This dataset was created to facilitate the conversion of Uniform Crime Reporting (UCR) Program state and county codes to Federal Information Processing Standards (FIPS) state and county codes. The four UCR agency-level data files archived at ICPSR in Uniform Crime Reporting Program Data: United States contain UCR state and county codes as geographic identifiers. Researchers who wish to use these data with other sources, such as Census data, may want to convert these UCR codes to FIPS codes in order to link the different data sources. This file was created to facilitate this linkage. It contains state abbreviations, UCR state and county codes, FIPS state and county codes, and county names for all counties present in the UCR data files since 1990. These same FIPS codes were used to create the UCR County-Level Detailed Arrest and Offense files from 1990-1996.

US Geographic Codes Dataset

This code is used to generate a combined data set of US ZIP, FIPS, and County data for most ZIP Codes in the U.S. (41,867 to be exact).

Code to generate the data set from the government files listed below can be found here.

The Data

The dataset is organized as follows:

• Zip Code: USPS ZIP code from here
• State Name: Full state name (E.g. Michigan)
• State Abrv: USPS abbreviated state name (E.g: MI)
• State Code: FIPS State Code from here
• County Name: County in which ZIP is located
• County Code: FIPS County Code
• FIPS Code: FIPS State Code + FIPS County Code from here
• ANSI Code: American National Standards Institute Code
• Centroid Lat: Latitude value of the county center
• Centroid Long: Longitude value of the county center

Sources

The data used to create this data set was taken from several recent government data sets.

These are:

• 2017 US Gazetteer FIPS Dataset
• 2017 US Census County Polygons Dataset
• 2015 Department of Labor GPCI Dataset
• General Census State Code Reference Document

Disclaimers

The final csv is in 'latin1' encoding to preserve the Spanish county names in Puerto Rico.

This data is from, and shall remain in the public domain, and the onus of responsibility lies with the user of this data.

The Geographic Names Information System (GNIS) was developed by the United States Geological Survey (USGS) to meet major national needs regarding geographic names and their standardization and dissemination. This dataset consists of standard report files written from the National Geographic Names Data Base, one of five data bases maintained in the GNIS. A standard format data file for each of the fifty States, the District of Columbia and the four Insular Territories of the United States is included, as well as a file that provides a Cross-Reference to USGS 7.5 x 7.5 minute quadrangle maps. The records in the data files are organized in an alphabetized listing of all of the names in a particular state or territory. The other variables available in the dataset include: Federal Information Processing Standard (FIPS) state/county codes, Geographic Coordinates-- latitude and longitude to degrees, minutes, and seconds followed by a single digit alpha directional character, and a GNIS Map Code that can be used with the Cross-Reference file to provide the name of the 7.5 x 7.5 minute quadrangle map that contains that geographic feature.

