TIGER/SDTS: Standardizing an Innovation

The explosion of computer processing capabilities for manipulating geographic data has produced a concomitant increase in the number of geographic data file formats available. The many formats make it difficult to exchange and manipulate geographic data from several sources, and sometimes even from the same source. The U.S. Bureau of the Census has been a contributor to the “Yet Another Geographic File Format” movement over the past two decades with its Address Coding Guides (following the 1970 decennial census), the GBF/DIME-Files (following the 1980 decennial census), and four different versions of its TIGER/Line files at various times during the 1990 decennial census cycle. The TIGER data base is a massive computer file that provides geographic information about the entire United States and its territories in great detail, down to the individual city block and its component boundary features. Its value to more than Census Bureau activities is enormous. To enhance the value of the TIGER data base, and to make it easier to use, the Census Bureau is releasing the file in the new Spatial Data Transfer Standard (SDTS) format. The benefits of a standard transfer format are manifold. This paper discusses some of the intergovernmental activities that were required before the exchange standard was adopted and some of the problems of implementing the standard within the Census Bureau. The Census Bureau is not alone in its decision to release geographic data files in the SDTS format, and some of the benefits of using the standard for exchanging data among agencies also are described.     

TIGER/SDTS Topology

The Census Bureau is committed to using the Spatial Data Transfer Standard (SDTS) and is developing an extract from the Census TIGER? called the TIGER/SDTS?. A single file of the prototype TIGER/SDTS is now available with which interested data users may experiment. This paper will graphically describe some of the SDTS concepts and census geographic concepts used in the TIGER/SDTS. The Census TIGER? and the TIGER/SDTS? are trademarks of the Bureau of the Census.     

The TIGER System: Yesterday,Today, and Tomorrow

The TIGER System is many things to many people. At this juncture, the TIGER System has fulfilled the precensus geographic support functions for which the Geography Division designed it. During the next 18 months, the TIGER System will support a number of functions needed to complete the tabulation of the collected data and make those data useful to the numerous constituencies that carry out the myriad tasks that define our lives. Simultaneously with the use of the TIGER System to support the data tabulation and dissemination missions of the Census Bureau, work will be under way to define a framework for the future of this bold new product – and this future looks bright. If the TIGER System is to be judged truly useful outside the Census Bureau, similar planning will need to be going on in offices and institutions across America. This is true especially in the context of geographic information system (GIS) applications involving the digital products of the TIGER System and the demographic data products of the 1990 census.     

Cartographic Support for the 2010 Decennial Census of the United States

As this article is published, the U.S. Census Bureau is completing work for the twenty third decennial census of the United States. Once again, the MAF/TIGER system served as the geospatial infrastructure supporting numerous census operations and data collection, tabulation, and dissemination activities. From data collection to data dissemination we trace the recent activities of the 2010 Decennial Census of the United States to illustrate the role maps and geospatial data play in an increasing variety of public and private sector activities across the nation. To ensure a successful 2010 Census, millions of maps had to be created. This article will give an overview of the automated mapping system designed to create these maps. This includes a discussion about associated software needed and the variety of map types that were developed. Finally, future map production and geospatial activities at the Census Bureau will be discussed.     

A Snake-based Approach for TIGER Road Data Conflation

The TIGER (Topologically Integrated Geographic Encoding and Referencing) system has served the U.S. Census Bureau and other agencies' geographic needs successfully for two decades. Poor positional accuracy has however made it extremely difficult to integrate TIGER with advanced technologies and data sources such as GPS, high resolution imagery, and state/local GIS data. In this paper, a potential solution for conflation of TIGER road centerline data with other geospatial data is presented. The first two steps of the approach (feature matching and map alignment) remain the same as in traditional conflation. Following these steps, a third is added in which active contour models (snakes) are used to automatically move the vertices of TIGER roads to high-accuracy roads, rather than transferring attributes between the two datasets. This approach has benefits over traditional conflation methodology. It overcomes the problem of splitting vector road line segments, and it can be extended for vector imagery conflation as well. Thus, a variety of data sources (GIS, GPS, and Remote Sensing) could be used to improve TIGER data. Preliminary test results indicate that the three-step approach proposed in this paper performs very well. The positional accuracy of TIGER road centerline can be improved from an original 100 plus meters' RMS error to only 3 meters. Such an improvement can make TIGER data more useful for much broader application.     

