al_pbg00

Metadata:


Identification_Information:
Citation:
Citation_Information:
Originator: Roger B. Hammer (Oregon State University), Volker C. Radeloff (University of Wisconsin Madison), and Susan I. Stewart (USDA Forest Service Northern Research Station)
Publication_Date: February, 1, 2008
Title:
al_pbg00
Geospatial_Data_Presentation_Form: vector digital data
Online_Linkage: \\Spiderman\Rad\Projects\wildfire\datafiles(d)\wui_data\pbg00_2007\new_coverages_for_web_10_3_2007\al_pbg00
Description:
Abstract:
The overarching goal of our analysis was to create a long-term dataset on housing density change that is accurate, spatially detailed, and consistent across the United States.  The maps and data were designed for strategic decision making and for the visualization of housing growth patterns over large areas.  The data are too coarse for most county- or township-level land use planning, and more detailed and current data are often available for local applications.

To calculate our housing growth estimates, we relied on existing data sources and made assumptions about past growth rates and settlement patterns.  Our maps represent a conservative estimate of change. It is important for users to understand how the dataset was generated, what errors the source data may contain, and upon which assumptions it is built.  The objective of this technical documentation is to provide this information.
The decennial census is the only national, comprehensive source of longitudinal information on housing patterns across the U.S. However, digitized census boundaries at fine scales only became available in 1990, and boundaries of census tracts, block groups, and blocks change so frequently that earlier data at these scales cannot be easily mapped.  We thus developed: Digital data on the smallest census units for which long-term housing data can be analyzed (partial block groups), and Algorithms to estimate housing density for each partial block group, by decade, back to 1940 and forward to 2030.  


Partial Block Group Formation

The smallest units for which the Census Bureau provides both detailed social data and digital geographic boundaries are block groups.  However, block groups are often subdivided into smaller spatial units by other boundaries such as those forming incorporated places, legal and census-designated county subdivisions, and rural/urban areas.  Block groups thus frequently consist of multiple "partial" block groups for which data tabulations are also provided. And housing unit density is often different among the partial block groups that make up a single block group. Analyzing housing density at the block group level obfuscates important housing density differences that are revealed by using partial block groups.

The formation of partial block groups began with 2000 Census blocks (U.S. Census Bureau, 2004).  Each Census block contains a sequence of  identifiers denoting both the block group to which it belongs, and any other geographic boundaries intersecting that block group (see above). Together the identifiers indicate the partial block group to which each block belongs.  We used these identifiers to remove all census block boundaries that fell within a given partial block group, dissolving census block boundaries to form partial block groups. It is important to note that partial block groups sometimes consist of multiple polygons that are not necessarily spatially contiguous. In our designation of partial block groups, we assumed that Census blocks with zero housing units in 2000 also had no houses in any prior decade and thus we excluded them from the partial block groups. 

While the Census Bureau does not provide partial block group boundaries readily, it does tabulate housing data at this level. The Summary File 3A (U.S. Bureau of the Census, 2002) includes tabulations for these partial block groups. 


Historic Estimates and Adjustments

Census takers ask "in what year was this housing unit built?" In 2000, the "year housing unit built" question was coded with the following response options: 1999 or 2000, 1995 to 1998, 1990 to 1994, 1980 to 1989, 1970 to 1979, 1960 to 1969, 1950 to 1959, 1940 to 1949, and 1939 or earlier. We aggregate the three initial categories between 1990 and 2000 to produce consistent decadal estimates.

Initial estimates of historic housing density (i.e., backcasts) were derived by summing all housing units built prior to a given decade for each partial block group (e.g., for a 1970 estimate we sum housing units built from 1939-earlier through 1960).  However, it is important to note that these initial estimates exclude housing units that were present in the past, but were no longer present in 2000.  We adjusted for these 'missing' housing units by comparing county-level totals of our initial estimates with historic county-level totals reported by the Census Bureau. If historic Census counts were greater than the county-level totals initially estimated, we applied a correction and distributed it across the partial block groups.  Essentially, we raised the housing density by a uniform factor for all partial block groups in the county to ensure that the historic estimates summed to the county level matched the recorded historic county totals.  

Census blocks can capture areas with no housing such as military and some other public lands.  However, no accurate, fine-scale, and consistent public land ownership data is available for the United States, and thus, no actual land ownership data was used in generating our maps and data.  This means that some partial block groups contain portions of public lands where housing is excluded, and may give the false impression that there are houses in areas where houses do not exist.  Users should be aware of this feature of our data.

