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Safety In Public Parks Presentation Safety In Public Parks Presentation Presentation Transcript

  • Park SafetyAnalyzing Safety around St. Louis County Public ParksBased on Crime and Population DensityBy: Bradley Lewis Date: April 25, 2013
  • Civic ProblemParks are supposed to be a place to relax and enjoy theoutdoors.However, are the parks we go to safe?Crimes are occuring in and around St. Louis County publicparks.To make parks safer, we have to know where the crimesare happening, what they are, and how to make the parkssafer.
  • SolutionTo create a workflow that pinpoints the parks with the mostsurrounding crime and the types of crime happening. My main product will be a spreadsheet that shows thenames of the St. Louis County parks with correspondingcrime and population data.This data can then be assessed and analyzed bycommunity planners, law enforcement, and parkmanagers to promote and develop safety measures in andaround parks with a high density of crimes.
  • Workflow and MethodologySelected only parks with names in St. Louis County (total of 68 records).Selected layers based on type of crime: Crimes Against Persons, CrimesAgainst Property, and Quality of Life Crimes, and exported them as featureclasses.Spatially joined the parks and census block data, and then the three crime datafeatures based on a 0.5 mile search radius.Added fields and calculated based on type of crime divided by population data.Exported to .dbf file and then saved it as an excel file to edit and clean the data.A model of my workflow created using Model Builder in ArcGIS.
  • Map ProductThe total crime map shows that many of the parks in the northeastern area of thecounty had more crime occur in or near the park than the central and west centralparts of the county.
  • Park_Name Crimes_Against_Persons Crimes_Against_Property Quality_of_Life_Crimes Total_Population_2010 Total_Crimes Crimes_Against_Persons_Divided_by_Pop Crimes_Against_Property_Divided_By_Pop Quality_of_Life_Divided_by_Pop Total_Crimes_Divided_By_PopGreaves 2 32 7 4398 41 0.000454752 0.00727603 0.00159163 0.0093224Forest_Staley 24 86 24 3185 134 0.007535320 0.02700160 0.00753532 0.0420722Buder 91 431 378 3593 900 0.025327000 0.11995500 0.10520500 0.2504870Memorial 352 932 840 4546 2124 0.077430700 0.20501500 0.18477800 0.4672240Larimore 401 1169 275 5110 1845 0.078473600 0.22876700 0.05381600 0.3610570Love 39 387 292 7590 718 0.005138340 0.05098810 0.03847170 0.0945982Ohlendorf_West 39 174 86 5779 299 0.006748570 0.03010900 0.01488150 0.0517391Lone_Elk 1 11 15 85 27 0.011764700 0.12941200 0.17647100 0.3176470Kinloch 74 210 91 1604 375 0.046134700 0.13092300 0.05673320 0.2337910Robert_Winter 13 43 10 2667 66 0.004874390 0.01612300 0.00374953 0.0247469Forman 21 106 52 5211 179 0.004029940 0.02034160 0.00997889 0.0343504Antire 0 8 4 105 12 0.000000000 0.07619050 0.03809520 0.1142860Ebsworth 0 0 0 1888 0 0.000000000 0.00000000 0.00000000 0.0000000Wayne_C_Kennedy 31 147 79 5682 257 0.005455830 0.02587120 0.01390360 0.0452306Bright 74 206 121 5760 401 0.012847200 0.03576390 0.02100690 0.0696181Queeny 21 151 68 6983 240 0.003007300 0.02162390 0.00973793 0.0343692Sylvan_Springs 205 676 351 4666 1232 0.043934800 0.14487800 0.07522500 0.2640380R_9 142 361 237 3213 740 0.044195500 0.11235600 0.07376280 0.2303140Sioux_Passage 17 62 28 2454 107 0.006927470 0.02526490 0.01140990 0.0436023Tilles 0 0 0 4190 0 0.000000000 0.00000000 0.00000000 0.0000000West_Tyson 4 24 