughout my master’s program, which has been a wonderful period of my life. Thank you to my thesis committee members: Professors Darren Ruddell, Jennifer Swift, and Daniel Warshawsky for their assistance and guidance throughout this process. I also want to thank the City of Brea, my family, friends, and Marie Knudsen without whom I could not have made it this far. Thank you! iii TABLE OF CONTENTS DEDICATION ii ACKNOWLEDGMENTS iii LIST OF TABLES iii LIST OF FIGURES iv LIST OF ABBREVIATIONS vi ABSTRACT vii CHAPTER 1: INTRODUCTION 1 1.1 Brea, California -
A Cross-Sectional Ecological Analysis of International and Sub-National Health Inequalities in Commercial Geospatial Resource Av
Dotse‑Gborgbortsi et al. Int J Health Geogr (2018) 17:14 https://doi.org/10.1186/s12942-018-0134-z International Journal of Health Geographics RESEARCH Open Access A cross‑sectional ecological analysis of international and sub‑national health inequalities in commercial geospatial resource availability Winfred Dotse‑Gborgbortsi1,2, Nicola Wardrop2, Ademola Adewole2, Mair L. H. Thomas2 and Jim Wright2* Abstract Background: Commercial geospatial data resources are frequently used to understand healthcare utilisation. Although there is widespread evidence of a digital divide for other digital resources and infra-structure, it is unclear how commercial geospatial data resources are distributed relative to health need. Methods: To examine the distribution of commercial geospatial data resources relative to health needs, we assem‑ bled coverage and quality metrics for commercial geocoding, neighbourhood characterisation, and travel time calculation resources for 183 countries. We developed a country-level, composite index of commercial geospatial data quality/availability and examined its distribution relative to age-standardised all-cause and cause specifc (for three main causes of death) mortality using two inequality metrics, the slope index of inequality and relative concentration index. In two sub-national case studies, we also examined geocoding success rates versus area deprivation by district in Eastern Region, Ghana and Lagos State, Nigeria. Results: Internationally, commercial geospatial data resources were inversely related to all-cause mortality. This relationship was more pronounced when examining mortality due to communicable diseases. Commercial geospa‑ tial data resources for calculating patient travel times were more equitably distributed relative to health need than resources for characterising neighbourhoods or geocoding patient addresses. -
Geocoding Guide for Slovakia Table of Contents
Spectrum Technology Platform Version 12.0 SP1 Geocoding Guide for Slovakia Table of Contents 1 - Geocode Address Global Adding an Enterprise Geocoding Module Global Database Resource 4 2 - Input Input Fields 7 Address Input Guidelines 7 Single Line Input 7 Street Intersection Input 9 3 - Options Geocoding Options 11 Matching Options 14 Data Options 18 4 - Output Address Output 22 Geocode Output 29 Result Codes 29 Result Codes for International Geocoding 33 5 - Reverse Geocode Address Global Input 39 Options 40 Output 44 1 - Geocode Address Global Geocode Address Global provides street-level geocoding for many countries. It can also determine city or locality centroids, as well as postal code centroids. Geocode Address Global handles street addresses in the native language and format. For example, a typical French formatted address might have a street name of Rue des Remparts. A typical German formatted address could have a street name Bahnhofstrasse. Note: Geocode Address Global does not support U.S. addresses. To geocode U.S. addresses, use Geocode US Address. The countries available to you depends on which country databases you have installed. For example, if you have databases for Canada, Italy, and Australia installed, Geocode Address Global would be able to geocode addresses in these countries in a single stage. Before you can work with Geocode Address Global, you must define a global database resource containing a database for one or more countries. Once you create the database resource, Geocode Address Global will become available. Geocode Address Global is an optional component of the Enterprise Geocoding Module. In this section Adding an Enterprise Geocoding Module Global Database Resource 4 Geocode Address Global Adding an Enterprise Geocoding Module Global Database Resource Unlike other stages, the Geocode Address Global and Reverse Geocode Global stages are not visible in Management Console or Enterprise Designer until you define a database resource. -
Census Bureau Public Geocoder