Positional Accuracy of TIGER 2000 and 2009 Road Networks

The Topologically Integrated Geographic Encoding and Referencing (TIGER) data are an essential part of the US Census and represent a critical element in the nation's spatial data infrastructure. TIGER data for the year 2000, however, are of limited positional accuracy and were deemed of insufficient quality to support the 2010 Census. In response the US Census Bureau embarked on the MAF/TIGER Accuracy Improvement Project (MTAIP) in an effort to improve the positional accuracy of the database, modernize the data processing environment and improve cooperation with partner agencies. Improved TIGER data were released for the entire US just before the 2010 Census. The current study characterizes the positional accuracy of the TIGER 2009 data compared with the TIGER 2000 data based on selected road intersections. Three US counties were identified as study areas and in each county 100 urban and 100 rural sample locations were selected. Features in the TIGER 2000 and 2009 data were compared with reference locations derived from high resolution natural color orthoimagery. Results indicate that TIGER 2009 data are much improved in terms of positional accuracy compared with the TIGER 2000 data, by at least one order of magnitude across urban and rural areas in all three counties for most accuracy metrics. TIGER 2009 is consistently more accurate in urban areas compared with rural areas, by a factor of at least two for most accuracy metrics. Despite the substantial improvement in positional accuracy, large positional errors of greater than 10 m are relatively common in the TIGER 2009 data, in most cases representing remnant segments of minor roads from older versions of the TIGER data. As a result, based on the US Census Bureau's suggested accuracy metric, the TIGER 2009 data meet the accuracy expectation of 7.6 m for two of the three urban areas but for none of the three rural areas. The suggested metric is based on the National Standard for Spatial Data Accuracy (NSSDA) protocol and was found to be very sensitive to the presence of a small number of very large errors. This presents challenges during attempts to characterize the accuracy of TIGER data or other spatial data using this protocol.     

A digital map of Public-Use Microdata Areas in the 1990 U.S. census

"Public-Use Microdata Areas (PUMAs) are the smallest geographic units for which many U.S. Census variables are reported. In particular, 1990 microdata records for households and individuals can be aggregated only by PUMA, metropolitan area, state, and region. The Census Bureau distributes maps of these PUMAs only on paper, however, and only for individual states. This note describes the construction of a national, digital base map of the PUMAs used in the 1990 U.S. Census microdata files (5% sample)."     

Reflections on Mapping Census 2000

Mapping Census 2000: The Geography of U.S. Diversity is an atlas containing 75 maps and presenting county- and state-level data for Census 2000. Cynthia Brewer and Trudy Suchan rapidly produced the atlas in the Population Division of the U.S. Census Bureau using ArcInfo 8.1 prerelease software. Redistricting data, on which the atlas was based, were released in March 2001 and the full-color atlas went to press in July 2001. It is the first decennial atlas produced by the Census Bureau in 80 years. Race maps in the atlas are designed to present the new Census 2000 data that include counts of people who indicated more than one race. Choropleth classifications are constructed to facilitate comparison among maps in series for all race/ethnicity groups, both large and small. Map series share breaks that are adjusted to include meaningful breaks based on overall U.S. percentages for individual groups. Additional shared meaningful breaks, such as "no change" and "50 percent of the population" also anchor classifications. Maps of prevalent groups and diversity provide syntheses of race/ethnicity data. Maps were evaluated at numerous levels in the Census Bureau, with issues from topic selection to page layout to title wording debated by many people. The essay describes the production processes, agency standards, and cartographic principles that come together to present these new data in an atlas that is a colorful showpiece.     

Assessing the Effect of Data Imports on the Completeness of OpenStreetMap – A United States Case Study

The assessment of OpenStreetMap (OSM) data quality has become an interdisciplinary research area over the recent years. The question of whether the OSM road network should be updated through periodic data imports from public domain data, or whether the currency of OSM data should rather rely on more traditional data collection efforts by active contributors, has led to perpetual debates within the OSM community. A US Census TIGER/Line 2005 import into OSM was accomplished in early 2008, which generated a road network foundation for the active community members in the US. In this study we perform a longitudinal analysis of road data for the US by comparing the development of OSM and TIGER/Line data since the initial TIGER/Line import. The analysis is performed for the 50 US states and the District of Columbia, and 70 Urbanized Areas. In almost all tested states and Urbanized Areas, OSM misses roads for motorized traffic when compared with TIGER/Line street data, while significant contributions could be observed in pedestrian related network data in OSM compared with corresponding TIGER/Line data. We conclude that the quality of OSM road data could be improved through new OSM editor tools allowing contributors to trace current TIGER/Line data.     

