{ "currentVersion": 10.81, "id": 3, "name": "% Non-white", "type": "Feature Layer", "description": "GR Vital Streets: Equity & Prioritization analysisAnalysis OVERVIEWA multi-variable analysis of demographic and geographic assets was conducted to aid the Vital Streets program in identifying target areas to prioritize for vital streets funding. This analysis in particular focuses on equity factors across the City of Grand Rapids along with geographic representation across different wards. The analysis is broken into two components:Demographic Need\u2013 This set of factors reflects equity and need considerations based on demographic characteristics and adjusted based on the overall population density of each census block.Connection Opportunity\u2013 Factors reflect desired destinations and areas of opportunity based on a spectrum of data inputs \u2013 including gaps in existing physical facilities and infrastructure, jobs, and transit connectivity.APPROACHEach of the analysis factors are aggregated into the 2010 census block level. The source for each factor and methods of aggregation are described below in the DATA LAYERS section.Each factor was generalized into a 1-5 score based on a quantile distribution (20% increments in values across the scores) unless otherwise noted below.Factors within each analysis component (Demographic Need and Connectivity Opportunity) were combined with equal weighting (calculation of mean score) to generate a component score. The Demographic Need score was filtered based on the census block's population density score such that less dense census blocks would receive a lower score relative to denser census blocks with the same Demographic need score. The following formulas were used for calculating these scores:Demographic Need: (([MedIncS] + [Ov65DenS] + [HHPovS] + [HHDisabS] + [NoWhiteS] + [Youth18S])/6)/(6- [PopDensS])Connection Opportunity: ([CommDenS]+ [JobDenS]+[ParkAccS]+[TransitS]+ [BikeConS]+ [BPCrashS]+ [TreeCanS]+ [SidewalkS])/8The two component scores were each normalized into a 1-5 score based on a quantile distribution.The resulting component scores were combined into an overall score for each Census Block by adding the two values together, resulting in a 2-10 score range for each Census block. Data DescriptionDemographic NeedThese factors relate to areas of the city where there may be a heightened need for projects to occur in order to support neighborhood stability, and address equity considerations.The data for the Demographic Need component was taken directly from Census 2010 and American Community Survey (ACS) data from 2015. Median Income [MedInc]2015 American Communities Survey, block-group level dataBlock-group level was transferred into the census block level data using a spatial join.1-5 scores classified based on five quantile breaks. Lower income prioritized. [MedIncS]Density of total population in Senior age brackets [Ov65Den]2010 Census, block level data, 65-years and olderThe density of seniors within each census block was calculated by dividing the total number of seniors by the acreage of the census block.1-5 scores classified based on five quantile breaks. Higher density prioritized [Ov65DenS]Density of total population in under 18 age brackets[Youth18]2010 Census, block level data, quantiles scoringThe density of youth within each census block was calculated by dividing the total number of youths by the acreage of the census block.1-5 scores classified based on five quantile breaks. Higher density prioritized [Youth18S]Density of households with a person with a disability[HHDisab] 2015 American Communities Survey, block-group level dataPercentage values were multiplied against the total household data to determine an estimated number of households with disabilities in each census block-group.Block-group level data was transferred into census block level data using a spatial join.The density of households with disabilities within each census block was calculated by dividing the total number of households with disabilities by the acreage of the census block.1-5 scores classified based on five quantile breaks. Higher density prioritized [HHDisabS]Density of households in poverty status [HHPov]2015 American Communities Survey, block-group level dataPercentage values were multiplied against the total household data to determine an estimated number of households in poverty within in each census block-group.Block-group level data was transferred into census block level data using a spatial join.The density of households in poverty within each census block was calculated by dividing the total number of households with disabilities by the acreage of the census block.1-5 scores classified based on five quantile breaks. Higher density prioritized [HHPovS]Density of population in non-white race demographic[NoWhite]2010 Census, block level data, quantiles scoringThe density of non-whites within each census block was calculated by dividing the total number of non-white people by the acreage of the census block.1-5 scores classified based on five quantile breaks. Higher density prioritized [NoWhiteS]Population density (people / acre)[PopDens]2010 Census, block level data, quantiles scoringThe density of people within each census block was calculated by dividing the total number of people by the acreage of the census block.1-5 scores classified based on five quantile breaks. Higher density prioritized [PopDensityS]Connection OpportunitiesThese factors consider locations where people may want to access, including job centers, recreational assets, cultural resources, schools, commercial areas, and other community destinations.Job Density [JobDen]Data from the Bureau of Labor Statistics \"On The Map\" census block level employment data for 2015. This data lists the number of employees working within each census block.The density of jobs within each census block was calculated by dividing the total number of jobs by the acreage of the census block.1-5 scores classified based on five quantile breaks. Higher density prioritized [JobDenS]Park Accessibility [ParkAcc]Access to park space based on a metric of 10 acres of park space per 1,000 residents within a ¼ mile radius. Analysis was conducted as follows:Acreage of parks (including school parks) was calculated.