1. What is Geocoding? Geocoding is an attempt to provide the geographic location (latitude, longitude) of an address by matching the address to an address range. The address ranges used in the geocoder are the same address ranges that can be found in the TIGER/Line Shapefiles which are derived from the Master Address File (MAF). The address ranges are potential address ranges, not actual address ranges. Potential ranges include the full range of possible structure numbers even though the actual structures might not exist. The majority of the address ranges we have are for residential areas. There are limited address ranges available in commercial areas. Our address ranges are regularly updated with the most current information we have available to us. The hypothetical graphic below may help customers understand the concept of geocoding and Census Geography (addresses displayed in this document are factitious and shown for example only.) If we look at Block 1001 in the example below the address range in red 101-199 is the range of numbers that overlap the actual individual house numbers associated with the blue circles (e.g. 103, 117, 135 and 151 Main St) on that side of the street (i.e. the Left side, note the arrow is pointing to the right on Main Street.) Based on this logic, the from address would be 101 and the to address would be 199 for this address range. Besides providing a user with the geographic location of an address the Census Geocoder can also provide all of the additional Census geographic information associated with a location, for example a Census Block, Tract, County, and State. -
Automatic Reconstruction of Itineraries from Descriptive Texts
Ecole´ doctorale des sciences exactes et leurs applications Escuela de Doctorado de la Universidad de Zaragoza Automatic reconstruction of itineraries from descriptive texts THESE` pour l’obtention du Doctorat de l’Universit´ede Pau de des Pays de l’Adour (France) (mention Informatique) et Doctor por la Universidad de Zaragoza (Espa˜na) (Programa de Doctorado de Ingenier´ıade Sistemas e Inform´atica) par Ludovic Moncla Composition du jury Rapporteurs : Christophe Claramunt Institut de Recherche de l’Ecole Navale (IRENav) Denis Maurel LI, Universit´eFran¸cois Rabelais, Tours Ross Purves University of Zurich Examinateurs : Philippe Muller IRIT, Universit´ePaul Sabatier, Toulouse Adeline Nazarenko LIPN, Universit´eParis 13 Invit´e: David Buscaldi LIPN, Universit´eParis 13 Directeurs : Mauro Gaio LIUPPA, Universit´ede Pau et des Pays de l’Adour Javier Nogueras Iso DIIS, Universidad de Zaragoza Co-Encadrant : S´ebastien Musti`ere COGIT IGN, Universit´eParis-Est Laboratoire d’Informatique de l’Universit´ede Pau et des Pays de l’Adour - EA 3000 Departamento de Inform´atica e Ingenier´ıa de Sistemas, Universidad de Zaragoza Laboratoire COGIT, IGN, Universit´eParis-Est Acknowledgments First of all, I wish to express my greatest thanks to my two supervisors Mauro Gaio and Javier Nogueras- Iso. Mauro Gaio for giving me the opportunity to do this PhD. His unconditional availability, encourage- ment and trust helped me a lot to accomplish this work. I thank him for all the interesting discussions we had, sharing ideas and talking about everything. Then, I thank Javier Nogueras-Iso for his availability, his patience, his hospitality and his precious advices. I also thank them for their great support during all stages of this work and for their help with administrative issues. -
PROC GEOCODE: Creating Map Locations from Your Data Darrell Massengill and Ed Odom, SAS Institute Inc., Cary, NC
SAS Global Forum 2009 Coders' Corner Paper 087-2009 PROC GEOCODE: Creating Map Locations from Your Data Darrell Massengill and Ed Odom, SAS Institute Inc., Cary, NC ABSTRACT How do you convert your address data into map locations? This is done through the process of geocoding. SAS/GRAPH® 9.2 now includes PROC GEOCODE to simplify this process for you. This presentation will briefly discuss the current capability of this procedure and show examples of both address geocoding and Web address (IP address) geolocating. A brief discussion of future directions will also be included. INTRODUCTION Every business or organization has a lot of data that includes an address. The address data is useful only if it is transformed into location information that can be viewed on a map, used in distance calculations, or processed in other similar ways. To make this data useful, you must convert the address to a location having a latitude and longitude. This conversion process is called geocoding. If the address is an IP address, the process is usually called geolocating. This paper will discuss both geocoding and geolocating using PROC GEOCODE. First, we will introduce the concepts needed to understand geocoding, and then we will discuss PROC GEOCODE’s current and planned functionality. Finally, examples will show how to use PROC GEOCODE. GEOCODING BASICS The geocoding process depends on having lookup data with the necessary information to make the conversion. This data is the key to geocoding. Factors such as age and granularity of the lookup data determine the geocoding results. Addresses routinely change with new construction, new roads being added, and postal codes being split and changed. -
