Baltimore County Public Schools Pupil Yield Study 017 Revised July 017
Acknowledgements Cropper GIS Consulting extends appreciation to the School Board for allowing us to work on the Pupil Yield Study: School Board Edward J. Gilliss, Esquire, Chair, Fifth Council District Verletta White, Secretary Treasurer Kathleen S. Causey, Third Council District June P. Eaton, Seventh Council District Julie Henn, Member-at-Large Charles M. McDaniels, Jr., Fourth Council District Anne Miller, Member-at-Large Nicholas C. Stewart, Esquire, First Council District David Uhlfelder, Member-at-Large Stephen L. Verch. Esquire, Sixth Council District Emory Young, Second Council District Roger B. Hayden, Member-at-Large Josie Shaffer, Student Board Member We also thank school district personnel for their support of this study: Russell Brown Ph.D., Chief Accountability Officer Kara Calder, Executive Director of Strategic Planning and Research Melissa E. Appler, Coordinator of Strategic Planning Christopher Brocato, Planning Analyst With much appreciation, Matthew Cropper, President Aaron Cropper, Senior GIS/Planning Specialist Andrew Doctor, Planning Analyst
Table of Contents Acknowledgments Table of Contents Preface 1 017 Pupil Yield Factor Methodolog 1 017 Pupil Yield Study Findings From Newer Development Maps: Baltimore County Election Districts 4 Baltimore County Pupil Yield Factors by Election District Multi-Family () Housing Type 6 Multi-Family () Housing Type 7 Single-Family Attached () Housing Type 8 Single-Family Attached () Housing Type 9 Single-Family Detached () Housing Type 10 Single-Family Detached () Housing Type 11 Conclusion 1
PREFACE: School districts are continually faced with the challenge of providing an adequate number of schools to accommodate growth in student population. Along with this comes the challenge of determining the number of facilities needed, identifying and purchasing preferred sites, and having sufficient capital and operating funds for the facilities. On the other hand, some districts need to plan for the utilization of space if enrollments decline. Both scenarios require having accurate enrollment projections: one to accommodate growth; and the other to allow the district to make decisions that could include a reduction in the number of schools and staff, and could necessitate boundary changes, etc. Both should be thoroughly researched, documented, and presented to all stakeholders. School districts must look closely at the demographics of the city, township, or county that they serve. The houses in these communities hold the key to the current and future enrollment of the school district, and the challenge then is to determine how many students live in each house, and how many will live in houses that are still in the planning or development stage. In other words: what are the pupil yield factors? BALTIMORE COUNTY PUBLIC SCHOOLS 017 PUPIL YIELD FACTOR METHODOLOGY To develop Pupil Yield Factors that describes the number of pupils that will come from post-199 subdivisions, Baltimore County Public Schools used three comprehensive databases to obtain base information: the Baltimore County (BC) Parcel Data, BC Address Points, and BCPS Student Enrollment Information. The County Parcel and Address Point data provided valuable housing unit information such as development information, housing type, and whether each housing unit is owned or rented. Using GIS as the primary tool it was possible to combine the Parcels and Address Point GIS data to determine how many housing units exist per development. The 017 Pupil Yield Study leverages the most reliable and accurate data sources available to BCPS. In order to develop the pupil yields for Baltimore County Public Schools, every viable type of development was researched throughout the County. Once developments and their housing unit counts were established, they were given attributes as to which Election