16 689 44 0.005805520 0.03483310 0.02322210 0.0638607Spanish_Lake 573 1619 390 6948 2582 0.082469800 0.23301700 0.05613130 0.3716180Classe 84 202 124 5146 410 0.016323400 0.03925380 0.02409640 0.0796735Endicott 79 321 462 3757 862 0.021027400 0.08544050 0.12297000 0.2294380Lilac_and_Dunn 186 791 166 2353 1143 0.079048000 0.33616700 0.07054820 0.4857630Fort_Belle_Fontaine 77 69 27 1833 173 0.042007600 0.03764320 0.01473000 0.0943808Bissel 263 1036 280 4797 1579 0.054825900 0.21596800 0.05836980 0.3291640Greensfelder 47 242 49 1961 338 0.023967400 0.12340600 0.02498730 0.1723610Creve_Coeur 19 96 27 7942 142 0.002392340 0.01208760 0.00339965 0.0178796Castle_Point 467 1175 469 3016 2111 0.154841000 0.38958900 0.15550400 0.6999340King 105 230 95 3190 430 0.032915400 0.07210030 0.02978060 0.1347960Gravios_Creek 40 202 117 3241 359 0.012341900 0.06232640 0.03610000 0.1107680Bohrer 102 695 399 4627 1196 0.022044500 0.15020500 0.08623300 0.2584830McDonnell 101 248 106 7238 455 0.013954100 0.03426360 0.01464490 0.0628627Mathilda_Welmering 181 657 340 5689 1178 0.031815800 0.11548600 0.05976450 0.2070660Deer_Creek 3 11 6 3571 20 0.000840101 0.00308037 0.00168020 0.0056007Gramond 93 280 130 5564 503 0.016714600 0.05032350 0.02336450 0.0904026Bishop_Long_Log_Cabin 12 44 30 3662 86 0.003276900 0.01201530 0.00819224 0.0234844St_Stanislaus 0 0 0 3616 0 0.000000000 0.00000000 0.00000000 0.0000000Champ 82 295 61 4828 438 0.016984300 0.06110190 0.01263460 0.0907208Faust 21 130 178 5328 329 0.003941440 0.02439940 0.03340840 0.0617492Bon_Oak 412 1249 323 5745 1984 0.071714500 0.21740600 0.05622280 0.3453440Veterans_Memorial 545 2026 304 10307 2875 0.052876700 0.19656500 0.02949450 0.2789370Affton_Community_Center 88 323 182 6150 593 0.014308900 0.05252030 0.02959350 0.0964228Ohlendorf 67 347 107 5545 521 0.012083000 0.06257890 0.01929670 0.0939585Jefferson_Barracks 364 1074 455 6493 1893 0.056060400 0.16540900 0.07007550 0.2915450Museum_of_Transportation 50 172 132 6978 354 0.007165380 0.02464890 0.01891660 0.0507309Bee_Tree 21 121 33 4090 175 0.005134470 0.02958440 0.00806846 0.0427873Clydesdale 115 506 197 6884 818 0.016705400 0.07350380 0.02861710 0.1188260Packwood 17 115 62 3356 194 0.005065550 0.03426700 0.01847440 0.0578069Hunters_Ford 1 5 0 186 6 0.005376340 0.02688170 0.00000000 0.0322581St_Vincent 176 522 388 4713 1086 0.037343500 0.11075700 0.08232550 0.2304260George_Winter 15 82 87 1437 184 0.010438400 0.05706330 0.06054280 0.1280450Belleview_Farms_Sherman_Beach 11 66 32 3417 109 0.003219200 0.01931520 0.00936494 0.0318993Lemay_Ferry 16 106 75 3002 197 0.005329780 0.03530980 0.02498330 0.0656229Albrecht 27 107 39 5068 173 0.005327550 0.02111290 0.00769534 0.0341358Black_Forest 110 341 135 2036 586 0.054027500 0.16748500 0.06630650 0.2878190Lemay 202 672 350 2726 1224 0.074101200 0.24651500 0.12839300 0.4490100Laumeier 0 0 0 1794 0 0.000000000 0.00000000 0.00000000 0.0000000Cliff_Cave 77 377 220 8933 674 0.008619720 0.04220310 0.02462780 0.0754506Bella_Fontaine 1729 5335 2608 15622 9672 0.110677000 0.34150600 0.16694400 0.6191270Widman 16 63 29 3366 108 0.004753420 0.01871660 0.00861557 0.0320856Lower_Meramec 22 255 92 4594 369 0.004788860 0.05550720 0.02002610 0.0803222Suson 71 279 147 5480 497 0.012956200 0.05091240 0.02682480 0.0906934Butler_Hill 2 13 8 1327 23 0.001507160 0.00979653 0.00602864 0.0173323Simpson 46 203 52 1070 301 0.042990700 0.18972000 0.04859810 0.2813080Steamboat_Island 0 5 3 408 8 0.000000000 0.01225490 0.00735294 0.0196078Unger 13 210 45 1172 268 0.011092200 0.17918100 0.03839590 0.2286690Excel Spreadsheet: Results
