Post on 10-Jul-2019
Compact City Scenarios Based onResident's Intention in the Small Town
Shota TamuraTakahiro TanakaDaisaku Nishina
02,0004,0006,0008,000
10,00012,00014,00016,000
2000
2005
2010
2015
2020
2025
2030
2035
2040
2045
2050
2055
2060
65歳以上 15~64歳 14歳以下[person
Population change in the futureLow density
Depopulation + low density
In recent years, compact city is becoming popular as a suiteurban structure for population decreasing society in Japan
Back ground
environment cost
Inhabitant
This study aims at building the compact scenarios based on the inhabitant’sintention and evaluating them from the viewpoints of CO2 emissions andinfrastructure maintenance costs
purpose
Back ground
Target area
prediction
Population decrease60000
50000
40000
30000
200001945 1970 2015 2035
50,417
35,192
25,793
Fuchu city[persons]
[year]
Hiroshima
TokyoRepublic of
Korea
Hiroshima Prefecture
Fuchu City
Fuchu City
0 5 10 20 30 40 Km
0 50 100 200 300 400 Km
(1) Extracting the critical factors of the scenarios for CO2 emissions and infrastructure maintenance costs.
(2) Examining inhabitant’s intention on the critical factors by questionnaire survey.
(3) Making scenarios based on the questionnaire survey results.
(4) Evaluating scenarios based on the inhabitant’s intention from the viewpoints of CO2 emissions and infrastructure maintenance costs.
Flow of the study
Definition of original words
Scenarios
Scenarios is defined as the spatial distribution of urban land use
Compact district
compact district is defined as the district which urban land use is concentrated
(1) Extracting the critical factors of the scenarios for CO2 emissions and infrastructure maintenance costs.
(2) Examining inhabitant’s intention on the critical factors by questionnaire survey.
(3) Making scenarios based on the questionnaire survey results.
(4) Evaluating scenarios based on the inhabitant’s intention from the viewpoints of CO2 emissions and infrastructure maintenance costs.
Flow of the study
0100002000030000400005000060000700008000090000100000
150
100 50 150
100 50 150
100 50 150
100 50 150
100 50 150
100 50 150
100 50 150
100 50 150
100 50 150
100 50 150
100 50 150
100 50 150
100 50 150
100 50 150
100 50 150
100 50 150
100 50 150
100 50
1 4 6 6 7 9 12 3 4 1 4 6 6 7 9 12 3 4
Urbandistrict
Wholearea
Urbandistrict
Wholearea
Urbandistrict
Wholearea
Urbandistrict
Wholearea
Urbandistrict
Wholearea
Urbandistrict
Wholearea
Urbandistrict
Wholearea
Urbandistrict
Wholearea
Fuchustation
The areaaround station
Elementary school district Junior high schooldistrict
Fuchustation
The districtaround station
Elementary schooldistrict
Former elementaryschool district
Junior high schooldistrict
singlecore
Multi core singlecore
Multi core
complete compact scenarios Partly compact scenario
Road Waterworks Sewer Elemntary school Junior high school Nursery Public hall Service costs
Population density (50 / 100 / 150 [person/ha])Number of compact district (1 / 3 / 4 / 6 / 7 /9 / 12)Urban planning area (The whole of target area / urban district )Place of compact district (the area around station/Elementary school district…)Single/Multi core modelPopulation balance (complete compact concentration / partly compact concentration)
Scenario factors
Previous study
Population balance
Population density
Compact village
Compact district
Contribution of critical factors for infrastructure maintenance costs
building costsmaintenance costs
0 500 1000 1500 2000 2500
Population balance
Population density
Compact village
Compact district
Contribution of critical factors for CO2 emissions
housesurban facilitiescars
0 2000 4000 6000 8000 10000
Population balance
Critical factors
Results of quantification method class 1
Compact district Population density
Population density
Population density
As for the population density, it is thought thatmost generally inhabitants don’t have sense onpopulation density
Necessity of some important facilities such assupermarket and clinic are asked in thequestionnaire survey.
The population densities in surrounding ofsuch facilities are analyzed and cumulativedistribution function curve and formula foreach facilities are made.