District each one fell within. This provided a total number of developments and units in each Election District for each housing type (Multi-Family ed, Multi-Family ed, Single-Family Attached ed, Single- Family Attached ed, and Single-Family Detached). The following is a description of each classification and an example of housing that falls within the type: 1. Multi-Family ed property included all developments that were classified as multi-family but had individual ownership. An example of this might be a high-rise condominium development.. Multi-Family ed property consists of housing developments that were rented. An example of this is apartment complexes.. Single-Family Attached ed property consists of all developments that are classified as single-family, but might have attached garages or buildings. Many condominium developments that are individually owned have attached garages or the buildings are attached. 4. Single-Family Attached ed would have the same definition as item # but the occupied persons rent the property as opposed to owning it.. Single-Family Detached ed are all properties that sit as an individual property on a land parcel and are owned. These are the most common classifications for individual houses. 6. Single-Family Detached ed are all properties that sit as an individual property on a land parcel and were being rented at the time of this study s creation. Certain developments were excluded from the new development analysis. These were: o Very old developments (i.e., ones which contained households prior to 199) o Developments which contained no pupils at all in any of the three years. Once the developments were selected and aggregated into Election Districts, student averages from 01-01 were generated for each subdivision and Election District. These student averages were classified as PS- th, 6-8 th, 9-1 th, and PS-1 th. Pupil yields per Election District were calculated by dividing the average number of students from 01-01 with the number of housing units. 1
017 PUPIL YIELD STUDY FINDINGS FROM NEWER DEVELOPMENTS The following tables reflect the findings as a result of the 017 yield study analysis, along with the housing and student information that were used to develop the yield factors. The purpose of these tables is to show the pupil yields from newer developments within Baltimore County. These tables show the yields from developments that were built between 199 to 01. 199 to 01 Developments Identity Developments Pupil Averages, 01-01 Yields District Type Tenure Count Built Units PS-th 6-8th 9-1th PS-1th PS-th 6-8th 9-1th PS-1th 1 4 4 18 9 6 11 11 4 9 48 76 66 7 14 44 698 6 181 11 11. 87. 9.67 4.67 06.00 00. 4.67 7.00 14 1.00 9..00. 41. 4.00 14.67 0.67 0.00 1.00 8.00 6.00 84.00 167.67. 4.67 6.. 7.00.67 1.00 14..67 11. 9.00 8.67 174. 0 79.67 98.00 1076.67.67 66. 0.67. 408. 61. 0.06 0.6 0.19 0.06 0.19 0.14 0.0 0.1 0.0 0.041 0.179 0.179 0.097 0.16 0.10 0.019 0.077 0.096 0.000 0.061 0.040 0.017 0.066 0.18 0.097 0.19 0.148 0.09 0.10 0.11 0.007 0.09 0.048 0.01 0.074 0.174 0.400 0.0 0.47 0.104 0.74 0.461 0.040 0.7 0.9 0.089 0.19 0.481 4 8 1 8 8 9 0 68 69 19 074 818 14 17 4 1 74 41 74 1. 18.67 7.67 4.67 1.67 40.00 19.00 60.00 1. 76.67 91.00 16.67 4.67 11.00.67 168.67 108. 1.67 14.00 0.67 0.67 4.00 44.67 7.67 8. 8.67 14. 141.67 4.00 0.. 1. 4.00 6.67 17. 44. 8. 1. 80.67 481.67 79.67. 106.00. 1.67 199. 41.67 0.117 0.71 0.404 0.17 0.8 0.60 0.060 0.180 0.04 0.106 0.67 0. 0.017 0.19 0.140 0.0 0.1 0.10 0.044 0.06 0.0 0.047 0.11 0.104 0.01 0.16 0.10 0.070 0.17 0.16 0.064 0.076 0.04 0.06 0.187 0.4 0.16 0.6 0.649 0.6 0.89 0.17 0.168 0.17 0.108 0.1 0.8 0.6 1 10.. 1. 8.00 0. 0. 0.1 0.800 6 7 8 9 16 8 08 14 88 16 878 68. 1. 16.67 10.67.00 69.00.67 6.67.67 7.67 88. 9.00 66. 19.00 8.67 6.67. 40.67 0.9 0.99 0.00 0.10 0.17 0.19 0.0 0.00 0.041 0.061 0.181 0.81 0.00 0.0 0.076 0.668 0.900 0.011 0.198 0.74 10 17 9 9 80 19 1. 7.67 0.67.67 1.67 0.00 4.67.67 0.00 8.00.00 0. 6.00 0..67 8.67 0.9 0. 0.01 0.0 0.18 0.18 0.000 0.008 0.10 0.086 0. 0.000 0.014 0.18 0.011 0.667 0. 0.0 0.98 0.80 806 6.00 1.67 0.00 8.67 0.0 0.016 0.0 0.07 9 88 4.67 1.67 0.00 6. 0.0 0.019 0.000 0.07 4. 0.00 0.00. 0.19 0.000 0.000 0.19 10 1.00 11. 17.00. 0.16 0.074 0.111 0.49