"Due to the size of this dataset, both Shapefile and Spreadsheet download options will not work as expected. The File Geodatabase is an alternative option for this data download"This is SCAG's 2019 Annual Land Use (ALU v. 2019.1) at the parcel-level, updated as of February 2021. This dataset has been modified to include additional attributes in order to feed SCAG's Housing Element Parcel Tool (HELPR), version 2.0. The dataset will be further reviewed and updated as additional information is released. Please refer to the tables below for data dictionary and SCAG’s land use classification.Field NameData TypeField DescriptionPID19Text2019 SCAG’s parcel unique IDAPN19Text2019 Assessor’s parcel numberCOUNTYTextCounty name (based on 2016 county boundary)COUNTY_IDDoubleCounty FIPS code (based on 2016 county boundary)CITYTextCity name (based on 2016 city boundary)CITY_IDDoubleCity FIPS code (based on 2016 city boundary)MULTIPARTShort IntegerMultipart feature (the number of multiple polygons; '1' = singlepart feature)STACKLong IntegerDuplicate geometry (the number of duplicate polygons; '0' = no duplicate polygons)ACRESDoubleParcel area (in acreage)GEOID20Text2020 Census Block Group GEOIDSLOPEShort IntegerSlope information1APN_DUPLong IntegerDuplicate APN (the number of multiple tax roll property records; '0' = no duplicate APN)IL_RATIODoubleRatio of improvement assessed value to land assessed valueLU19Text2019 existing land useLU19_SRCTextSource of 2019 existing land use2SCAGUID16Text2016 SCAG’s parcel unique IDAPNText2016 Assessor’s parcel numberCITY_GP_COText2016 Jurisdiction’s general plan land use designationSCAG_GP_COText2016 SCAG general plan land use codeSP_INDEXShort IntegerSpecific plan index ('0' = outside specific plan area; '1' = inside specific plan area)CITY_SP_COText2016 Jurisdiction’s specific plan land use designationSCAG_SP_COText2016 SCAG specific plan land use codeCITY_ZN_COText2016 Jurisdiction’s zoning codeSCAG_ZN_COText2016 SCAG zoning codeLU16Text2016 existing land useYEARLong IntegerDataset yearPUB_OWNShort IntegerPublic-owned land index ('1' = owned by public agency)PUB_NAMETextName of public agencyPUB_TYPETextType of public agency3BF_SQFTDoubleBuilding footprint area (in square feet)4BSF_NAMETextName of brownfield/superfund site5BSF_TYPETextType of brownfield/superfund site5FIREShort IntegerParcel intersects CalFire Very High Hazard Local Responsibility Areas or State Responsibility Areas (November 2020 version) (CalFIRE)SEARISE36Short IntegerParcel intersects with USGS Coastal Storm Modeling System (CoSMos)1 Meter Sea Level Rise inundation areas for Southern California (v3.0, Phase 2; 2018)SEARISE72Short IntegerParcel intersects with USGS Coastal Storm Modeling System (CoSMos)2 Meter Sea Level Rise inundation areas for Southern California (v3.0, Phase 2; 2018)FLOODShort IntegerParcel intersects with a FEMA 100 Year Flood Plain data from the Digital Flood Insurance Rate Map (DFIRM), obtained from Federal Emergency Management Agency (FEMA) in August 10, 2017EQUAKEShort IntegerParcel intersects with an Alquist-Priolo Earthquake Fault Zone (California Geological Survey; 2018)LIQUAFAShort IntegerParcel intersects with a Liquefaction Susceptibility Zone (California Geological Survey; 2016)LANDSLIDEShort IntegerParcel intersects with a Landslide Hazard Zone (California Geological Survey; 2016)CPADShort IntegerParcel intersects with a protected area from the California Protected Areas Database(CPAD) – www.calands.org (accessed April 2021)RIPARIANShort IntegerParcel centroid falls within Active River Areas(2010)or parcel intersects with a Wetland Area in the National Wetland Inventory(Version 2)WILDLIFEShort IntegerParcel intersects with wildlife habitat (US Fish & Wildlife ServiceCritical Habitat, Southern California Missing Linkages, Natural Lands & Habitat Corridors from Connect SoCal, CEHC Essential Connectivity Areas,Critical Coastal Habitats)CNDDBShort IntegerThe California Natural Diversity Database (CNDDB)includes the status and locations of rare plants and animals in California. Parcels that overlap locations of rare plants and animals in California from the California Natural Diversity Database (CNDDB)have a greater likelihood of encountering special status plants and animals on the property, potentially leading to further legal requirements to allow development (California Department of Fish and Wildlife). Data accessed in October 2020.HCPRAShort IntegerParcel intersects Natural Community & Habitat Conservation Plans Reserve Designs from the Western Riverside MHSCP, Coachella Valley MHSCP, and the Orange County Central Coastal NCCP/HCP, as accessed in October 2020WETLANDShort IntegerParcel intersects a wetland or deepwater habitat as defined by the US Fish & Wildlife Service National Wetlands Inventory, Version 2.UAZShort IntegerParcel centroid lies within a Caltrans Adjusted Urbanized AreasUNBUILT_SFDoubleDifference between parcel area and building footprint area expressed in square feet.6GRCRY_1MIShort IntegerThe number of grocery stores within a 1-mile drive7HEALTH_1MIShort IntegerThe number of healthcare facilities within a 1-mile drive7OPENSP_1MIShort IntegerQuantity of open space (roughly corresponding to city blocks’ worth) within a 1-mile drive7TCAC_2021TextThe opportunity level based on the 2021 CA HCD/TCAC opportunity scores.HQTA45Short IntegerField takes a value of 1 if parcel centroid lies within a 2045 High-Quality Transit Area (HQTA)JOB_CTRShort IntegerField takes a value of 1 if parcel centroid lies within a job centerNMAShort IntegerField takes a value of 1 if parcel centroid lies within a neighborhood mobility area.ABS_CONSTRShort IntegerField takes a value of 1 if parcel centroid lies within an absolute constraint area. See the Sustainable Communities Strategy Technical Reportfor details.VAR_CONSTRShort IntegerField takes a value of 1 if parcel centroid lies within a variable constraint area. See the Sustainable Communities Strategy Technical Reportfor details.EJAShort IntegerField takes a value of 1 if parcel centroid lies within an Environmental Justice Area. See the Environmental Justice Technical Reportfor details.SB535Short IntegerField takes a value of 1 if parcel centroid lies within an SB535 Disadvantaged Community area. See the Environmental Justice Technical Reportfor details.COCShort IntegerField takes a value of 1 if parcel centroid lies within a Community of Concern See the Environmental Justice Technical Reportfor details.STATEShort IntegerThis field is a rudimentary estimate of which parcels have adequate physical space to accommodate a typical detached Accessory Dwelling Unit (ADU)8.SBShort IntegerIndex of ADU eligibility according to the setback reduction policy scenario (from 4 to 2 feet) (1 = ADU eligible parcel, Null = Not ADU eligible parcel)SMShort IntegerIndex of ADU eligibility according to the small ADU policy scenario (from 800 to 600 square feet ADU) (1 = ADU eligible parcel, Null = Not ADU eligible parcel)PKShort IntegerIndex of ADU eligibility according to parking space exemption (200 square feet) policy scenario (1 = ADU eligible parcel, Null = Not ADU eligible parcel)SB_SMShort IntegerIndex of ADU eligibility according to both the setback reduction and small ADU policy scenarios (1 = ADU eligible parcel, Null = Not ADU eligible parcel)SB_PKShort IntegerIndex of ADU eligibility according to both the setback reduction and parking space exemption scenarios (1 = ADU eligible parcel, Null = Not ADU eligible parcel)SM_PKShort IntegerIndex of ADU eligibility according to both the small ADU policy and parking space exemption scenarios (1 = ADU eligible parcel, Null = Not ADU eligible parcel)SB_SM_PKShort IntegerIndex of ADU eligibility according to the setback reduction, small ADU, and parking space exemption scenarios (1 = ADU eligible parcel, Null = Not ADU eligible parcel)1. Slope: '0' - 0~4 percent; '5' - 5~9 percent; '10' - 10~14 percent; '15' = 15~19 percent; '20' - 20~24 percent; '25' = 25 percent or greater.2. Source of 2019 existing land use: SCAG_REF- SCAG's regional geospatial datasets;ASSESSOR- Assessor's 2019 tax roll records; CPAD- California Protected Areas Database (version 2020a; accessed in September 2020); CSCD- California School Campus Database (version 2018; accessed in September 2020); FMMP- Farmland Mapping and Monitoring Program's Important Farmland GIS data (accessed in September 2020); MIRTA- U.S. Department of Defense's Military Installations, Ranges, and Training Areas GIS data (accessed in September 2020)3. Type of public agency includes federal, state, county, city, special district, school district, college/university, military.4. Based on 2019 building footprint data obtained from BuildingFootprintUSA (except that 2014 building footprint data was used for Imperial County). Please note that 2019 building footprint data does not cover the entire SCAG region (overlapped with 83% of parcels in the SCAG Region).5. Includes brownfield/superfund site whose address information are matched by SCAG rooftop address locator. Brownfield data was obtained from EPA's Assessment, Cleanup and Redevelopment Exchange System (ACRES) database, Cleanups in my community (CIMC), DTSC brownfield Memorandum of Agreement (MOA). Superfund site data was obtained from EPA's Superfund Enterprise Management System (SEMS) database.6. Parcels with a zero value for building footprint area are marked as NULL to indicate this field is not reliable.7. These values are intended as a rudimentary indicator of accessibility developed by SCAG using 2016 InfoUSA business establishment data and 2017 California Protected Areas data. See documentation for details.8. A detailed study conducted by Cal Poly Pomona (CPP) and available hereconducted an extensive review of state and local requirements and development trends for ADUs in the SCAG region and developed a baseline set of assumptions for estimating how many of a jurisdiction’s parcels

This table contains information about the Transit Link Dial-a-Ride Service Areas in the Twin Cities Metro Area.
Transit Link is the Metropolitan Council sponsored small bus dial-a-ride service for the general public, where regular route transit service is not available. (ADA service is provided by Metro Mobility, see table ADAService.dbf.)

Transit Link service was implemented in 2010, replacing a system of community based Dial-a-Ride programs.

This table can be joined to the "Counties and Cities & Townships, Twin Cities Metropolitan Area" spatial dataset using the COCTU_CODE field (concatenation of 3-digit FIPS county code and 5-digit FIPS place code). This will allow users to create maps and conduct spatial analyses with the data in this table.

This layer was developed by the Research & Analytics Division of the Atlanta Regional Commission from ARC's Regional Plan Update to show employment forecasts by census tract for the Atlanta region.Attributes:GEOID10 = The entire Federal Information Processing Series (FIPS) code for this geography. FIPS codes were formerly known as Federal Information Processing Standards codes, until the National Institute of Standards and Technology (NIST) announced its decision in 2005 to remove geographic entity codes from its oversight. The Census Bureau continues to maintain and issue codes for geographic entities covered under FIPS oversight, albeit with a revised meaning for the FIPS acronym. Geographic entities covered under FIPS include states, counties, congressional districts, core based statistical areas, places, county subdivisions, subminor civil divisions, consolidated cities, and all types of American Indian, Alaska Native, and Native Hawaiian areas. FIPS codes are assigned alphabetically according to the name of the geographic entity and may change to maintain alphabetic sort when new entities are created or names change. FIPS codes for specific geographic entity types are usually unique within the next highest level of geographic entity with which a nesting relationship exists. For example, FIPS state, congressional district, and core based statistical area codes are unique within nation; FIPS county, place, county subdivision, and subminor civil division codes are unique within state. The codes for American Indian, Alaska Native, and Native Hawaiian areas also are unique within state; those areas in multiple states will have different codes for each state.NAME10 = Census tract numberPLNG_REGIO = Planning regionPercent_BA_or_Higher = Percentage of population that has a bachelor's degree or higherMedian_household_income = Median household incomeSquare_Miles = Total area in square milesTotal Jobs, 2015 = Total number of jobs forecasted for 2015Total Jobs, 2020 = Total number of jobs forecasted for 2020Total Jobs, 2030 = Total number of jobs forecasted for 2030Total Jobs, 2035 = Total number of jobs forecasted for 2035Total Jobs, 2040 = Total number of jobs forecasted for 2040Change in Jobs, 2015-2040 = Forecasted change in the total number of jobs between 2015 and 2040Change in Jobs per Square Mile, 2015-2040 = Forecasted change in the number of jobs per square mile from 2015 to 2040Population Change per square mile 2000-2010 = The actual population change per square mile from 2000 to 2010Change in Jobs per Square Mile 2015-2040 = Forecasted change in the number of jobs per square mile from 2015 to 2040Shape.STArea() = Total area in square feetSource: Atlanta Regional CommissionDate: 2015For additional information, please visit the Atlanta Regional Commission at www.atlantaregional.com