城市人口地理信息系统建设模式探讨

分析了国内外人口地理信息系统的发展概况，简述了目前我国建立城市人口地理信息系统的技术、数据基础和社会背景，初步提出一种建设城市人口地理信息系统的三层结构模式，以广州市的具体情况为例，探讨了人口地理信息系统建设过程中数据，数据库设计、人口数据仓库的建立、城市综合数据分析方法等关键问题。     

Data visualization at the US census bureau – an American tradition

Recent developments in data visualization, developer Application Program Interfaces (APIs), and web services reinforce a long American tradition of statistical mapping and innovation at the US Census Bureau. Consistent with other international statistical agencies, the Census Bureau has used contemporary innovations in statistical mapping and data visualization to disseminate national census results for over 14 decades. The US Census Bureau’s data products and analyses have enabled decision makers and the public to access census results quickly and easily. The new information technology environment requires the Census Bureau to more rapidly expedite these results and deliver mapping products to new customers as well as to its traditional data consumers. The Census API has empowered developers and commercial companies to test the limits of a new emerging world of big data solutions. This article presents some of the most recent data visualization products from the Census Bureau, including an expanding Data Visualization Gallery to merge geospatial information and statistics on the map.     

The U.S. Geological Survey Land Remote Sensing Program

The U.S. Geological Survey has been a provider of remotely sensed information for decades. As the availability and use of satellite data has grown, USGS has placed increasing emphasis on expanding the knowledge about the science of remote sensing and on making remotely sensed data more accessible. USGS encourages widespread availability and distribution of these data and through its programs, encourages and enables a variety of research activities and the development of useful applications of the data. The science of remote sensing has great potential for assisting in the monitoring and assessment of the impacts of natural disasters, management and analysis of environmental, biological, energy, and mineral investigations, and supporting informed public policy decisions. By establishing the Land Remote Sensing Program (LRS) as a major unit of the USGS Geography Program, USGS has taken the next step to further increase support for the accessibility, understanding, and use of remotely sensed data. This article describes the LRS Program, its mission and objectives, and how the program has been structured to accomplish its goals.     

Estimating Small-Area Populations by Age and Sex Using Spatial Interpolation and Statistical Inference Methods

The objective of this research is to compute population estimates by age and sex for small areas whose boundaries are different from those for which the population counts were made. In our approach, population surfaces and age‐sex proportion surfaces are separately estimated. Age‐sex population estimates for small areas and their confidence intervals are then computed using a binomial model with the two surfaces as inputs. The approach was implemented for Iowa using a 90 m resolution population grid (LandScan USA) and U.S. Census 2000 population. Three spatial interpolation methods, the areal weighting (AW) method, the ordinary kriging (OK) method, and a modification of the pycnophylactic method, were used on Census Tract populations to estimate the age‐sex proportion surfaces. To verify the model, age‐sex population estimates were computed for paired Block Groups that straddled Census Tracts and therefore were spatially misaligned with them. The pycnophylactic method and the OK method were more accurate than the AW method. The approach is general and can be used to estimate subgroup‐count types of variables from information in existing administrative areas for custom‐defined areas used as the spatial basis of support in other applications.     

TIGER空间数据模型及空间数据标准问题探讨

以TIGER这种既成事实的空间数据格式为例,详细介绍了TIGER的数据模型及文件组织形式,对TI-GER/Line如何描述空间对象信息进行分析,把这种格式作为空间对象拓扑模型实际实施的一种范例作以详细介绍,以起到抛砖引玉的作用,使读者能够更深入地了解空间对象表示的基本要求,对未来空间数据标准化起到一定的参考作用。     

A SEMI-GRAPHIC CONSTRUCTION FOR THE CONICAL ORTHOMORPHIC PROJECTION WITH ONE STANDARD PARALLELt

Abstract

The advantages of orthomorphic projections for topographical maps, whether for civil or military uses, have been increasingly realised in recent years. This has led to their gradual adoption as bases for map series by the leading countries, the conical type having been adopted in France for the new 1 : 50,000 maps, in Canada for the National Defence maps and in Britain by the Directorate of Military Survey for some useful European series. Appreciation of the nature and properties of graticules can best be achieved through an understanding of the theory of the projection system, whether the exposition be mathematically or partly graphically developed. Whereas the cylindrical and zenithal types of the orthomorphic projections have some explanation in graphical form there has been no comparable alternative to the difficult mathematical treatment of the conical type. The semi-graphic method presented here has been developed to contribute towards such a graphical exposition and in its method demands only a modest mathematical ability.     

