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Residential Land Use Change, Replacing the Single-Family Home for High-Density Affordable Housing

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Residential Land Use Change, Replacing the Single-Family Home for High-Density Affordable Housing

  1. 1. Residential Land Use Change, Replacing the Single-Family Home for High-Density Affordable Housing Case Study Analysis of Eau Claire and La Crosse, Wisconsin B y P a u l S c h m i t t
  2. 2. Research Paradigm C r i t i c a l R e a l i s m Spatial events throughout the world understood as products of deeper structural forces and causal mechanisms causing change (Gomez and Jones 2010, 24).
  3. 3. Outline of Presentation 1) Research Question and Scholarly Objective 2) Literature Review 3) Background 4) Proximity Maps of Study Areas Defined by Opportunity Zones 5) Establishing Study Areas for Survey Analysis Through Proximity Buffer Zones 6) Methodology for Predictive Modelling of Determining Future Residential Developments in Wisconsin Case Study Cities 7) Predictive Modelling Results 8) Explanations of Analysis 9) Conclusions 10) Acknowledgements
  4. 4. Research Question and Scholarly Objective R e s e a r c h Q u e s t i o n Which residential parcels containing pre-existing residential properties or unused property sites portray a high likelihood of future residential developments correlating to affordable, high-density housing units? S c h o l a r l y O b j e c t i v e Evaluation on the transitional effects and implications to an influx of future affordable, high-density residential development projects on the physical and sociological suburban landscapes within Eau Claire and La Crosse, Wisconsin by replacing the single-family home along with its subsequently outdated neighborhood design.
  5. 5. Literature Review C i t y o f L a C r o s s e a n d C i t y o f E a u C l a i r e C o m p r e h e n s i v e P l a n s Figure 1. Source: City of La Crosse Planning and Development Department Figure 2. Source: City of Eau Claire Planning Division
  6. 6. Literature Review P r e d i c t i n g L a n d U s e C h a n g e a n d L a n d U s e C h a n g e M o d e l l i n g Considerable amount of work is found in this area. It is a critical component for conducting analyses and implementing specific processes in the methodology section. • “Predicting land-use change” Veldkamp, A., and E. F. Lambin • “Rates and patterns of land use change in the Upper Great Lakes States, USA: A framework for spatial temporal analysis” Pijanowski, Bryan C., and Kimberly D. Robinson • “Urban land-use change: The role of strategic spatial planning” Hersperger, Anna M., et al. • Among others
  7. 7. Literature Review R e s i d e n t i a l a n d S u b u r b a n R e d e v e l o p m e n t Essential component to review in use with case study analysis of redevelopment areas. • “Residential density change: Densification and urban expansion” Broitman, Dani, and Eric Koomen • “New Visions for Suburbia: Reassessing Aesthetics and Place-making in Modernism, Imageability and New Urbanism” Forsyth, Ann, and Katherine Crewe • “North American suburbia in flux” Nijman, Jan • “The Impact of a Large City on Land Use in Suburban Area - The Case of Wrocław (Poland)” Tokarczyk-Dorociak, Katarzyna, Jan Kazak, and Szymon Szewrański • Among others
  8. 8. Literature Review S u r v e y A n a l y s i s w i t h G o o g l e S t r e e t Vi e w Among other literature, residential land use change survey methods required review for application to research methods. • “Using Google Street View to Audit Neighborhood Environments” Rundle, Andrew G., Michael D. M. Bader, Catherine A. Richards, Kathryn M. Neckerman, and Julien O. Teitler • “Assessing residential front yards using Google Street View and geospatial video: A virtual survey approach for urban pollinator conservation” Burr, Andrea, Nicole Schaeg, and Damon M. Hall
  9. 9. Background P o r t l a n d , O r e g o n “ T h e B e s t P l a n n e d C i t y ” • Large-scale river city model • Intensive land use change history and development interests (Gibson and Abbot, 2002) • The regional government Metro and 2040 Growth Concept (Oregon Metro) • Externalities of development that Portland, Oregon struggles with are valuable for consideration in the context of Wisconsin case studies E a u C l a i r e a n d L a C r o s s e , Wi s c o n s i n • Mid-sized river cities for case study analysis • The Comprehensive Plan • Accommodating future growth, redevelopment and reinvestment for the future • Predictive modelling and its prominent applications
  10. 10. Proximity Maps of Portland, Oregon Urban RenewalAreas and Eau Claire and La Crosse, Wisconsin Opportunity Zones
  11. 11. Figure 3.