WARNING: This is a pre-release dataset and its fields names and data structures are subject to change. It should be considered pre-release until the end of 2024. Expected changes:

• Metadata is missing or incomplete for some layers at this time and will be continuously improved.
  
• We expect to update this layer roughly in line with CDTFA at some point, but will increase the update cadence over time as we are able to automate the final pieces of the process.

Purpose

County and incorporated place (city) boundaries along with third party identifiers used to join in external data. Boundaries are from the authoritative source the California Department of Tax and Fee Administration (CDTFA), altered to show the counties as one polygon. This layer displays the city polygons on top of the County polygons so the area isn"t interrupted. The GEOID attribute information is added from the US Census. GEOID is based on merged State and County FIPS codes for the Counties. Abbreviations for Counties and Cities were added from Caltrans Division of Local Assistance (DLA) data. Place Type was populated with information extracted from the Census. Names and IDs from the US Board on Geographic Names (BGN), the authoritative source of place names as published in the Geographic Name Information System (GNIS), are attached as well. Finally, coastal buffers are removed, leaving the land-based portions of jurisdictions. This feature layer is for public use.

Related Layers

This dataset is part of a grouping of many datasets:

1. Cities: Only the city boundaries and attributes, without any unincorporated areas
   • With Coastal Buffers
   • Without Coastal Buffers
2. Counties: Full county boundaries and attributes, including all cities within as a single polygon
   • With Coastal Buffers
   • Without Coastal Buffers
3. Cities and Full Counties: A merge of the other two layers, so polygons overlap within city boundaries. Some customers require this behavior, so we provide it as a separate service.
   • With Coastal Buffers
   • Without Coastal Buffers (this dataset)
4. Place Abbreviations
5. Unincorporated Areas (Coming Soon)
6. Census Designated Places (Coming Soon)
   
7. Cartographic Coastline
   • Polygon
   • Line source (Coming Soon)

Point of Contact

California Department of Technology, Office of Digital Services, odsdataservices@state.ca.gov

Field and Abbreviation Definitions

• COPRI: county number followed by the 3-digit city primary number used in the Board of Equalization"s 6-digit tax rate area numbering system
• Place Name: CDTFA incorporated (city) or county name
• County: CDTFA county name. For counties, this will be the name of the polygon itself. For cities, it is the name of the county the city polygon is within.
• Legal Place Name: Board on Geographic Names authorized nomenclature for area names published in the Geographic Name Information System
• GNIS_ID: The numeric identifier from the Board on Geographic Names that can be used to join these boundaries to other datasets utilizing this identifier.
• GEOID: numeric geographic identifiers from the US Census Bureau Place Type: Board on Geographic Names authorized nomenclature for boundary type published in the Geographic Name Information System
• Place Abbr: CalTrans Division of Local Assistance abbreviations of incorporated area names
• CNTY Abbr: CalTrans Division of Local Assistance abbreviations of county names
• Area_SqMi: The area of the administrative unit (city or county) in square miles, calculated in EPSG 3310 California Teale Albers.
• COASTAL: Indicates if the polygon is a coastal buffer. Null for land polygons. Additional values include "ocean" and "bay".
• GlobalID: While all of the layers we provide in this dataset include a GlobalID field with unique values, we do not recommend you make any use of it. The GlobalID field exists to support offline sync, but is not persistent, so data keyed to it will be orphaned at our next update. Use one of the other persistent identifiers, such as GNIS_ID or GEOID instead.

Accuracy

CDTFA"s source data notes the following about accuracy:

City boundary changes and county boundary line adjustments filed with the Board of Equalization per Government Code 54900. This GIS layer contains the boundaries of the unincorporated county and incorporated cities within the state of California. The initial dataset was created in March of 2015 and was based on the State Board of Equalization tax rate area boundaries. As of April 1, 2024, the maintenance of this dataset is provided by the California Department of Tax and Fee Administration for the purpose of determining sales and use tax rates. The boundaries are continuously being revised to align with aerial imagery when areas of conflict are discovered between the original boundary provided by the California State Board of Equalization and the boundary made publicly available by local, state, and federal government. Some differences may occur between actual recorded boundaries and the boundaries used for sales and use tax purposes. The boundaries in this map are representations of taxing jurisdictions for the purpose of determining sales and use tax rates and should not be used to determine precise city or county boundary line locations. COUNTY = county name; CITY = city name or unincorporated territory; COPRI =

This is a lookup table containing various data related to cities, townships, unorganized territories (CTUs) and any divisions created by county boundaries splitting them. These are termed Minor Civil Division (MCDs) by the Census Bureau. The table encompases the Twin Cities 7-county metropolitan area. It is intended to be a Council wide master lookup table for these entites. It contains official federal and state unique identifiers for CTUs and MCDs as well as identifiers created and used by other organizations. The table also contains historical MCDs dating back to the 1990s and a few other non-MCD records that are of importance to Met. Council use of this table.

The County CTU Lookup Table relates to the Counties and Cities & Townships, Twin Cities Metropolitan Area dataset here: https://gisdata.mn.gov/dataset/us-mn-state-metc-bdry-metro-counties-and-ctus

NOTES:

- On 5/28/2014 a new field was added to reflect the new community designations defined in the Council's Thrive MSP 2040 regional plan - COMDES2040

- On 3/17/2011 it was discovered that the CTU ID used for the City of Lake St. Croix Beach was incorrect. It was changed from 2394379 to 2395599 to match GNIS.

- On 3/17/2011 it was discovered that the CTU ID used for the City of Lilydale was incorrect. It was changed from 2394457 to 2395708 to match GNIS.

- On 11/9/2010 it was discovered that the CTU ID used for the City of Crystal was incorrect. It was changed from 2393541 to 2393683 to match GNIS.

- Effective April 2008, a change was made in GNIS to match the FIPS place codes to the "civil" feature for each city instead of the "populated place" feature. Both cities and townships are now "civil" features within GNIS. This means that the official GNIS unique ID for every city in Minnesota has changed.

- As of January 1, 2006, the five digit FIPS 55-3 Place codes that were used as unique identifiers in this dataset (CTU_CODE and COCTU_CODE fields) were officially retired by the Federal governement. They are replaced by a set of integer codes from the Geographic Names Information System (GNIS_CODE field). Both codes will be kept in this database, but the GNIS_CODE is considered the official unique identifier from this point forward. The GNIS codes are also slated to become official ANSI codes for these geographic features. While GNIS treats these codes as 6 to 8 digit integer data types, the Census Bureau formats them as 8 digit text fields, right justified with leading zeros included.

