Average daily border waiting time from the U.S. Customs and Border Protection (CBP)

Average daily border waiting time from the U.S. Customs and Border Protection (CBP)

Employment Centers are identified as areas with a high concentration of employment based on SANDAG’s 2016 employment inventory from Urbansim summarized to quarter-mile radius hexagons. Local-maxima were identified as starting points, and regions were grown to include neighboring hexagons meeting a minimum employment density threshold within an approximate 2-mile radius. The resulting boundaries were generalized (taking into account major barrier features such as topography and freeways) and used to select SANDAG Master Geographic Reference Areas (MGRAs) by activity-weighted (population and employment) centroid. Employment centers are ranked by Tier based on total number of jobs:

Tier 1: 50,000 or more jobs

Tier 2: 25,000 to 49,999 jobs

Tier 3: 15,000 to 24,999 jobs

Tier 4: 2,500 to 14,999 jobs

Hexbin geography (where people live map layers) – generated using a quarter-mile radius hex bin grid overlay on the region. Data is summarized by hex bin spatially using the centroid of an overlying geography.

Where people live by Employment Center they Work In –2015 LEHD census block level data; converted to hexbin (see hexbin geography). LEHD data was used as it contains information on both the home and work location. Data represents an employee residence by the employment center they work in. https://lehd.ces.census.gov/data/.

The Bureau of Transportation Statistics (BTS) Border Crossing Data provide summary statistics for inbound crossings at the U.S.-Canada and the U.S.-Mexico border at the port level. Data are available for trucks, trains, containers, buses, personal vehicles, passengers, and pedestrians. Border crossing data are collected at ports of entry by U.S. Customs and Border Protection (CBP). The data reflect the number of vehicles, containers, passengers or pedestrians entering the United States.

This dataset contains building outline polygons to support the ongoing development and maintenance of SANDAG's land inventory system (SPACECORE). The SanGIS Parcels feature class and the imagery captured by EagleView/Pictometry during the San Diego regional imagery acquisition partnership project in Spring 2017 were the basis for defining where building outlines were created using EagleView/Pictometry's ChangeFinder methodology. Additional buildings within road rights-of-way were also delineated by the EagleView/Pictometry team. SANDAG will be adding attribution to this dataset as part of our SPACECORE integration process.

TIGER blocks were adjusted to better align with local administrative geography, specifically 2020 jurisdictional boundaries and 2020 Community Planning Area boundaries for both the City of San Diego and the County of San Diego. Please note: SANDAG consolidated some blocks with adjacent blocks in cases where there was no visible population. This was done prior to the release of the redistricting tables. The ocean blocks were also removed.

2020 Census Tracts. Census Tracts were dissolved from Census Block Groups, the latter having been dissolved from Census Blocks. The blocks were TIGER blocks adjusted to match local jurisdictional and district boundaries. The ocean tracts were also removed.

2020 Census Tracts. Census Tracts were dissolved from Census Block Groups, the latter having been dissolved from Census Blocks. The blocks were TIGER blocks adjusted to match local jurisdictional and district boundaries. The ocean tracts were also removed.

District boundaries for the transit operators in the San Diego region: Metropolitan Transit System (MTS) and North County Transit District (NCTD)

2010 Colleges. Includes colleges, universities, and other postsecondary education schools. Street addresses were geocoded to SanGIS parcel centroids or street centerlines. Using aerial imagery as a background, some points were manually relocated over school buildings.