Census Bureau Public Geocoder
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2019 TIGER/Line Shapefiles Technical Documentation
TIGER/Line® Shapefiles 2019 Technical Documentation ™ Issued September 2019220192018 SUGGESTED CITATION FILES: 2019 TIGER/Line Shapefiles (machine- readable data files) / prepared by the U.S. Census Bureau, 2019 U.S. Department of Commerce Economic and Statistics Administration Wilbur Ross, Secretary TECHNICAL DOCUMENTATION: Karen Dunn Kelley, 2019 TIGER/Line Shapefiles Technical Under Secretary for Economic Affairs Documentation / prepared by the U.S. Census Bureau, 2019 U.S. Census Bureau Dr. Steven Dillingham, Albert Fontenot, Director Associate Director for Decennial Census Programs Dr. Ron Jarmin, Deputy Director and Chief Operating Officer GEOGRAPHY DIVISION Deirdre Dalpiaz Bishop, Chief Andrea G. Johnson, Michael R. Ratcliffe, Assistant Division Chief for Assistant Division Chief for Address and Spatial Data Updates Geographic Standards, Criteria, Research, and Quality Monique Eleby, Assistant Division Chief for Gregory F. Hanks, Jr., Geographic Program Management Deputy Division Chief and External Engagement Laura Waggoner, Assistant Division Chief for Geographic Data Collection and Products 1-0 Table of Contents 1. Introduction ...................................................................................................................... 1-1 1. Introduction 1.1 What is a Shapefile? A shapefile is a geospatial data format for use in geographic information system (GIS) software. Shapefiles spatially describe vector data such as points, lines, and polygons, representing, for instance, landmarks, roads, and lakes. The Environmental Systems Research Institute (Esri) created the format for use in their software, but the shapefile format works in additional Geographic Information System (GIS) software as well. 1.2 What are TIGER/Line Shapefiles? The TIGER/Line Shapefiles are the fully supported, core geographic product from the U.S. Census Bureau. They are extracts of selected geographic and cartographic information from the U.S. -
The Global Positioning System the Global Positioning System
The Global Positioning System The Global Positioning System 1. System Overview 2. Biases and Errors 3. Signal Structure and Observables 4. Absolute v. Relative Positioning 5. GPS Field Procedures 6. Ellipsoids, Datums and Coordinate Systems 7. Mission Planning I. System Overview ! GPS is a passive navigation and positioning system available worldwide 24 hours a day in all weather conditions developed and maintained by the Department of Defense ! The Global Positioning System consists of three segments: ! Space Segment ! Control Segment ! User Segment Space Segment Space Segment ! The current GPS constellation consists of 29 Block II/IIA/IIR/IIR-M satellites. The first Block II satellite was launched in February 1989. Control Segment User Segment How it Works II. Biases and Errors Biases GPS Error Sources • Satellite Dependent ? – Orbit representation ? Satellite Orbit Error Satellite Clock Error including 12 biases ? 9 3 Selective Availability 6 – Satellite clock model biases Ionospheric refraction • Station Dependent L2 L1 – Receiver clock biases – Station Coordinates Tropospheric Delay • Observation Multi- pathing Dependent – Ionospheric delay 12 9 3 – Tropospheric delay Receiver Clock Error 6 1000 – Carrier phase ambiguity Satellite Biases ! The satellite is not where the GPS broadcast message says it is. ! The satellite clocks are not perfectly synchronized with GPS time. Station Biases ! Receiver clock time differs from satellite clock time. ! Uncertainties in the coordinates of the station. ! Time transfer and orbital tracking. Observation Dependent Biases ! Those associated with signal propagation Errors ! Residual Biases ! Cycle Slips ! Multipath ! Antenna Phase Center Movement ! Random Observation Error Errors ! In addition to biases factors effecting position and/or time determined by GPS is dependant upon: ! The geometric strength of the satellite configuration being observed (DOP). -
Identifying Locations of Social Significance: Aggregating Social Media Content to Create a New Trust Model for Exploring Crowd Sourced Data and Information