- The Census Bureau will continue to create FIPS 55 Place codes for new cities and townships through the 2010 Census. After that, no new FIPS 55 codes will be created. Note that for townships that wholly incorporate into cities, the same FIPS 55 code will be used for the new city. (GNIS creates a new ID for the new city.)

- Cities and townships have also been referred to as ''MCDs'' (a Census term), however this term technically refers to the part of each city or township within a single county. Thus, a few cities in the metro area that are split by county boundaries are actually comprised of two different MCDs. This was part of the impetus for a proposed MN state data standard that uses the ''CTU'' terminology for clarity.

- A variety of civil divisions of the land exist within the United States. In Minnesota, only three types exist - cities, townships and unorganized territories. All three of these exist within the Twin Cities seven county area. The only unorganized territory is Fort Snelling (a large portion of which is occupied by the MSP International Airport).

- Some cities are split between two counties. Only those parts of cities within the 7-county area are included.

- Prior to the 2000 census, the FIPS Place code for the City of Greenwood in Hennepin County was changed from 25928 to 25918. This dataset reflects that change.

This data set contains Illinois county boundaries in line and polygon formats. The polygon attribute data include county name and number (FIPS) designations. The line attributes indicate which county lines also form the state boundary. The data were extracted from, and are redundant with, ISGS feature dataset IL_Public_Land_Survey_System. The data set is maintained as a separate entity for ease of query and display. The nominal scale is 1:62,500. As of 2003, the data are typically distributed in geographic coordinates (longitude and latitude), decimal degrees, and the North American Datum (NAD) of 1983, and this is the default spatial reference of the ArcSDE feature dataset in which the data are stored. The data were originally developed, however, in a custom Lambert Conformal Conic projection and were distributed in that coordinate system for several years. The data were digitized in the late 1960s and in 1984-85 from 7.5- and 15-minute USGS topographic quadrangles. Errors in the location of a given feature are dependent on the accuracy of the original maps and on the accuracy of digitizing. Estimates are that features have an average locational error of at least plus/minus 100 feet.

Polygons depict the boundaries of Washington State's incorporated municipalities, as recorded by the Washington State Office of Financial Management. Attributes include city names as provided by the Washington State Office of Financial Management, and Federal Information Processing Standard codes(FIPS) as provided by the National Institute of Standards and Technology. The Washington State Office of Financial Management provided FIPS codes for cities incorporated after the National Institute of Standards and Technology's FIPS code publication date. GNIS (Geographic Name Information System) codes provided by the Washington State Department of Revenue have been included for this quarter. The calendar date shown by Time_Period_Of_Content is the date of annexation approval and certification by the Washington State Office of Financial Management. Please direct questions about this dataset to: TransportationGISDataSteward@wsdot.wa.gov.

US Northeast Census Tracts contains the US Census tract geometries used as the unit of analysis for network metrics. The file "northeast_tracts.shp" includes a merged dataset with the borders of all census tracts in Connecticut, Maine, Massachusetts, New Hampshire, New York, Rhode Island, and Vermont. All other files in this repository are the original state-by-state sources used to create the final merged dataset. Census Tracts The 2020 census tract file is based on the 2020 Census. The following fields are included: USPS: United States Postal Service state abbreviation. GEOID: Geographic identifier — fully concatenated geographic code (State FIPS, County FIPS, Census Tract number). GEOIDFQ: Fully qualified geographic identifier — used to join with data.census.gov data tables. ALAND: Land area (square meters) — created for statistical purposes only. AWATER: Water area (square meters) — created for statistical purposes only. ALAND_SQMI: Land area (square miles) — created for statistical purposes only. AWATER_SQMI: Water area (square miles) — created for statistical purposes only. INTPTLAT: Latitude (decimal degrees). The first character is blank or “–” denoting North or South latitude respectively. INTPTLONG: Longitude (decimal degrees). The first character is blank or “–” denoting East or West longitude respectively. The .shp file in this repository includes its required companion files for correct GIS operation: .shx (spatial index), .dbf (attribute table), .prj (projection information), and .cpg (character encoding).

This layer was developed by the Research & Analytics Division of the Atlanta Regional Commission to represent the United States Census Bureau's 2000 Decennial Census data at the block geography.Attributes:FIPSSTCO = The Federal Information Processing Series (FIPS) state and county codes. FIPS codes were formerly known as Federal Information Processing Standards codes, until the National Institute of Standards and Technology (NIST) announced its decision in 2005 to remove geographic entity codes from its oversight. The Census Bureau continues to maintain and issue codes for geographic entities covered under FIPS oversight, albeit with a revised meaning for the FIPS acronym. Geographic entities covered under FIPS include states, counties, congressional districts, core based statistical areas, places, county subdivisions, subminor civil divisions, consolidated cities, and all types of American Indian, Alaska Native, and Native Hawaiian areas. FIPS codes are assigned alphabetically according to the name of the geographic entity and may change to maintain alphabetic sort when new entities are created or names change. FIPS codes for specific geographic entity types are usually unique within the next highest level of geographic entity with which a nesting relationship exists. For example, FIPS state, congressional district, and core based statistical area codes are unique within nation; FIPS county, place, county subdivision, and subminor civil division codes are unique within state. The codes for American Indian, Alaska Native, and Native Hawaiian areas also are unique within state; those areas in multiple states will have different codes for each state.TRACT2000 = Census Tract Codes and Numbers. Census tracts are identified by an up to four-digit integer number and may have an optional two-digit suffix; for example 1457.02 or 23. The census tract codes consist of six digits with an implied decimal between the fourth and fifth digit corresponding to the basic census tract number but with leading zeroes and trailing zeroes for census tracts without a suffix. The tract number examples above would have codes of 145702 and 002300, respectively.BLOCK2000= Census Block Numbers are numbered uniquely with a four-digit census block number from 0000 to 9999 within census tract, which nest within state and county. The first digit of the census block number identifies the block group. Block numbers beginning with a zero (in Block Group 0) are only associated with water-only areas.STFID = A concatenation of FIPSSTCO, TRACT2000, and BLOCK2000, which creates the entire FIPS code for this geography.WFD = Workforce Development Area (WFD) is a seven-county area created by agreement of county chief-elected officials, administered by the Atlanta Regional Commission and funded for training and employment activities under the federal Workforce Investment Act (WIA). For more information on ARC’s Workforce Development programs and services please consult www.atlantaregional.com/workforce/workforce.html.RDC_AAA = ARC Area Agency on Aging is a 10-county area funded by the Department of Human Resources and designated by the Older Americans Act to plan for the needs of the rapidly expanding group of older citizens in the Atlanta region. It is part of a statewide network of 12 AAAs and a national network of more than 670 AAAs. For more information on aging services please consult www.agewiseconnection.com.MNGWPD = The Metro North Georgia Water Planning District provides water resource plans, policies and coordination for metropolitan Atlanta. The District has developed regional plans for stormwater management, wastewater treatment and water supply and water conservation. The 15-county Water Planning District includes the ten counties in the ARC plus five additional counties (Bartow, Coweta, Forsyth, Hall, & Paulding). For more information please consult www.northgeorgiawater.org. MPO = The Metropolitan Planning Organization (MPO) is a 19-county area federally-designated for regional transportation planning to meet air quality standards and for programming projects to implement the adopted Regional Transportation Plan (RTP). The MPO planning area boundary includes the 10-county state-designated Regional Commission and nine additional counties (all of Coweta, Forsyth, & Paulding and parts of Barrow, Dawson, Newton, Pike, Spalding and Walton). This boundary takes into consideration both the current urbanized area as well as areas forecast to become urbanized in the next 20 years.MSA = the 29-County “Atlanta-Sandy Springs-Roswell, GA” Metropolitan Statistical Area (MSA) and the 39-county “Atlanta--Athens-Clarke County--Sandy Springs, GA” Combined Statistical Area (CSA), which includes the 29 counties of the Atlanta MSA along with the Athens-Clarke County and Gainesville MSAs and the micropolitan statistical areas of Calhoun, Cedartown, Jefferson, LaGrange and Thomaston, GA. The U.S. Office of Management and Budget (OMB) defines CSAs, MSAs and the smaller micropolitan statistical areas nationwide according to published standards applied to U.S. Census Bureau data. These various statistical areas describe substantial core areas of population together with adjacent communities having a high degree of economic and social integration, often illustrated in high rates of commuting from the adjacent areas to job locations in the core. For more information, please consult http://www.census.gov/population/metro/data/metrodef.htmlF1HR_NA = The Federal 1-Hour Air Quality Non-Attainment Area is a fine particulate matter standard (PM2.5). The non-attainment area under this standard includes the 15-county eight-hour ozone nonattainment area plus Barrow, Carroll, Hall, Spalding, Walton, and small parts of Heard and Putnam counties.F8HR_NA: The Federal 8-Hour Air Quality Non-Attainment Area for the 2008 eight-hour ozone standard is 15 counties.ACRES = The number of acres contained within the Block.SQ_MILES = The number of square miles contained within the Block.Source: United States Census Bureau, Atlanta Regional CommissionDate: 2000For additional information, please visit the Atlanta Regional Commission at www.atlantaregional.com

