|
|
|
ProximityOne Digital Map Database
.. viewing, mapping or analyzing the 636 K-12 public schools in context of the 147,293 street/road segments in Orange County, CA, most any large county, can be challenging without the proper data and tools .. see map graphic examples below. Uee the ProximityOne Digital Map Database to perform this type of task. Add your data and annotations. Share resulting map graphics real-time in a collaborative session and/or add static graphics or videos to presentations and reports. Take the tools and data with you; here you are not tied to Internet. The ProximityOne Digital Map Database (DMD) is set of integrated U.S. national scope and world by country shapefiles organized and ready-to-use with the ProximityOne CV XE GIS software. The DMD basic version includes integrated business, demographic, economic subject from the ProximityOne Situation & Outlook database. Add your data. Develop maps and perform geospatial analyses down to the subneighborhood block group level of geography using these resources. The ProximityOne DMD is based in part on an augmented version of the Census Bureau TIGER geographic data -- the geographic backbone for Census 2020 and many other statistical programs. Warren Glimpse, principal and chief statistician at ProximityOne, developed the prototype Census TIGER data and is leading expert on use of these data. Advantages & Benefits • The most comprehensive and accurate source of vector-based digital map data • Fully consistent with Census Bureau geography. • Use with any software on any platform that can process shapefiles. • CV XE GIS features new Census 2020 geography. • Provided with ProximityOne CV XE GIS software and GIS project. • Start applications today; no wait time. • Integrated and ready-to-use; removes the cost, tedium, time, process of building and maintaining your own. • Supported with documentation and standards providing uniform and connected resources. • Optionally integrated with ProximityOne Data Service, monthly updates with business, demographic, economic current data and projections not available elsewhere. • The ProximityOne Data Service is also available without ProximityOne. Start-up View of DMD GIS Project The following graphic shows the start-up view of the DMD GIS project. A GIS project is a file that manages the appearance and collection of layers present in the GIS project. Easily develop GIS project variations that might be as simple as 2 or 3 layers. Layers are rendering of shapefiles included in the DMD. Layers in the start-up GIS project are listed in the legend panel at the left of the map view and described in more detail in the table below the map graphic. This GIS project has been used to develop the U.S. by county 2010-19 population change thematic pattern map described in more detail in the CountyTrends2019 section. Click graphic for larger view. Expand browser to full window for best quality view.  • view developed using the ProximityOne CV XE GIS software and standard DMD GIS project. • use these tools on your computer to examine these data & related geography/subject matter. • learn more in the no cost web sessions. Layers/Files Included in the DMD There are 25 layers included in the DMD basic configuration. All layers are shapefile based except the Base Layers which are tiling topology. All shapefile based layers have U.S. national scope coverage except World by Country which is global. Click Layer link in first column to view scope of subject matter in shapefile.
ProximityOne DMD Availability ProximityOne DMD is available as a Level 1 base structure as described above or Level 2 subscription. The Level 1 base structure includes limited integrated subject matter. The Level 2 subscription version includes an extended set of subject matter and is updated monthly. For example, the base structure includes a U.S. by county shapefile, but no employment situation subject matter. The subscription version is updated monthly to include the new, updated subject matter data. For example, the county and city shapefiles include monthly updates to the employment situation and residential construction -- two examples. The monthly data start January 2018 and run continuously through the recent month -- monthly updates. Adjusting the Scope of Geography to Meet Your Needs The standard version of ProximityOne DMD is as described above, U.S. national