Yasunaka Cho Portfolio
Mahasarakham Dawontown Revitalize Plan Thailand, June 2012
With Ico and Yuwadee
/
CRITERIA ELEMENTS STRENGTHS
WEAKNESSES
OPPORTUNITIES
THREATS
Socio-economics
High economic dynamic
Few regulations on landuse
Increase of economic activities
Increase of informal development
Young population
Centralized political power
Formalize existing commercial activities
Reduction of city beauty
Medium to high income students
Lack of civic discipline
Attract additional youth
Risk of political corruption
Many local private businesses
Low income farmers
Consume local food
Inconsistent development
Education center of Isan
Lack of administrative collaboration
Evolve into mature economy
Decrease of the number of farmers
Agricultural activities
Few leisure attractions
Large working population
Less attractive places
Strong service sector
Lack of interaction with nature
Social capital
Increase living cost
People's welcoming attitude
Lack of skilled workers
Increase of learning community
Risk of auto accidents Lower growth rates
Culinary culture Strong existing social bonds
Monopoly
shift from production to service economy
Lack of cohesions
Cultural activities
Environmental
Physical Context
ASEAN2015
Lack of regulation on commercial activities
Large amount of green space
Lack of solid waste management
Opportunity of new developing model
Ecosystem degradation
Several natural water bodies
Too many motorcycles
Possibility for diverse water management
Elevated CO2 emission
Few factories
High fuel consumption
Use of relative healthy soil
Few impervious surfaces
Lack of natural places
Chance of forest recovery
Existing biodiversity
Pollution (air, water, solid waste)
Rich in minerals
Low land productivity
Improve local ecosystem
A nearby national park
Lack of water management
Create of new green public spaces
Endemic species
Pesticides used in farming
Attract nature-interested tourism
Good soil conditions
River erosion for construction
Convenient location to explore Southeast Asia Constructed ponds and canals Road communication ・bypass#23 Educational institutions Land use diversity Cultural and religious sites Relatively low built environment Regular topography Diverse development suitability
Increase in the number of mosquitoes ・health issues
Shortage of emergency organizations
Develop regional strategy
Lack of collaboration between political jurisdictions
Improve built landscape
Lack of crosswalks
Develop alternative transportation
Improve production dynamics Shortage of public transportation
Reduce city inner transit
Lack of parking spaces
Keep youth population
Sprawing
Attract new population
Lack of respect for public realm
Increase knowledge production
Lack of transit signals
Maximize tourism potential
Lack of public spaces
Encourage smart growth
Road conditions
Take advantage of diverse development suitability
・loss of soil quality Limited food security
Lack of correlation in regional management Increase in private transportation means Creation of community malfunction Increase of accidents rate Emerge congestion Possibility of transit chaos Decrease of vehicle quality
THE IMAGE OF THE CITY ANALYSIS
Kantarawichai 213
0
2
4km
Mueang and Mahasarakham Districts have developed rapidly, especially with regard to the speed of economic and population growth. Due to the fast development speed, the region cannot deal with its environmental and transportation issues. Urban sprawl has generally been viewed as an undesirable pattern of growth, which results in longer commute times, higher cost of infrastructure to be built and paid by governments to support the new development of suburbs, increases in greenhouse gases due to the rising number of people driving cars back and forth between their homes and workplaces, underground and surface water degradation as runoff water passes through parking lots and roads, reduction of farmland and forest lands (Daniels, 2001).
2367 208
Concentrating residences in the core of cities would bolster the city center’s economy as there would be more demand for commodities and more people would be employed. In turn, the crime rate would also decrease. As Henry (2011) writes, “A more efficient business climate can result from employment centers located in close proximity rather than in scattered sites. The health of central city downtowns is intertwined with that of the region as a whole.”(Henry, 2011) The development would create more jobs in the city center, elevate the standard of living of people in the city, and provide more housing opportunities.
Mueang Maha Sarakham
References Daniels, Tom. Smart Growth: A New American Approach to Regional Planning. Research, Vol. 16, Nos. 3/4, pp. 271–279, 2001.
Planning Practice &
Henry, Yahya Aribra. "5 Reasons Why Infill Development is needed Now." Last modified December 20, 2011. Accessed July 12, 2012. http://aribra.com/5-reasons-why-infill-development-is-needed-now.
Legend A.D.1057 A.D.1865 A.D.1912 A.D.1947 A.D.1968 A.D.1989
23
23
A.D.1999 A.D.2007 No Data
2040
0
2
4km
Paths
Districts
Kantarawichai
Kantarawichai 213
2367 208 Mueang Maha Sarakham
Mueang Maha Sarakham
Legend
paths
paths
Primary Secondary
Primary
Terciary
Secondary
landmarks
Terciary
landmarks temples edges
temples
23
23
nodes
nodes
Legend edges districts
districts
2040 0
Temples, Landmarks, and Nodes
4km
2
0
Edges
Kantarawichai
213
2367
2367
208
208
Mueang Maha Sarakham
Mueang Maha Sarakham
paths
paths
Legend Primary
Primary
Secondary
Secondary
Terciary
Terciary
landmarks
landmarks
temples edges districts
4km
Kantarawichai 213
nodes
2
temples
23
23
Legend nodes edges districts
2040
0
2
4km
23
23 2040
0
2
4km
THE IMAGE OF THE CITY ANALYSIS
THE IMAGE OF THE CITY ANALYSIS
93,312
1993 2003
96,408
2011
153,274
2021
Mueang Maha Sarakham Population 60% of MSU students commute in motorcycles: about 25,267 units
Solid waste Mobility Food production Construction Social impact
228,378
Scenario 1: Existing Direction Pattern Producing each one: - 0.65 kg of solid waste - 120 liters of wastewater - 0.45 kg of Greenhouse gases
EVERY DAY!