Identifying Locations of Social Significance: Aggregating Social Media Content to Create a New Trust Model for Exploring Crowd Sourced Data and Information Al Di Leonardo, Scott Fairgrieve Adam Gribble, Frank Prats, Wyatt Smith, Tracy Sweat, Abe Usher, Derek Woodley, and Jeffrey B. Cozzens The HumanGeo Group, LLC Arlington, Virginia, United States {al,scott,adam,frank,wyatt,tracy,abe,derek}@thehumangeo.com Abstract. Most Internet content is no longer produced directly by corporate organizations or governments. Instead, individuals produce voluminous amounts of informal content in the form of social media updates (micro blogs, Facebook, Twitter, etc.) and other artifacts of community communication on the Web. This grassroots production of information has led to an environment where the quantity of low-quality, non-vetted information dwarfs the amount of professionally produced content. This is especially true in the geospatial domain, where this information onslaught challenges Local and National Governments and Non- Governmental Organizations seeking to make sense of what is happening on the ground. This paper proposes a new model of trust for interpreting locational data without a clear pedigree or lineage. By applying principles of aggregation and inference, it is possible to identify locations of social significance and discover “facts” that are being asserted by crowd sourced information. Keywords: geospatial, social media, aggregation, trust, location. 1 Introduction Gathering geographical data on populations has always constituted an essential element of census taking, political campaigning, assisting in humanitarian disasters/relief, law enforcement, and even in post-conflict areas where grand strategy looks beyond the combat to managing future peace. Warrior philosophers have over the millennia praised indirect approaches to warfare as the most effective means of combat—where influence and information about enemies and their supporters trumps reliance on kinetic operations to achieve military objectives. -
Glossary of Redistricting Terms
Glossary of Redistricting Terms Apportionment or Reapportionment Following each decennial census, seats in the United States House of Representatives are apportioned to each state based on population figures derived from the census. Apportionment is the process of determining how many Congressional Districts to allocate to each state, and is different from ‘redistricting,’ which involves redrawing district lines within a state. At-large An election in which candidates run in all parts of a jurisdiction rather than from districts or wards within the jurisdiction. All members of EVIT’s Board of Governors are elected from specific districts within EVIT’s boundary. There are no at-large election contests. Census Block The smallest level of census geography used by the Census Bureau to collect and report census data. Census Blocks are labeled with a four digit number such as 2025 or 1006A. Census Block Group A group of Census Blocks all having the same first block digit. Block 2025 is in Block Group 2. There are 1,023 whole or partial Block Groups within EVIT’s jurisdiction. The latest available population data for this redistricting process is at the Block Group level. Census data Information and statistics on the population of the United States gathered by the Census Bureau and released to the public. Census Tract A level of census geography larger than a census block or census block group that often corresponds to neighborhood boundaries. There are 385 whole or partial Census Tracts within EVIT’s boundary – too few for our purpose in redistricting. Community of interest An area that is defined by residents’ shared demographics or by common threads of social, economic, or political interests such that the area may benefit from common representation. -
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 -
The Global Positioning System II Field Experiments