population density (person/ha)
Location probability(%)
questionnaire
Location probability
Location probability(%)
Location of post office
The number of mesh where the facility exist
The number of mesh where people live × 100=
Place of residense
Place of residense
Non-inhabitable area
The mesh where people live
The mesh where the facility (post office exist)
Place of residense
Post office
y = ‐0.006x2 + 1.409x + 20.656R² = 0.9082
0
20
40
60
80
100
120
0 50 100 150 200
Locatio
n Prob
ability
population density (persons/ha)
Post office
55 persons/ha
0~5 (persons/ha) Location probability =
5~10 (persons/ha) Location probability =
120~125 (persons/ha) Location probability =
4649140
×100 = 3.0114%
31290
×100 = 28.8461%
Number of the mesh having post office (population density5-10)
Number of the mesh having post office (population density5-10)
33
×100 = 100%
Population density (Location probability is 50%)
population density (person/ha)
Population density(Location probability is 80%)
Location probability(%)
100(%)
80(%)
50(%)
Location probability
0~10 10~20 20~30 30~40 40~50 50~60 60~70 70~80 80~90 90~1001.02 persons/ha 31.2 persons/ha
3.16 persons/ha 33.7persons/ha
23.7 persons/ha 52.9 persons/ha
5.95 persons/ha 36.7 persons/ha
27.3 persons/ha 57.4 persons/ha
30.2 persons/ha 58.8 persons/ha
22.7 persons/ha 52 persons/ha
24.7 persons/ha
26.7 persons/ha
54.6 persons/ha
56.8 persons/ha
28.5 persons/ha
26.9 persons/ha
59.9 persons/ha
60.7 persons/ha
3.14 persons/ha 34.3 persons/ha
14.1 persons/ha 40 persons/ha
13.5 persons/ha 41.2 persons/ha
24.5 persons/ha 54.2 persons/ha
23.1 persons/ha 55 persons/ha
57.3 persons/ha
99.6 persons/ha
Restaurant
Sports & Leisure facility
Grocery & Luxury store
Department store & suoermarket
Drugstore
Convenience store
beauty salon
LaundryElectrical equipment shop
Textile & clothing shop Furniture & Household goods
Welfare facility
Dental clinic
clinic
Nursery
Post office
Bank
Population density in the surrounding of facilities
Location probability
Questionnaire survey
Outline of questionnaire survey
Population balance
Population density
Compact district
Critical factors Questions for making scenarios to inhabitant
Which area will you want to live in the future?(downtown area or suburb)
what facility should be centrally located in the future?
What facility do you want to have in compact district in the future?
20’s women30’s women40’s women50’s women
20’s men30’s men40’s men50’s men
Men more than 60
Women more than 60
Downtown area56%
Other areas44%
Difference of sex and ageIntention of the place to live in
the future
Downtown area other areas0 10 20 30 40 50 60 70 80 90 100
Downtown area Outside of downtown area
Elderly men Women and younger men 56 %44 %
31 %69 %
65 %35 %
Major inhabitant
Population balance
Inhabitant intention
Elderly men Women and younger men Major inhabitant
Beauty saionRestaurant
Grocery and luxury storeDental clinic
ClinicDrugstoreNurseryLaundry
Electrical equipment shopConvenience store
Textile and clothing shopFurniture store
BankWelfare facilitySports FacilityLeisure facility
Department storeSupermarketPost office
Household goods store
Beauty saionRestaurant
Grocery and luxury storeDental clinic
ClinicDrugstoreNurseryLaundry
Electrical equipment shopConvenience store
Textile and clothing shopFurniture store
BankWelfare facilitySports FacilityLeisure facility
Department storeSupermarketPost office
Household goods store
Beauty saionRestaurant
Grocery and luxury storeDental clinic
ClinicDrugstoreNurseryLaundry
Electrical equipment shopConvenience store
Textile and clothing shopFurniture store
BankWelfare facilitySports FacilityLeisure facility
Department storeSupermarketPost office
Household goods store
0 10 20 40 50 60 0 10 20 40 50 60 0 10 20 40 50 60
Post office
Supermarket
Convenience store
Grocery and luxury store
Post office
Convenience store
Grocery and luxury store
Clinic
Post office
Supermarket
Convenience store
Inhabitant intention
Necessary of the facilities
Major inhabitant
Beauty saionRestaurant
Grocery and luxury storeDental clinic
ClinicDrugstoreNurseryLaundry
Electrical equipment shopConvenience store
Textile and clothing shopFurniture store
BankWelfare facilitySports FacilityLeisure facility
Department storeSupermarketPost office
Household goods store
0 10 20 40 50 60
Post office
Supermarket
Convenience store
Grocery and luxury store
Inhabitant intention
Necessary of the facilities
0~10 10~20 20~30 30~40 40~50 50~60 60~70 70~80 80~90 90~1001.02 persons/ha 31.2 persons/ha
3.16 persons/ha 33.7persons/ha
23.7 persons/ha 52.9 persons/ha
5.95 persons/ha 36.7 persons/ha
27.3 persons/ha 57.4 persons/ha
30.2 persons/ha 58.8 persons/ha
22.7 persons/ha 52 persons/ha
24.7 persons/ha
26.7 persons/ha
54.6 persons/ha
56.8 persons/ha
28.5 persons/ha
26.9 persons/ha
59.9 persons/ha
60.7 persons/ha
3.14 persons/ha 34.3 persons/ha
14.1 persons/ha 40 persons/ha
13.5 persons/ha 41.2 persons/ha
24.5 persons/ha 54.2 persons/ha
23.1 persons/ha 55 persons/ha
57.3 persons/ha
99.6 persons/ha
Restaurant
Sports & Leisure facility