  • Park_Name C_A_Persons C_A_Property QOL_Crimes Total_Pop TotalCrimes CAPerson_ByPop CAProperty_ByPop QOL_ByPop TotalCrimes_ByPopCastle_Point 467 1175 469 3016 2111 0.154841000 0.38958900 0.15550400 0.6999340Lilac_and_Dunn 186 791 166 2353 1143 0.079048000 0.33616700 0.07054820 0.4857630Lemay 202 672 350 2726 1224 0.074101200 0.24651500 0.12839300 0.4490100Spanish_Lake 573 1619 390 6948 2582 0.082469800 0.23301700 0.05613130 0.3716180Bon_Oak 412 1249 323 5745 1984 0.071714500 0.21740600 0.05622280 0.3453440Larimore 401 1169 275 5110 1845 0.078473600 0.22876700 0.05381600 0.3610570Bissel 263 1036 280 4797 1579 0.054825900 0.21596800 0.05836980 0.3291640Lone_Elk 1 11 15 85 27 0.011764700 0.12941200 0.17647100 0.3176470Queeny 21 151 68 6983 240 0.003007300 0.02162390 0.00973793 0.0343692Creve_Coeur 19 96 27 7942 142 0.002392340 0.01208760 0.00339965 0.0178796Faust 21 130 178 5328 329 0.003941440 0.02439940 0.03340840 0.0617492Excel Spreadsheet: Selected Results
  • AdviceConsider the type of of crime to examine.After assessing the data and map products, prioritize which parks to allocate resources to. **Some ofmy recommendations include Castle Point, Spanish Lake, Bella Fontaine, and Lemay.Survey and examine these areas around the parks. Look for reasons crime may occur in these parks.Do they have lights? What kind of facilities and programs do they have? Is there a school or policestation nearby? Are there cameras? Fill out a detailed “inventory” form when doing this examination.** St. Louis County has no cameras and no or only one dusk to dawn light in the maintenance buildingsin the parks mentioned above.Based on the inventory form, decide which parks you want to center in on. Focus budgets on addingfacilities to bring the community together. Extend and implement community programming and thehours of park operation (with the help of added LED lights) by having professionally supervisedrecreation programs.Cameras can be added, but do cost more and need to be monitored by trained professionals andintegrated with other policing functions.Cameras may displace or avert crime from the parks, but police officials can identify the areassusceptible to crime displacement and place officers in these locations. ** In Chicago and Baltimore,for every dollar spent on a camera, it yielded a benefit anywhere from $1.50-$4.30.
  • References:Donahue, Ryan. “Pedestrians and Park Planning: How Far Will People Walk?”http://cityparksblog.org/2011/05/13/pedestrians-and-park-planning-how-far-will-people-walk/. Accessed April 23, 2013.Federal Bureau of Investigation. “Crime in the U.S. 2010: Caution Against Ranking.”http://www.fbi.gov/about-us/cjis/ucr/crime-in-the-u.s/2010/crime-in-the-u.s.-2010/caution-against-ranking. Accessed April 22, 2013.Gerken, Jim. Operations Manager for St. Louis County Public Parks.Lord-Castillo, Brett. GIS Programmer for St. Louis County Emergency Management.Markman, Joshua, Nancy G. La Vigne, and Samantha S. Lowry. “Evaluating the Use ofPublic Surveillance Cameras for Crime Control and Prevention. September2011.http://www.cops.usdoj.gov/Publications/e071112381_EvalPublicSurveillance.pdf.Accessed April 23, 2013.The National Recreation and Park Association. “Creating Safe Park Environments toEnhance Community Wellness.”http://www.nrpa.org/uploadedFiles/nrpaorg/Grants_and_Partners/Recreation_and_Health/Resources/Issue_Briefs/Park-Safety.pdf. Accessed April 23, 2013.
