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PURPOSE | This data was created by the San Francisco Department of Public Health to identify street segments and intersections in San Francisco that have a high number of pedestrian fatalities and severe injuries. As of 2014, this network is being used to inform Vision Zero.| B. METHODOLOGY | Pedestrian high injury corridors were originally derived from 2005-2009 Statewide Integrated Traffic Records System (SWITRS) injury records. All pedestrian injuries resulting from a collision between a vehicle and a pedestrian were used in the analysis, for a total of 3,883 pedestrian injuries (383 of which were severe) and 97 fatalities (16 pedestrian injuries were not able to be geocoded\u200b).For this analysis, severe and fatal injuries were weighted by multiplying those counts times 3 while complaints of pain and visible injury were assigned a count of 1. Weighted injuries were then aggregated at an intersection level (based on primary and secondary streets in SWITRS) and then assigned their adjoining street segments. Potential high injury density corridors were defined by first identifying street segments with weighted counts =>9 and then assessing whether there was a linear pattern of higher injury counts proximate to those segments and following the street network. A kernel density geoprocessing tool that takes into account the area density of the mapped, weighted injuries served as a qualitative check that area-level concentrations of injury were captured.These high injury corridors were revised in 2013 using SWITRS injury records from 2010 and 2011. With the additional two years of data there were a total of 5,452 pedestrian injuries, out of which 127 were fatalities (48 pedestrian injuries were not able to be geocoded and were thus excluded from the analysis). New HICs and HIC extensions were identified by assessing both absolute changes in injury density from 2005-2009 compared to 2007-2011 as well as segment-level weight injury counts for 2007-2011 compared to 2005-2009. The data was split into two overlapping groups of 5-year periods to account for the small sample of size of injuries occurring per year and associated issues with respect to random variation and regression to the mean. In addition, intersections a relatively high rate of (pedestrian injuries/pedestrian volumes), were identified using pedestrian volumes estimated from a pedestrian volume model developed for San Francisco. The HIPIs identified have a weighted total pedestrian injury count >=4 and a pedestrian crossing risk (weighted total pedestrian injuries / pedestrian volume) >= 3 injuries annually per 1 million walk trips (intersections in the 97thpercentile and higher of all intersections with an estimated pedestrian crossing risk, utilizing injury data from 2005-2011). Also identified were intersections with a relatively higher number of pedestrian injuries that were not located on HICs. These intersections had a total of 9 or more weighted total pedestrian injuries from 2005-2011. http://www.sfhealthequity.org/component/jdownloads/finish/8-transportation/280-identifying-high-pedestrian-injury-corridors-for-targeted-safety-improvements/0?Itemid=0| C. UPDATE FREQUENCY | This dataset will be updated in 2015/16 using 2009-2013 injury when available from SWITRS. This update schedule is tentative and pending approval from the MTA/DPH. Please contact Devan Morris (devan.morris@sfdph.org) to inquire about the latest pedestrian high injury network.| D. OTHER CRITICAL INFO | This is one of three networks that make up the Vision Zero High Injury Network. All injury data was geocoded to the nearest intersection for this analysis and available on www.transbasesf.org. A complete methodology is available here: http://bit.ly/1QQxU79.| E. ATTRIBUTES |OBJECTID: Unique record identifier;geom: PostGIS/ArcGIS geometry identifier;cnn_sgmt_pkey: This attribute is the same as Centerline Network Number Unique ID (CNN) found in other road network feature classes throughout the city;street_name: Street name excluding prefix and suffix;street_type: Street suffix;street_layer: SFDPW street classification;full_street_name: Full street name including suffix;class_code: Class code used for symbolizing;gis_length_miles: Street length representing duel carriage ways as one street segment instead of two;duel_car_way_yn: Street is represented as a duel carriage way;duel_car_way_id: Unique ID assigned for each side of a duel carriage way;corrected_length_miles: Street length representing duel carriage ways as one street segment instead of two;f_node_cnn_intrsctn_fkey: Unique intersection ID at start of street segment;t_node_cnn_intrsctn_fkey: Unique intersection ID at end of street segment;shape_length: Object length created by ArcGIS;sgmt_ped_hgh_injry_crrdr_pkey: Unique identifier used by TransBASE;hic_code: Unique code created for each pedestrian high injury corridor;hic_name: Name of each pedestrian high injury corridor;cross_street_1: Starting cross street for pedestrian high injury corridor;cross_street_2: Ending cross street for pedestrian high injury corridor;geom_Length: Object length created by ArcGIS", "geometryType": "esriGeometryPolyline", "sourceSpatialReference": { "wkid": 4326, "latestWkid": 4326, "xyTolerance": 8.98315284119521E-9, "zTolerance": 0.001, "mTolerance": 0.001, "falseX": -400, "falseY": -400, "xyUnits": 9.999999999999999E8, "falseZ": 0, "zUnits": 1, "falseM": 0, "mUnits": 1 }, "copyrightText": "| A. CUSTODIAN | Devan Morris, devan.morris@sfdph.org, Population Health, San Francisco Department of Public Health;\nMegan Wier, megan.wier@sfdph.org, Population Health, San Francisco Department of Public Health\n\n| B. 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B) Methodology: Manually updatedC) Updated: annuallyD) Critical Info: No information for the 2011-12 school year; this does not mean that no schools participated, but rather that spatial documentation is unavailable.E) Attributes:Streetname: street name;Type: street type;Odd_even: whether the school is on the odd or even side of the street;NEWFIELD1: school name;Grade: school grade levels;Former_nam: former school name;Supdist: supervisorial district;Public: whether school is public or private;GD_FOR_MAP: school grade level category for symbology;Status: notes about school status;School: school name for labeling;Installed: 0 = 15 mph school zone present; 1 or 3 = 15 mph school zone not present;Address_fu: school address;Neighborho: neighborhood", "geometryType": "esriGeometryPolygon", "sourceSpatialReference": { "wkid": 4326, "latestWkid": 4326, "xyTolerance": 8.98315284119521E-9, "zTolerance": 0.001, "mTolerance": 0.001, "falseX": -400, "falseY": -400, "xyUnits": 9.999999999999999E8, 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