Grocery & Luxury store
Department store & suoermarket
Drugstore
Convenience store
beauty salon
LaundryElectrical equipment shop
Textile & clothing shop Furniture & Household goods
Welfare facility
Dental clinic
clinic
Nursery
Post office
Bank
Population density in the surrounding of facilities
55 (persons/ha)
58.8 (persons/ha)
57.4 (persons/ha)
36.7 (persons/ha)
Compact district population density is average of these population
51.9 (persons/ha)
Shopping center is preferable
15.9% 15.2% 53.7%
0% 20% 40% 60% 80% 100%
Railway stationElementary schoolJunior high schoolShopping streetCity hallShopping centerOthers
Center place of compact district
Inhabitant intention
Population density (persons/ha)StationRail road
0 10 20 30 40 50 60 Shopping center
making from major inhabitant intentionScenario1Scenario1
Scenario based on inhabitant intentions
Compact district population density 52(persons/ha)
PopulationCompact districtSuburb
14,444 persons (56%)11,349 persons (44%)
Scenario based on inhabitant intentions
Population density (persons/ha)StationRail road
0 10 20 30 40 50 60 Shopping center
Scenario2Scenario2 respecting the life in the suburb
Compact district population density 47.6(persons/ha)
PopulationCompact districtSuburb
7,790 persons (31%)18,003 persons (69%)
Population density (persons/ha)StationRail road
0 10 20 30 40 50 60 Shopping center
Scenario3Scenario3 Respecting the life in the compact district
Scenario based on inhabitant intentions
Compact district population density 57.2(persons/ha)
PopulationCompact districtSuburb
16,766 persons (56%)9,027 persons (44%)
Scenario evaluation
Urban infrastructure costs
Urban infrastructure development costs
Urban infrastructuremaintenance costs+
Target of urban infrastructure
7. Road
2. Waterworks 3. Sewer 4. Elementary school
5. Junior high school 6. Nursey
1. Public hall
8. Development costs
These infrastructures are considered to be affected by urban structure change
The methods of estimating urban infrastructure costs
Scenario evaluation
Making the estimation formula by actual data concerning urban infrastructure in Fuchu city
Evaluating scenarios from view points of urban infrastructure development and maintenance
Ex. Elementary schoolDevelopment costs (yen) = maintenance floor area (m2) × 188,093(yen/m2)
Maintenance costs (yen) = ∑ (yen) + Li (yen)
Ki : Service costs of all elementary school in the scenario Li : labor costs of all elementary school in the scenario
Scenario evaluation
CO2 emissions
These infrastructures are considered to be affected by urban structure change
Cars HousesUrban facilities
Scenario evaluation
CO2 emissions from carsJoge city
Fukuyama city
Gocho city
City hallJR lineMain roads
CO2 emission from cars used byinhabitants in Fuchu and surroundingarea are examined by person trips survey.
MethodCO2 emissions are calculated bymultiplying the number of moving carsamong each area by their movementdistances and CO2 emissions per units ofdistances.
L = ∑ × Kod × MvL: CO2 emissions (t-CO2) Tod: traffic density distribution
Kod: distance between with each area (km)
Mv: unit of CO2 emission from cars types
Scenario evaluation
CO2 emissions from facilitiesCO2 emissions are calculated by multiplying amounts or costs ofdevelopment and maintenance by actual data in Fuchu city or unit of CO2emission extracted from reference.
Ex. Elementary school
・ CO2 emission from maintenance
development cost ×3.649[kg-CO2/thousands yen]
unit of CO2 emissions per development costs based on the value of reference
・ CO2 emission from development
number of class ×12.31[t-CO2/class]
unit of CO2 emissions calculated by usage of electric power , gas and oil amount in elementary school
Scenario evaluation
CO2 emissions from housesCO2 emissions from air-conditioner, CO2 emissions from construction, repair,renewal and scrap and CO2 emissions from using common area in apartmentare calculated for each scenario.
Method CO2 emissions from houses are calculated by the number of detached houseand apartments by each unit of CO2 emissions.
戸建住宅 集合住宅(3~5階建)
冷暖房 住宅棟数 [棟]×0.65 [t-CO 2/棟] 住宅棟数 [棟]×10.92 [t-CO 2/棟]
建設 住宅棟数 [棟]×1.12 [t-CO 2/棟] 住宅棟数 [棟]×42.68 [t-CO 2/棟]
修繕・更新 住宅棟数 [棟]×0.23 [t-CO 2/棟] 住宅棟数 [棟]×16.65 [t-CO 2/棟]
解体 住宅棟数 [棟]×0.15 [t-CO 2/棟] 住宅棟数 [棟]×10.78 [t-CO 2/棟]
共用部 - 住宅棟数 [棟]×14.10 [t-CO 2/棟]
The number of building ×10.92 [t-CO2/building]
The number of building ×42.68 [t-CO2/building]
The number of building ×16.65 [t-CO2/building]
The number of building ×10.78 [t-CO2/building]
The number of building ×14.10 [t-CO2/building]
The number of building×0.65 [t-CO2/building]
The number of building×1.12 [t-CO2/building]
The number of building×0.23 [t-CO2/building]
The number of building×0.15 [t-CO2/building]
Detached house apartmentAir-conditioner
Construction
Repair/Renewal
Scrap
Common area
conclusionAll three scenarios are more efficient in both CO2 emissions and infrastructuremaintenance costs than BAU scenario. It can be said that the scenario basedon the inhabitant’s intention may also have effects.
Results
Scenario evaluation