Census 2010 Main
Census 2020 Main
Census 2020 LUCA Program
- tools and methods to make Census 2020 more accurate
- benefit from minimized undercount for your area
.. what would be the financial impact of a one-percent understatement in the Census 2020 population count? Many political districts are drawn based upon population change and shifts, and allocations of government funding and services are made based upon official population data. Consider this one specific example. For each one-percent of the Atlanta MSA population missed in Census 2020, potentially due to less than fully accurate address and location data, the financial impact could be on the order of $414 million per year. How and why? At margin, each person not counted in the decennial census results in a per capita disposable income loss for the area in the magnitude of $5,494 in 2010, and $6,770 per person in 2020. 61,100 people undercounted times $6,770 yields $414 million.
The Census 2020 Local Update of Census Addresses Operation (LUCA) program is underway. This important MAF/TIGER address-plus update program will help insure improved accuracy for Census 2020. LUCA is a geographic data development program engaging local communities across the U.S.
This section provides selected topics updates about Census 2020 LUCA, background on the role and scope of the Census Bureau Local Update of Census Addresses Operation (LUCA) program and ProximityOne participation working with local areas to improve the TIGER/Line files leading up to Census 2020. Using the CV XE GIS software and specialized expertise, we helped hundreds of governmental units, including all of the State of Georgia, improve the coverage and content of the TIGER/Line files and thus the accuracy and completeness of Census 2010. We help users and stakeholders of the Census 2010 data knit these data together with related data to achieve improved decision-making information solutions.
Census 2020 LUCA & Related Digital Geodata Updates
ProximityOne GIS tools, experience and knowledge will be applied to meet the needs of Census 2020. The CV LUCA software extension will precisely meet the Census 2020 and much more. Census 2020 LUCA participants (partners) may use this software starting in 2016.
This same set of resources is applied to augment the Census Bureau TIGER/Line files and develop the related ProximityOne Digital Map Database (DMD). In addition, this set of resources can be applied to the road/"edge" structure of any roads digital data file, keeping these critically important transportation and related land feature attributes up-to-date.
Census 2020 LUCA Features
See related Census LUCA operational plan (PDF)
Include census structure coordinates in the census address list; allows partners to return structure coordinates as part of submission
Provide ungeocoded (no geographic coordinates) U.S. Postal Service Delivery Sequence File addresses to State and County partners
Provide address list in more standard formats (.xlsx & .csv)
ProximityOne provides CV LUCA extension in 2016 for use by participants (partners).
Provide address counts in early 2017, a public geocoding tool to geocode local address list to assess type of participation
Census 2020 LUCA Schedule Overview
Advanced Notice Mailing: February 2017
Program Invitation: July 2017
Materials Available for Review: February 2018
LUCA Feedback Provided: August 2019
LUCA Appeals: October 2019
Census 2010 LUCA: Resources, Processing & Applications
The remainder of this document provides details relating to Census 2010 LUCA developments. It also also provides background on the importance of LUCA more generally.
What would be the impact of a one-percent understatement in the Census 2010 population count? Many political districts are drawn based upon population change and shifts, and allocations of government funding and services are made based upon official population data. Consider this one specific example. For each one-percent of the Atlanta MSA population missed in Census 2010, potentially due to less than fully accurate address and location data, the financial impact could be on the order of $220 million per year. How and why? At margin, each person not counted in the decennial census results in a per capita disposable income loss for the area in the magnitude of $3,389 in 2005, and $4,000 per person in 2010. 55,000 people undercounted times $4,000 yields $220 million.
More details ... the 2005 per capita current transfer payments in the Atlanta-Sandy Springs-Marietta MSA were $3,389, up from $2,519 in 2000. The figure in 2010 may be $4,000. For each one-percent of the Atlanta MSA population (55,000 people) missed in Census 2010, potentially due to less than fully accurate address and location data, the financial impact could be in the order of $220 million (55,000 x $4,000) per year as of Census 2010.
How can the accuracy be improved? One way is through effective implementation of the Census 2010 LUCA Program.
The Local Update of Census Addresses (LUCA) program is a decennial census geographic partnership program focused on updating geographic data. It will help the Census Bureau use local knowledge in developing its Master Address File (MAF) for the 2010 Census. The LUCA program presents an important opportunity to cities and other governmental units to participate in the development of the most accurate census possible. By improving the accuracy of the census, localities improve their opportunity to receive their fair share of Federal and other governmental funding and services. In states where a congressional seat might be potentially added or lost, the more important the collective participation of local governments across the state.