scope and world by country. You can also use subnational versions: • Selected state(s) • Selected metros(s) • Selected counties(s) • Some combination of the above Roads & Rails .. goto top Detailed roads, intersection to intersection line segments, are available as optional separate shapefile(s). We develop an augmented version of the TIGER roads and rails "edges" shapefiles. These line shapefiles include road/street intersection to intersection segments - more than 70 million segments for the U.S. The left and right side of the segment is coded with address range and geographic reference code (geocodes) such as census block, block group, census tract, ZIP code among others. In the Census TIGER version, many of these attributes are incomplete or not present. We work continuously to update these attributes. K-12 Schools .. goto top U.S. national scope approximately 100,000 K-12 schools are available as optional separate point shapefiles(s). Views Illustrating K-12 Schools and Detailed Roads/Streets .. goto top There are 636 K-12 public schools and 147,293 road/street segments in Orange County, CA .. a "5,000 foot view". Click graphic for larger view; expand browser to full window for best quality view.  Zoom-in to Newport Beach, CA Illustrating K-12 Schools and Streets Profiles/Attributes Zoom-in to a neighborhood to examine details ... an example in the Newport Beach (Orange County), CA area. School marker (orange) with school profile  Streets; selected street segment profile  Patterns of Economic Prosperity by Block Group .. goto top The graphic shown below illustrates use of the CV XE GIS software with the DMD GIS project to create a thematic pattern map of median household income ($MHI) by block group in context of 116th Congressional Districts (bold boundary, white CD label) in the Orange County, CA area. See inset legend for color/$MHI intervals. Click graphic for larger view; expand browser to full window for best quality view.  116th Congressional Districts - base data items .. goto top Sources: ACS 2018 5 Year and ACS 2018 1 Year
ACS 18 5 year (last field name digit indicates 5 year):
B01001_0015 Total Population B01001_0025 Male B01001_0265 Female B02001_0025 White alone B02001_0035 Black or African American alone B02001_0045 American Indian and Alaska Native alone B02001_0055 Asian alone B02001_0065 Native Hawaiian and Other Pacific Islander alone B02001_0075 Some other race alone B02001_0085 Two or more races B03002_0125 Hispanic (any race) B09020_0015 Population 65 years and over B11002_0015 Population in Households B11001_0015 Total Households B11001_0025 Family Households B15002_0015 Population 25 years and over B15002_0115 High school graduate (Male, age 25+) B15002_0285 High school graduate (Female, age 25+) B25003_0015 Total housing units B25003_0025 Owner occupied units B25003_0035 Renter occupied units B25002_0035 Vacant units B19013_0015 Median Household Income B19113_0015 Median Family Income B25077_0015 Median housing value B25064_0015 Median gross rent ACS 18 1 year (last field name digit indicates 1 year): B01001_0011 Total Population B01001_0021 Male B01001_0261 Female B02001_0021 White alone B02001_0031 Black or African American alone B02001_0041 American Indian and Alaska Native alone B02001_0051 Asian alone B02001_0061 Native Hawaiian and Other Pacific Islander alone B02001_0071 Some other race alone B02001_0081 Two or more races B03002_0121 Hispanic (any race) B09020_0011 Population 65 years and over B11002_0011 Population in Households B11001_0011 Total Households B11001_0021 Family Households B15002_0011 Population 25 years and over B15002_0111 High school graduate (Male, age 25+) B15002_0281 High school graduate (Female, age 25+) B25003_0011 Total housing units B25003_0021 Owner occupied units B25003_0031 Renter occupied units B25002_0031 Vacant units B19013_0011 Median Household Income B19113_0011 Median Family Income B25077_0011 Median housing value B25064_0011 Median gross rent 116th Congressional Districts - ACS 2018 5-year & 1-year Estimates .. Interactive Table .. goto top Use this table to see how the ACS 2018 5-year (data collected 2014 through 2018) and ACS 2018 1-year (data collected during 2018) estimates of total population and median housing income ($MHI) differ for each 116th Congressional District. Both 5-year and 1-year data are included for a wide set of items in the 116th