20250306 11245200 1.0 FALSE swVolumeSensitiveBasins 002 445356.744133 692604.588875 1180699.254126 1426775.263942 1 Projected GCS_North_American_1983 Linear Unit: Foot_US (0.304801) NAD_1983_StatePlane_Florida_West_FIPS_0902_Feet <ProjectedCoordinateSystem xsi:type='typens:ProjectedCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/10.7'><WKT>PROJCS[&quot;NAD_1983_StatePlane_Florida_West_FIPS_0902_Feet&quot;,GEOGCS[&quot;GCS_North_American_1983&quot;,DATUM[&quot;D_North_American_1983&quot;,SPHEROID[&quot;GRS_1980&quot;,6378137.0,298.257222101]],PRIMEM[&quot;Greenwich&quot;,0.0],UNIT[&quot;Degree&quot;,0.0174532925199433]],PROJECTION[&quot;Transverse_Mercator&quot;],PARAMETER[&quot;False_Easting&quot;,656166.6666666665],PARAMETER[&quot;False_Northing&quot;,0.0],PARAMETER[&quot;Central_Meridian&quot;,-82.0],PARAMETER[&quot;Scale_Factor&quot;,0.9999411764705882],PARAMETER[&quot;Latitude_Of_Origin&quot;,24.33333333333333],UNIT[&quot;Foot_US&quot;,0.3048006096012192],AUTHORITY[&quot;EPSG&quot;,2237]]</WKT><XOrigin>-17791300</XOrigin><YOrigin>-41645400</YOrigin><XYScale>3048.0060960121928</XYScale><ZOrigin>0</ZOrigin><ZScale>1</ZScale><MOrigin>0</MOrigin><MScale>1</MScale><XYTolerance>0.0032808333333333331</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>102659</WKID><LatestWKID>2237</LatestWKID></ProjectedCoordinateSystem> 20250502 15532000 20250502 15574000 150000000 5000 NAP Version 6.2 (Build 9200) ; Esri ArcGIS 10.7.1.11595 swVolumeSensitiveBasins 2025-05-02T00:00:00 1 -82.654843 -81.886809 28.258746 27.580360 This dataset identifies volume sensitive areas which are defined as systems that do not have a positive outfall for storm events less than or equal to the 25-year, 24-hour event. In addition, sites which do not directly discharge into a well-defined conveyance system (e.g., ditch, storm sewer, etc.) are considered to be volume sensitive as well. <DIV STYLE="text-align:Left;"><DIV><DIV><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>Throughout Hillsborough County, there are many areas prone to flooding. Many of these areas operate at or near their maximum capacity, yet they lie within the path of future development. To overcome any adverse impacts that may result from future development within these areas, the County has classified certain receiving systems as either peak sensitive or volume sensitive areas. Volume sensitive areas are defined as systems that do not have a positive outfall for storm events less than or equal to the 25-year, 24-hour event. In addition, sites which do not directly discharge into a well-defined conveyance system (e.g., ditch, storm sewer, etc.) are considered to be volume sensitive as well. A detailed analysis utilizing the latest approved County Watershed Management Master Plan (WMMP) models was conducted to determine the peak and volume sensitive basins. The complete methodology report can be found on the HC Watershed Model Data SharePoint site.