20240905
10045700
1.0
FALSE
Neighborhood_Mobility_poly_scag
002
0.000
287957.174700
725476.621900
3615130.078900
3861673.518800
1
Projected
GCS_North_American_1983
Linear Unit: Meter (1.000000)
NAD_1983_UTM_Zone_11N
<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/10.8'><WKT>PROJCS["NAD_1983_UTM_Zone_11N",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["Transverse_Mercator"],PARAMETER["False_Easting",500000.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-117.0],PARAMETER["Scale_Factor",0.9996],PARAMETER["Latitude_Of_Origin",0.0],UNIT["Meter",1.0],AUTHORITY["EPSG",26911]]</WKT><XOrigin>-5120900</XOrigin><YOrigin>-9998100</YOrigin><XYScale>10000</XYScale><ZOrigin>0</ZOrigin><ZScale>1</ZScale><MOrigin>0</MOrigin><MScale>1</MScale><XYTolerance>0.001</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>26911</WKID><LatestWKID>26911</LatestWKID></ProjectedCoordinateSystem>
20241112
14110300
20241112
14110300
150000000
5000
FGDC
Version 6.2 (Build 9200) ; Esri ArcGIS 10.8.1.14362
Neighborhood_Mobility_poly_scag
1
-119.319980
-114.533157
34.897475
32.650813
Neighborhood Mobility Areas (NMAs), one of four Priority Development Areas (PDAs) used in Connect SoCal 2024. NMAs are built from City/split Tier2 Transportation Analysis Zone (TAZ) geography.
<div style='text-align:Left;'><div><div><p><span>Neighborhood Mobility Areas (NMAs) are areas that focus on creating, improving, restoring and enhancing safe and convenient connections to schools, hospitals, shopping, services, places of worship, parks, greenways and other destinations. SCAG uses four empirical measures in its initial identification of NMAs: 1) Intersection density, 2) Low-speed streets, 3) Land use entropy (mixing), and 4) Accessibility to amenities within 1-mile using street network distances. In order to weight these four measures equally, each was converted to a z-score at the TAZ-level. A z-score of zero indicates that a TAZ is at the regional average for that measure – positive scores reflect above-average TAZs, and negative scores reflect below average TAZs. A composite score was developed for each TAZ by summarizing the z-scores for all four measures. Based on the results of this process, SCAG took the top 25 percent performing TAZs and identified them as NMAs, to reflect the “top one-fourth” of the region for neighborhood mobility. These preliminary NMAs were then provided to local jurisdictions for review and refinement.</span></p><p><span /></p><p><span style='font-weight:bold;'>Field Description/Field Values Description:</span></p><p><span><span>COUNTY – County the jurisdiction is located in</span></span></p><p><span><span>COUNTY_ID – County ID the jurisdiction is located in</span></span></p><p><span><span>CITY – Jurisdiction name</span></span></p><p><span><span>CITY_ID – Jurisdiction ID number</span></span></p><p><span><span>TIER2 – Tier2 Transportation Analysis Zone</span></span></p><p><span><span>CT2 – City Tier 2 Transportation Analysis Zone</span></span></p><p><span /></p></div></div></div>
SCAG
SCAG
Connect SoCal 2024
Neighborhood Mobility Areas
NMA
Lyle Janicek
SCAG
900 Wilshire Blvd., Ste 1700
Los Angeles
CA
90017
janicek@scag.ca.gov
US
213-236-1966
Every fourth year, alongside RTP/SCS adoption
<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>NOTE: This data is intended for planning purposes only, and SCAG shall incur no responsibility or liability as to the completeness, currentness, or accuracy of this information. SCAG assumes no responsibility arising from use of this information by individuals, businesses, or other public entities. The information is provided with no warranty of any kind, expressed or implied, including but not limited to the implied warranties of merchantability and fitness for a particular purpose.</SPAN></P></DIV></DIV></DIV>
Feature Class
0.000
dataset
EPSG
6.13(3.0.1)
0
Simple
FALSE
0
TRUE
FALSE
Neighborhood_Mobility_Areas_poly_scag
Feature Class
0
OBJECTID
FID
OID
4
10
0
Internal feature number.
Esri
Sequential unique whole numbers that are automatically generated.
Shape
Shape
Geometry
4
0
0
Feature geometry.
Esri
Coordinates defining the features.
county
county
String
14
0
0
County the jurisdiction is located in
county_id
county_id
String
3
0
0
Federal Information Processing Standard code referring to county identification number.
U.S. Census Bureau
city_id
city_id
String
5
0
0
Jurisdiction ID number
tier2
tier2
String
8
0
0
Tier2 Transportation Analysis Zone
ct2
ct2
String
16
0
0
City Tier 2 Transportation Analysis Zone
city
city
String
36
0
0
Jurisdiction name
YEAR
YEAR
Integer
4
10
0
Year of Plan Adoption
SCAG
Shape.area
Shape.area
Double
0
0
0
Shape.len
Shape.len
Double
0
0
0
20241112
Lyle Janicek
SCAG
900 Wilshire Blvd., Ste. 1700
Los Angeles
CA
90017
janicek@scag.ca.gov
213-236-1966
Every fourth year, alongside RTP/SCS adoption
<DIV STYLE="text-align:Left;"><DIV><P><SPAN>See description.</SPAN></P></DIV></DIV>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