Description: This layer documents all 4,538 fatal and serious injury (KSI) crashes from 2018-2022 reported within the City of Phoenix and within 300 feet of its Boundaries. This layer does not include crashes on freeway mainlines but it does include crashes on freeway ramps and crashes on ADOT right of way on City of Phoenix arterials. This database was used as reference for the 2024 High Injury Network Evaluation.
Description: This layer includes crashes within 150 feet of a HIN intersection (382 crashes at signalized intersections, 9 crashes at unsignalized intersections – some of which were already considered within the segments) and crashes within 100 feet of the segment centerline (499 segment crashes). This layer does not include crashes within 150 feet of a signalized intersection that is not on the HIN, even if the segment adjacent to the intersection is on the HIN Segment.
Description: Arterial and collector segments were evaluated by Engineering Mapping Solutions and Y2K Engineering to identify their number of KSI crashes per mile reported between 2018 and 2022. Crashes on the freeways and crashes within 150 feet of a traffic signal were not included in the evaluation of segment crashes. Segments with at least 3 crashes and 12 or more KSI crashes per mile in the 5 year period were included in the 2024 High Injury Network.
Description: Signalized intersections were evaluated by Engineering Mapping Solutions and Y2K Engineering to identify their number of KSI crashes per mile reported between 2018 and 2022. Crashes within 150 feet of the signalized intersection were considered at the intersection. Signalized intersections with 6 or more KSI crashes in the five-year period were included in the 2024 High Injury Network.
Description: Signalized intersections were evaluated by Engineering Mapping Solutions and Y2K Engineering to identify their number of KSI crashes per mile reported between 2018 and 2022. Crashes within 150 feet of the signalized intersection were considered at the intersection. Signalized intersections with 6 or more KSI crashes in the five-year period were included in the 2024 High Injury Network.
Description: This layer assesses and identifies communities that are disadvantaged according to updated Justice40 Initiative criteria. Census tracts in the U.S. and its territories that meet the Version 1.0 criteria are shaded in semi-transparent blue colors to work with a variety of basemaps. See this web map for use in your dashboards, story maps, and apps.Details of the assessment are provided in the popup for every census tract in the United States and its territories American Samoa, Guam, the Northern Mariana Islands, Puerto Rico, and the U.S. Virgin Islands. This map uses 2010 census tracts from Version 1.0 of the source data downloaded November 22, 2022.If you have been using a previous version of the Justice40 data, please know that this Version 1.0 differs in many ways. See the updated Justice40 Initiative criteria for current specifics. Use this layer to help plan for grant applications, to perform spatial analysis, and to create informative dashboards and web applications. See this blog post for more information.From the source:This data "highlights disadvantaged census tracts across all 50 states, the District of Columbia, and the U.S. territories. Communities are considered disadvantaged:If they are in census tracts that meet the thresholds for at least one of the tool’s categories of burden, orIf they are on land within the boundaries of Federally Recognized TribesCategories of BurdensThe tool uses datasets as indicators of burdens. The burdens are organized into categories. A community is highlighted as disadvantaged on the CEJST map if it is in a census tract that is (1) at or above the threshold for one or more environmental, climate, or other burdens, and (2) at or above the threshold for an associated socioeconomic burden.In addition, a census tract that is completely surrounded by disadvantaged communities and is at or above the 50% percentile for low income is also considered disadvantaged.Census tracts are small units of geography. Census tract boundaries for statistical areas are determined by the U.S. Census Bureau once every ten years. The tool utilizes the census tract boundaries from 2010. This was chosen because many of the data sources in the tool currently use the 2010 census boundaries."Source: https://services.arcgis.com/P3ePLMYs2RVChkJx/arcgis/rest/services/usa_november_2022/FeatureServerBrowse the DataView the Data tab in the top right of this page to browse the data in a table and view the metadata available for each field, including field name, field alias, and a field description explaining what the field represents.Symbology updated 2/19/2023 to show additional tracts whose overlap with tribal lands is greater than 0% but less than 1%, to be designated as "Partially Disadvantaged" alongside tracts whose overlap with tribal lands is 1% or more.
Copyright Text: Council on Environmental Quality, Esri
N_HLTH
(
type: esriFieldTypeInteger, alias: Health Disadvantaged
)
SN_C
(
type: esriFieldTypeInteger, alias: Identified as disadvantaged
)
SN_T
(
type: esriFieldTypeString, alias: Identified as disadvantaged due to tribal overlap, length: 80
)
DLI
(
type: esriFieldTypeInteger, alias: Greater than or equal to the 90th percentile for diabetes, is low income, and has a low percent of higher ed students?
