Fort Walton Beach Ordinance — 1757 Public School Facilities Element — reading text

i 7 O O 70O W a w 0 0 0 F O 2 cc c Z LL LL LL Z CC CC CC 0 M O , W W W 9 d J o W 3 3 o Z W > > 7 w it h O 3 y2 Z W W W O O O X X X LY w '- OJ 2 N m v . W O- 2 2 2 2 2 Jiii j 4§41, J. i.W v i: O i. i.' riiillhnhgrryyii... isl; Ss 1= ID IN c U W i W Q 1 11. .. 1 W E U J a i— d' D W U A._._ J m 1 1 CL r'''') 1.-_ gsf t Aso - ° oco a 1• nq t. g m w U  4.; ' s s' ' 1;; it ou it` s' S; Lr' f_oi SDkt: s{. -+ r 6;,' T' •° fin`' '- et t .. Byil u` i' Description of the Methodology Applied in the Calculation of Student Generation Rates for Okaloosa County The purpose of this endeavor was to determine the rate at which newly developed projects in Okaloosa County, Florida can be expected to generate an increased demand for school capacity as it relates to proportionate share mitigation for school concurrency. Historical data from the Okaloosa County School District and the Okaloosa County GIS Department was used to calculate a student generation rate multiplier. A database containing student name and address information for the 2006- 2007 school year was provided by the school district' s MIS Department. Okaloosa County provided access to their FTP site with the path as follows: i' tp: iI ttpilis. co. oka1oosa. 11. usipublic/ Property Appraiser' Shapel-ilesrparcell Detailed parcel data collected by the property appraiser' s office was obtained from the file public.dbfwith the relevant information found in the USEDESC ( use code description) field. The use code description categorizes the type of property found on each recorded parcel in the county (e. g. single family, multifamily, townhouse, condominium and mobile home). Both the student address and use code description, or dwelling type, data were geo- coded using Transfinder Transportation Management software. This is a program owned by the school district and maintained for the purpose of transportation system routing. However, the underlying Mapinfo enabled mapping functions and its ease of adaptability made it a useful tool for the purposes of generation rate calculation. The geo- coding process resulted in a manipulatable map that displayed all students as data points on a map of the county with the dwelling type listed within each parcel. After calculating a statistically adequate sample size for the population, the mapping tools in Transfinder were used to isolate samples of addresses across the county. Samples were selected from each of six CSA' s established by the Interlocal Agreement for Public School Facility Planning( i.e. Baker, Laurel Hill, Crestview, Niceville, Choctaw and Ft. Walton Beach) with varying population densities. Each sample was comprised of a list of student names and addresses within the selected area and a map indicating the location of each student. While the same technique was applied to all of the samples taken, there were some differences between areas that  Student Generation Rate Multipliers became apparent in the analysis. In the predominantly rural areas of the county, the dwelling types were typically mixed as opposed to the more segregated, suburban areas. Additionally, the only dwelling types found in significant numbers in the rural areas were single family and mobile home. The low frequency of dwelling types other than single family and mobile home made the calculation of an accurate generation rate multiplier for other dwelling types in the Baker and Laurel Hill CSA' s problematic. As a result, a single, county-wide multiplier was calculated for each dwelling type using the combined measurements for all CSA' s. This allows for the calculation of proportionate share mitigation for developments of dwelling types that may not currently exist in a particular CSA. In the rural CSA' s ( Baker and Laurel Hill), the map of each sample was analyzed and a determination of the dwelling type classification for each parcel and the number of students for each dwelling type noted. The same process was applied to the other CSA' s. However, it was simplified in the more developed areas because each sample typically contained only one dwelling type. After measuring an adequate number of sample addresses, a student generation rate multiplier was calculated for each dwelling type by dividing the number of students in each by the total number of addresses. The results are reported below: Dwelling Dwelling Type Rate Type Addresses Students Single Family 0. 4681 Single Family 1863. 872 Multi- Family 0. 3384 Multi- Family 978 331 Condominium 0. 0534 Condominium 262 14 Mobile Home 0. 4697 Mobile Home 577 271 Source data can be found in Appendix 3/ 12/ 2008 2 of 3  Student Generation Rate Multipliers IIAppendix CSA Dwelling Type Addresses Students Sgl Family 326 134 Multi- Family 40 15 Baker Condominium 0 0 Mobile Home 110 51 Total 476 200 Sgl Family 189 86 Multi- Family 89 14 Laurel Hill Condominium 0 0 Mobile Home 100 51 Total 378 151 Sgl Family 349 166 Multi- Family 179 64 Crestview Condominium 0 0 Mobile Home 45 25 Total 573 255 Sgl Family 303 183 Multi- Family 198 59 Niceville Condominium 0 0 Mobile Home 114 45 Total 615 287 Sgl Family 308 149 Multi- Family 224 80 Choctaw Condominium 148 11 Mobile Home 119 66 Total 799 306 Sgl Family 388 154 Ft. Walton Multi- Family 248 99 Bch. Condominium 114 3 Mobile Home 89 33 Total 839 289 3/ 12/ 2008 3 of 3  r SCHOOL DISTRICT OF OKALOOSA COUNTY SUPFR N ENDENT OF SCHOOLS ALEXIS TIBBETTS, Ed.D. BOARD MEMBERS