This is SCAG's 2019 Annual Land Use (ALU v. 2019.1) at the parcel-level, updated as of February 2021. This dataset has been modified to include additional attributes in order to feed SCAG's Housing Element Parcel Tool (HELPR), version 2.0. The dataset will be further reviewed and updated as additional information is released. Please refer to the tables below for data dictionary and SCAG’s land use classification. Field Name Data TypeField DescriptionPID19Text2019 SCAG’s parcel unique IDAPN19Text2019 Assessor’s parcel numberCOUNTYTextCounty name (based on 2016 county boundary)COUNTY_IDDoubleCounty FIPS code (based on 2016 county boundary)CITYTextCity name (based on 2016 city boundary)CITY_IDDoubleCity FIPS code (based on 2016 city boundary)MULTIPARTShort IntegerMultipart feature (the number of multiple polygons; '1' = singlepart feature)STACKLong IntegerDuplicate geometry (the number of duplicate polygons; '0' = no duplicate polygons)ACRESDoubleParcel area (in acreage)GEOID20Text2020 Census Block Group GEOIDSLOPEShort IntegerSlope information1APN_DUPLong IntegerDuplicate APN (the number of multiple tax roll property records; '0' = no duplicate APN)IL_RATIODoubleRatio of improvement assessed value to land assessed valueLU19Text2019 existing land useLU19_SRCTextSource of 2019 existing land use2SCAGUID16Text2016 SCAG’s parcel unique IDAPNText2016 Assessor’s parcel numberCITY_GP_COText2016 Jurisdiction’s general plan land use designationSCAG_GP_COText2016 SCAG general plan land use codeSP_INDEXShort IntegerSpecific plan index ('0' = outside specific plan area; '1' = inside specific plan area)CITY_SP_COText2016 Jurisdiction’s specific plan land use designationSCAG_SP_COText2016 SCAG specific plan land use codeCITY_ZN_COText2016 Jurisdiction’s zoning codeSCAG_ZN_COText2016 SCAG zoning codeLU16Text2016 existing land useYEARLong IntegerDataset yearPUB_OWNShort IntegerPublic-owned land index ('1' = owned by public agency)PUB_NAMETextName of public agencyPUB_TYPETextType of public agency3BF_SQFTDoubleBuilding footprint area (in square feet)4BSF_NAMETextName of brownfield/superfund site5BSF_TYPETextType of brownfield/superfund site5FIREShort IntegerParcel intersects CalFire Very High Hazard Local Responsibility Areas or State Responsibility Areas (November 2020 version) (CalFIRE)SEARISE36Short IntegerParcel intersects with USGS Coastal Storm Modeling System (CoSMos)1 Meter Sea Level Rise inundation areas for Southern California (v3.0, Phase 2; 2018)SEARISE72Short IntegerParcel intersects with USGS Coastal Storm Modeling System (CoSMos)2 Meter Sea Level Rise inundation areas for Southern California (v3.0, Phase 2; 2018)FLOODShort IntegerParcel intersects with a FEMA 100 Year Flood Plain data from the Digital Flood Insurance Rate Map (DFIRM), obtained from Federal Emergency Management Agency (FEMA) in August 10, 2017EQUAKEShort IntegerParcel intersects with an Alquist-Priolo Earthquake Fault Zone (California Geological Survey; 2018) LIQUAFAShort IntegerParcel intersects with a Liquefaction Susceptibility Zone (California Geological Survey; 2016)LANDSLIDEShort IntegerParcel intersects with a Landslide Hazard Zone (California Geological Survey; 2016)CPADShort IntegerParcel intersects with a protected area from the California Protected Areas Database(CPAD) – www.calands.org (accessed April 2021)RIPARIANShort IntegerParcel centroid falls within Active River Areas(2010)or parcel intersects with a Wetland Area in the National Wetland Inventory(Version 2)WILDLIFEShort IntegerParcel intersects with wildlife habitat (US Fish & Wildlife ServiceCritical Habitat, Southern California Missing Linkages, Natural Lands & Habitat Corridors from Connect SoCal, CEHC Essential Connectivity Areas,Critical Coastal Habitats)CNDDBShort IntegerThe California Natural Diversity Database (CNDDB)includes the status and locations of rare plants and animals in California. Parcels that overlap locations of rare plants and animals in California from the California Natural Diversity Database (CNDDB)have a greater likelihood of encountering special status plants and animals on the property, potentially leading to further legal requirements to allow development (California Department of Fish and Wildlife). Data accessed in October 2020. HCPRAShort IntegerParcel intersects Natural Community & Habitat Conservation Plans Reserve Designs from the Western Riverside MHSCP, Coachella Valley MHSCP, and the Orange County Central Coastal NCCP/HCP, as accessed in October 2020WETLANDShort IntegerParcel intersects a wetland or deepwater habitat as defined by the US Fish & Wildlife Service National Wetlands Inventory, Version 2. UAZShort IntegerParcel centroid lies within a Caltrans Adjusted Urbanized AreasUNBUILT_SFDoubleDifference between parcel area and building footprint area expressed in square feet.6GRCRY_1MIShort IntegerThe number of grocery stores within a 1-mile drive7HEALTH_1MIShort IntegerThe number of healthcare facilities within a 1-mile drive7OPENSP_1MIShort IntegerQuantity of open space (roughly corresponding to city blocks’ worth) within a 1-mile drive7TCAC_2021TextThe opportunity level based on the 2021 CA HCD/TCAC opportunity scores.HQTA45Short IntegerField takes a value of 1 if parcel centroid lies within a 2045 High-Quality Transit Area (HQTA)JOB_CTRShort IntegerField takes a value of 1 if parcel centroid lies within a job centerNMAShort IntegerField takes a value of 1 if parcel centroid lies within a neighborhood mobility area. ABS_CONSTRShort IntegerField takes a value of 1 if parcel centroid lies within an absolute constraint area. See the Sustainable Communities Strategy Technical Reportfor details.VAR_CONSTRShort IntegerField takes a value of 1 if parcel centroid lies within a variable constraint area. See the Sustainable Communities Strategy Technical Reportfor details.EJAShort IntegerField takes a value of 1 if parcel centroid lies within an Environmental Justice Area. See the Environmental Justice Technical Reportfor details.SB535Short IntegerField takes a value of 1 if parcel centroid lies within an SB535 Disadvantaged Community area. See the Environmental Justice Technical Reportfor details.COCShort IntegerField takes a value of 1 if parcel centroid lies within a Community of Concern See the Environmental Justice Technical Reportfor details.STATEShort IntegerThis field is a rudimentary estimate of which parcels have adequate physical space to accommodate a typical detached Accessory Dwelling Unit (ADU)8. SBShort IntegerIndex of ADU eligibility according to the setback reduction policy scenario (from 4 to 2 feet) (1 = ADU eligible parcel, Null = Not ADU eligible parcel)SMShort IntegerIndex of ADU eligibility according to the small ADU policy scenario (from 800 to 600 square feet ADU) (1 = ADU eligible parcel, Null = Not ADU eligible parcel)PKShort IntegerIndex of ADU eligibility according to parking space exemption (200 square feet) policy scenario (1 = ADU eligible parcel, Null = Not ADU eligible parcel)SB_SMShort IntegerIndex of ADU eligibility according to both the setback reduction and small ADU policy scenarios (1 = ADU eligible parcel, Null = Not ADU eligible parcel)SB_PKShort IntegerIndex of ADU eligibility according to both the setback reduction and parking space exemption scenarios (1 = ADU eligible parcel, Null = Not ADU eligible parcel)SM_PKShort IntegerIndex of ADU eligibility according to both the small ADU policy and parking space exemption scenarios (1 = ADU eligible parcel, Null = Not ADU eligible parcel)SB_SM_PKShort IntegerIndex of ADU eligibility according to the setback reduction, small ADU, and parking space exemption scenarios (1 = ADU eligible parcel, Null = Not ADU eligible parcel)1. Slope: '0' - 0~4 percent; '5' - 5~9 percent; '10' - 10~14 percent; '15' = 15~19 percent; '20' - 20~24 percent; '25' = 25 percent or greater.2. Source of 2019 existing land use: SCAG_REF- SCAG's regional geospatial datasets;ASSESSOR- Assessor's 2019 tax roll records; CPAD- California Protected Areas Database (version 2020a; accessed in September 2020); CSCD- California School Campus Database (version 2018; accessed in September 2020); FMMP- Farmland Mapping and Monitoring Program's Important Farmland GIS data (accessed in September 2020); MIRTA- U.S. Department of Defense's Military Installations, Ranges, and Training Areas GIS data (accessed in September 2020)3. Type of public agency includes federal, state, county, city, special district, school district, college/university, military.4. Based on 2019 building footprint data obtained from BuildingFootprintUSA (except that 2014 building footprint data was used for Imperial County). Please note that 2019 building footprint data does not cover the entire SCAG region (overlapped with 83% of parcels in the SCAG Region).5. Includes brownfield/superfund site whose address information are matched by SCAG rooftop address locator. Brownfield data was obtained from EPA's Assessment, Cleanup and Redevelopment Exchange System (ACRES) database, Cleanups in my community (CIMC), DTSC brownfield Memorandum of Agreement (MOA). Superfund site data was obtained from EPA's Superfund Enterprise Management System (SEMS) database.6. Parcels with a zero value for building footprint area are marked as NULL to indicate this field is not reliable.7. These values are intended as a rudimentary indicator of accessibility developed by SCAG using 2016 InfoUSA business establishment data and 2017 California Protected Areas data. See documentation for details.8. A detailed study conducted by Cal Poly Pomona (CPP) and available hereconducted an extensive review of state and local requirements and development trends for ADUs in the SCAG region and developed a baseline set of assumptions for estimating how many of a jurisdiction’s parcels could accommodate a detached ADU. Please note that these estimates (1) do not include attached or other types of ADUs such as garage conversions or Junior ADUs, and (2)

