Conflict Between Growth And Quality Of Urban Life: Initial Findings From An Ongoing Study In Metropolitan Istanbul Perver K. Baran - NC State University Handan D. Türkoglu - Istanbul Technical University Fulin Bolen - Istanbul Technical University Robert W. Marans - University of Michigan Paper presented at EDRA37, Atlanta, May 3-7, 2006
1. Background 2. Theoretical Framework 3. Quality of Life Study in Metro Istanbul 4. Research Methodology 5. Initial Findings 6. Future Work Overview
1. Background 2001 Detroit Area Study (DAS) A program of research at the University of Michigan that measures and monitors the quality of community life in metro Detroit. It s intent is to inform public and private decision makers whose policies affect the lives of metro area citizens.
World Cities and Regions: DAS Partners and Potential Partners 1. Background BEIJING SALZBURG/LINZ BELO HORIZONTE WARSAW CORE ISSUES/ QUESTIONS TAIPEI DETROIT BRABANT REGION JOHANNESBURG ISTANBUL BRISBANE
Models 2. Theoretical Framework
MODEL SHOWING RELATIONSHIPS BETWEEN DOMAIN SATISFACTIONS AND LIFE SATISFACTION(QOL)* Personal Characteristics Standards of Comparison Domain 1 Objective Attributes Perceived Attributes Evaluated Attributes Satisfaction with Domain 1 Domain 2 Objective Attributes Perceived Attributes Evaluated Attributes Satisfaction with Domain 2 Life Satisfaction Coping and Adaptive Behavior Domain 3 Objective Attributes Perceived Attributes Evaluated Attributes Satisfaction with Domain 3 * From Campbell, Converse, and Rodgers, 1976.
MODEL SHOWING RELATIONSHIPS BETWEEN RESIDENTIAL DOMAIN SATISFACTIONS AND QOL* Person Characteristics Standards of Comparison Residential Domains House/dwelling Objective Environmental Attributes (Eo) Perceptions of Environmental Attributes (Es) Assessments of Perceived Environmental Attributes Housing Satisfaction Micro- Neighborhood Eo Es Assessments Micro- Neighborhood Satisfaction Macro- Neighborhood Eo Es Assessments Macro- Neighborhood Satisfaction City, Town Eo Es Assessments Community Satisfaction Overall Quality of Life Experience Other Domain Satisfactions * Adapted from Marans and Rodgers, 1975.
MODEL SHOWING RELATIONSHIPS BETWEEN OBJECTIVE CONDITIONS, SUBJECTIVE RESPONSES, AND NEIGHBORHOOD SATISFACTION Resident Characteristics Standards of Comparison Decibel level Perception of noise Assessment of noise KEY OUTCOME (hu/sq.km.) Assessment of crowding Traffic counts Student test scores Awareness of school quality Assessment of traffic Assessment of school quality NEIGHBORHOOD SATISFACTION Distance to nearest park Amount of parkland (no. of acres within sq.mi.) Other objective conditions Awareness of parkland Assessment of parks Friendliness of neighbors Other responses Feelings about house and community OBJECTIVE CONDITIONS SUBJECTIVE RESPONSES
Concern for safety Rating of school quality Public transit use Rating of public transit Likelihood of moving Neighborhood preference Neighborhood involvement Number of shopping trips Where children play Park visits Amount of Walking Amount of Experience Other Possible Outcomes Physical Health
How can indicators influence public policy? Other factors Needed Indicators Establish & Evaluate Policies, Plan Making Existing/Available Indicators Public Collection & Analysis of New Indicators
3. Quality of Life Study in Metro Istanbul Project support Istanbul Technical University Research Foundation Greater Istanbul Municipality Istanbul Strategic Plan 1:100,000 scale 1:25,000 scale
Turkey Istanbul
Istanbul - Population Growth 12,000,000 10,000,000 8,000,000 6,000,000 4,000,000 2,000,000 0 1927 1935 1940 1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 2000
Metro Istanbul - Population Black Sea Bosphorus Marmara Sea Europe 5,820,580 62% Asia 3,584,733 32%
4. Research Methodology 1. Survey: Face-to-Face Interviews with Residents N=1,635 2. Observations: Environmental Inventory 3. GIS data