CD shapefile as shown above. Both 5-year and 1-year estimates are subject to estimation error. These data are intended to show change over time but show how the estimation results for different time periods differ. As an example, the most recent population estimate for Alabama CD 01 (0101) is 715,346 (ACS 2018 1-year estimate). But when comparing the CD population with a different geographic area (like block group; no 1-year estimates available) it would be preferred to use the ACS 2018 5-year estimate 706,503. See usage notes below table. See related interactive tables. Usage Notes • Click ShowAll between queries/filters. • Use left-most column to select by state. • Click ShowAll button between Find/Queries (reset table). • Click column header cell to sort table on that column; click again to sort other direction. • Use mouseover on column header to view column description. Counties- File 1 - base data items .. goto top Model-based Population Estimates & Components of Change
- Area Name
- USPS State abbreviation - State+County FIPS Code - CBSA code - Population estimate 7/1/2010 - Population estimate 7/1/2011 - Population estimate 7/1/2012 - Population estimate 7/1/2013 - Population estimate 7/1/2014 - Population estimate 7/1/2015 - Population estimate 7/1/2016 - Population estimate 7/1/2017 - Population estimate 7/1/2018 - Population change 7/1/2010-6/30/18 - Population percent change 7/1/2010-6/30/18 - Change in resident total population 7/1/2010 to 7/1/2011 - Change in resident total population 7/1/2011 to 7/1/2012 - Change in resident total population 7/1/2012 to 7/1/2013 - Change in resident total population 7/1/2013 to 7/1/2014 - Change in resident total population 7/1/2014 to 7/1/2015 - Change in resident total population 7/1/2015 to 7/1/2016 - Change in resident total population 7/1/2016 to 7/1/2017 - Change in resident total population 7/1/2017 to 7/1/2018 - Change in resident total population 7/1/2018 to 7/1/2019 - Births in period 7/1/2010 to 7/1/2011 - Births in period 7/1/2011 to 7/1/2012 - Births in period 7/1/2012 to 7/1/2013 - Births in period 7/1/2013 to 7/1/2014 - Births in period 7/1/2014 to 7/1/2015 - Births in period 7/1/2015 to 7/1/2016 - Births in period 7/1/2016 to 7/1/2017 - Births in period 7/1/2017 to 7/1/2018 - Births in period 7/1/2018 to 7/1/2019 - Deaths in period 7/1/2010 to 7/1/2011 - Deaths in period 7/1/2011 to 7/1/2012 - Deaths in period 7/1/2012 to 7/1/2013 - Deaths in period 7/1/2013 to 7/1/2014 - Deaths in period 7/1/2014 to 7/1/2015 - Deaths in period 7/1/2015 to 7/1/2016 - Deaths in period 7/1/2016 to 7/1/2017 - Deaths in period 7/1/2017 to 7/1/2018 - Deaths in period 7/1/2018 to 7/1/2019 - Natural increase in period 7/1/2010 to 7/1/2011 - Natural increase in period 7/1/2011 to 7/1/2012 - Natural increase in period 7/1/2012 to 7/1/2013 - Natural increase in period 7/1/2013 to 7/1/2014 - Natural increase in period 7/1/2014 to 7/1/2015 - Natural increase in period 7/1/2015 to 7/1/2016 - Natural increase in period 7/1/2016 to 7/1/2017 - Natural increase in period 7/1/2017 to 7/1/2018 - Natural increase in period 7/1/2018 to 7/1/2019 - Net international migration in period 7/1/2010 to 7/1/2011 - Net international migration in period 7/1/2011 to 7/1/2012 - Net international migration in period 7/1/2012 to 7/1/2013 - Net international migration in period 7/1/2013 to 7/1/2014 - Net international migration in period 7/1/2014 to 7/1/2015 - Net international migration in period 7/1/2015 to 7/1/2016 - Net international migration in period 7/1/2016 to 7/1/2017 - Net international migration in period 7/1/2017 to 7/1/2018 - Net international migration in period 7/1/2018 to 7/1/2019 - Net domestic migration in period 7/1/2010 to 7/1/2011 - Net domestic migration in period 7/1/2011 to 7/1/2012 - Net domestic migration in period 7/1/2012 to 7/1/2013 - Net domestic migration in period 7/1/2013 to 7/1/2014 - Net domestic migration in period 7/1/2014 to 7/1/2015 - Net domestic migration in period 7/1/2015 to 7/1/2016 - Net domestic migration in period 7/1/2016 to 7/1/2017 - Net domestic migration in period 7/1/2017 to 7/1/2018 - Net domestic migration in period 7/1/2018 to 7/1/2019 - Net migration in period 7/1/2010 to 7/1/2011 - Net migration in period 7/1/2011 to 7/1/2012 - Net migration in period 7/1/2012 to 7/1/2013 - Net migration in period 7/1/2013 to 7/1/2014 - Net migration in period 7/1/2014 