199 to 01 Developments Identity Developments Pupil Averages, 01-01 Yields District Type Tenure Count Built Units PS-th 6-8th 9-1th PS-1th PS-th 6-8th 9-1th PS-1th 10 9 161 4.67 4.67 9.00 97. 0.71 0.1 0.180 0.60 11 4 4 11 189 0 108. 70. 68.67 7..67 77. 0.00 7. 18. 16.67 1. 181. 0.087 0.7 0.9 0.0 0.16 0.17 0.04 0.14 0.17 0.1 0.6 0.6 4 0 78 1. 8. 6. 4.67.00 16.00 9.67.67 18.67 6.67 1.00 61.00 0.060 0. 0.8 0.0 0.10 0.0 0.047 0.147 0.9 0.10 0.600 0.78 1 04 99.00 44.00 61. 04. 0.196 0.087 0.1 0.40 18 8.00 10.67 1.00 69.67 0.09 0.09 0.11 0.8 1.67.67 4. 1.67 0.46 0.19 0.188 0.94 1 14 4 6 1 11 144 66 81 1.67. 4.67 1 174. 1.00 10.00 4.00 0.67 41.00 87. 1.00 11.00.67.00 0.00 110.67 1. 4.67 1 8. 4.00 7.. 0.19 0.167 0.0 0. 0.1 0.01 0.089 0.1 0.00 0.06 0.108 0.01 0.098 0.08 0.01 0.076 0.16 0.04 0.81 0.7 0.08 0.70 0.49 0.104 6 1 7 6 48 16 49 18 0.00. 0.67 7.67 17.67 0.67. 0.00 17.00 9. 0.00 1. 1.67 1.67 0.67 11. 0..67 6.00. 9. 8. 1.00 0.000 0.89 0.014 0.4 0.61 0.004 0. 0. 0.000 0.104 0.190 0.000 0.190 0.78 0.0 0.17 0.1 0.00 0.4 1.000 0.049 0.8 0.78 0.00 8 791 6.00 79.67 111.00 416.67 0.86 0.101 0.140 0.7 1 7 4 107.67 41.67 6.67 1.00 0.44 0.171 0.6 0.877 0 17 99. 141.00 19.67 6.00 0.4 0.114 0.16 0.1 1 84 18.00 1.67 18.00 48.67 0.14 0.11 0.14 0.79 M 1 48 1.00 6. 10. 9.67 0.0 0.06 0.04 0.10
The following map reflects the Election Districts in Baltimore County, which is how the pupil yields were reported. 4
Baltimore County Public Schools Pupil Yield Study 017 July 017 The map below shows the yield factors by housing type for each Election District. The color scale on the map indicates yellow as the lowest pupil yield and dark red as the highest range. The shades between yellow and dark red are the intermediate ranges of pupil yields. This shows the areas of the district that are yielding the most students, and how these areas change based on the housing type that was analyzed. The primary purpose of the color scales is to show the difference in pupil yields from housing throughout the district. The legend in each map should be examined to determine the intensity of pupil yields in various color shaded areas.
The map below shows the Multi-Family () pupil yields for PS-1th. 6
The map below shows the Multi-Family () pupil yields. 7
The map below shows the Single-Family Attached () pupil yields. 8
The map below shows the Single-Family Attached () pupil yields. 9
The map below shows the Single-Family Detached () pupil yields. 10
The map below shows the Single-Family Detached () pupil yields. 11
CONCLUSION This study provides comprehensive data and analysis regarding housing developments and pupil yield rates within Baltimore County Public Schools. This report is meant to be used as a planning tool for the Baltimore County Public Schools and other county offices, in gaining a better understanding of the student populations and yields within communities throughout the school district. This report will also help to provide valuable insight regarding the amount of students that new residential developments will likely yield. Although the report provides full detail about each Election District, the table to the right depicts a summary of the highest pupil-yielding Election Districts per housing type. In order to gain a complete understanding of how communities throughout the County are yielding students, it is necessary to review the full tables and maps included in this report. Housing Type Highest Yield Rate Election District Single Family Attached () 0.6 11 Single Family Attached () 0.877 1 Single Family Detached () 0.9 7 Single Family Detached () 1 1 Multi-Family () 0.4 1 Multi-Family () 0.40 1 1