Alternative Direction Pattern 93,312
1993 2003
96,408
2011
153,274
2021
Mueang Maha Sarakham Population
Curitiba Transportation System
John Todd’s Living Machine
228,378
Scenario 2:
Appropriate managmement of: - 0.65 kg of solid waste p/p - 120 liters of wastewater p/p Enjoying a healthy environment
EVERY DAY!
GIS Analysis for Community Revitalization Cincinnati OH, April 2012
a. Project This project aims to find the most appropriate five vacant buildings for artist communites. The condition is 5 -10 minutes walk-distance from dense residence areas. b. Analytical Process First of all, I used clip tool to create the maps of
Figure 1.
vacant building as well as residence use (Figure1). Then, I created Kernel density by using all residences in all Cincinnati neighborhoods (Figure2). Next, among a couple of places that show much denser than other places, I intentionally choose the CUF that is the nearest neighborhood from downtown Cincinnati (Figure3). After this operation, I used median center tool to figure out what is the center of the CUF residences (Figure4). Finally, I used Kernel density and
Figure 2.
buffer the buffer to find the closest cluster from the median center in CUF (Figure5 and 6). c. Result The analysis shows the best place for the place for new art communities for local artists. The 13 vacant buildings in CUF are found as the best places for the customer after the series of analyses Source: CAGIS and OKI
Figure 3.
Figure 4.
Figure 5.
Figure 6.
Evaluation of the Baan Mankong Slum Upgrading Project in Thailand
1. Globalization Globalization has taken place since the 1970s, at first gradually and now at a quickened pace. As capitalism grew and counties or nation-states were established, these sovereign or independent political units engaged in economic relations with one another. “Globalization reflects (1) the geographic reorganization of industrial production and service provision; (2) the interpenetration of corporations across national boundaries; (3) the worldwide diffusion and deliberate creation of markets being offered identical or nearly identical consumer goods; (4) the internal movement of populations within developing countries to large cities, and the immigration of people from developing countries to the United States, Canada, and Western Europe” (Kaplan, Wheeler & Holloway, 2008). Globalization increases the speed and global scale of economic interactions, as well as increases the mobility of goods and people. The profound economic changes that characterize globalization have deepened economic and social polarization in both country and city levels. The emergence of so-called world cities, such as New York, London, and Tokyo, play key roles in the new concentrated financial system. Figure1. Connectedness of Global Cities: α, β and γ tiers
BAL CITIES
ONIOUS
DEVELOPMENT
acc o to G rding aW C
pments have had an increasing impact on cities, regions and territories from the societal, d geographical points of view. Since 1998 the d cities into globalization has been extensively Globalization and World Cities (GaWC) Research
s a geographic and economic-based overview
s discourse is its categorization of world tiers2, based upon their international
is observed from the point of view of the the world cities, a new image emerges, where tually oriented to other cities of the same level ctivity. National or continental maps give way to
ears utterly separated from its geographical nd closer to other cities of same level. The
tions, primarily in the global economic system.
ws the world cities according to the GaWC
ere expected national and local boundaries in their real disposition based upon their onnectedness.