</SPAN></SPAN></P><P STYLE="margin:0 0 0 0;"><SPAN /><SPAN /></P><P STYLE="margin:0 0 0 0;"><SPAN><SPAN>The project to update the peak and volume sensitive basins was completed in November of 2022, and the revised basin designations have been used for permitting purposes since July 1</SPAN></SPAN><SPAN><SPAN>st</SPAN></SPAN><SPAN>, 2023.</SPAN></P></DIV></DIV></DIV> Hillsborough County, FL WATER STORMWATER BOUNDARY REFERENCE VOLUME SENSITIVE <DIV STYLE="text-align:Left;"><DIV><P><SPAN>Hillsborough County makes no warranty, representation or guarantee as to the content, sequence, accuracy, timeliness, or completeness of any of the information provided herein. The reader should not rely on the data provided herein for any reason. Hillsborough County explicitly disclaims any representations and warranties, including, without limitation, the implied warranties of merchantability and fitness for a particular purpose. Hillsborough County shall assume no liability for: 1. Any errors, omissions, or inaccuracies in the information provided regardless of how caused; or 2. Any decision made or action taken or not taken by any person in reliance upon any information or data furnished hereunder. This dataset is provided by Hillsborough County for informational purposes and Hillsborough County does not guarantee the accuracy or content of the data. Hillsborough County is not liable for any deficiencies in the dataset or analyses/applications using the dataset. This data should not be construed as legal advice or legal opinion on any specific facts or circumstances. The contents are intended for general information purposes only, and you are urged to consult your own lawyer concerning your own situation and any specific questions you may have. Infrastructure records, drawings, and other documents have been gathered over many decades, using differing standards for quality control, documentation and verification. All of the data provided represents current information in a readily available format. While the data is generally believed to be accurate, occasionally it proves to be incorrect; thus its accuracy is not warranted. Prior to making any property purchases or investments, or taking any other action based in full or in part upon the material provided, it is specifically advised that you independently field verify the information contained in county records.</SPAN></P></DIV></DIV> Feature Class dataset EPSG 5.3(9.0.0) 6665 Simple FALSE 6665 TRUE FALSE swVolumeSensitiveBasins Feature Class 6665 OBJECTID OBJECTID OID 4 10 0 Internal feature number. Esri Sequential unique whole numbers that are automatically generated. BasinName BasinName String 25 0 0 NodeName NodeName String 25 0 0 AreaName AreaName String 100 0 0 AreaID AreaID String 5 0 0 SubWatershed SubWatershed String 100 0 0 BasinAcres BasinAcres Double 8 38 8 FinalVolSensitiveDesignation