to 7/1/2015 - Net migration in period 7/1/2015 to 7/1/2016 - Net migration in period 7/1/2016 to 7/1/2017 - Net migration in period 7/1/2017 to 7/1/2018 - Net migration in period 7/1/2018 to 7/1/2019 - Group Quarters Population estimate 7/1/2010 - Group Quarters Population estimate 7/1/2011 - Group Quarters Population estimate 7/1/2012 - Group Quarters Population estimate 7/1/2013 - Group Quarters Population estimate 7/1/2014 - Group Quarters Population estimate 7/1/2015 - Group Quarters Population estimate 7/1/2016 - Group Quarters Population estimate 7/1/2017 - Group Quarters Population estimate 7/1/2018 - Group Quarters Population estimate 7/1/2019 Places - base data items .. goto top Sources: Model-based Population Estimates & ACS 2018 5 year estimates 19,510 cities
- City Name
- State USPS - Place Code - County Code - Metro Code - Principal City Status - Type of City - Land Area, SqMi - Water Area SqMi - Internal point, latitude - Internal point, longitude - Population Census 2010 - Population Base 2010 - Population 7/1/2010 - Population 7/1/2011 - Population 7/1/2012 - Population 7/1/2013 - Population 7/1/2014 - Population 7/1/2015 - Population 7/1/2016 - Population 7/1/2017 - Population 7/1/2018 - Population 7/1/2019 - Pop Chg 2010-19 - %Pop Chg 2010-19 - Pop Chg 2018-19 - %Pop Chg 2018-19 ACS 2018 5 year estimates - ACS18POP - Total population - ACS18CVAP - Citizen voting age populaiton - ACS18HS - Percent High School Graduate (25 yrs+) - ACS18COLL - Percent College Graduate (25 yrs+) - ACS18MHI - Median Household Income - ACS18AHI - Mean Household Income - ACS18MFI - Median Family Income - ACS18AFI - Mean Family Income - ACS18PCI - Per capita income - ACS18HU - Housing units - ACS18HUO - Occupied housing Units (households) - ACS18HUV - Vacant housing units - ACS18HUOVR - Owner occupied vacancy rate - ACS18HURVR - Renter occupied vacany rate - ACS18HUOO - Owner occupied units - ACS18HURO - Renter occupied units - ACS18MHV - Median housing value - ACS18MRENT - Median rent - Area - Perimiter Block Groups - base data items .. goto top Sources: ACS 2018 5 Year
B01001_001E Total Population
B01001_002E Male B01001_026E Female B02001_002E White alone B02001_003E Black or African American alone B02001_004E American Indian and Alaska Native alone B02001_005E Asian alone B02001_006E Native Hawaiian and Other Pacific Islander alone B02001_007E Some other race alone B02001_008E Two or more races B03002_012E Hispanic (any race) B09020_001E Population 65 years and over B11002_001E Population in Households B11001_001E Total Households B11001_002E Family Households B15002_001E Population 25 years and over B15002_011E High school graduate (Male, age 25+) B15002_028E High school graduate (Female, age 25+) B25003_001E Total housing units B25003_002E Owner occupied units B25003_003E Renter occupied units B25002_003E Vacant units B19013_001E Median Household Income B19113_001E Median Family Income B25077_001E Median housing value B25064_001E Median gross rent Block Group Points .. goto top The Block Group Points shapefile is a variation of the block group area/polygon shapefile. The point shapefile has some application advantages over the area shapefile. &nbps; • it displays much faster. US1_BG.GIS GIS Project - Start-up View .. with national scope us1_bpts.shp added (red markers)  Zoom-in View; north Dallas County this view also shows the stores layer with store markers shown in the map view. the pointer is located at the "internal point" for BG 481130197002 this view shows point for the specific BG in context of the BG polygon. the BG GEOID is the same for the point or area -- 481130197002      Support Using these Resources Learn more about accessing and using demographic-economic data and related analytical tools. Join us in a Data Analytics Lab session. There is no fee for these one-hour Web sessions. Each informal session is focused on a specific topic. The open structure also provides for Q&A and discussion of application issues of interest to participants. ProximityOne User Group Join the ProximityOne User Group to keep up-to-date with new developments relating to geographic-demographic-economic decision-making information resources. Receive updates and access to tools and resources available only to members. Use this form to join the User Group. Additional Information 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. |
|
|