Tribal, state, and local governments can contribute to a more complete and accurate census for their community by reviewing and commenting on the list of housing unit and group quarters addresses that the Census Bureau will use to deliver questionnaires within their community.
ProximityOne and the LUCA Program. The ProximityOne CV XE GIS software (http://proximityone.com/cv.htm) and related data resources can help tribal, state, and local governments participating in the LUCA program maximize the comprehensiveness, quality, and usefulness of the LUCA-related data. The ProximityOne program provides a means for LUCA program participants to use the data that they help develop and establishes a structure and tools for accessing and analyzing Census 2010 data in a manner integrated with other data. This Web page provides a summary of key elements of the LUCA program and the ProximityOne LUCA support program. ProximityOne is not funded by any Federal agency.
The Census Bureau will provide software which is expected to meet the basic requirements of the LUCA Program. The ProximityOne CV XE GIS provides all of those same capabilities plus provides many other related and important capabilities. The ProximityOne CV XE GIS software features ease-of-use as a top priority. All that is required to use the most basic version of CV XE GIS is a stand-alone personal computer with a Windows 98/XP operating system with minimal configuration. Users with limited or no GIS experience can use the basic version of CV XE GIS. Internet access is not required for the basic version of CV XE GIS. In the simplest configuration of CV XE GIS, which supports all LUCA requirements, there are no external file dependencies (beyond LUCA files themselves) and only an executable program is required -- less than 5MB footprint.
Like the Census Bureau supplied software, the basic version of CV XE GIS is available to LUCA program participants (formally designated LUCA liaison) at no fee. An optional support is available for a nominal fee.
Unlike the Census Bureau supplied software, the CV XE GIS software is designed to make analytical use of census-sourced and non-census data. It can be used as a key component of Census 2000 and Census 2010 data access and analysis. Optionally available features of CV XE GIS, also unlike the Census Bureau supplied software, will geocode address data. In addition, optionally available features of CV XE GIS, unlike the Census Bureau supplied software, enables the user to integrate shapefiles and subject matter data from many Federal agencies and statistical programs.
LUCA Program Overview. Through the LUCA program designated representatives of local, state, and tribal governments may participate in review of addresses contained in the Master Address File (MAF) being developed for the 2010 Census. The program operates as follows:
Address List Data Security. The Census address list contains Title 13 data and, therefore, must be protected during shipment from and to the Census Bureau and the participant. To ensure the secure distribution of Title 13 data, the Census Bureau will use SecureZIP to encrypt and zip the address list into a self-decrypting archive using a password provided by the Census Bureau. The participant will then use this password for zipping the updated Census address list before shipment back to the Census Bureau. The participant may use any zipping software that enables password protection, such as PKZIP and WinZip.
Using CV XE GIS Software to Meet LUCA and Extended Objectives
CV & Address List Operations
Address List Fields (see documentation for current version)
The CV dBrowse operation is used to import the address list file into a dbase structure. Actions listed below are made using the dBrowse tool. Upon completion of editing, the file is exported to ASCII structure and sent to Census using prescribed operations.
Address List Action Codes
Below is the current list of potential action codes that the participant can assign to a Census address record (in the Action Code field - see above). Note that the participant must indicate an address record as a group quarters via the Group Quarters Flag field.
‘A’ – Address added
‘C’ – Address field(s) was modified (changed)
‘D’ – Address to delete
‘N’ – Address is nonresidential or commercial
‘J’ – Address is outside of the jurisdiction and not enough information is available for correction (to make it within the jurisdiction)
CV/LUCA Address List Update Rules
1. The participant can update city-style addresses only.
2. The participant can assign only one action code to an address record.
3. If a participant challenges the housing unit or group quarters count for a block, the participant then cannot provide any updates for individual address records associated with that block and vice versa.
4. The participant can update any field for city-style address records except for the MAFID.
5. The participant may not update the MAFID.
6. If the participant copies the information from an existing address record to a new one, the new address record must have a unique MAFID. The participant determines the highest current value assigned to an existing MAFID, adds a value of “1” and assigns that value to the new address record.
7. The participant can select an address record in the address list, and the respective block will be noted on the map.
8. The participant can select an address record in the address list, and the values for the block for that address will be noted on the address count list.
