compact city scenarios based on resident's intention in...

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 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 =



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%)


100(%)

80(%)

50(%)


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




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






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


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

















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


Clinic

Post office

Supermarket

Convenience store


Necessary of the facilities

Major inhabitant









0 10 20 40 50 60

Post office

Supermarket

Convenience store



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






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






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


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%)




Scenario2Scenario2 respecting the life in the suburb

Compact district population density 47.6(persons/ha)


7,790 persons (31%)18,003 persons (69%)



Scenario3Scenario3 Respecting the life in the compact district


Compact district population density 57.2(persons/ha)


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×0.65 [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

compact city scenarios based on resident's intention in...

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