FinalVolSensitiveDesignation String 50 0 0 SHAPE SHAPE Geometry 4 0 0 Feature geometry. Esri Coordinates defining the features. SHAPE.STArea() SHAPE.STArea() Double 0 0 0 SHAPE.STLength() SHAPE.STLength() Double 0 0 0 20250502 /9j/4AAQSkZJRgABAQEAYABgAAD/2wBDAAMCAgMCAgMDAwMEAwMEBQgFBQQEBQoHBwYIDAoMDAsK CwsNDhIQDQ4RDgsLEBYQERMUFRUVDA8XGBYUGBIUFRT/2wBDAQMEBAUEBQkFBQkUDQsNFBQUFBQU FBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBQUFBT/wAARCADIASwDASIA AhEBAxEB/8QAHwAAAQUBAQEBAQEAAAAAAAAAAAECAwQFBgcICQoL/8QAtRAAAgEDAwIEAwUFBAQA AAF9AQIDAAQRBRIhMUEGE1FhByJxFDKBkaEII0KxwRVS0fAkM2JyggkKFhcYGRolJicoKSo0NTY3 ODk6Q0RFRkdISUpTVFVWV1hZWmNkZWZnaGlqc3R1dnd4eXqDhIWGh4iJipKTlJWWl5iZmqKjpKWm p6ipqrKztLW2t7i5usLDxMXGx8jJytLT1NXW19jZ2uHi4+Tl5ufo6erx8vP09fb3+Pn6/8QAHwEA AwEBAQEBAQEBAQAAAAAAAAECAwQFBgcICQoL/8QAtREAAgECBAQDBAcFBAQAAQJ3AAECAxEEBSEx BhJBUQdhcRMiMoEIFEKRobHBCSMzUvAVYnLRChYkNOEl8RcYGRomJygpKjU2Nzg5OkNERUZHSElK U1RVVldYWVpjZGVmZ2hpanN0dXZ3eHl6goOEhYaHiImKkpOUlZaXmJmaoqOkpaanqKmqsrO0tba3 uLm6wsPExcbHyMnK0tPU1dbX2Nna4uPk5ebn6Onq8vP09fb3+Pn6/9oADAMBAAIRAxEAPwD9U6KK KACiiigAooooAKKikk2KzHd8v90bqhtblby3jnjL7ZF3LvVkb/vlqALdFFFABXn3xa8HweKPD8dy zQrPpTveRfaOUb5G3K3t/wDE16DXAfGrWbvQfhzqV1YrE91uijTzjtQbpUHzVcL8ysa0m1Ujbe55 t8GdWttG154rmFWuFii03el15vkfc/h/22df++f96voivinRLyO88VaU2uRLpt3FPvSVImi8pdiP 87/8tdiJ8v8AFX134e8V6R4mtjNpepQ3qrjeqN88f+8v3l/4FW+IjaV0d2Oivacy6m3RRRXKeYFF FFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABVWa4S3UM 24/Mq/KrN941arg/HjDRdM0zUGtrrUbmxu4/s0VvJtlkZvk+f+91+amNa6HbopV2bczbv4f7tUtT 1Q6fLaILS5uftMnlbreLf5X+0/oteRap8YtaurywjTRpNGs/tKtdSSS7pGiT/Whfk2f+Pf3P71dN 4iXUdP8AEXh+5stRuG02UwWqkz5jkf593m/7yfxf3v8Aa2Vp7NrfQ3dCcbc2l/6+87XVpr7yohpq wyS+cqy+Y3Cp/FVDxP4w0rwlo1/f3d3bD7JEzeS0yIzNt3BP95qyfHfi+w+G/htWV4bedgkdqswZ kHzom5tv8K71r5o8cWDaTFqc8t9PrFxcean2v7jys3zumxt+3/4lKqnSdS/Y1o4d179EutjXtf2q PFGo3VwbW10+dLqVoraKYqix/wBz+Pdu/wC+vm/u1e8EL4t+M15Jpmp+JL+bRYmSW6uLTykU/uvk /g/56qrf8BevIrP7Df3CWdzdSXOnrL5v7nf5Stv2f6rfu3f/ABr/AG69l8E6xaeD9PiuYtNb+0fE VxLbQ3C3Lr5ETNFuZl+T+OVvn+Vv9qt5QUY3W511KUYQ5orU5rxNouoaL4luLSJp7P7K0sv9t6nE yPLEvyfIqJt+58q/L/HXtvwd+GaeFdPi1SHVbXUpbuKLbNFZ7EWMhWcJ82759qct/cX5ay/HHg/x Br1joPhs6wuoJ5bpqLQ7EuHVnTypfm3tsX+L+9t/3a9Q8JvfyaJC155iszv5SXEeyVY9x2B/m+9t rGpUlJWuclbETqRSbOb8ceLtb8I2eq3KWtrNH5qrp6lGbeqxKztI2772/eqrx90Uuk+PjrHw5tfE Ye0s4/Kf7XLJuaKJlVl3qq8su8L8v901B8edMGo/D25k3XA+yyJOFtVZnf8Ahx8v+9Wr4Y8EpoPw +TQreZ5HkhlJlu13Ykl3M+9V2/Luc/LxWb5eRdzL3PZrvcp+FviIPEVvpHmFIXvY2gLC3lTN0i73 2qw/1W35lbdXHfDv42az4s+JFx4f1KysdNtUVnX5ZVd/7uxn27v++K2tF8CeKPDd0jHxWIbJ1WKd 5hv/ALqIkSN8sX/xT/xVwmufsu6lF4uTXdM1yS+R7pLieG8bZcN8+5v3q0Ll1FH2eqPoHVLi5t4o 2tLX7TK0qKULhdq7vmb/AL53Vo1Sv5ri3sbiS3g+1XCpujg37Nzf3d1K32iex+X/AEWdo/8Af8ts f+PVmYFyiuUuJtU8M+EdQuL7Uob/AFCBJHjupIPKT/YVkWrHhjxbpviSH/RbmL7Siq01vvy8WVH/ AH1/vU7aXL5Xbm6GvqE8tvY3E0EH2iWONmSIH7zf3a+d9d+NnijV49S0+xW30u7tAwmltY/NniZN +5HRvu7tlfSlcNqnw30vUdUv9SvBGXmVVX90qLGq5Pzf3vmZm3VpTlFP3kb4eVOMv3qujotK1a31 