Addressing for Emergencies
Foreword By Nancy von Meyer This book is a compendium of the best papers presented during 4 years of URISA Street Smart and Address Savvy Conferences. The book also contains additional papers that are being published here for the first time. The need for this publication has come from several fronts. URISA’s membership has had a keen interest in the use of address information and its application for data integration and decision support for many years. Nearly every URISA Annual Conference has had sessions and tracks related to addressing, there have been several addressing standards task forces, and in the past few years the Street Smart and Address Savvy Conference has been a highly successful stand-alone specialty event on the topic. The importance of emergency response has been highlighted in the year since September 11, 2001. Address is a critical component of emergency response and hence a critical part of homeland security. The time had come to pull together a summary of some of the recent thinking on address standards, address design and address applications. This compendium begins with five papers related to address design and the use of addresses in databases and geographic information systems (GIS). Mike Walls describes how to begin an address design project and focuses on the work of a data modeler confronted with designing an address database. Morten Lind provides an international taste of address formulation. The potential of a simple data element that can release "spatial power" is enormous because thousands of private and public databases reference address information. Morten’s paper is based on experiences with standardization, data modeling, legisla- tion and geo-coding of address data in Denmark and in other Scandinavian countries. -
Product Data Sheet
PRODUCT DATA SHEET Pitney Bowes Spectrum™ Enterprise Location Intelligence Solution ENTERPRISE GEOCODING MODULE WITH INTERNATIONAL COVERAGE THE EXACT INFORMATION YOU NEED WHEN LOCATION REALLY COUNTS Product overview EXPECTED ROI More Precise and More Consistent Data and Analysis More exact geocodes. More No matter where your customers, prospects or company assets are located, domain- precise calculations. Better specific data drives decisions. These decisions can impact virtually every aspect of your decisions. Reduced business risk. business – from market analysis and risk assessment to targeting, portfolio management and network investments. The Enterprise Geocoding Module The Pitney Bowes Spectrum Enterprise Location Intelligence Solution, Enterprise helps you determine the exact Geocoding Module performs address or street, postal code, and city geocoding as well as geographical coordinates for any reverse geocoding for locations in the U.S., Canada, Australia and many other countries. address – even, in some places, This module provides you with actual location coordinates, including latitude and longitude, building entries. You’ll get and, for the U.S., altitude and Accessor’s Parcel Number (APN), which makes it easier for you to analyze data geographically – and make better business decisions. outstanding accuracy, coverage, and depth of insight that can accelerate your success across a Benefit broad range of business initiatives that depend on location data, With Pinpoint Precision, You’ll Know Your Customers Better including: While an address is important for postal delivery, it does not, by itself, give you the answers • Risk Assessment you need to run your business effectively. Especially if your business processes depend on • Market Analysis precise location. • Network Optimization The Enterprise Geocoding Module returns specific geographical coordinates so you can • Effective Targeting assess risk, determine eligibility for service, calculate distance between two points, locate • Portfolio Management prospects, and more. -
Mapmarker USA V31.0.0 Developer Guide