The Global Positioning System II Field Experiments Geo327G/386G: GIS & GPS Applications in Earth Sciences Jackson School of Geosciences, University of Texas at Austin 10/8/2020 5-1 Mexico DGPS Field Campaign Cenotes in Tamaulipas, MX, near Aldama Geo327G/386G: GIS & GPS Applications in Earth Sciences 10/8/2020 Jackson School of Geosciences, University of Texas at Austin 5-2 Are Cenote Water Levels Related? Geo327G/386G: GIS & GPS Applications in Earth Sciences 10/8/2020 Jackson School of Geosciences, University of Texas at Austin 5-3 DGPS Static Survey of Cenote Water Levels Geo327G/386G: GIS & GPS Applications in Earth Sciences 10/8/2020 Jackson School of Geosciences, University of Texas at Austin 5-4 Determining Orthometric Heights ❑Ortho. Height = H.A.E. – Geoid Height Height above MSL (Orthometric height) H.A.E. Geoid height Earth Surface = H.A.E. Geoid Ellipsoid Geoid Height Geo327G/386G: GIS & GPS Applications in Earth Sciences 10/8/2020 Jackson School of Geosciences, University of Texas at Austin 5-5 Determining Orthometric Heights ❑Ortho. Height = (H.A.E. – Geoid Height) Need: 1) Ellipsoid model – GRS80 – NAVD88 ❑reference stations: HARN (+ 2 cm), CORS (+ ~2 cm) 2) Geoid model – GEOID99 ( + 5 cm for US) Procedure: Base receiver at reference station, rover at point of interest a) measure HAE, apply DGS corrections b) subtract local Geoid Height Geo327G/386G: GIS & GPS Applications in Earth Sciences 10/8/2020 Jackson School of Geosciences, University of Texas at Austin 5-6 Sources of Error ❑Geoid error – model less well constrained in areas of few gravity measurement ❑NAVD88 error – benchmark stability, measurement errors ❑GPS errors – need precise ephemeri, tropospheric delay model, equipment (antennae should be same for base and rover) Geo327G/386G: GIS & GPS Applications in Earth Sciences 10/8/2020 Jackson School of Geosciences, University of Texas at Austin 5-7 Static Carrier-phase solutions obtained by: ❑Commercial post-processing software ❑e.g. -
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. -
Gravity, Geoid and Earth Observation IAG Commission 2: Gravity Field, Chania, Crete, Greece, 23-27 June 2008
S.P. Mertikas (Ed.) Gravity, Geoid and Earth Observation IAG Commission 2: Gravity Field, Chania, Crete, Greece, 23-27 June 2008 Series: International Association of Geodesy Symposia, Vol. 135 ▶ State of the art scientific achievements of gravity field research prospects These Proceedings include the written version of papers presented at the IAG International Symposium on "Gravity, Geoid and Earth Observation 2008". The Symposium was held in Chania, Crete, Greece, 23-27 June 2008 and organized by the Laboratory of Geodesy and Geomatics Engineering, Technical University of Crete, Greece. The meeting was arranged by the International Association of Geodesy and in particular by the IAG Commission 2: Gravity Field. The symposium aimed at bringing together geodesists and geophysicists working in the 2010, XXXIV, 702 p. 340 illus. general areas of gravity, geoid, geodynamics and Earth observation. Besides covering the traditional research areas, special attention was paid to the use of geodetic methods for: Earth observation, environmental monitoring, Global Geodetic Observing System (GGOS), Printed book Earth Gravity Models (e.g., EGM08), geodynamics studies, dedicated gravity satellite Hardcover missions (i.e., GOCE), airborne gravity surveys, Geodesy and geodynamics in polar regions, and the integration of geodetic and geophysical information. ▶ 299,99 € | £249.99 | $379.99 ▶ *320,99 € (D) | 329,99 € (A) | CHF 354.00 eBook Available from your bookstore or ▶ springer.com/shop MyCopy Printed eBook for just ▶ € | $ 24.99 ▶ springer.com/mycopy Order online at springer.com ▶ or for the Americas call (toll free) 1-800-SPRINGER ▶ or email us at: [email protected]. ▶ For outside the Americas call +49 (0) 6221-345-4301 ▶ or email us at: [email protected]. -
What3words Geocoding Extensions and Applications for a University Campus
WHAT3WORDS GEOCODING EXTENSIONS AND APPLICATIONS FOR A UNIVERSITY CAMPUS WEN JIANG August 2018 TECHNICAL REPORT NO. 315 WHAT3WORDS GEOCODING EXTENSIONS AND APPLICATIONS FOR A UNIVERSITY CAMPUS Wen Jiang Department of Geodesy and Geomatics Engineering University of New Brunswick P.O. Box 4400 Fredericton, N.B. Canada E3B 5A3 August 2018 © Wen Jiang, 2018 PREFACE This technical report is a reproduction of a thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Engineering in the Department of Geodesy and Geomatics Engineering, August 2018. The research was supervised by Dr. Emmanuel Stefanakis, and support was provided by the Natural Sciences and Engineering Research Council of Canada. As with any copyrighted material, permission to reprint or quote extensively from this report must be received from the author. The citation to this work should appear as follows: Jiang, Wen (2018). What3Words