Spatial Mapping of HITECH Grants

Visualizing Health and Community Grant Locations in the U.S

By US Open Data Portal, data.gov [source]

About this dataset

This dataset provides crucial geographic data related to two of the U.S. Health Information Technology for Economic and Clinical Health (HITECH) Act programs: the Health IT Regional Extension Centers (REC) Program and the Beacon Communities Program. As part of the American Recovery and Reinvestment Act (ARRA), these grants were made available to provide citizens with access to health IT infrastructure investments throughout diverse communities across the United States. This crosswalk is an essential resource for anyone looking to link regional, state, county and zip code level program financials with performance metrics for visualization or comparison. With detailed information about region counties, codes, states, FIPS codes and ZIP codes associated with local HITECH grantees, this data presentation helps shed light on a financially impactful initiative from our federal government that can drastically improve healthcare delivery in thousands of cities nationwide!

More Datasets

For more datasets, click here.

Featured Notebooks

• 🚨 Your notebook can be here! 🚨!

How to use the dataset

This dataset provides geographic data for the service areas of two of the HITECH programs, the Health IT Regional Extension Centers (REC) Program and the Beacon Communities Program. This can be used to map and visualize data related to those programs. Here is a guide on how to use this dataset:

• Get familiar with key columns: Familiarize yourself with the columns included in this dataset, including column names and descriptions for each column such as region, region_code, county_name, state_fips, county_fips and zip.
• Review data formats: If there are any discrepancies between your current format of data presented in this dataset versus what you may have currently in your system or within other sources of information - make sure to review those discrepancies prior exploring more from here onwards.
• Understand regional coverage: Refine the analysis by filtering out different grantee located based on specific regions or states - use necessary filters such as Region code or County FIPs code that will give you an easier view on which region/county grantee has been provided funding through these HHS programs as part of Hitech Act program distribution.
• Map & Visualize grantees: We can visualise geographically where are REC-Program & Beacon Communities Grants distributed across US by making a heatmap while taking desired geolocation coordinates like zip codes; query all available details under columns we need like zip codes along their respective countyp location & state value so that grants can be highlighted after it renders practical Map visuals for us giving an ease if further status / details required about entities who had taken these grants within certain area / regions!

Research Ideas

• Creating an interactive map to visualize grant program performance by region and county.
• Using the data to create a color-coded scatterplot graphic to show active grant program sites in the US.
• Generating reports on HITECH Grantee performance over time, grouped by geographic area or region

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

Unknown License - Please check the dataset description for more information.

Columns

File: healthit-dashboard-areatype-crosswalk-csv-1.csv | Column name | Description | |:------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------| | region | The region of the grantee. (String) | | region_code | The code for the region of the grantee. (String) | | county_name | The name of county where the grantee is located. (String) | | state_fips | The Federal Information Processing Standard (FIPS) code for knowledge of which state it is located in. (String) | | county_fips | The Federa...