  12. 12. Figure 4.
  13. 13. Figure 5.
  14. 14. Figure 6.
  15. 15. Figure 7.
  16. 16. Figure 8.
  17. 17. Establishing Study Areas for Survey Analysis Through Proximity Buffer Zones C e n t r a l B u s i n e s s D i s t r i c t 0 . 5 - M i l e B u f f e r Z o n e s M a i n R o a d 0 . 5 - M i l e B u f f e r Z o n e s U.S. highways, state roads, and coinciding major roadways utilized for buffer zones. P u r p o s e a n d R a t i o n a l e Proximity to the central business district as the economic, civic, and entertainment center has considerable leverage in guiding redevelopment patterns (Comprehensive Plans). Proximity to main transportation routes often regulates intensity of redevelopment patterns and supports the character of adjacent neighborhoods and districts (Comprehensive Plans). Historical references of development and current development patterns utilized for determining central business districts. Physical geography of case study landscapes important to consider.
  18. 18. Establishing Study Areas for Survey Analysis Through Proximity Buffer Zones Buffer zones implemented in large-scale city model to display comparative spatial variations in residential land use change to Wisconsin mid-sized case study cities. P o r t l a n d , O r e g o n E a u C l a i r e a n d L a C r o s s e , Wi s c o n s i n Buffer zones implemented to determine: • Locality of residential land use survey analysis • Range of residential land use survey analysis
  19. 19. Figure 9.
  20. 20. Figure 10.
  21. 21. Figure 11.
  22. 22. Figure 12.
  23. 23. Methodology for Predictive Modelling of Determining Future Residential Developments in Wisconsin Case Study Cities Determining factors that promoted residential development to be considered in Wisconsin case study model: • Historical development patterns • Property values pre-development and post-development • Number of residents a housing unit can support • Zoning ordinances • City policies P o r t l a n d , O r e g o n L a n d U s e C h a n g e S u r v e y A s s e s s m e n t
  24. 24. Methodology for Predictive Modelling of Determining Future Residential Developments in Wisconsin Case Study Cities Determining factors included in modelling future residential development: • Spatio-temporal data collected from Google Street View surveys and on-site land use surveys • Ownership fragmentation • Property values pre-development and post-development • Number of residents a housing unit supports pre-development and post-development • Pearson’s product-moment correlation: property value and number of residents in unit • Proximity to central business district buffer zone and main road buffer zone • Zoning ordinances • City policies following Comprehensive Plans E a u C l a i r e a n d L a C r o s s e , Wi s c o n s i n C a s e S t u d y C i t i e s
  25. 25. Methodology for Predictive Modelling of Determining Future Residential Developments in Wisconsin Case Study Cities • Google Street View residential land use change surveys • On-site residential land use change surveys E a u C l a i r e a n d L a C r o s s e , Wi s c o n s i n 1 1 Ye a r R e s i d e n t i a l L a n d U s e C h a n g e S u r v e y s ( 2 0 0 8 - 2 0 1 9 ) Figure 13. Source: Google Maps, Google Street View Figure 14. Source: Google Maps, Google Street View
  26. 26. Figure 15.
  27. 27. Figure 16.
  28. 28. Figure 17.
  29. 29. Figure 18.
  30. 30. Figure 19.
  31. 31. Methodology for Predictive Modelling of Determining Future Residential Developments in Wisconsin Case Study Cities P e a r s o n ’s P r o d u c t - M o m e n t C o r r e l a t i o n o f S u r v e y e d R e s i d e n t i a l D e v e l o p m e n t s , P r o p e r t y Va l u e s a n d N u m b e r o f R e s i d e n t s i n H o u s i n g U n i t s Table 1. Table 2.