For further details on the estimation of historic housing densities, please consult Hammer et al. 2004. Characterizing spatial and temporal residential density patterns across the U.S. Midwest, 1940-1990. Landscape and Urban Planning 69: 183-199


Future Estimates and Adjustments

The 2000 partial block group geography created for the backcasts was maintained in producing forecasts for 2010, 2020, and 2030. Initial estimates were produced by extrapolating 1990s housing growth rates over the coming three decades. To control for potential over- or underestimation arising from unique, localized growth patterns occurring during the 1990s, initial future estimates were adjusted using commercially produced population estimates from Woods and Poole Economics (W&P) (http://www.woodsandpoole.com/).  W&P population projections (Woods & Poole 2004) were converted to housing unit projections based on county-specific household size in 2000, as reported in the same dataset.  This results in a conservative estimate of future housing unit projections in relation to population because household size may continue its decline in the future, thus raising the number of housing units associated with a given population. We used the resulting county housing projections to control our partial block group estimates for future decades, just as we use the historic county Census totals to modify backcasts (i.e., summing to the county level and comparing our county estimate to the county W&P control total, adjusting our county estimate as needed, and distributing the adjustment to the constituent partial block groups).

References
U.S. Census Bureau, 2004.  "2004 TIGER/Line Files".
U.S. Census Bureau, 2002.  "2000 Census of Population and Housing, Summary File 3".
Woods & Poole Economics Inc. 2004. "2004 Regional Projections and Database". Washington D.C.
Purpose:
Housing density estimates for 1940 - 2030. Intended for broad-scale analyses.
Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 1940, 1950, 1960, 1970, 1980, 1990, 2000, 2010, 2020, and 2030
Currentness_Reference:
Based on the 1990 and 2000 US Decennial Census
Status:
Progress: Complete
Maintenance_and_Update_Frequency: Updates are planned as new US Census data become available.
Spatial_Domain:
Bounding_Coordinates:
West_Bounding_Coordinate: -88.663383
East_Bounding_Coordinate: -84.446141
North_Bounding_Coordinate: 35.185024
South_Bounding_Coordinate: 29.884820
Keywords:
Theme:
Theme_Keyword: United States Census
Theme_Keyword: Housing density
Theme_Keyword: Partial-block group
Place:
Place_Keyword: United States
Access_Constraints: None
Use_Constraints:
Please cite "Hammer, R. B. S. I. Stewart, R. Winkler, V. C. Radeloff, and P. R. Voss. 2004. Characterizing spatial and temporal residential density patterns across the U.S. Midwest, 1940-1990. Landscape and Urban Planning 69: 183-199" in all products, publications, and presentations utilizing these data.
Point_of_Contact:
Contact_Information:
Contact_Person_Primary:
Contact_Person: Volker C. Radeloff
Contact_Organization: University of Wisconsin
Contact_Position: Assistant Professor
Contact_Address:
Address_Type: mailing and physical address
Address:
University of Wisconsin
Address:
Forest and Wildlife Ecology
Address:
1630 Linden Drive
City: Madison
State_or_Province: WI
Postal_Code: 53706
Country: USA
Contact_Voice_Telephone: (608) 263-4349
Contact_Facsimile_Telephone: (608) 292-9922
Contact_Electronic_Mail_Address: radeloff@wisc.edu
Native_Data_Set_Environment:
Microsoft Windows 2000 Version 5.2 (Build 3790) Service Pack 2; ESRI ArcCatalog 9.2.4.1420
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Data_Quality_Information:
Lineage:
Process_Step:
Process_Description:
Metadata imported.
Source_Used_Citation_Abbreviation:
Z:\Projects\Wildfire\Datafiles(D)\wui_data\pbg00_2007\new_coverages_for_web_10_3_2007\al_pbg00\metadata.xml
Process_Step:
Process_Description:
Metadata imported.
Source_Used_Citation_Abbreviation:
Z:\Projects\Wildfire\Datafiles(D)\wui_data\pbg00_2007\new_coverages_for_web_10_3_2007\md_pbg00\metadata.xml
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Spatial_Data_Organization_Information:
Direct_Spatial_Reference_Method: Vector
Point_and_Vector_Object_Information:
SDTS_Terms_Description:
SDTS_Point_and_Vector_Object_Type: Complete chain
Point_and_Vector_Object_Count: 171464
SDTS_Terms_Description:
SDTS_Point_and_Vector_Object_Type: Label point
Point_and_Vector_Object_Count: 76625
SDTS_Terms_Description:
SDTS_Point_and_Vector_Object_Type: GT-polygon composed of chains
Point_and_Vector_Object_Count: 76625
SDTS_Terms_Description:
SDTS_Point_and_Vector_Object_Type: Point
Point_and_Vector_Object_Count: 4
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Spatial_Reference_Information:
Horizontal_Coordinate_System_Definition:
Planar:
Map_Projection:
Map_Projection_Name: Albers Conical Equal Area
Albers_Conical_Equal_Area:
Standard_Parallel: 29.500000
Standard_Parallel: 45.500000
Longitude_of_Central_Meridian: -96.000000
Latitude_of_Projection_Origin: 23.000000
False_Easting: 0.000000
False_Northing: 0.000000
Planar_Coordinate_Information:
Planar_Coordinate_Encoding_Method: coordinate pair
Coordinate_Representation:
Abscissa_Resolution: 0.000000
Ordinate_Resolution: 0.000000
Planar_Distance_Units: meters
Geodetic_Model:
Horizontal_Datum_Name: North American Datum of 1983
Ellipsoid_Name: Geodetic Reference System 80
Semi-major_Axis: 6378137.000000
Denominator_of_Flattening_Ratio: 298.257222
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Entity_and_Attribute_Information:
Detailed_Description:
Entity_Type:
Entity_Type_Label: al_pbg00.pat
Attribute:
Attribute_Label: FID
Attribute_Definition:
Internal feature number.
Attribute_Definition_Source:
ESRI
Attribute_Domain_Values:
Unrepresentable_Domain:
Sequential unique whole numbers that are automatically generated.
Attribute:
Attribute_Label: Shape
Attribute_Definition:
Feature geometry.
Attribute_Definition_Source:
ESRI
Attribute_Domain_Values:
Unrepresentable_Domain:
Coordinates defining the features.
Attribute:
Attribute_Label: AREA
Attribute_Definition:
Area of feature in internal units squared.
Attribute_Definition_Source:
ESRI
Attribute_Domain_Values:
Unrepresentable_Domain:
Positive real numbers that are automatically generated.
Attribute:
Attribute_Label: PERIMETER
Attribute_Definition:
Perimeter of feature in internal units.
Attribute_Definition_Source:
ESRI
Attribute_Domain_Values:
Unrepresentable_Domain:
Positive real numbers that are automatically generated.
Attribute:
Attribute_Label: AL_PBG00#
Attribute_Definition:
Internal feature number.
Attribute_Definition_Source:
ESRI
Attribute_Domain_Values:
Unrepresentable_Domain:
Sequential unique whole numbers that are automatically generated.
Attribute:
Attribute_Label: AL_PBG00-ID
Attribute_Definition:
User-defined feature number.
Attribute_Definition_Source:
ESRI
Attribute:
Attribute_Label: PBG00
Attribute_Definition:
Unique character strings that identify the partial-block group to which individual polygons belong.  A partial-block group may contain one or more polygons.
Attribute:
Attribute_Label: PBGPR00
Attribute_Definition:
Positive real numbers that quantify the proportion of the total partial-block group area covered by this polygon.
Attribute:
Attribute_Label: SUMPBGAREA
Attribute_Definition:
Positive real numbers that quantify the total area of the partial-block group to which this polygon belongs.
Attribute:
Attribute_Label: WATER00
Attribute_Definition:
Water flag (1 = water, 0 = not water).
Attribute:
Attribute_Label: STCNTY
Attribute_Definition:
5 character string of state and county FIPS code.
Attribute:
Attribute_Label: HDEN40
Attribute_Definition:
1940 housing density (housing units / squared-km).
Attribute:
Attribute_Label: HDEN50
Attribute_Definition:
1950 housing density (housing units / squared-km).
Attribute:
Attribute_Label: HDEN60
Attribute_Definition:
1960 housing density (housing units / squared-km).
Attribute:
Attribute_Label: HDEN70
Attribute_Definition:
1970 housing density (housing units / squared-km).
Attribute:
Attribute_Label: HDEN80
Attribute_Definition:
1980 housing density (housing units / squared-km).
Attribute:
Attribute_Label: HDEN90
Attribute_Definition:
1990 housing density (housing units / squared-km).
Attribute:
Attribute_Label: HDEN00
Attribute_Definition:
2000 housing density (housing units / squared-km).
Attribute:
Attribute_Label: HDEN10
Attribute_Definition:
2010 housing density (housing units / squared-km).
Attribute:
Attribute_Label: HDEN20
Attribute_Definition:
2020 housing density (housing units / squared-km).
Attribute:
Attribute_Label: HDEN30
Attribute_Definition:
2030 housing density (housing units / squared-km).
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Distribution_Information:
Resource_Description: Downloadable Data
Standard_Order_Process:
Digital_Form:
Digital_Transfer_Information:
Transfer_Size: 76.504
Fees: None
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Metadata_Reference_Information:
Metadata_Date: 20080307
Metadata_Contact:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization: University of Wisconsin
Contact_Person: Volker C. Radeloff
Contact_Address:
Address_Type: Forest and Wildlife Ecology, 1630 Linden Drive
City: Madison
State_or_Province: WI
Postal_Code: 53706
Contact_Voice_Telephone: (608) 263-4349
Metadata_Standard_Name: FGDC Content Standards for Digital Geospatial Metadata
Metadata_Standard_Version: FGDC-STD-001-1998
Metadata_Time_Convention: local time
Metadata_Extensions:
Online_Linkage: http://www.esri.com/metadata/esriprof80.html
Profile_Name: ESRI Metadata Profile
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