Broadband internet speed map showing maximum available broadband internet speed per US Census block (2010). Data does not include satellite internet providers and terrestrial fixed wireless. Only the providers with the highest maximum advertised downstream speed are displayed. Providers with a lower maximum advertised downstream speed are omitted. Geolocation of 2020 FCC Fixed Broadband Deployment data is based upon the 2010 census blocks created by the US Census Bureau.Data Fields:Max Advertised Downstream Speed (mbps) (megabit per second)Max Advertised Upstream Speed (mbps) (megabit per second)Provider NameHolding Company Name (as filed on FCC Form 477)Technology Code (2-digit code indicating the Technology of Transmission used to offer broadband service); 10 - Asymmetrical xDSL (copper wireline), 11 - ADSL2 (copper wireline), 12 - VDSL (copper wireline), 20 - Symmetrical xDSL (copper wireline), 30 - Other Copper Wireline, 40 - Cable Modem, 41 - Cable Modem DOCSIS 1, 1.1, and 2.0 (DOCSIS: Data Over Cable Service Interface Specification), 42 - Cable Modem DOCSIS 3.0 (DOCSIS: Data Over Cable Service Interface Specification), 43 - Cable Modem DOCSIS 3.1 (DOCSIS: Data Over Cable Service Interface Specification), 50 - Optical Carrier/Fiber to the End User (FTTx), 0 - All OtherBLOCKCE10 (Census Block FIPS Code)STATEFP10 (State FIPS Code)COUNTYFP10 (County FIPS Code)TRACTFP10 (Tract FIPS Code)GEOID10 (Census Block Geographic Identification Number)StateData Sources:External Link: FCC Fixed Broadband Deployment Data: December 2020External Link: US Census Bureau TIGER/Line Shapefiles, 2010 CensusExternal Link: US Census Bureau TIGER/Line Shapefiles, 2020 Census_For questions, problems, or more information, contact gis@atcog.org Ark-Tex Council of Governments Homepage: https://atcog.org/Open Data Portal Homepage: https://open-data-portal-atcog.hub.arcgis.com/_

Landuse circa 1800 is a statewide database for Michigan based on original surveyors tree data and descriptions of the vegetation and land between 1816 and 1856. This is a fully attributed version that contains all vegetation codes (see attribute information). The database creators recognize that there are errors in the database due to interpretation and data input. Errors of comission and omission may still exist in the current version of the database. For concerns on the use, see the limitations listed below, refer to the references provided, or call the contact for more information. Database has county codes and data in it from IDENTITY process run against the stco100 database. This provides county names and FIPS codes. Ran the ADDAREA command to add area in acres and square miles as well. Please do not redistribute this database - please have requestors contact the source. Also note the version/edition number on this database release. Any future updates or modifications will have a version/edition number assigned. All previous versions/editions should be destroyed or removed to an archive status. Version 1.0 - completed QA/QC Version 1.1 - Annotation removed from all LU1800 databases.More Metadata

This CD consists of the Tiger/Line files corresponding to North Carolina (Alamance to Stokes Counties). The TIGER/Line files contain information which describes the points, lines, and areas on Census Bureau maps. The files are extracts of selected geographic and cartographic data from the Census Bureau's Census TIGERTM (Topologically Integrated Geographic Encoding and Referencing) System which is used to support mapping and other geographic activities of its decennial census and sample survey programs. The TIGER/Line files provide information on streets, rivers, railroads, and other line features, where they intersect and the areas they enclose, in a form that can be processed by a computer. TIGER/Line records contain latitude/longitude coordinates, codes identifying census geographic areas, and address ranges and ZIP CodesR. While these files contain geographic data, they are not maps or geographic information systems by themselves. Users must first import or reformat the data into an application system or software. TIGER/Line, 1992 replaces the earlier version -- TIGER/Line Files, 1990. TIGER/Line, 1992 extends the address range and ZIP Code coverage by 60 percent, identifies several new geographic areas, and includes viewing software. New Address Ranges and ZIP Codes -- Additional potential address ranges and ZIP Codes have been added based upon a match with the 1990 Census master address list. This expands the coverage to include over 80 million residential addresses (earlier versions covered only about 50 million addresses). New Geographic Areas -- TIGER/Line, 1992 adds codes for new geographic areas such as congressional districts (as of the 103rd Congress), 1990 Urbanized Areas, school districts, and new cities and towns incorporated since the 1990 Census. Viewing Software - LandViewTM, a public domain software developed by the Environmental Protection Agency, is added to this newest version of TIGER/Line. Up to 14 separate files, each corresponding to a TIGER/Line, 1992 record type, are provided for each county. A st Directory and individu al cty Subdirectories (where st = Federal Information Processing Standard [FIPS] State Code and cty = FIPS County Code) are used to store the county file sets on the disc. Note to Users: This CD is part of a collection located in the Data Archive of the Odum Institute for Research in Social Science, at the University of North Carolina at Chapel Hill. The collection is located in Room 10, Manning Hall. Users may check the CDs out subscribing to the honor system. Items can be checked out for a period of two weeks. Loan forms are located adjacent to the collection.

Coordinate system Update:Notably, this dataset will be provided in NAD 83 Connecticut State Plane (2011) (EPSG 2234) projection, instead of WGS 1984 Web Mercator Auxiliary Sphere (EPSG 3857) which is the coordinate system of the 2023 dataset and will remain in Connecticut State Plane moving forward.Ownership Suppression and Data Access:The updated dataset now includes parcel data for all towns across the state, with some towns featuring fully suppressed ownership information. In these instances, the owner’s name will be replaced with the label "Current Owner," the co-owner’s name will be listed as "Current Co-Owner," and the mailing address will appear as the property address itself. For towns with suppressed ownership data, users should be aware that there was no "Suppression" field in the submission to verify specific details. This measure was implemented this year to help verify compliance with Suppression.New Data Fields:The new dataset introduces the "Land Acres" field, which will display the total acreage for each parcel. This additional field allows for more detailed analysis and better supports planning, zoning, and property valuation tasks. An important new addition is the FIPS code field, which provides the Federal Information Processing Standards (FIPS) code for each parcel’s corresponding block. This allows users to easily identify which block the parcel is in.Updated Service URL:The new parcel service URL includes all the updates mentioned above, such as the improved coordinate system, new data fields, and additional geospatial information. Users are strongly encouraged to transition to the new service as soon as possible to ensure that their workflows remain uninterrupted. The URL for this service will remain persistent moving forward. Once you have transitioned to the new service, the URL will remain constant, ensuring long term stability.For a limited time, the old service will continue to be available, but it will eventually be retired. Users should plan to switch to the new service well before this cutoff to avoid any disruptions in data access.The dataset has combined the Parcels and Computer-Assisted Mass Appraisal (CAMA) data for 2024 into a single dataset. This dataset is designed to make it easier for stakeholders and the GIS community to use and access the information as a geospatial dataset. Included in this dataset are geometries for all 169 municipalities and attribution from the CAMA data for all but one municipality. Pursuant to Section 7-100l of the Connecticut General Statutes, each municipality is required to transmit a digital parcel file and an accompanying assessor’s database file (known as a CAMA report), to its respective regional council of governments (COG) by May 1 annually. These data were gathered from the CT municipalities by the COGs and then submitted to CT OPM. This dataset was created on 10/31/2024 from data collected in 2023-2024. Data was processed using Python scripts and ArcGIS Pro, ensuring standardization and integration of the data.CAMA Notes:The CAMA underwent several steps to standardize and consolidate the information. Python scripts were used to concatenate fields and create a unique identifier for each entry. The resulting dataset contains 1,353,595 entries and information on property assessments and other relevant attributes.CAMA was provided by the towns.Spatial Data Notes:Data processing involved merging the parcels from different municipalities using ArcGIS Pro and Python. The resulting dataset contains 1,290,196 parcels.No alteration has been made to the spatial geometry of the data.Fields that are associated with CAMA data were provided by towns.The data fields that have information from the CAMA were sourced from the towns’ CAMA data.If no field for the parcels was provided for linking back to the CAMA by the town a new field within the original data was selected if it had a match rate above 50%, that joined back to the CAMA.Linking fields were renamed to "Link".All linking fields had a census town code added to the beginning of the value to create a unique identifier per town.Any field that was not town name, Location, Editor, Edit Date, or a field associated back to the CAMA, was not used in the creation of this Dataset.Only the fields related to town name, location, editor, edit date, and link fields associated with the towns’ CAMA were included in the creation of this dataset. Any other field provided in the original data was deleted or not used.Field names for town (Muni, Municipality) were renamed to "Town Name".The attributes included in the data: Town Name OwnerCo-OwnerLinkEditorEdit DateCollection year – year the parcels were submittedLocationMailing AddressMailing CityMailing StateAssessed TotalAssessed LandAssessed BuildingPre-Year Assessed Total Appraised LandAppraised BuildingAppraised OutbuildingConditionModelValuationZoneState UseState Use DescriptionLand Acre Living AreaEffective AreaTotal roomsNumber of bedroomsNumber of BathsNumber of Half-BathsSale PriceSale DateQualifiedOccupancyPrior Sale PricePrior Sale DatePrior Book and PagePlanning RegionFIPS Code *Please note that not all parcels have a link to a CAMA entry.*If any discrepancies are discovered within the data, whether pertaining to geographical inaccuracies or attribute inaccuracy, please directly contact the respective municipalities to request any necessary amendmentsAdditional information about the specifics of data availability and compliance will be coming soon.If you need a WFS service for use in specific applications : Please Click Here

