20240927 11142500 1.0 FALSE EquityPriorityCommunity 002 Projected GCS_North_American_1983 Linear Unit: Foot_US (0.304801) <ProjectedCoordinateSystem xsi:type='typens:ProjectedCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.6.0'><WKT>PROJCS["NAD_1983_StatePlane_California_II_FIPS_0402_Feet",GEOGCS["GCS_North_American_1983",DATUM["D_North_American_1983",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Lambert_Conformal_Conic"],PARAMETER["False_Easting",6561666.666666666],PARAMETER["False_Northing",1640416.666666667],PARAMETER["Central_Meridian",-122.0],PARAMETER["Standard_Parallel_1",38.33333333333334],PARAMETER["Standard_Parallel_2",39.83333333333334],PARAMETER["Latitude_Of_Origin",37.66666666666666],UNIT["Foot_US",0.3048006096012192],AUTHORITY["EPSG",2226]]</WKT><XOrigin>-115211800</XOrigin><YOrigin>-93821500</YOrigin><XYScale>3048.0060960121928</XYScale><ZOrigin>0</ZOrigin><ZScale>1</ZScale><MOrigin>0</MOrigin><MScale>1</MScale><XYTolerance>0.0032808333333333331</XYTolerance><ZTolerance>2</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>102642</WKID><LatestWKID>2226</LatestWKID></ProjectedCoordinateSystem> NAD_1983_StatePlane_California_II_FIPS_0402_Feet 20260603 11155700 20260605 7144700 5000000 5000 ItemDescription Esri ArcGIS 13.3.0.52636 EquityPriorityCommunity The purpose of developing EPCs was to identify communities that have historically been marginalized and underserved by transportation projects. The EPC methodology predominantly focuses on demographic characteristics within communities, rather than broader mobility concerns, including barriers to access and quality of life issues. EPCs are Census block groups that have higher concentrations of demographic characteristics than other areas within the same county. As mentioned above, EPCs were developed in partnership with community members, with each criteria weighed differently by each county, depending on which were important and relevant to the local context. EPCs include criteria that are not featured in other geographies in this analysis, such as linguistic isolation, educational attainment, cost burden (housing and transportation), age, and ability. <DIV STYLE="text-align:Left;"><DIV><DIV>Equity Priority Communities (EPCs) are historically disadvantaged communities defined at the unit of Census Block Groups within SACOG area.There are three types of EPCs:1) Home-based EPCs2) Destination-based EPCs3) Both Home- and Destination-based EPCsA. Home-based EPCs are based on the following criteria:1. Race and Ethnicity - percentage of Latino and/or Non-White population based on ACS 2018-2022 5-year estimates (Block Groups)2. Low Income - percentage of Households below 200% of the Federal Poverty Level based on ACS 2018-2022 5-year estimates (Block Groups)3. Cost Burden - CNT Housing + Transportation (H+T) 2022 (Census Tract)4. Pollution Burden - CalEnviroScreen 4.0 Pollution Burden Percentile (Census Tract)5. Youth - percentage of population 17 and younger based on ACS 2018-2022 5-year estimates (Block Groups)6. Older Adults - percentage of population 65 and older based on ACS 2018-2022 5-year estimates (Block Groups)7. People with Disabilities - percentage of population with disabilities based on ACS 2018-2022 5-year estimates (Census Tract)8. Linguistic Isolation - percentage of households with Limited English Proficiency based on ACS 2018-2022 5-year estimates (Block Groups)9. Educational Attainment - percentage of Adults with no High-School Diploma based on ACS 2018-2022 5-year estimates (Block Groups)10. Selected Tribal Areas - Census Block groups adjacent to Auburn Historic and Enterprise RancheriasThe EPCs status was defined based on a score estimated in the following way:1. Standardization of the criteria by County2. Weighting of criteria based on the public and interested parties engagement (more details