CV Address List Sorting
The CV dBrowse operation is used to sort the address list file (using the same dbase file as described above). Sorting is accomplished by using an SQL-like operation that can be applied to any field or combination of fields. Upon completion of editing, the file is exported to ASCII structure and sent to Census using prescribed operations.
The following list provides examples of sorts that users will find useful.
Sort by Line Number
Line Number | State Code | county Code | tract code | block code | StName Pfx Qual | StName Pfx Dir | StName Pfx Type | StName | StName Sfx Type | StName Sfx Dir | StName Sfx Qual | House Number.
(default sort order provided by the Census Bureau)
Sort by Geography: State Code | County Code | Tract Code | Block Code | Line Number
Sort by ZIP Code: City-Style Mailing ZIP Code | Line Number.
Sort by House Name/Street Number
StName Pfx Qual | StName Pfx Dir | StName Pfx Type | StName | StName Sfx Type | StName Sfx Dir | StName Sfx Qual | House Number
Sort by Geography/Address
State Code | County Code | Tract code | Block code | StName Pfx Qual | StName Pfx Dir | StName Pfx Type | StName | StName Sfx Type | StName Sfx Dir | StName Sfx Qual | House Number
Sort by ZIP Code/Address City-Style Mailing ZIP Code | StName Pfx Qual | StName Pfx Dir | StName Pfx Type | StName | StName Sfx Type | StName Sfx Qual | House Number
Sort by Action Code/Geography Action Code | State Code | County Code | Tract code | Block code | Line Number
Sort by Action Code/House Name/Street Number Action Code | StName Pfx Qual | StName Pfx Dir | StName Pfx Type | StName | StName Sfx Type | StName Sfx Dir | StName Sfx Qual | House Number
Abbreviations: StName=Street Name, Pfx=Prefix, Sfx=Suffix, Qual=Qualifier, Dir=Direction
The participant must return the data in the exact same layout as was provided to the participant in order for the Census Bureau to use the file for updating the MAF.
CV & Address Count Operations
Address Count List Fields (see documentation for current version)
The CV dBrowse operation is used to import the address count list file into a dbase structure. Actions listed below are made using the dBrowse tool. Upon completion of editing, the file is exported to ASCII structure and sent to Census using prescribed operations.
CV/LUCA Address Count List Update Rules
1. The participant provides a value in the Local Count of Housing Unit Addresses and Local Count of Group Quarters Addresses fields for any block in their geographic extent.
2. As noted above, the participant may not provide any updates for individual address records associated with a block if the participant challenges the housing unit or group quarters count for that block.
3. The participant can select a block in the address county list, and the respective block will be noted on the map.
4. The participant can select a block in the address count list, and the addresses within that block will be noted on the address count list.
CV & Map Updating and Operations
The CV project is developed using a template structure with the shapefiles provided by the Census Bureau. Standard map navigation tools are available for zoom, pan, identify and locate. Upon completion of editing, the file is exported to ASCII structure and sent to Census using prescribed operations.
Legal Transactions (per LUCA Guidelines)
Add line/Add name/Add MTFCC
-- line added with GeoEditor; existing line attributes edited with dBrowse tool
-- performed using GeoEditor
Copy name, MTFCC, and address ranges from existing line/Add new line/ Delete existing line
-- line added/deleted with GeoEditor; line attributes edited (key in, copy/paste, etc.) with dBrowse tool
-- performed with GeoEditor
-- performed with GeoEditor
Add structure point (for the Feedback phase only)
-- click on with add point feature or batch process with many points
Move structure point (for the Feedback phase only)
-- performed with GeoEditor
Delete structure point (for the Feedback phase only)
-- performed with GeoEditor
Add node/ Split line/Duplicate attributes
-- click on with add point/line feature
CV Supported ('Participant Allowed Actions') Operations (all supported with combination of GeoEditor tools and dBrowse feature)
1. The participant may add a linear feature.
1.1. The participant may start and end the feature at an intersection or at the end of a linear feature (point), on a linear feature (line), or in space. The participant may add curve points between the start and the end points
1.2. The participant must choose a classification (listed in the Feature Classifications section below).
1.3. The participant must name added road features.
1.4. The participant may name the feature with acceptable prefixes and types.
2. The participant may delete features (existing segments/ 1-cells)
2.1. The participant may delete existing features.
2.2. If feature is a block boundary, the participant must change the MTFCC for the visible feature to the MTFCC for a must-hold block boundary in order to maintain the topology.