美军数字化战场剖析及对我军测绘保障发展的几点认识

本文剖析了美军数字化部队和数字化战场的内涵，阐述了对发展我军测绘保障的一些认识。     

A Comparative Analysis of Areal Interpolation Methods

Over the years many approaches to areal interpolation have been developed and utilized. They range from the simple 2-D areal weighing method which uses only the spatial Z variable being processed, to more sophisticated approaches which use auxiliary variable(s) to provide more specificity to the results. In the research reported here, four promising approaches are implemented and comparatively tested. These approaches have widely varying conceptual foundations, and different auxiliary variables, if used. The areal weighing reflects many earlier methods which assumes uniform distributions of the spatial Z variable, and does not use any auxiliary variable. Tobler's pycnophylactic method uses a volumetric preservation approach, which assumes spatial Z variable is heterogeneously distributed, but does not use any auxiliary variable. The traditional dasymetric method of Wright is used with remote sensing spectral data of land use. Xie's road network hierarchically weighted interpolation uses the road network as the auxiliary variable, and assumes that population density is related to the class of the road, and to the density of the road network. The research design implemented here uses Census population distributions at different levels in the hierarchy as the source and target variables analyzed. The source zone population is taken at the Census Tract level, and the target zones are specified at the Census Block Group level in the hierarchy. The first two tests use only the Census population Z data, and no auxiliary variables, whereas the next uses remotely sensed land use data as the auxiliary data variable, and the fourth test utilizes the road network hierarchy as the auxiliary variable. The paper reports on the findings from these tests, and then interprets them in a spatial setting in terms of accuracy and effectiveness. This research points to the network method as the most accurate of the areal interpolation methods tested in this research.     

Establishing Classification and Hierarchy in Populated Place Labeling for Multiscale Mapping for The National Map

Current standards for federal mapping call for use of the Geographic Names Information System (GNIS) point layer for placement of United States populated place labels. However, this point layer contains limited classification information and hierarchy information, resulting in problems of map quality for database-driven, multi-scale, reference mapping, such as maps served by The National Map Viewer from USGS. Database-driven mapping often relies simply on what labels fit best in the map frame. Our research investigates alternative sources for labeling populated places, including polygons defined by the U.S. Census Bureau, such as incorporated place, census designated place (CDP), and economic place. Within each of these polygon layers we investigate relevant attributes from the decennial and economic censuses, such as population for incorporated places and CDPs, and the number of employees for economic places. The data selected are available for the entire country to serve national mapping requirements. This combination of data allows a more refined classification of populated places on maps that better represents relative importance. Visual importance on maps through scale should derive from more than simply residential population, but also economic importance, though comparison is made to this simpler case. We differentiate a fourth category of GNIS populated place points, essentially “neighborhoods” and related features—which are not incorporated places, CDPs, nor economic places. Populated places in this fourth class do not have federally defined boundaries, necessitating an alternative method for determining hierarchy in label presentation through scale.     

A spatial analysis of non‐English Twitter activity in Houston,TX

The use of social media data in geographic studies has become common, yet the question of social media's validity in such contexts is often overlooked. Social media data suffers from a variety of biases and limitations; nevertheless, with a proper understanding of the drawbacks, these data can be powerful. As cities seek to become “smarter,” they can potentially use social media data to creatively address the needs of their most vulnerable groups, such as ethnic minorities. However, questions remain unanswered regarding who uses these social networking platforms, how people use these platforms, and how representative social media data is of users' everyday lives. Using several forms of regression, I explore the relationships between a conventional data source (the U.S. Census) and a subset of Twitter data potentially representative of minority groups: tweets created by users with an account language other than English. A considerable amount of non‐stationarity is uncovered, which should serve as a warning against sweeping statements regarding the demographics of users and where people prefer to post. Further, I find that precisely located Twitter data informs us more about the digital status of places and less about users' day‐to‐day travel patterns.     

基于GIS的城镇近郊区空心化村庄信息系统的设计与实践

城镇近郊区的一些村庄受城镇经济发展与工作政策等因素的影响,逐渐变成了空心村。开发空心化村庄信息系统是保障村庄信息查询与统计分析工作的科学性、高效性运行的重要技术手段。本系统基于ArcGIS Engine与.NET平台技术,使用C/S服务器与客户端模式,利用C#语言编程实现。该系统在建立综合数据库的基础上,实现了村庄信息数据的更新与管理;根据用户需求,提供查询统计、空间分析、潜力评估、趋势预测4个模块。