C1tVFzE9zLAk23cu/wCZfvba165Twz4Z0i0sYL2wtbU3bRZS6XMu1tu35Xb5ttdLDv8AKXzWVpNv zMo+Ws2czViasldctzpT6lIJLS2RGd/tEbKyqvfbWtRSEVrW4jvLeKeBw8Uiqyv/AHlqzRRQAUUU UAFFFFABRRRQAUUUUAFFFFABRRRQAVzdrpzR+I7uSSOb7Iyq6eZcmWIybm+6jfcb/drpKiV927/Z /wBmgDmfHWq6BpulltfWG4t/vx2zpvaXb97av8X3v1rgNa+MlpoXhmzi8L6fNc7dkVsJV+TyE+82 N+77inarY7V2Xi7wXZ+N0vNPlW4sLxfLddWigUOMPvVUb/ZqDQ/Afhvw/bnUrXT1+37flk1Jm37m +X5t33d1bRcEtdzqg6Sh76bf4Hyn4n0efUrPU9T8Q6naTah/y9J/rXi3S/wf98f9817T4A+F9vZ+ BdatItF0u8muI5fst35wnli3W8flbfvbd252+8vUf3q2NQ/Z/wBAuhq1m2ryK88X7q3kKYtld/7q 7dy/Iqru/uV67p+nw6dawwQqqqiqnH+yu2rqVE7cqNa2IjKypqyPk+1+ELxWGr6nrttF4d0yzgi2 TSwbXllaXd9zbu3fcT/arxya51C80vUFgs7m5df3tzNNEm+Lb/f++23f/f8A7n+3XtP7SHjbSrX4 sW8UYe4lt9M+z3iW77PNZvN2Rbv7y7t9c7oPg1fE3iCXQdVu20q6l05pVmuLrZ9qbY7+VLt+79/e +/d9ytoyvFzZ2Qm5U3Uk/lY9D+DnxH06+8HWGgajdw3V8VmtLq11O7k33O5dkSxP8y7W+7/D0r6N s/8Aj1h/d/Z/lX93/d/2a+UfBvwS8vWfsOoXljC0TNKkVpdM12qxPs81Itv8Lq3/AH392vp/VrXU bnQbiCyuRDftHsjuPugN/e/irkmldWZ5lWMFL3Xe5pSRLNG0cqq6Mu1lb+Kq9laR2tnFbIGSONdq L5jN8o+781GmWs1pYwQXNy93PGu17iRVVpT/AHsL0q9WZzhUUzSKn7tVdv8AabbUFzqNtaTQQyzK ks7bY1b+I1coGFZepa9Y6RcWsN3dR20t1J5cKN/y0bjgf99LWizhFZj0WvIbnTtP+N2oQSzXN9pc vh658yKexlTZIzOGX767vuxp/Cv32ppX3Kir6vY9T1S1TUNPuLd4oZkljZfLuY/Mib2Zf4lrzb4h /C06rZ21/wCF3j0e8tlaVVsx5Xm/I23bt/irstGuNVXzJNWuNPVJ5VSzjtNxDL8zfeb7zMvp6Vf0 6ZbiWaWO8imtdqotuhXELKW3fMv+flqlJxeg4ylTd4s8e8E/tCWs82haFqGn3bX0yQWkt15n/LVv lDvv2/eb/gXNe5fJMrL8rr91q4j4kaPp0nhu9u57a1hn8ryPt00W/wAhX+Xd935uv/j1VtOs3+Gf w/vrq2nGs/N9qj8tPKQ7lVf9r5f4qbtLVFyUJK8NPI67fb+H9Lcyxw2trbhsJCmFVd3y/KKwvB/x O0LxhM8Nrc+VeqzJ9mnK7229Su0/MPmFW9c0vTfF2khdUjuILCNvPJlbyg6j5vm7qv8AvbW47VxN v8D7K11K11LRNV8i3RvNi85PtG0/KysjbvZv++2px5GveepVONJxfO2mepWd4LoSnypIdkjRfvV2 7tv8S/7NXapHUbYSQR+dGZZ1Zok3f6zb121drI5gooooAKKKKACiiigAooooAKKKKACiiigAoooo AKpanZ/2haPAJ5rbcV/ewNtcfN2q7XPaDqdteaprEUEF1DPHcgzi4TaG+XYrJ/skR0xl+SK+NxG8 VyvlF8yJLFuOzb/DgrtO7+9urG8QQ6fC8+orpv8AbFw7QJLBb/O/7p22tt/2WY1t6rp/9pabdWiT yWzTRtH50P349w+8teY/DP4b6P4D8UeIILcapPd3Ea+bqFxbeRD838MTqF3N/u/3aBq1r9Tcj+Hs T6xrN/qkl1eprCLD5Pm820W3ft+X+6y/Lt9a4X49/GC58JWMWh6VB5U17FLbyTX26IoufLVkLf8A Am3f7FdF8UfFuix6Drlrf+LG08xIhWLTW2XETfc2M38Ss3+7Xx34+8da34u1FdQ1u/8ANutqxbtn 7lYtqbV+R32/xu9axjfWWx0Qg2+aewW1m15dPeS+Rc3tvdL9qmml817pd+z5Eb7zb97bq6i/1u8+ wSy6hYxzSrffL9oZ0lX5PuSuqbvub/8Ax/5KxfBnh6fUr+3ljijfVftW+ztHgd0nb/Y27Pl3/wAb v/31XuFx8AvEmoLo13fXjXE01ykt1DIu7yGd23Ps+7sVdvy7u1dV4xVm7HouUIwtJ2ufPMNx4p0X xpLPaare3niW33eVcW7M+5WTa/z791e+/AnXtbXxza3Op6xqGpy6tB5c9oFWXaV+dHeWT5lRVd/u 17X4s+EfhzxVpWqrc6TZT6teWht21BoF87eEwrbsfK33TXlfwR+D8T6TqJvVl06SGYWu61ucSsyn 96rn+43y5X7rVgpRlFto44ypyhK+h75oeu2/iLTYr603G3l5TcuNy5+9UWuNq83kRaZ5UJaVGknm G7bHvXeoX+8V3VheBdL1HS9Q1e2kxDokMgi0+1aPZ5SL/c/2Pu1hfET4veHtMjudGh1yOK989bW9 Nqd0trG3yu/+8tYcutkcjh71olWb4oeCIfGF/eapdNb6hZbrVZbj95Cdvzfutv8AFVX4vfGibwfq OlaTpyxh9Qg89rwyJvgXd8vyN/7NXiXjzwnZ6l8V9Vg0SBtala6+1T7bX77Mrysif/Ff/tVSm1Jt bv4lklV/KgZ99xP867UiRETciL9xK640lJpnpUsOpuLv8j67tZ4tS8B2lze38yJNZxTSX0DbX5VW 