{ "culture": "en-US", "name": "", "guid": "", "catalogPath": "", "snippet": "This feature includes all related attributes for the capacity spatial analysis project for PA; the influence codes were summarized by have/need to get the final ranking.", "description": "
This feature includes all related attributes for the capacity spatial analysis project for PA; the influence codes were summarized by have/need to get the final ranking.<\/SPAN><\/P> Influence attributes<\/SPAN><\/P> influence_member / Influence - Member<\/SPAN>: % of constituents within census tract broken into 5 groups by quantile breaks; HAVE capacity code from 0-4 with 4 being the highest.<\/SPAN><\/P> influence_restoration / Influence <\/SPAN>- Restoration: # of sites (landowner and/or project) within a census tract; HAVE capacity code >20 is .5 and all other values are 0.<\/SPAN><\/P> influence_leadership / Influence <\/SPAN>- Leadership: The weight of value given to a House/Senate representative based on values shared by CBF staff; NEED capacity code from 0-3 with 3 being the highest.<\/SPAN><\/P> influence_lcv / Influence - LCV<\/SPAN>: The lifetime score given to a House/Senate representative (if there was no lifetime score this was calculated using the % D vote within the district); NEED capacity code is 0.5 for scores between 20 and 80 and all other scores given the code 0.<\/SPAN><\/P> influence_election / Influence <\/SPAN>- Election: Difference between democratic and republican votes during the 2020 election in a precinct; NEED capacity code is .5 for any value ranging between -20 and 20 and all other scores given the code 0.<\/SPAN><\/P> haveInfluence_rank_1 / Have influence - Membership (rank)<\/SPAN>: Calculated HAVE influence sum using the value for influence_member; >2 is HIGH and all other values are LOW.<\/SPAN><\/P> haveInfluence_rank_2 / Have influence - Membership + Rest (rank)<\/SPAN>: Calculated HAVE influence sum using the value for influence_member and influence_restoration; >2 is HIGH and all other values are LOW.<\/SPAN><\/P> needInfluence_rank / Need influence (rank)<\/SPAN>: Calculated NEED influence sum using the value for influence_leadership (House, Senate), influence_lcv (House, Senate), and influence_election; >2 is HIGH and all other values are LOW.<\/SPAN><\/P> capacity_rank_1 / Capacity Rank (Membership)<\/SPAN>: Combine the HAVE influence that only include membership influence (haveInfluence_rank_1) with NEED influence (needInfluence_rank).<\/SPAN><\/P> capacity_rank_2 / Capacity Rank (Membership + Rest): <\/SPAN>Combine the HAVE influence that includes membership and restoration influence (haveInfluence_rank_2) with NEED influence (needInfluence_rank).<\/SPAN><\/P> <\/P> This feature was updated 9/91021 to include new restoration project location and landowner count and influence values.<\/SPAN><\/P> <\/P> <\/P> <\/P> <\/P> <\/P><\/DIV><\/DIV><\/DIV>",
"summary": "This feature includes all related attributes for the capacity spatial analysis project for PA; the influence codes were summarized by have/need to get the final ranking.",
"title": "Capacity ranking",
"tags": [
"PA",
"2021",
"capacity"
],
"type": "",
"typeKeywords": [],
"thumbnail": "",
"url": "",
"minScale": 150000000,
"maxScale": 5000,
"spatialReference": "",
"accessInformation": "Spatial analysis process and final data product created by M. Finch (CBF, 2021).",
"licenseInfo": " Created for use by the CBF PA Office staff.<\/SPAN><\/P><\/DIV><\/DIV> <\/P><\/DIV><\/DIV>",
"portalUrl": ""
}