Geocoding Extensions and Applications for a University Campus. M.Sc.E. thesis, Department of Geodesy and Geomatics Engineering Technical Report No. 315, University of New Brunswick, Fredericton, New Brunswick, Canada, 116 pp. ABSTRACT Geocoded locations have become necessary in many GIS analysis, cartography and decision-making workflows. A reliable geocoding system that can effectively return any location on earth with sufficient accuracy is desired. This study is motivated by a need for a geocoding system to support university campus applications. To this end, the existing geocoding systems were examined. Address-based geocoding systems use address-matching method to retrieve geographic locations from postal addresses. They present limitations in locality coverage, input address standardization, and address database maintenance. -
PROBLEMATIC TAXIWAY GEOMETRY STUDY OVERVIEW January 2018 6
DOT/FAA/TC-18/2 Problematic Taxiway Geometry Federal Aviation Administration William J. Hughes Technical Center Study Overview Aviation Research Division Atlantic City International Airport New Jersey 08405 January 2018 Final Report This document is available to the U.S. public through the National Technical Information Services (NTIS), Springfield, Virginia 22161. U.S. Department of Transportation Federal Aviation Administration NOTICE This document is disseminated under the sponsorship of the U.S. Department of Transportation in the interest of information exchange. The United States Government assumes no liability for the contents or use thereof. The United States Government does not endorse products or manufacturers. Trade or manufacturer's names appear herein solely because they are considered essential to the objective of this report. The findings and conclusions in this report are those of the author(s) and do not necessarily represent the views of the funding agency. This document does not constitute FAA policy. Consult the FAA sponsoring organization listed on the Technical Documentation page as to its use. This report is available at the Federal Aviation Administration William J. Hughes Technical Center’s Full-Text Technical Reports page: actlibrary.act.faa.gov in Adobe Acrobat portable document format (PDF). Technical Report Documentation Page 1. Report No. 2. Government Accession No. 3. Recipient's Catalog No. DOT/FAA/TC-18/2 4. Title and Subtitle 5. Report Date PROBLEMATIC TAXIWAY GEOMETRY STUDY OVERVIEW January 2018 6. Performing Organization Code ANG-E261 7. Author(s) 8. Performing Organization Report No. 1 2 3 Lauren Vitagliano , Garrison Canter , and Rachel Aland 9. Performing Organization Name and Address 10. -
Geocoding and Buffering Addresses in Arcgis
Spatial Structures in the Social Sciences Geocoding Geocoding and Buffering Addresses in ArcGIS INTRODUCTION Geocoding is the process of assigning location coordinates in a continuous, globlal reference system (Latitude and Longitude, for instance) to street addresses. While street addresses are an easy to understand way for us to make sense of locations in a local area there are many problems will using them for distinguishing locations in the world. Street addresses are generally considered location identifiers within a local reference system; furthermore, a street address system is often discrete, meaning it is only effective for positions that fall on the street network. For this reason the US street network has been digitized and coordinates (lat/long for instance) have been determined for the two points that specify individual line segments (smallest line segments possible). In addition to the global coordinates the street address range for each side of the street is also specified for that segment of the street network. Therefore, based on the known range of street addresses and lat/long coordinates a reasonable approximation can be made of the location of an address on a street in global coordinates. DATA and SHAPEFILES Geocodebuffer.zip can be downloaded from the S4 tutorials section of the training page (http://www.s4.brown.edu/S4/about.htm) It contains: 1) NOSchoolsaddrs.xls: Excel file of addresses of currently open schools in New Orleans 2) NOstreets.shp: a street file for all of Louisiana, the state in which you will be geocoding addresses. 3) Katrina_damage_all2.shp: a file displaying damage sustained across New Orleans from Katrina.