3gr0qgPCemaH4Nn0y4ttNZJofJl3t9liuB821Wb5m/nWd8HfE0mteHobO5jaO4tYInX5fuxsPkX7 votY3jrUPGV1rktpH4U0fW9KiuU+xx3wd33bf9b93b/e/wB2udxcZcrOGdOUJuD6F2TwfaeLfBGk 6LqNjf2U1jfBVisL5ZZbBk3bG83+7sdf9ra61laDD468A3lxaTXdnrvh2P5or3UblbeWV22/IrfN 82/f9/8A8dqj4r+IXxE8L6xoNlBoeizXWuzS7LRXZWGzY2GdmRd21tv+1trcs/Aeg+KfDcF1deGt Ra5tLy4uFs7yfbL5rv8AP827bt6f98/72VtuLWK97qdlqXhS28W6FBY6rdyXsccm6byGMCzujfxB e25aoxeFNF/svT4byB7e1s5fMsbaW5dfLwoYo2H/AHn3Xbnd8tYV9Ya7f+ME1lG1OwtWgigW3Sf5 JZVlf5XTZ8qf3n/2vlqP4/eC9Z8aeE4rXRmuDdxS71hhVNjt/tbnXj739771T5XIXRXLd74m8Vrc 2V7a6PBr/h+63Ya1kVXkjcZiZlf/AD81X7fxtYR3UVk8E+jmSb7PbWM9ttadfVF/g3My/e+X5f8A eqp4Q8WWngvwTodj4p1D7HqsVij3K3cm514b73/fD/8AfNeQy+LNS8S3kPiS7ttS+w6ffW8s8tvA +2LZcbtn3fn+R0+WtYQ5r30OilRVS99Lfiz2Wz8DnUPFltrmp6jduYf3tnpzvt8jpuRtvysqt/Jf x9CrzjwN8UvDfxEvY7iztruK/gaW3RLyzdXRfkZm3Y2hfud69HrKV9mc0m3o+gUUUVJAUUUUAFFF FABRRRQAUUUUAFFFFABRRRQAUUUUAFZ+s61YeH9NlvtSuo7Ozi+/NLwq1oVieLNGHiXw1qmlhlVr u2eFXYZVWZSFb86APjD40i68ceJtf1nw7pt3daKjf8fMMUoidtiea+7Zs/g/i/8AQq8+sPDep+Ib /U20+2vnii3PPK9q8rwLsT7+1K+/vhx8PdO+GXh4aLpks0sHmtNvuH3Nubr/AOg1uWej2Om3F3Pa 20cMt4/mzsg/1jf3mrVVGtEdPtrKyR8y/syfDfW/D/imbULzR5oNJSBpra4u1aJ/MlVM7U/i+5/4 /X1JBJJJApkVUl2/MqndtaqGof2lcWc62fk29yr4jaYblZa1E3bfm61m3zamU5czuOqlqF9DpdjP eTvst4VaWRlXPy9au1la9Z3Go6Tc21tdy2M7p8s0KKzL+DfLSMzz7wH8efDnirRJL6/vLbR5Y5/K MdxLt3f3dv8An/0Kq3gVvC2uJq+nR+EbzR76Sz33hmtH3srr9xZG+bd/s15R8Nf2ZbnUbqbU9Qvo rGxh1H7XaWUP+lQybd6Orqf9xf8Aer6UvtEv7rxLpt4moiDTLNHP2COD/WyFdqsz5+6oZvl+laOy ehvO0bpHjHg3w74j8H+MbbUrnS49L0IM5a4mvFVYoG+8jY+Xrtb5v+A10nx41TT9P8JxT/L9phvM r/Bj5BK7L8vzfw/N/eb/AICdXx18RvDfgbVYNH1eO/v31BYwlrBb+dHGnzbfl/4B/vdK4/4nL4W8 M+MvCMqxWej6hdPJLJfSwb3SLZ8vz4b5t+35f/2qtSk5KTNlUnKpGo90YXwX+Jml+F9LuZdZkabU 7o+UrRSxN+6i+7uX5dv+t/8AQv8AgXaa9oHxC1REvPBHiWy0/Trq6aeRtRt53uNmNv8Ay13/ANz7 qon3q8O+Gfg7/hY02v22j61Dozq6fIYm2z73dNrt/e+T7n/stfSnjqfxV4f8HaVY+GR/aOuyyxWp urmBnRVx80rf3fm2/ep1LX31DEWc7p3fU57RfiL4t/tKystR0nbJb2sUt1D9ndp5f78qhOF+Rd23 +8+2u5bwqmo6fqIl1E6kLtmEQuv3kUS79wXarLu2t/tfw1J4FXVJtBt7/XbW0ttbvI1kuhaRsg/2 Vbd825V45rp3+ZDhtv8AtVjJp7KxhOalblVjzh4fDviLxMvhqCXU459HKzOLW9lijVt2/wCb5vm+ bb/31WP4s+LOlafZ6rqVn4ie0k025jtZ7W4tGYsyvKuF/wB/H/jg+7urtrHUrzRfD97deIZrJ7mz Znkaw+UFdvy7lbo7f+zCvM/iVZ6d40+EfiHVbSzS1ubtt26xk3fafIdn3L93d/Hu/wB1quK62Kgr 6202Oi+Ifw7sPil4PtLjTL630WK6db+TUVt13zxNA4+b7v8AeU9f4ab8H/CdtZ+B3064nmuZL+3W WdPN82JVZNmVbbt3Nt3/AN7kbqyvhH4m0v4j+HfDdhGFFxoVqvn280O+Jl8ryv8AZ+baf7vG6u5b wVJZ+KrPVdJv49Ms4rZbWXT0ttyyJ5hfg7vl+8f4am7XusXNJXg2VPhr8J9N+G02pT2s8l9c30u5 7i4Hzqv9z/vqu/rK03S5rS4v5Z7xrkXModUK7ViXbtCrWrUt31ZjKTk7sKKKKQgooooAKKKKACii igAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKAPIvB/wt1Hwx8UNT1szxNptzFP8AMCS/ 72VHWJF/5Zqmz/P8LrjVvEdh4u1SDRL06ra6b+7l0qeJmla4n/eI3m/88lV/9n7tek2+tWtzpSX8 TubVk3LJ5TZ/75+9Ul08dqJJUjD3DLu2rtVpdv8AD81Vza3NHPmd2jz7xp4g8VaD4OtrwaPa3viG W5WIxW8PmosfzM+0btzfIleGftCa0zfEy986+nhnsVijs4UZdm37Pvf/AMfr6A1bwzbal4T1gab/ AGhbaxIrSZjuxLewXPk7VXezsqPtbZ977rfe7188eHPhZrOueJdQ+0XkVtrqwfaLO11Z2llv1aLZ vd/vJsdW/grWm0ndnRhpRi+aTsUvg38RIvC8moTLqq210itstLhdyS7t331T+Lf/AHP9uvV/A/x0 m8aSWvhjW7VtN12YKk8trMYPmaT+H+Jfk/8AHq80s7/S/hTajS9W8Kzf8JH9n+0PqqyLceRvl27W X7nyMu35Grk9a8QT3mpWWq3kSzSywLFLsXZ8q/O/yf7+z5kf+D/brpcY1Vd7o73Tp1oa6SXXuj6+ 8TfFTQvCdxFBevOyy2y3MbRLv3IzbRx96uxhuI7qFZYJFliZdyurblavjvwnJatrVrBbQyapb/dt neJmf5kRPK3v9z/ZSvbvA90Ph7pt1L4mmu9LjaZlthdT+bF5ef4VX7v+8396sqlFRjdO7OathY04 JxleXY9SvtPttSt2t7qGO4gf70cqhlaornSbW502bT2iVLOaJoXjT5fkZdpFQ6P4g03X4Xm06+t7 2JeC0Eofb/vf3apaX420nWNSn0+ynkluLfcJP9GlVF2/7ZXb+tcp51mc7ofww0PwX4uuvEMFx9hi uFS3isg2y3V2+XP+0zfLXYatrEOkLa+du3XU6W0e1N3zN/7LXmHxV8E6V8RPEFrpp8Qvaas0DKln 80i/L/HhflRh83/jtejr4f0+7t9LN0q3sun7TFcP94Ov8X5rTfS7NJdHJ3NS1WWO3jSWTzpVX5pN u3c1Wazf7atG1yTSPMH21IFujGe6Mzrn80atKpMgooooAKKKKACiiigAooooAKKKKACiiigAoooo AKKKKACiiigAooooAKKKKACiiigDifHF7eXegXo0HWltNTsm3eXAqSvLIqbvs/zf3vl/2q4zxQze NfANpL4m11/A97cRSwS6fDPjY0qPs83+LdsG7+H+KqWsfA2ws/H1x4n1bxFcLDe6ir2lrENmyRpV fbu/4C1drqvwp0LVP7aufIazv9SmEk+ooytK4X+HLfdX+HbV6I10jZpnkem+G9Z+AurxQW/iG68Q T6hLCskBgZt7tti3y/8Asvzfw16n4n1uzvvDeta1pzX19eWNs8DR2ckqfO2z5l+dfu7f4G/vV8+f EzxlqXxL8dfZvD5XS70Trpv2WNpWS8/e7Vmd/K2bf9V8r/8AstfQvw9+GNz4F+3SyaguqySQrBCr K0SbB/eXLVb5eVX3NZcnIr7r+tT5j8YeNL7x9DBca9PHbTQt5VtbxRSvbr8n8T73Zmf/AHN3yr83 y1yfiJJYbPz7lo7bUImZGt0idP4Nn3Pu/wAFfWGgXHhr4hS65aWOl2+i6lBDNaxtDZ/Z72L7yS7W wv8AF/6FXyz/AMIfqGm6l9hufItkeeX7T/0y+fZv2Mn8G+t4S5k0kd9GXMnCMbHtXwU1TXp4tQXS oLaaK3tVivopv4tqfJs2v8zv8/z1614d8N6VrEmpX99ps0slxP8AvbbVYVkRG/2dyf8AAf8AK15F 8IfD7+Fda0ZL+xhmudUVWW3vmVJli+7u2v8A3du7+82+vp1m2qTWdaWunU5cTP3nbrbVHLaV4V0T wfd6pqlrFDp0c6rJKVVIoolVfmx02j5dzV5z43+KKeCdYimt/Dt7JBAggtHaby7Wd3b70Q+633vv V6jcagNU0PzIrDUJFut0fkp+4mX7399l29K8rsfh7d+M/Gd3d6ppZtPDy3vn/Z7rdvkddn31b7+5 l/2l+ZtrVELXfOY0uXmbqmx4DvrXXvGr3dxpFvDcrbyyLe/ZpYnaTcqvt3/738P96u/8O+F7bwz9 uFo8zLeXL3TrK2VVm+9t/u1k+LvBf9saDa6Vpph06JblZW2Ls2oG3sE2/dO7bW74c0OPw7o9vYRS yTJEMbpmyxqZtS95aeQqs1UvNaX6eQkVuya7LObSEK9sqPdZ/esVdsJt/ujezf8AAq16rXl1FYWs tzcNsiiVmZ/7q0+GdLiJZY2Dxsu5WX+IVmc5NRRUEc8cxcRyK21trbW5VqAJ6KKKACiiigAooooA KKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigDxuTwP4u8TrcWmoam1npcd55sAuds0rxbH Xa3/AI7/ABfxtVHxl4T8aTeOIJoYv7W8N7IFlt5JwyzsndonZdrblDfJXr2paxDZafqE6yws1mjN Isk6xqny7vnb+H606DUoptoIeKYruaOUbXX7u7/0Jfu1pzs39tLayt2KOq6fZSQzz61Hay28Vwtx Cdu3bt2sv+825c1k6l8WPDOl6Ta6k2prc2907xQGBd251+8v+z/wKsXxPqFp4N8Qw3kmp6i91eTt JLavc/6OkHlS5b5l2hU27qzvCvwP0ax1hL+9nvtdVAs9sLiVfssbfL92JW27l2L/AA7fm/75my6k JRWsjvvDuk6XJM3iC30r7BqOpxLLO8sWyf7q/I9Yd18J9GnOrStulutTuvtL3VxFFM8X95E3L8q7 dy/8DNbniGLU7HT7m90S2+3arhVW3uLl1hb5vm+UttXio/CPiZdbie2up7Q67Zt5d9a2jZET/wDA vm2/do16CvK10zC8ZeBbDxFq+lzu+of2jpUPm2arDvt2Ktn5srt3fKvRlau10pribTrZ7xVS6aNW kWP7u7Hasvxpq19o/h2afT9JOsXpKxJZK3ytuO35v9mtq2RUt4kWMQqqr+7X+H/ZpX6C5m1Zlmik zzio5o/OjZdzLuXbuWkScf4X8Taxc69daPrOmrbyRR+elykqlXXp92unsYbiKJluZlncyOyts24X d8q/9802LS7WG6S68lXu1i8v7Q67pdv93dUt55/2OX7L5f2na3l+Z9zdjviqbuVKSk9FYz9Y8Tad