)
ALI
(
type: esriFieldTypeInteger, alias: Greater than or equal to the 90th percentile for asthma, is low income, and has a low percent of higher ed students?
)
PLHSE
(
type: esriFieldTypeInteger, alias: Greater than or equal to the 90th percentile for households at or below 100% federal poverty level, has low HS attainment, and has a low percent of higher ed students?
)
LMILHSE
(
type: esriFieldTypeInteger, alias: Greater than or equal to the 90th percentile for low median household income as a percent of area median income, has low HS attainment, and has a low percent of higher ed students?
)
ULHSE
(
type: esriFieldTypeInteger, alias: Greater than or equal to the 90th percentile for unemployment, has low HS attainment, and has a low percent of higher ed students?
)
EPL_ET
(
type: esriFieldTypeInteger, alias: Greater than or equal to the 90th percentile for expected population loss
)
EAL_ET
(
type: esriFieldTypeInteger, alias: Greater than or equal to the 90th percentile for expected agricultural loss
)
EBL_ET
(
type: esriFieldTypeInteger, alias: Greater than or equal to the 90th percentile for expected building loss
)
EB_ET
(
type: esriFieldTypeInteger, alias: Greater than or equal to the 90th percentile for energy burden
)
PM25_ET
(
type: esriFieldTypeInteger, alias: Greater than or equal to the 90th percentile for PM 2.5 exposure
)
DS_ET
(
type: esriFieldTypeInteger, alias: Greater than or equal to the 90th percentile for diesel particulate matter
)
TP_ET
(
type: esriFieldTypeInteger, alias: Greater than or equal to the 90th percentile for traffic proximity
)
LPP_ET
(
type: esriFieldTypeInteger, alias: Greater than or equal to the 90th percentile for lead paint and the median house value is less than 90th percentile
)
KP_ET
(
type: esriFieldTypeInteger, alias: Greater than or equal to the 90th percentile for share of homes without indoor plumbing or a kitchen
)
HB_ET
(
type: esriFieldTypeInteger, alias: Greater than or equal to the 90th percentile for housing burden
)
RMP_ET
(
type: esriFieldTypeInteger, alias: Greater than or equal to the 90th percentile for Risk Management Plan (RMP) proximity
)
NPL_ET
(
type: esriFieldTypeInteger, alias: Greater than or equal to the 90th percentile for NPL (superfund sites) proximity
)
TSDF_ET
(
type: esriFieldTypeInteger, alias: Greater than or equal to the 90th percentile for proximity to hazardous waste sites
)
WD_ET
(
type: esriFieldTypeInteger, alias: Greater than or equal to the 90th percentile for wastewater discharge
)
UST_ET
(
type: esriFieldTypeInteger, alias: Greater than or equal to the 90th percentile for leaky underwater storage tanks
)
DB_ET
(
type: esriFieldTypeInteger, alias: Greater than or equal to the 90th percentile for diabetes
)
A_ET
(
type: esriFieldTypeInteger, alias: Greater than or equal to the 90th percentile for asthma
)
HD_ET
(
type: esriFieldTypeInteger, alias: Greater than or equal to the 90th percentile for heart disease
)
LLE_ET
(
type: esriFieldTypeInteger, alias: Greater than or equal to the 90th percentile for low life expectancy
)
UN_ET
(
type: esriFieldTypeInteger, alias: Greater than or equal to the 90th percentile for unemployment
)
LISO_ET
(
type: esriFieldTypeInteger, alias: Greater than or equal to the 90th percentile for households in linguistic isolation
)
POV_ET
(
type: esriFieldTypeInteger, alias: Greater than or equal to the 90th percentile for households at or below 100% federal poverty level
)
LMI_ET
(
type: esriFieldTypeInteger, alias: Greater than or equal to the 90th percentile for low median household income as a percent of area median income
)
IA_LMI_ET
(
type: esriFieldTypeInteger, alias: Low median household income as a percent of territory median income in 2009 exceeds 90th percentile
)
IA_POV_ET
(
type: esriFieldTypeInteger, alias: Percentage households below 100% of federal poverty line in 2009 exceeds 90th percentile
)
TC
(
type: esriFieldTypeDouble, alias: Total threshold criteria exceeded
)
CC
(
type: esriFieldTypeDouble, alias: Total categories exceeded
)
IAULHSE
(
type: esriFieldTypeInteger, alias: Greater than or equal to the 90th percentile for unemployment and has low HS education in 2009 (island areas)?