  • Park SafetyAnalyzing Safety around St. Louis County Public ParksBased on Crime and Population DensityBy: Bradley Lewis Date: April 25, 2013References: Donahue, Ryan. “Pedestrians and Park Planning: How Far Will People Walk?”http://cityparksblog.org/2011/05/13/pedestrians-and-park-planning-how-far-will-people-walk/.Accessed April 23, 2013. Federal Bureau of Investigation. “Crime in the U.S. 2010: Caution Against Ranking.”http://www.fbi.gov/about-us/cjis/ucr/crime-in-the-u.s/2010/crime-in-the-u.s.-2010/caution-against-ranking. Accessed April 22, 2013. Gerken, Jim. Operations Manager for St. Louis County Public Parks. Lord-Castillo, Brett. GIS Programmer for St. Louis County Emergency Management. Markman, Joshua, Nancy G. La Vigne, and Samantha S. Lowry. “Evaluating the Use of PublicSurveillance Cameras for Crime Control and Prevention. September2011.http://www.cops.usdoj.gov/Publications/e071112381_EvalPublicSurveillance.pdf. AccessedApril 23, 2013. The National Recreation and Park Association. “Creating Safe Park Environments to EnhanceCommunity Wellness.”http://www.nrpa.org/uploadedFiles/nrpaorg/Grants_and_Partners/Recreation_and_Health/Resources/Issue_Briefs/Park-Safety.pdf. Accessed April 23, 2013.Civic Problem Parks are supposed to be a place to relax andenjoy the outdoors. However, are the parks we goto safe? Crimes are occuring in and around St.Louis County public parks. To make parks safer,we have to know where the crimes are happening,what they are, and how to make the parks safer.Solution I want to create a workflow that pinpoints theparks with the most surrounding crime andspecific type of crime. My main product will be aspreadsheet that shows the names of the St. LouisCounty parks with corresponding crime andpopulation data. This data can then be assessed and analyzed bycommunity planners, law enforcement, and parkmanagers to promote and develop safetymeasures in and around parks with a highdensity of crimes.Results and Analysis The total crime map shows that many of the parks in thenortheastern area of the county had more crime occur in or nearthe park than the central and west central parts of the county.Advice Consider the type of of crime to examine. After assessing the data and mapproducts, prioritize which parks to allocateresources to. (Some may include CastlePoint, Spanish Lake, Bella Fontaine, andLemay.) Survey and examine these areas around theparks. Look for reasons crime may occur inthese parks. Do they have lights? What kind offacilities and programs do they have? Is therea school or police station nearby? Are therecameras? Fill out a detailed “inventory” formwhen doing this examination. (St. LouisCounty has no cameras and no or only onedusk to dawn light in the parks in thespreadsheet below.) Based on the inventory form and which parksyou want to center in on, focus budgets onadding facilities to bring the communitytogether. Extend and implement communityprogramming and the hours of park operation(with current or added LED lights) by havingprofessionally supervised recreationprograms. Cameras can be added, but do cost more andneed to be monitored by trained professionalsand integrated with other policing functions. Cameras may displace or avert crime from theparks, but police officials can identify theareas susceptible to crime displacement andplace officers in these locations.Workflow and MethodologySelected only parks with names in St.Louis County (total of 68 records).Selected layers based on type ofcrime: Crimes Against Persons,Crimes Against Property, and Qualityof Life Crimes, and exported them asfeature classes.Spatially joined the parks and censusblock data, and then the three crimedata features based on a 0.5 milesearch radius.Added fields and calculated based ontype of crime divided by populationdata.Exported to .dbf file and then saved itas an excel file to edit and clean thedata.Park_Name Castle_Point Lemay Spanish_Lake Bella_FontaineC_A_Persons 467 202 573 1729C_A_Property 1175 672 1619 5335QOL_Crimes 469 350 390 2608Total_Pop 3016 2726 6948 15622TotalCrimes 2111 1224 2582 9672CAPerson_ByPop 0.155 0.074 0.082 0.111CAProperty_ByPop 0.390 0.247 0.230 0.342QOL_ByPop 0.156 0.128 0.056 0.167TotalCrimes_ByPop 0.700 0.449 0.372 0.619