obrFeTujsu8KsbMdv/ARWtEyvGjJ93b8tcNr1xo260i8Rgy6wkG5obUS7NrMeu35cfK33vSt7S/E WiPb2tpZ39sVCrFFEJPm/uhcVcorlTSZtKn7ilFPrft8i5rlze2uns+n2Rv7r+GLzFT9WrnvhppN /oui3EWpQyJeSTtKzzMrNL8qjd8rt6V2tFRzPl5TJTtFxtuFFRSTJDG0kjKiL95mpIZkmjWSNldG +6yt96pIJqKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKx9aXUm+wtp1zb24W 5Rrn7QhO6D+NV/2qAMfxZ4j0PwpY6jfXF1HbOzL5v2fa80rqg+Xb/e2bf+A1v3zNvSOND5sqsol8 nei/71cL4NXbo+t6l9kl0ODUNTe4kk1SVdyrtRPNX5dq/Mo2qa6fUWkutSSwkivp7C+jz5sO0RQb f7zZ3fNlfy/3qCvI574q/CHRPidZ777zbbVLeBkttQiZt8X8XC/davLvgb8a7fA0K/uotjJNPHqF 3P5UUYULtTY33f4v4q+gyLX/AJB7TAM8fy2/mbWEf3fl/irzvxd8I/B7aNcBdAsbSG3dZpbh5Wt1 gh3bpSrL/dVd2z7tWpaWZpCS5XCXU729mg09bnWAt1dYtwfIt90pZV+YbY/73zVkLo8P2p/E+nWL QavcWrL9lu28jzWO3aJOG2t8orT0ya6vtQjvILy0uNAltka28sbpGc/x7um3bWzJGsm3cqtt+b5q lOxnzNbHMeGPG0eraDbX2qWzaBcSSeQ1rqDqn7xfvBW/i/8ArVf1bxZYaKkEk8rsk/EXlRMwb/gX 3apeONB0rWrK3m1iRUsNPnW8kE2GibZn5XVvl/irltV8YWWuTSeEbXTLuDUIyqxboUSIbX+98rMy r8jfw1cYqTV9jSnGEpJS26+h6PZ6hBqFlHdwSK8Ei7lerKMsi7lbcrdK8nsfEVn4Oglg1e7t760u /wB1FZWk/mvu/j+Vtu371dzoMdlfW+lX+nYhs4rZoI7cLjavyfL/AMB2UThyvR3RVamqcnyu8ejO ioqpcQxXDQs+7MbblwzL82Cv/s1W6zOc4Lxx4Xur7UI9Ss4/NdYBFKu7DFVZmTH/AH21cToiRw69 ZXKN8jTxblX+L50+evZYI7lL24aSdXgbb5cPl7WT+9838Vcfe6Tb+B7i51u1tDPExiQQtMyiHcyp 8ibTx93/AMerupV7U3Sav2PZw+NcaLw8le+i+Z31Fcp4R8cWviq3ZdotLxXlVrVn3NtRyu5f7wrq 645RcXZnkyhKD5ZKzOc8XeG/+EktLeISLC0Mvmh2Td/Cw/rU/hfS7nRdKS0uZI5vKOIzEv8ADW5R T5ny8nQr2kvZ+zb03CiiioMgooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACuQvHPiDUL jStW09Y9LlG2FpbnbLcMrfP8i/w/d/ztrJ+IHxK0zwyfsDa3baZqW5H/AHyo5dd33F3MqqzcDe/y ruritU+NXg2+8SWEuuag9vaW0iTQWtxAsqs0kS8ttXCmLLfxN96nZ9SrM9g1TStP8YaHPZ30DXWl 3kXly28qsm9f0asjS7O1+Gvhi10+C31HUbaKSTb9nje4lVWdn+b+L+KqHxI8V31p4RhvPDuy++1v tFxbvu2xbHbejf3vlp/wbvLrUPhvpd1dfaku5jKz/bTudT5rf+O07aXK5fd5hdU03StU1pdatjPY eIFRbO3vLq2lVYwfmCbXXb82/b/wLj5q4X4nfET7Hq194c1DQ59R0+OTe87am8AeJ0Tcu2NMuv73 Zt+avbZLeKZU86NX2tuXd821qwfEvgnRfFy7dTslmdQUZ1+VmVlwU3L82004tJ3kVSlFTTqK6OU0 bxRf+H/h3/akHh5bW2thldPlvmeWNP8Avj5f92srRPibrvjbXtLjtNHu9Jt4p/8ASUkRnSWJhEyP v2f9df8AvmvXLHT7bTYBDaQR28Q/gRcVh6T4ba18Rajqt3JFcS3LL5Py/NGq7wo/75dqaktW0OM4 6trU6GaHzdvzMm1t3y96ytei1Ro0fSZ7eK4T5mSePcsv+zu/hrZO75cfjXnXxEZ7XUdPljvp4Xki b9ws7Kp2Mnzqv/A//QadKHtJqKHh6TrVFTXUytB+EuoJ4nXXdSv47iZ33TxTwLO7bdmzY7fc/wBX /wCPV6PfasLG+tbb7PLL5qu2+NflTavSuV8J+NkvP9B1S6X7SZfKjkddm47d21v4c429/m3Cta8+ IGg6ffrZ3GoLHcbmXyzG+dy5/wBn/Zb8qdSM+dxktUaVo1PaOE1quwy+8YSxxxR2ukX1zdSxq6xy J5Q+b+Fm/hausrCXVF8QaTctol7GJ1+RZmTcqN/u1p2fn/ZYvtGzz9i+bs+7u/ixWbttY5pWWlrM tVzPjy1lu/DN1FBG0su6J9iLuYqsqM36CtfVNLttVtfs92jyRbt21GZf/Qa8vufA+m2PjjbbSRmw VPtt+t1JuSFVZztH9z769f4UqqfxXvsaUbKfM3a2v3HTfD/wnDpOmw3s9s8Wou05O9mG1XlZgNp+ 78u2qXj7xFqvh+9Bha4hsTCv72G1Mu1vm/i2t83Su20qeynsUawkhltedrQsGT9Ky/GGgt4i0tYo tq3MUqyxMzMqA/dbdj/YZquM06nNPU1hW5q6nWV156/1Y8jk8SatqmoWuNR1D7G0TbcNLDul3ovy t8u7+Na9r8PtcSaLZtd7vtLRL5m9drZ96ytP8GxQro8l3L5sun2scCxp/q9y/wAddVVVakaiXKrF 4nEQqpRjFKxl2Wqpe6rf2ka8WZjV3/22Xdj/AL52/wDfValZdho8Vjqmo3quzSXzIzL/AHdi7a1K 