3. The participant may add nodes to a line to split a feature. When the participant adds a node to split a feature, the new segments must have the attributes (names, addresses, classification code) of the original feature. The participant may modify the lines and their names and classifications separately.
4. The participant may add, edit, and delete primary names.
5. The participant may not add, edit, nor delete alternate names.
6. The participant must provide the name, MTFCC, and address ranges (attributes) for all new road features.
7. The participant must provide the MTFCC for all new lines.
8. The participant may edit the classification of a feature.
9. The participant may view attribute information (all names, addresses, classification code, left geography 2-cell, and right geography 2-cell) for all features.
10. For the initial LUCA products, the participant may change or delete structure points for city-style address only. Additionally, the participant must correct or delete the associated address record on the address list.
11. If the participant marks an address record for a city-style address in the address list with a ‘Delete’ action code, the participant must also mark the associated structure point as deleted on the map.
12. For feedback LUCA products, the participant may move, add, and delete structure points. The participant must also move, add, or delete the associated structure point on the map.
13. The participant can select a block on the map, and the addresses within that block will be noted on the address list.
14. The participant can select a block on the map, and the values for that block will be noted on the address count list.
Feature Classifications The following features will appear on the map for the user to view and/or edit (these are attributes that may be flexibly seleted and postioned with the layer editor).
1. Road Features
2. Water Features
4. Miscellaneous Features
1. The participant can perform only those actions that will enforce the basic rules of topology in order to ensure that coincident features remain coincident.
2. All topological requirements are met before the participant delivers the updated file to the Census Bureau.
1. Jurisdiction is the entity or entities that the user is associated with and has registered to participate in the 2010 LUCA program.
2. Geographic extent is the geographic area for which the user has permission to submit LUCA updates for a given jurisdiction. This is equal to the geographic area(s) of the jurisdictions for which they are responsible plus the geographic area of the county or counties surrounding the geographic area(s).
3. City-style addresses are those address records with a house number and street name. These are identified in the address list by having a value in the ‘Mailing House Number/Building Number’ and ‘Mailing Street Name/Building Name’ fields.
4. MAF is the acronym for the Master Address File. The MAF is a nationwide list of all addresses to support many of the Census Bureau’s operations. Besides containing mailing addresses and ZIP Codes, a MAF record also contains geographic information about the location of addresses.
5. Feedback is the phase of the 2010 LUCA program where the Census Bureau provides data back to participants providing the disposition of the 2010 LUCA program-related updates that they provided to the Census Bureau.
6. Structure point is a map spot. A structure point is defined as a type of point feature that acts as a designation on a Census Bureau map to mark the location of one or more living quarters. Each structure point within a census block is assigned a unique number, which corresponds to an address in the MAF. A structure point will have an associated set of latitude/longitude coordinates.
7. TIGER is the acronym for the Topologically Integrated Geographic Encoding and Referencing System (TIGER). TIGER is a computer database that contains a digital representation of all map features (streets, roads, rivers, railroads, lakes, and so forth) required to support Census Bureau operations, the related attributes for each, and the geographic identification codes for all entities used by the Census Bureau to tabulate data for the United States, Puerto Rico, and the Island Areas.
8. MAF/TIGER Feature Class Code (MTFCC) is intended to classify and describe geographic objects or features. A feature class is a grouping of features in MAF/TIGER that share basic characteristics. A “feature” differs from a “feature class” in that the feature is an instance of the feature class. For example, “Lake” and “Road” are feature classes while “Lake Superior” and “Suitland Road” are features. The first letter of the MTFCC is used to group features into their common feature category. There are eleven feature categories. See table.
ProximityOne develops geographic-demographic-economic data and analytical tools and helps organizations knit together and use diverse data in a decision-making and analytical framework. We develop custom demographic/economic estimates and projections, develop geographic and geocoded address files, and assist with impact and geospatial analyses. Wide-ranging organizations use our tools (software, data, methodologies) to analyze their own data integrated with other data. Follow ProximityOne on Twitter at www.twitter.com/proximityone. Contact ProximityOne (888-364-7656) with questions about data covered in this section or to discuss custom estimates, projections or analyses for your areas of interest.