  32. 32. Methodology for Predictive Modelling of Determining Future Residential Developments in Wisconsin Case Study Cities P e a r s o n ’s P r o d u c t - M o m e n t C o r r e l a t i o n o f S u r v e y e d R e s i d e n t i a l D e v e l o p m e n t s , P r o p e r t y Va l u e s a n d N u m b e r o f R e s i d e n t s i n H o u s i n g U n i t s Graph 1. Graph 2.
  33. 33. Methodology for Predictive Modelling of Determining Future Residential Developments in Wisconsin Case Study Cities Eau Claire, Wisconsin O p t i m a l Z o n i n g O r d i n a n c e s Zoning Ordinance Zoning Description RM(P) Mixed Residential District (Planned Development) R2 One and Two-Family District R3 Low-Rise Multiple Family District R4(P) High-Rise Multiple Family District (Planned Development) CBD(P) Central Business District (Planned Development) Table 3. Source: Municipal Code of Ordinances, City of Eau Claire, Wisconsin
  34. 34. Methodology for Predictive Modelling of Determining Future Residential Developments in Wisconsin Case Study Cities La Crosse, Wisconsin O p t i m a l Z o n i n g O r d i n a n c e s Zoning Ordinance Zoning Description R5 Multiple Dwelling R6 Special Multiple Dwelling TND Traditional Neighborhood Development WR Washburn Residential Neighborhood PS Public and Semi-Public PD Planned Development Table 4. Source: Municipal Code of Ordinances, City of La Crosse, Wisconsin
  35. 35. Predictive Modelling Results
  36. 36. Figure 20.
  37. 37. Figure 21.
  38. 38. Explanations of Analysis A s s e s s m e n t o f P r e d i c t i v e M o d e l l i n g R e s u l t s Eau Claire, Wisconsin • University of Wisconsin-Eau Claire and influence of the student population • Significant ownership fragmentation • Single-family homes and duplexes dominate the case study landscape • Comparative influences of Water Street business improvement district and South Barstow Street business improvement district (City of Eau Claire Redevelopment Department)
  39. 39. Explanations of Analysis A s s e s s m e n t o f P r e d i c t i v e M o d e l l i n g R e s u l t s La Crosse, Wisconsin • Viterbo University and Western Technical College influences of the student population • Ownership fragmentation correlating with colleges and their surrounding localities • High-profile owner investments focused within south side La Crosse Opportunity Zone (census tract 4) • Single-family homes, unused parcels, and undeveloped apartments dominate the case study landscape
  40. 40. Conclusions • Increasing student body of universities and colleges, meeting the demand for low-cost housing for a large, non-permanent student population • Various sociological changes to an influx of high-density housing units • Rehabilitation of existing housing units and infill development will progress as case study areas contain a limited supply of land • Future redevelopment areas to occur farther outside of central business district buffer zone • Major shifts in urban, residential, and neighborhood design as well as functionality • Downtown revitalizations including business improvement districts to have substantial impacts on future residential developments (type of housing unit, density, locality) • Highly targeted redevelopment and reinvestment to intensify land use patterns (Comprehensive Plans) • Mixed-use and multiple-use developments are becoming more prevalent and are recommended in compatible areas (Comprehensive Plans) F u t u r e I m p l i c a t i o n s o f R e s i d e n t i a l D e v e l o p m e n t a n d R e s i d e n t i a l L a n d U s e C h a n g e
