Tag Archives: Census
With the newly elected 113th United States Congress starting its term, Esri is pleased to offer the new USA 113th Congressional Districts dataset and map service to all ArcGIS users.
We are pleased to announce that the new 2010 U.S. Census datasets with their new geometry and attributes are now available as layer packages on ArcGIS.com. Block Group, Tract, County, and State are all represented as polygons with over 40 attribute fields containing population totals by age and race, along with family and household information. Census Blocks are represented as points with total population and household information.
Average family size by Block Group
Visit the Esri Data & Maps United States Census page on the ArcGIS Content Resource Center for a list of all the census layers available for download on ArcGIS.com.
By Jim Herries, Cartographic Product Engineer
“I’m a VERY novice GISer. I work for a fire department. My Chief wants me to be able to add demographic layers to our district map, but when I look around, the maps are all “Google Earth” types or PDF files, which I can’t do anything with. Where and how do I get demographic data I can add to my map as a layer?”
Creating locators with ArcGIS 10 out of the box address locator styles requires the specific address attributes in one feature class. As the TIGER 2010 dataset consists of multiple feature classes and tables, creating locators with ArcGIS 10 out of the box locator styles requires the tables to be joined properly in advance and are exported to one feature class.
Alternatively, a custom locator style, TIGER – Edges-Dual Ranges, allows you to create locators with the feature classes/tables from the TIGER 2010 data without preprocessing the tables. The locator style requires the following feature classes and tables in the TIGER 2010 dataset:
You can download the locator style and sample data/tool from the Geocoding resource center:
Due to multiple table joins and selection queries, creating a locator using this locator style may take some time especially if the feature classes contain many features. Preprocessing the tables and exporting the address attributes to one feature class is an option as creating locators with one feature class using the out of the box locator style is generally faster.