Appendix D: Property Specific Inventory INTEGRATED PLANNING & PUBLIC WORKS

Transcription

1 Appendix D: Property Specific Inventory INTEGRATED PLANNING & PUBLIC WORKS

2 Property Specific Inventory Contents: 1. Introduction 3 2. Methodology 5 3. Assumptions 9 4. Summary Statistics 11 2

3 1. Introduction The Property-Specific Inventory contains detailed information on all properties within the Station Areas and Nodes and Corridors in the City of Waterloo. This information captures existing land use, building typology, building height, total floor area and number of residents and employees on a property-by-property basis. The inventory establishes a baseline within these key areas where intensification is expected over time, in order to track change and achievement of growth targets. Inventory includes: Assessment Roll Number (ARN) Street address Property Code (from MPAC) Existing building /land use typology Property area Location within and name of: Station Area (as well as Inner or Outer Station Area Boundary) Node/Corridor Student Housing Boundary and/or Northdale Neighbourhood Number of buildings on property Total area of building footprint(s) Number of storeys (if applicable) Gross GFA (if applicable) Net GFA (if applicable) Number of individual addresses/units (applies to Multi-Unit Residential and Townhouse Typologies) Number or residents and/or jobs Comments 3

4 Map 1: Inventory Boundaries Research & Technology Park Northfield Conestoga Mall Inventory Area includes: 6 Station Areas Nodes and Corridors University of Waterloo Seagram Uptown 4

5 2. Methodology The following methodology was used to develop the Property-Specific Inventory. In some cases, property specific data exists, however, in most cases building typologies and standard density factors were developed and applied. 1. Developed property typologies and standard unit size/population factors for each typology (see page 6-9) 2. ARN used as property specific unique identifier to generate a list of properties 3. Identify Building/Property Typology for each property 4. Input existing property/building/population data 5. Where existing data not available, fill in table using assumptions/typologies/field checked info 6. Calculate number of residents/employees per property using unit size/population factors 7. Noted any irregularities/site specific details/questions in Comments column 8. Site-by-site review, correction and refinement 9. Calculation of overall population density 5

6 2. Methodology Data Hierarchy Existing data was reviewed and analyzed to ensure that where property specific data was available and where assumptions were to be applied. The following hierarchy was used to determine which existing sources of data to draw on for various types of information. 1. Site Specific Property Information Number of employees/residents (Sun Life Building, 27 John St) GFA (Manulife Buildings) 2. Address Count GIS layer Number of individual addresses on each property for most Multi-Unit Residential and Townhouse Typology properties 3. Building Permit Data Building Height (# Storeys) # Units GFA only for New developments (not interior alternations or renovations, etc) 4. Visual Verification via Google Street View Building Height (# Storeys) 5. OASYS Structure Information Building Height (# Storeys) # Units GFA (converted from sq.f. to sq.m.) 6. Building Footprint GIS Layer Building Footprint Size (sq.m.) 6

7 2. Methodology Typologies Typology Descriptions Typology Low-Density Residential / Duplex Townhouse Multi-Unit Residential Commercial (Retail) Office Institutional Industrial Care Home Hotel Unoccupied Properties NONBUILD Includes Single family, detached or semi-detached homes Row housing with multiple addresses on the same property Apartment, condominium or student residence buildings Auto dealership, auto servicing/repair, bank/financial institution, gas station, post office, retail use within converted house, restaurant/pub, club, shopping centre, business and personal services, funeral home Medical/dental office, standard office building, office use within converted house, industrial condo, industrial mall Museum/art gallery, concert/live theatre/cinema, sports complex, recreation centre, library, school, postsecondary institution, place of worship Assembly, manufacturing, processing, warehousing Group home, retirement home Hotel, motel, inn Communications building, transformer station, parking garage/lot, water treatment facility, vacant land Designated park/open space, railway right-of-way, non-buildable land, cemetery

8 Map 2: Typologies Typologies 8

9 3. Assumptions Population/Unit Size Factors Typology Population & Unit Size Factors Typology Density Factors Unit Size Factors (sq. m.) Gross : Net GFA Detached/Semi-Detached Residence 3.3 (ppu) - - Townhouse Unit 2.18 (ppu) % Apartment Unit 1.76 (ppu) 90 85% Student Townhouse 3 (ppu) % Student Apartment/Unit 5 (ppu) % Student House 3.9 (ppu) - - Industrial Condo/Mall 26 m2 / employee - 90% Industrial - Other 83.5 m2 / employee - 90% Institutional 37 m2 / employee - 90% Education 68 m2 / employee - 90% Office 26 m2 / employee - 90% Retail 37 m2 / employee - 90% Hotel 37 m2/ employee - 90% Care Home 1.76 (ppu) 90 85%

10 3. Assumptions Other Typology Assumptions Typology Assumptions Industrial Banks/Personal Services Townhouses Typology Duplex/Semi-Detached with Both Units on one Property Townhouse / Multi-Unit Residential Mixed-Use Retail/Residential & Mixed-Use Retail Office Building height = 1 storey Building height = 1 storey Building height = 3 storeys Assumption # of units = 2 (single family residential) # of units = Sum of number of address points within property polygon Assume ground floor retail, upper floors residential (apartment units factors), or office (office factors) 10

11 4. Summary Statistics All Areas Residents and Jobs All Areas Area Nodes and Corridors outside Station Areas Total # of Properties Residents Total Jobs Total Total People + Jobs ,993 12,919 23,912 Conestoga Mall 877 3,525 7,514 11,039 Northfield 385 2,249 7,411 9,660 Research & Technology Park 316 4,598 8,467 13,065 Seagram 127 8,695 3,254 11,949 University of Waterloo ,038 6,212 21,250 Uptown 2,318 11,516 10,732 22,249 TOTAL 5,309 56,615 56, ,123 11

12 4. Summary Statistics Station Areas Residents and Jobs Station Areas Station Area Total # of Properties Residents Total Jobs Total Total People + Jobs Conceptual Station Boundary 1,956 35,561 37,491 73,052 Outside Conceptual Boundary 2,574 10,061 6,098 16,159 TOTAL 4,530 45,662 43,589 89,211 12

13 4. Summary Statistics Conceptual Station Area Population Density Residents and Jobs Conceptual Station Areas Station Area Area (hectares) Units/ha People + Jobs/ha Conestoga Mall Northfield R&T Park Seagram University of Waterloo Uptown Remaining Nodes and Corridors TOTAL (Average) 1,

14 Map 3: Summary Population Statistics Research & Technology Park 4,600 residents + 8,500 jobs Northfield 2,200 residents + 7,400 jobs Seagram 8,700 residents + 3,300 jobs Remaining Nodes & Corridors 11,000 residents + 13,000 jobs Conestoga Mall 3,500 residents + 7,500 jobs University of Waterloo 15,000 residents+ 6,200 jobs Uptown 11,500 residents + 10,700 jobs Total Population 56,600 residents + 56,500 jobs = 113,100 people and jobs Average Population Density 81 people + jobs/hectare 14