  41. 41. Conclusions A s s o c i a t e d E x t e r n a l i t i e s f o r C o n s i d e r a t i o n • The City of Eau Claire and the City of La Crosse understand that it will take a long time to achieve their extensive goals of redevelopment across the Opportunity Zone areas • During this transition period of development, temporary inconsistencies and incompatible residential land use relationships to be expected (Comprehensive Plans) • Housing rehabilitation and reinvestment to be given priority for owner-occupants and households with low income (Comprehensive Plans) • Strong reliance on the profit motives of the private sector as a central redevelopment resource (Comprehensive Plans) • Targeted redevelopment of riverfront locations may be given priority over distressed neighborhoods
  42. 42. Conclusions F u t u r e S t u d i e s • Administer residential land use surveys and predictive modelling to greater extent of case study cities • Difficult to identify all potential areas that may become feasible for residential redevelopment over the coming decades • As development occurs, new Opportunity Zones could present themselves, requiring new models of sustainable growth
  43. 43. Acknowledgements • Research Mentor Ezra Zeitler • Capstone Instructor Ryan Weichelt • Yvonne Plomedahl • University of Wisconsin Eau-Claire Geography Department
  44. 44. References • Gomez, Basil and Jones, John Paul. 2010. Research Methods in Geography. New Jersey: Blackwell Publishing. • The City Government of La Crosse, Wisconsin. Confluence: The La Crosse Comprehensive Plan. December 2002. Accessed March 12, 2019. https://www.cityoflacrosse.org/filestorage/593/844/3606/5145/Plan_Elements_WEB.pdf • The City Government of Eau Claire, Wisconsin. City of Eau Claire Comprehensive Plan 2015. September 2015. Accessed March 12, 2019. https://www.eauclairewi.gov/home/showdocument?id=27846. • Veldkamp, A., and E. F. Lambin. 2001. “Predicting land-use change.” Agriculture, Ecosystems & Environment 85 (1):1-6. doi: 10.1016/S0167-8809(01)00199-2. • Pijanowski, Bryan C., and Kimberly D. Robinson. 2011. “Rates and patterns of land use change in the Upper Great Lakes States, USA: A framework for spatial temporal analysis.” Landscape & Urban Planning 102 (2):102-116. doi: 10.1016/j.landurbplan.2011.03.014. • Hersperger, Anna M., Eduardo Oliveira, Sofia Pagliarin, Gaëtan Palka, Peter Verburg, Janine Bolliger, and Simona Grădinaru. 2018. "Urban land-use change: The role of strategic spatial planning." Global Environmental Change Part A: Human & Policy Dimensions 51:32-42. doi: 10.1016/j.gloenvcha.2018.05.001. • Broitman, Dani, and Eric Koomen. 2015. "Residential density change: Densification and urban expansion." Computers, Environment & Urban Systems 54:32-46. doi: 10.1016/j.compenvurbsys.2015.05.006. • Forsyth, Ann, and Katherine Crewe. 2009. "New Visions for Suburbia: Reassessing Aesthetics and Place-making in Modernism, Imageability and New Urbanism." Journal of Urban Design 14 (4):415-438. doi: 10.1080/13574800903265470.
  45. 45. References • Nijman, Jan. 2015. "North American suburbia in flux." Environment & Planning A 47 (1):3-9. doi: 10.1068/a4701ge. • Tokarczyk-Dorociak, Katarzyna, Jan Kazak, and Szymon Szewrański. 2018. "The Impact of a Large City on Land Use in Suburban Area - The Case of Wrocław (Poland)." Journal of Ecological Engineering 19 (2):89-98. doi: 10.12911/22998993/81783. • Rundle, Andrew G., Michael D. M. Bader, Catherine A. Richards, Kathryn M. Neckerman, and Julien O. Teitler. 2011. "Using Google Street View to Audit Neighborhood Environments." American Journal of Preventive Medicine 40 (1):94-100. doi: 10.1016/j.amepre.2010.09.034. • Burr, Andrea, Nicole Schaeg, and Damon M. Hall. 2018. "Assessing residential front yards using Google Street View and geospatial video: A virtual survey approach for urban pollinator conservation." Applied Geography 92:12-20. doi: 10.1016/j.apgeog.2018.01.010. • Gibson, K., and C. Abbott. 2002. "Portland, Oregon." Cities 19 (6):425. doi: 10.1016/S0264-2751(02)00075-6. • Oregon Metro. 2014. 2040 Growth Concept. Accessed March 17, 2019. • Google Maps. 2019. Google Street View. Accessed March 2019.

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