¼ mile buffers were created around each park site (no dissolve on the buffers) with the park acreage ascribed to each park's buffer.The spatial join tool was used to total the population from census blocks that intersected the ¼ mile buffer rings.A new attribute was calculated in the in the resulting layer for the rate at which park acreage was allocated to each resident within its ¼ mile service area (Total Acres / Total People). A second spatial join was used on the census block data to sum the park acreage allocation rate for all parks within ¼ mile of the census block. The resulting data was manually classified and scored as follows [ParkAccS] :5 = No access to park space4 = Underserved (less than 10 acres of park space per 1000 people)3 = Modestly served (10 \u2013 23 acres per 1000 people)2 = Served (24-55 acres per 1000 people)1 = Well served (more than 55 acres per 1000 people)Proximity to Transit Service [Transit]Transit data from The Rapid. A spatial join was used within a ¼ mile radius from centroid of each census block to determine the number of transit stops in proximity. Stop data includes a single point for each bus route, with multiple points at a single location where more than one route is present.1-5 scores classified based on five quantile breaks. Areas with more transit stops prioritized [TransitS]Connectivity to Bicycle Facilities [BikeConS]Connectivity to bicycle facilities based on the GR Vital Streets Bicycle Facilities Plan. This analysis aims to identify locations where there is a confluence of existing AND proposed facilities in close proximity in order to emphasis building onto the existing network rather than building isolated, disconnected facilities.Existing facilities that are slated to remain in place (per the Bicycle Facility Plan) were isolated from the dataset and exported as their own existing facility layer.Proposed physical facilities as well as identified priority community routes (a subset of all community routes) were isolated from the data set and exported as their own later.Spatial join was used to link census blocks to the existing and proposed facility layer and calculate a number of street blocks with bicycle facilities that were within ¼ mile of the centroid of each census block.A 1-5 score for the existing facilities and a separate 1-5 score for the proposed facilities were calculated based on quantile distribution. A two-digit combined score was calculated (tens digits reflecting the existing facility score and one's digit reflecting the proposed facility score). The resulting values were manually classified into an overall score as follows:\"5\" High Opportunity: 55, 54, 45\"4\" Moderate/High Opportunity: 53, 44, 43, 35, 34\"3\" Moderate Opportunity: 52, 42, 33, 25, 24, 32, 23, 22\"2\" Moderate/Low Opportunity: 15, 14, 13, 13 (Reflects locations where there are no existing facilities in close proximity but some amount of proposed facilities).\"1\" Low Opportunity: 11, 21, 31, 41, 51 (Low opportunity reflects locations where there are no proposed facilities in close proximity at all).Sidewalk gaps [Sidewalk]Gaps in the sidewalks were determined for each census block as follows:A spatial join tool was used to determine the amount of public roadway that was adjacent to each census block. A second spatial join was used to determine the amount of sidewalk (from the GR city sidewalk inventory data) was adjacent to each census block.A sidewalk ratio was calculated as a new attribute by dividing the total length of sidewalk by the total length of adjacent road right-of-way. In a typical situation, a values close to \"1\" reflects the presence of sidewalks along all roadsides.1-5 scores classified based on five quantile breaks. Areas with more sidewalk gaps prioritized [SidewalkS]Commercial Centers / Zoning Designations [CommDen]Commercial destinations were identified using ESRI Community Analyst business data for NACIS codes 42 (wholesale), 44/45 (retail), 71 (arts, entertainment, and recreation), and 72 (accommodations and food service).The count of commercial destinations within each census block was calculated using a spatial join too.The density of commercial destinations was calculated based on the number of jobs / total acres of the census block. 1-5 scores classified based on five quantile breaks. Areas with greater commercial density were prioritized [CommDenS]Crash Data (Safety Factor) [BPCrash]Combined Bike and Pedestrian Crash data from the City of Grand Rapids for 2010-2015 was used.A spatial join with a 150' buffer around each census block was used to count the number of crashed in proximity.1-5 scores classified based on five quantile breaks. Areas with greater total crashes were prioritized [BPCrashS]Tree Canopy (Environmental Factor) [TreeCanS]The City of Grand Rapids tree canopy data was used.Canopy geometry was sliced along census block boundaries and canopy area (acres) was recalculated. The canopy acreage was calculated for each census block using the spatial join tool. Canopy area was divided by the total block area to determine a % canopy cover by census block.1-5 scores classified based on five quantile breaks. Areas with lower tree canopy area were prioritized. 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