5jgCiiigAooooAKKKKACiiigAooooAKKKKACiiigAorkfiBpWs6tpCR6PdyW1wG+ZYW2My/729cV meBV1Lw3pul6Bc273l+qyT3dw827y42lfbufb8zc42/7NXy6Xuacnuc1/kS698NfCuu6pqDy29vD rl9Fuaddj3Cr8q71Vwy/wjnbW3q/g3RvEjQS6pZRajLFC0KyTd1b71O8UeGIfEum3Nu8kttJKmz7 RbP5cv8Au7sfdqpo2gXWl6Q1ktz9nbai/aAzSszLFEm/5v8Acb/0KpuTv1OY1Xw/pFv4ajbwpY2t 0/h64hZYLV1kZvIZv3G4bm3Lubhu5+tdR4H1DU9X0p9R1PdC11Izx2LKoezX/nk5H3mqnp3gez8O pqM+kiC21+8F1N9okZ9jzStvdim77u/bW5otjc2uk28WqTRXt9hhPMsexXZvb/x2hh0L8c0F1GXR 0lRW+8rbvmWvL9a+NH9n+LY7C0sV1HTjtVriESq6f33+5tZVr0XS9F07w/pps7S3jtbPcx8pR8mW aquh6Hpmm2b/AGG0MUdz8zearbz8v3WDfN/wGqjyq/MXBwV3JXLk7f2ppMp0+5WNpo28m4Ubgrc/ NWRPq934dsdDhu0+13FzOlrPIjfd3fxVszQTQwKti0UZXaqROv7tVB/2f9mpbvTLa/aBriGOYwt5 kW4fdb1pX6dCVJdVoWJFZkZVbY396vKfEngPVEmW9ku5tcumHltKkXlSr/d+42Nv/Aa9arnLbxpp N5qK2cEzSTNI0WVjbbuV2U/N/vI1aUpShLmijfD1alGfPTV7eR4Df6a1zvmu42SBomXd5u9E3fx/ N/F/7L/dr0bUtfsPEHhGy07ULdru5lso5/P8pdm/5l/i/wBw13cvg3RLjzQdMtt0nVlj2sP91h93 /gNcZceAbzWNcYXAa002NvKhlt7jbtgX7iqv97+9u/2q6vbQqNXVreZ6UsVSxDi5q3Lrvv8Ah3OG 8K2t54N06ya2kke6gZXnW3ldIp9v39yJ8v3F/u16bqXxg0ax+yrGs19JOu7baLvVeP738X/Ac1Xt fhTLZXfmW2uXNtBuy3kmVZiv9zf5uP8Ax2tib4aeH7rY1zayXUyf8vE1zKZeu772+oq1KU2nYwxF ehVqKTjp5fqaPhfxCviTS2u/INuVlaJk3bun/wC1WrdWcF7BLBPGssMq7ZEdflZaraTpNpo1r9mt I/IjB3YLs/8A481aVckrX93Y82fK5PlVkU9PsbXTbVYLWGO2hXokShVq5RRU+pO+rCiiigQUUUUA FFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFRyfdbbu/4DQBJWbpOrf2pHM/2S6tPLfZ/pUWzd/tL zytRabPqctxefbYreKBZdtt5MjOzp/efKja3+zV68Mq27mFFklx8qs23/wAeoAhVYNG08Cadkt4F +aa4l3fL6szVPCsiRL57q8v95V21FbWv2V53M0s3mvu2Stu2fL91axPFnhPS/GMlhBeSyrJZyrdI tvO0TMo452nlaY15mtZ6XDZXl9cRffvJVll4X72xU/8AQUWtKiikIovaAzTyb2bzFVfLb5kUg/eC +v8A8TVmMttUMys38W2sKHxnpb3rWdzP/Z8+4oi3o8nzf9zd96taPULaa6ntY51eeDb5san5k3fd p7Daa3LlFFFIRn6tqtto9m1zdy+TAvV9jN/6DXi1xZ3KNZS3MElhcLG8qxP9+LdcSy/+zJ/3xXpH jrQ7vVrVZobtYY7aNpGjdTtdse1ea20MsO/zbmS5dm375m3vXp4OmpSv2PoMroRnLn3tv+n6nrXh XWrfUtNgi+2i7vIoY/Pdl2MzFfvbfevP9b8QXMPii/1CC4mWOCfasO/5f3Xysm3/AGtrU3w1pus3 1282kv8AZmj3I1xLwv8Au/Mrbq0G+G+t3UdwZ7uyllnaVmddy/fd2/u/7VKMaVGq4yd1YmFPD4XE TjUleNvx/wAz1OvLJvH2q/aJlVodqyuq/u/4VbFU5PiJregltNnk0281O3IikEi+UZW7MBv/AIqw naby1dlXe/zS/wCzVYfDrV1FdWNMBgtXKtG8baHY6dr3iTxKz2lpd2towTc0/k/Ov+6TuX/x2vR4 wyooZt7f3q5HwX4Xk0Xzrqa482S5jTEfl7PKUbj/AN9fN/47XZVxVpQc/wB2tDyMVKlKq1RVohRR RWByBRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFACbarx2sM MskiRIskmN7Ko3N/vUUUAUx/aP8AbpDLD/ZXkfK3/LXzd/8A6DtqO40M3Gv22pG7uFS3jaNbVG2x Fm6s396iimO5pyRrNG0bruVl2steI32lXekbILuP7A235Wl/e/8As/zfdoorqw9SUJNR6no4GtOn Nwj9o6jwr4k8m6t9L0XTt1o212eWRvN/h81jvr0yiipxEVCSS7EYynGnNRj2MnxDp8mqaPdWkDKs sqYXf92uc8J+B/skqXmpKrTr/q4M7lX/AGm/2qKKyVSUY8iejOeGIqQpypRdkzuaKKKzMAooooAK KKKACiiigAooooAKKKKAP//Z 1EDF09FA-6427-4B21-B90D-55EFBD8CC658 external 6024ebf0cf071db5e21bfbd536ee577a Hillsborough County Performance, Data, & Analytics Department Information & Innovation Office 601 E. Kennedy Blvd. Tampa FL 33602 GIS-Support@hillsboroughcounty.org True Hillsborough County