Location Intelligence Geographic Information Systems MapMarker Plus Version 31 Developer Guide Information in this document is subject to change without notice and does not represent a commitment on the part of the vendor or its representatives. No part of this document may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, without the written permission of Pitney Bowes, 350 Jordan Road, Troy, New York 12180-8399. ©1994-2019 Pitney Bowes All rights reserved. MapInfo, Group 1 Software, Centrus, and MapMarker are trademarks of Pitney Bowes All other marks and trademarks are property of their respective holders. Contact information for all Pitney Bowes Inc. offices is located at:: pitneybowes.com Java and all Java-based trademarks and logos are trademarks or registered trademarks of Sun Microsystems, Inc. in the United States and other countries. The following trademarks are owned by the United States Postal Service: LACSLink, SuiteLink, DPV, ZIP + 4, ZIP Code, ZIP, CASS, CASS Certified, Post Office, P.O. Box USPS, U.S. Postal Service and United States Postal Service. Pitney Bowes is a non-exclusive DPV and LACSLink Licensee of the United States Postal Service® AD#1.08 Portions © January 2019 TomTom Inc. © 1987 - 2019 HERE. All rights reserved Shapefile C Library v. 1.2.10 is licensed under the MIT Style License. The license can be downloaded from: . © 1998 Frank Warmerdam. The source code for this library is available from . January 2019 Table of Contents 1 - Introduction 4 5 - Using -
Geocoding Best Practices: Review of Eight Commonly Used Geocoding Systems
Geocoding Best Practices: Review of Eight Commonly Used Geocoding Systems Jennifer N. Swift Daniel W. Goldberg John P. Wilson Prepared for: Division of Cancer Prevention and Control National Center For Chronic Disease Prevention and Health Promotion Center for Disease Control and Prevention Swift, Goldberg and Wilson Cover Photos: Google Maps Street View, geocoded data in ArcGIS and USC Geocode Correction Service examples, by D. Goldberg and J. Swift (2008). Preferred Citation: Swift JN, Goldberg DW, and Wilson JP 2008 Geocoding Best Practices: Review of Eight Commonly Used Geocoding Systems. Los Angeles, CA, University of Southern California GIS Research Laboratory Technical Report No 10. All material in this report is in the public domain and may be reproduced or copied without permission. However, citation as to source is requested. ii Geocoding Best Practices: Review of Eight Commonly Used Geocoding Systems Table of Contents List of Figures.................................................................................................................................................... iv List of Tables ...................................................................................................................................................... v Executive Summary .......................................................................................................................................... vi 1 Introduction.................................................................................................................................................. -
Informatica Address Verification
Informatica® Address Verification 5.14.0 Release Guide (On-Premises) Informatica Address Verification Release Guide (On-Premises) 5.14.0 November 2018 © Copyright Informatica LLC 2013, 2020 This software and documentation are provided only under a separate license agreement containing restrictions on use and disclosure. No part of this document may be reproduced or transmitted in any form, by any means (electronic, photocopying, recording or otherwise) without prior consent of Informatica LLC. U.S. GOVERNMENT RIGHTS Programs, software, databases, and related documentation and technical data delivered to U.S. Government customers are "commercial computer software" or "commercial technical data" pursuant to the applicable Federal Acquisition Regulation and agency-specific supplemental regulations. As such, the use, duplication, disclosure, modification, and adaptation is subject to the restrictions and license terms set forth in the applicable Government contract, and, to the extent applicable by the terms of the Government contract, the additional rights set forth in FAR 52.227-19, Commercial Computer Software License. Informatica, AddressDoctor, the Informatica logo, and any other Informatica-owned trademarks that appear in the document are trademarks or registered trademarks of Informatica LLC in the United States and many jurisdictions throughout the world. A current list of Informatica trademarks is available on the web at https:// www.informatica.com/trademarks.html. Other company and product names may be trade names or trademarks of their respective owners. Portions of this software and/or documentation are subject to copyright held by third parties, including without limitation: Copyright DataDirect Technologies. All rights reserved. Copyright © Sun Microsystems. All rights reserved. Copyright © RSA Security Inc.