in the methodology document)3. The Block Groups were ranked by weighted sum of the criteria and top-scoring ones were selected with the goal to achieve the population target of 20% per County in selected EPCs.B. Destination-based EPCs are based on the volume of trips originating from selected Home-based EPCs and are meant to reflect the destinations where disadvantaged communities are typically travelling to. The analysis of trip volumes was based on Replica 2024 data - Origin-Destination trip matrix on Block Group level. The Block Groups with over 4,000 daily trip destinations were selected as Destination-based EPCs.</DIV></DIV></DIV> Mobility Zones, STEER https://sacog.primegov.com/viewer/preview?id=5951&type=2 EPC DAC MTP 2025 <DIV STYLE="text-align:Left;"><DIV><DIV>SACOG provides data as a public service. These data are provided "as-is." While every effort has been made to ensure the accuracy or correctness of these data, SACOG makes no warranty, expressed or implied, as to its accuracy or correctness and expressly disclaims liability for the accuracy thereof. In no event shall SACOG become liable to users of these data, or any other party, for any loss or damages, consequential or otherwise, including but not limited to time, money, or goodwill, arising from the use, operation or modification of the data. In using these data, users further agree to indemnify, defend, and hold harmless SACOG for any and all liability of any nature arising out of or resulting from the lack of accuracy or correctness of the data, or the use of the data. Users will not distribute these data to other potential users. Instead, they will refer those users to SACOG for an independent dataset and documentation. To assist SACOG in the maintenance of the data, users should provide SACOG's GIS staff information concerning errors or discrepancies found in using the data.</DIV></DIV></DIV> Enterprise Geodatabase Feature Class dataset EPSG 5.3(9.0.0) 0 Simple FALSE 0 TRUE FALSE EquityPriorityCommunity Feature Class 0 OBJECTID OBJECTID OID 4 10 0 Internal feature number. Esri Sequential unique whole numbers that are automatically generated. Shape Shape Geometry 8 0 0 Feature geometry. Esri Coordinates defining the features. STATEFP STATEFP String 2 0 0 COUNTYFP COUNTYFP String 3 0 0 TRACTCE TRACTCE String 6 0 0 BLKGRPCE BLKGRPCE String 1 0 0 GEOID GEOID String 12 0 0 NAMELSAD NAMELSAD String 13 0 0 MTFCC MTFCC String 5 0 0 FUNCSTAT FUNCSTAT String 1 0 0 GEOID_Join GEOID_Join String 254 0 0 GEOCODE_Blkgrp GEOCODE Blkgrp String 1073741822 0 0 Geographic_Code_Identifier Geographic Code Identifier BigInteger 8 19 0 Tahoe Tahoe Integer 4 10 0 CountyCode CountyCode Integer 4 10 0 CountyName CountyName String 1073741822 0 0 EPC_SELECTED EPC_SELECTED Integer 4 10 0 EPC_RankbyCounty EPC Rank Integer 4 10 0 EPC_Score EPC Score Double 8 38 8 EPC_NormScore EPC Score (normalized) Double 8 38 8 Population Population Integer 4 10 0 KeyDest KeyDest Integer 4 10 0 Type EPC Type String 1073741822 0 0 KD_Trips Trips from EPCs Integer 4 10 0 KD_RankbyCounty Key Destinanation Rank Integer 4 10 0 TEST_EPC TEST_EPC Integer 4 10 0 TEST_KD TEST_KD Integer 4 10 0 new_EPC new EPC Integer 4 10 0 removed_EPC removed EPC Integer 4 10 0 new_KD new KD Integer 4 10 0 removed_KD removed KD Integer 4 10 0 Race Race and Ethnicity (%) Double 8 38 8 Youth Youth (%) Double 8 38 8 Older_adults Older Adults (%) Double 8 38 8 Linguistic_isolation Linguistic Isolation (%) Double 8 38 8 Disability People with Disabilities (%) Double 8 38 8 Education Educational Attainment (%) Double 8 38 8 Pollution Pollution Burden (0-100) Double 8 38 8 Cost_burden Cost Burden (0-100) Integer 4 10 0 Income Low Income (%) Double 8 38 8 EPC_Type_u EPC_Type_u String 255 0 0 Shape.STArea() Shape.STArea() Double 0 0 0 Shape.STLength() Shape.STLength() Double 0 0 0 20260605