Perceptions and Attitudes Quality of life Quality of neighborhood Public services and facilities Commercial facilities Environment and conservation of open land Residential history, mobility and preferences Travel behavior Community involvement and participation Neighboring Fear of crime Parks and recreation services Family health status Physical activity, etc. Survey
Observations Environmental Inventory Visible environment around respondent s home
Observations Environmental Inventory Visible environment around respondent s home Study II Physical Characteristics of Residential Environments 200 meters around respondent s home
GIS Database GIS Database Land Use, etc. Survey Data Study II Physical Characteristics of Residential Environments Environmental Inventory
Sampling Strategy Stratified Cluster Sampling 1. Categorize mahalle s (wards) 2. Identify cluster beginning points 3. Identify residential units 4. Identify respondents
1. Grouping of mahalle s (wards) Land value/meter square 2002 Tax assessment data Net residential densities 2000 Census data Low Medium High Low 162 mahalle s 84 39 Medium 29 87 111 High 46 110 69 Study area: 737 mahalle s; 15,375 ha
0.1 100 person/ha 100 300 persons/ha 300 1000 persons/ha of Mahalle s
Average s of Mahalle s 0.1 50 YTL/m 2 50 150 YTL/ m 2 150 950 YTL/ m 2
Low density low land value Low density medium land value Low density high land value Medium density low land value Medium density medium land value Medium density high land value High density low land value High density medium land value High density high land value Mahalle Groupings
Group Character Low Medium High Low Medium High 11314
Group Character Low Medium High Low Medium High 12377
Group Character Low Medium High Low Medium High 13466
Group Character Low Medium High Low Medium High 15583
Group Character Low Medium High Low Medium High 26690
Group Character Low Medium High Low Medium High 27768
Group Character Low Medium High Low Medium High 18821
Group Character Low Medium High Low Medium High 19843
2. Identify Cluster Beginning Points Total 423 clusters Target: 6 questionnaires per cluster Database Used GIS data of building entrances by 9 sampling regions Method Systematic random selection proportional to housing units in the residential building entrance Software ArcGIS 9.1 and SAS 9.1.3.
2. Identify Cluster Beginning Points
3. Identifying Residential Units Field enumeration
4. Identifying Respondents Kish Method 12 randomly assigned tables
Initial sample size: 2,538 5. Initial Findings Administered questionnaires: 1,645 October 2005 February 2006 Response rate: 65% Interview duration: Average = 40 minutes Response by gender: Male 580 35% Female 1065 65%
5. Initial Findings Overall neighborhood satisfaction by mahalle category 6.0 5.0 4.0 3.0 2.0 1.0 0.0 LD LLV LD MLV LD HLV MD LLV MD MLV MD HLV HD LLV HD MLV HD HLV Low Medium High Rating scale: 1 = not satisfied at all; 7 = very satisfied Istanbul average
5. Initial Findings Overall neighborhood satisfaction by mahalle category for Europe and Asia 7.0 6.0 5.0 4.0 3.0 2.0 1.0 0.0 LD LLV LD MLV LD HLV MD LLV MD MLV MD HLV HD LLV HD MLV HD HLV Rating scale: 1 = not satisfied at all; 7 = very satisfied Europe Asia
5. Initial Findings Overall neighborhood satisfaction by age groups 5.6 5.4 5.2 5.0 4.8 Istanbul average 4.6 4.4 4.2 4.0 Age 18-30 Age 31-45 Age 46-64 Age > 64 Rating scale: 1 = not satisfied at all; 7 = very satisfied
6. Future Work Analyses within Istanbul Metro Area Descriptive Statistics and Comparative analysis By nine regions Europe and Asia Istanbul Metro Redefine geographic units (growth stages in Istanbul?) Analyze relationship between subjective evaluations and objective environmental measurements Analyses between metro areas Compare & contrast Istanbul data with data from Detroit, Brisbane, etc. entire metro area & parts e.g. urban core, older suburbs, etc. Challenges: Cultural differences, etc??