)
IAPLHSE
(
type: esriFieldTypeInteger, alias: Greater than or equal to the 90th percentile for households at or below 100% federal poverty level and has low HS education in 2009 (island areas)?
)
IALMILHSE
(
type: esriFieldTypeInteger, alias: Greater than or equal to the 90th percentile for low median household income as a percent of area median income and has low HS education in 2009 (island areas)?
)
IALMIL_76
(
type: esriFieldTypeDouble, alias: Low median household income as a percent of territory median income in 2009 (percentile)
)
IAPLHS_77
(
type: esriFieldTypeDouble, alias: Percentage households below 100% of federal poverty line in 2009 for island areas (percentile)
)
IAULHS_78
(
type: esriFieldTypeDouble, alias: Unemployment (percent) in 2009 for island areas (percentile)
)
LHE
(
type: esriFieldTypeInteger, alias: Low high school education and low percent of higher ed students
)
IALHE
(
type: esriFieldTypeInteger, alias: Low high school education in 2009 (island areas)
)
IAHSEF
(
type: esriFieldTypeDouble, alias: Percent individuals age 25 or over with less than high school degree in 2009
)
N_CLT_EOMI
(
type: esriFieldTypeInteger, alias: At least one climate threshold exceeded
)
N_ENY_EOMI
(
type: esriFieldTypeInteger, alias: At least one energy threshold exceeded
)
N_TRN_EOMI
(
type: esriFieldTypeInteger, alias: At least one traffic threshold exceeded
)
N_HSG_EOMI
(
type: esriFieldTypeInteger, alias: At least one housing threshold exceeded
)
N_PLN_EOMI
(
type: esriFieldTypeInteger, alias: At least one pollution threshold exceeded
)
N_WTR_EOMI
(
type: esriFieldTypeInteger, alias: At least one water threshold exceeded
)
N_HLTH_88
(
type: esriFieldTypeInteger, alias: At least one health threshold exceeded
)
N_WKFC_89
(
type: esriFieldTypeInteger, alias: At least one workforce threshold exceeded
)
FLD_PFS
(
type: esriFieldTypeDouble, alias: Share of properties at risk of flood in 30 years (percentile)
)
WFR_PFS
(
type: esriFieldTypeDouble, alias: Share of properties at risk of fire in 30 years (percentile)
)
FLD_ET
(
type: esriFieldTypeInteger, alias: Greater than or equal to the 90th percentile for share of properties at risk of flood in 30 years
)
WFR_ET
(
type: esriFieldTypeInteger, alias: Greater than or equal to the 90th percentile for share of properties at risk of fire in 30 years
)
ADJ_ET
(
type: esriFieldTypeInteger, alias: Is the tract surrounded by disadvantaged communities?
)
IS_PFS
(
type: esriFieldTypeDouble, alias: Share of the tract's land area that is covered by impervious surface or cropland as a percent (percentile)
)
IS_ET
(
type: esriFieldTypeInteger, alias: Greater than or equal to the 90th percentile for share of the tract's land area that is covered by impervious surface or cropland as a percent and is low income?
)
AML_ET
(
type: esriFieldTypeInteger, alias: Is there at least one abandoned mine in this census tract, where missing data is treated as False?
)
FUDS_RAW
(
type: esriFieldTypeString, alias: Is there at least one Formerly Used Defense Site (FUDS) in the tract?, length: 80
)
FUDS_ET
(
type: esriFieldTypeInteger, alias: Is there at least one Formerly Used Defense Site (FUDS) in the tract, where missing data is treated as False?
)
IMP_FLG
(
type: esriFieldTypeString, alias: Income data has been estimated (imputed) based on neighbor income, length: 80
)
DM_B
(
type: esriFieldTypeDouble, alias: Percent Black or African American
)
DM_AI
(
type: esriFieldTypeDouble, alias: Percent American Indian / Alaska Native
)
DM_A
(
type: esriFieldTypeDouble, alias: Percent Asian
)
Description: This layer contains Census data from the 2021 American Community Survey reflecting Block Group characteristics from 2017-2021, sourced from the MAG Open Data Portal: https://geodata-azmag.opendata.arcgis.com/search?q=acs [geodata-azmag.opendata.arcgis.com]. An equity analysis was performed using data for age,race, poverty and vehicle ownership at the Block Group level. The four data sets at the block level were assigned equal weight and averaged together to produce a composite percentage ('Combined' field).
Copyright Text: Census Bureau, Engineering Mapping Solutions, Y2K Engineering, STR-GIS,