{
 "culture": "en-US",
 "name": "",
 "guid": "",
 "catalogPath": "",
 "snippet": "For planning analyses and mapping",
 "description": "<DIV STYLE=\"text-align:Left;\"><P STYLE=\"font-size:16ptmargin:7 0 7 0;\"><SPAN><SPAN>This dataset identifies \u201ccommunities of concern,\u201d and is designated for SCAG\u2019s 2020 Regional Transportation Plan/Sustainable Communities Strategies (RTP/SCS) Environmental Justice Analysis Report. Communities of Concern Data Methodology by Kimberly Clark and Tom Vo, April 26, 2019. Using data from the 2013-2017 ACS 5 Year Estimates at the Census Designated Place level (CDP), calculate total percentage of minority population and total percentage of households in poverty for each CDP. Also using census tract data from the 2013-2017 ACS 5 Year Estimates, tabulate percentage of minority population and total percentage of households in poverty for each City of Los Angeles Community Planning Area (CPAs). Intersect CPAs with Census Tracts and tabulate new totals for partial CPA/Census Tracts based on spatial interpolation. Sum total Poverty, households, minority, and population values for each CPA. Merge CDPs and City of Los Angeles Community Planning Areas to create a single \u201cPlace\u201d file for the entire SCAG region. Remove the City of Los Angeles CDP from layer. Tabulate % of households in poverty and % of minority population for each \u201cPlace.\u201d Using Rank and Percentile tool in Excel, select the places that are in the upper third in the SCAG region for both % of households in poverty (x &gt; 0. 17096018735) and% minority (x &gt; 0. 78260869565). <\/SPAN><\/SPAN><\/P><DIV><DIV><P STYLE=\"margin:0 0 11 0;\"><SPAN /><\/P><\/DIV><\/DIV><\/DIV>",
 "summary": "For planning analyses and mapping",
 "title": "Communities_of_Concern",
 "tags": [
  "Communities of Concern",
  "SCAG",
  "0913"
 ],
 "type": "",
 "typeKeywords": [],
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 "minScale": 150000000,
 "maxScale": 5000,
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 "licenseInfo": "<p>This dataset is provided by SCAG for general planning and informational purposes only, and SCAG shall incur no responsibility or liability as to the completeness, correctness, or accuracy of this information. All information is provided \"as is\" without warranty of any kind, express or implied, including warranties of accuracy, completeness, timeliness, merchantability, fitness for a particular purpose, or non-infringement.<\/p>\n                       <p>The dataset may include third-party data not maintained by SCAG. SCAG makes no guarantees regarding such data and assumes no liability for errors, omissions, or outcomes arising from its use.<\/p>\n                       <p>Users are strongly encouraged to verify information with original sources. Where applicable, consult local jurisdictions for official land use, zoning, or other authoritative data.<\/p>",
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}