This layer was developed by the Research & Analytics Division of the Atlanta Regional Commission and represents the 100-year and 500-year floodplain data as delineated on Flood Insurance Rate Maps (FIRMs) published by FEMA. Features captured from the paper FIRMs include floodplain boundaries, political boundaries, FIRM panel areas, and USGS 7.5-minute quadrangle boundaries. Potential applications of this "Q3" flood data include floodplain management, hazards analysis and risk assessment. In addition, the risk zones serve to establish premium rates for flood insurance offered through the National Flood Insurance Program. For more information, go to https://msc.fema.gov.Attributes:FIPS Standard 5-digit State and County FIPS codes. Definition source is from Federal Information Processing Standard (FIPS), National Institute of Standards & Technology (NIST); first 2 digits for state, last 3 digits for county.COMMUNITY Identifies a county, city, or other community responsible for flood plain management. Numeric value assigned by FEMA,(0..9999).FIRM_PANEL Eleven-digit alpha-numeric code identifies portion of community covered or not covered by a FIRM panel. Code comprises a unique alpha-numeric sequence based on FIPS and FEMA Community and Panel identification.QUAD USGS 7.5-minute quadrangle identifier.ZONE Flood hazard zone designation. Multiple Codes refer to "Q3 Flood Data Specifications" VALUES DESCRIPTION V An area inundated by 100-year flooding with velocity hazard (wave action); no Base Flood Elevation (BFEs) have been determined. VE An area inundated by 100-year flooding with velocity hazard (wave action); BFEs have been determined. A An area inundated by 100-year flooding, for which no BFEs have been determined. AE An area inundated by 100-year flooding, for which BFEs have been determined. AO An area inundated by 100-year flooding (usually sheet flow on sloping terrain), for which average depths have been determined; flood depths range from 1 to 3 feet. AOVEL An alluvial fan inundated by 100-year flooding (usually sheet flow on sloping terrain), for which average flood depths and velocities have been determined; flood depths range from 1 to 3 feet. AH An area inundated by 100-year flooding (usually an area of ponding), for which BFEs have been determined; flood depths range from 1 to 3 feet. A99 An area inundated by 100-year flooding, for which no BFEs have been determined. This is an area to be protected from the 100-year flood by a Federal flood protection system under construction. D An area of undetermined but possible flood hazards. AR An area inundated by flooding, for which BFEs or average depths have been determined. This is an area that was previously, and will again, be protected from the 100-year flood by a Federal flood protection system whose restoration is Federally funded and underway. X500 An area inundated by 500-year flooding; an area inundated by 100-year flooding with average depths of less than 1 foot or with drainage areas less than 1 square mile; or an area protected by levees from the 100-year flooding. X An area that is determined to be outside the 100- and 500-year floodplains. 100IC An area where the 100-year flooding is contained within the channel banks and the channel is too narrow to show to scale. An arbitrary channel width of 3 meters is shown. BFEs are not shown in this area, although they may be reflected on the corresponding profile. 500IC An area where the 500-year flooding is contained within the channel banks and the channel is too narrow to show to scale. An arbitrary channel width of 3 meters is shown. FWIC An area where the floodway is contained within the channel banks and the channel is too narrow to show to scale. An arbitrary channel width of 3 meters is shown. BFEs are not shown in this area, although they may be reflected on the corresponding profile. FPQ An area designated as a "Flood Prone Area" on a map prepared by USGS and the Federal Insurance Administration. This area has been delineated based on available information on past floods. This is an area inundated by 100-year flooding for which no BFEs have been determined.FLOODWAY Channel, river or watercourse reserved for flood discharge. Multiple Codes refer to "Q3 Flood Data Specifications".COBRA Undeveloped Coastal Barrier Area. Multiple Codes refer to "Q3 Flood Data Specifications".SFHA In/Out of flood zone designation, determined from data topology. VALUES DESCRIPTION IN An area designated as within a "Special Flood Hazard Area" (or SFHA) on a FIRM. This is an area inundated by 100-year flooding for which no BFEs or velocity may have been determined. No distinctions are made between the different flood hazard zones that may be included within the SFHA. These may include Zones A, AE, AO, AH, A99, AR, V, or VE. OUT An area designated as outside a "Special Flood Hazard Area" (or SFHA) on a FIRM. This is an area inundated by 500-year flooding; an area inundated by 100-year flooding with average depths of less than 1 foot or with drainage areas less than 1 square mile; an area protected by levees from 100-year flooding; or an area that is determined to be outside the 100- and 500-year floodplains. No distinctions are made between these different conditions. These may include both shaded and unshaded areas of Zone X. ANI An area that is located within a community or county that is not mapped on any published FIRM. UNDES A body of open water, such as a pond, lake ocean, etc., located within a community's jurisdictional limits, that has no defined flood hazard.SYMBOL Polygon shade symbols for graphic output, based on polygon codes. Multiple Codes refer to "Q3 Flood Data Specifications"PANEL_TYP Type of FIRM panel represented. Multiple Codes refer to "Q3 Flood Data Specifications".ST_FIPS State FIPS codeCO_FIPS County FIPS codeSource: Federal Emergency Management Agency (FEMA), Atlanta Regional CommissionDate: 1998

Original census file name: tl_2020_