© α++ city 2012
α+ city α city α- city connection with α group city β+ city β city β- city connection with β group city γ+ city γ city γ- city
β- cities
OSAKA OK_25.20 BRISBANE BB_28.98
CALGARY CG_25.36
DENVER DV_27.90 ST. LOUIS SL_26.74 DETROIT DT_28.43 CLEVELAND CV_25.74 RIO JANEIRO BIRMINGHAM RJ_29.48 BM_29.51 CASABLANCA COLOGNE CS_27.44 CO_26.82 LAGOS STUTTGART LG_25.88 GENEVA GN_28.59 ST_27.10 BRATISLAVA HELSINKI BV_27.55 SOFIA HL_26.73 NICOSIA SO_26.91 NC_29.58 MANAMA MM_27.11 PORT LOUIS ABU DHABI PL_27.44 AB_29.84 CALCUTTA PERTH CC_28.47 PE_25.82 SHENZHEN SZ_25.80
Source: http://www.lboro.ac.uk/gawc/visual/globalcities2010.pdf
SAN DIEGO SD_26.07 MONTERREY MY_27.81 GUATEMALA GT_25.30 PANAMA PN_26.14 SAN JUAN SN_25.45
AUCKLAND AK_33.53
GUANGZHOU GZ_34.12
KARACHI KR_31.21 CHENNAI CN_32.81
HO CHI MINH HC_33.86
BUDAPEST BD_34.91 KIEV KV_33.38 BEIRUT BT_34.74 RIYADH RY_30.51
MANCHESTER MC_31.43 OSLO OS_33.51
β cities
LUXEMBOURG CAPE TOWN LX_34.56 CT_30.69 BUCHAREST BU_32.38
MONTEVIDEO MV_30.45
CARACAS CR_33.97
SEATTLE SE_34.01
MINNEAPOLIS MP_30.34 LIMA LM_31.05
MANILA MN_37.20
BANGALORE BN_36.58
MONTREAL MT_38.13
β+ cities
DUSSELDORF DS_38.91 BERLIN HAMBURG BL_36.83 HB_37.30 ROME COPENHAGEN RM_38.10 CP_36.57 ATHENS STOCKHOLM AS_36.77 PRAGUE SK_38.53 CAIRO PR_38.50 CA_36.42 TEL AVIV TA_36.59
VANCOUVER VN_35.61 HOUSTON HS_37.17
SHANGAI SH_62.70
HONG KONG HK_72,96
DUBAI DU_61.36
PARIS PA_68.28
TOKIO TK_63.75 SYDNEY SY_61,06
BOGOTA BG_35.62
α+ cities
SINGAPORE SG_67.46
α++ cities
Map of Global Cities 2010. The map clearly shows areas of the world rather dense and others almost irrelevant in terms of world city connectivity
CHICAGO CH_61.60
NEW YORK NY_94.35
THESIS
LONDON LN_100
Shape of connectivity amongst world cities of same tier and Proportional Global Network Connectivity (GNC) Scores 2010, according to GaWC
01
2. Urbanization The United Nations (UN) has projected that 70% of all populations in the world will live in urban areas by 2050. This is a result of changing demographic, technological, and international relationships. The main reasons for urbanization are the rapid decline in death rates, rise in birth rates, and rural to urban migration. Rural to urban migration is a common trend a in many countries as impoverished rural residents migrate to the larger towns and cities in search of a more prosperous life. They are driven by the desire for employment and the prospect of access to public facilities and services that are often unavailable in rural regions (Knox & McCarthy, 2005). However, they have poured into cities out of desperation and hope, rather than being drawn by actual jobs and opportunities. Urbanization has the potential to be positive in terms of economic development, easier access to health centers, and educational facilities. However, rural immigrants typically cannot afford to live in the formal sector of urban areas due to land price. Typically, they end up living in the slums. Figure2. The new urban world The new urban world The earth reaches a momentous milestone: by next year, for the first time in history, more than half its population will be living in cities. Those 3.3 billion people are expected to grow to 5 billion by 2030 — this unique map of the world shows where those people live now
Norway
Canada 26.3 80%
Ireland
New York 21.8
Urban population in millions
81%
Urban percentage Portugal
Mexico 84.392 77% Mexico City 22.1
Nicaragua Costa Rica Panama
Colombia 34.3 73% Ecuador Peru 21.0 73% Bolivia
Predominantly rural 25—49% urban Predominantly rural 0—24% urban Cities over 10 million people (greater urban area)
Chile 14.6 88%
Ivory Coast 8.6
Venezuela 26.0 94%
8.7
Predominantly urban 50—74%
Italy 39.6 68%
Spain 33.6 77%
Liberia
Trinidad & Tobago
Predominantly urban 75% or over
Switzerland
Morocco 19.4 Gambia 60% Senegal Guinea-Bissau Mauritania Lagos Sierra Leone Guinea 10.0
Haiti Dominican Puerto Republic Rico
Honduras
Key
Germany 62.0 75%
Belgium 10.2 97%
Algeria 22.0 65%
Guatemala El Salvador
Belarus
Denmark
Mali Burkina
Ghana 11.3 49% Togo
Brazil 162.6 85%
7.4
Paraguay
Argentina Uruguay 35.6 Buenos 90% Aires
Canton 14.5
Romania 11.6 Istanbul 54%
Slovenia Croatia Serbia & Mont Bulgaria Bosnia Macedonia Albania
Greece
Cairo 15.9
Lebanon Palestine
Egypt 33.1 43%
Libya Niger
Chad
Sudan 16.3 43%
11.7
Syria 10.2 51%
Eritrea
Ethiopia 13.0 16%
Tajikistan
Afghanistan 7.8
Bhutan
By 2030, the towns and cities of the developing world will make up 80% of urban humanity
Mauritius
Hong Kong
Burma 16.5 32%
Bangladesh 38.2 26%
India 329.3 29%
Somalia
Madagascar
42% Nepal
Dacca 13.8
Delhi 21.1
Laos
Cambodia
Thailand 21.5 33% Malaysia 18.1 69% Singapore
Sri Lanka
Calcutta 15.5
Seoul 23.2
Vietnam 23.3 27%
Bombay 21.3
Swaziland Lesotho
Japan 84.7 66%
S Korea 39.0 81%
Urban percentage
Karachi 14.8
Yemen
N Korea 14.1 62%
Urban population in millions
Pakistan 59.3 36%
Kenya
Zimbabwe
S Africa 28.6 60%
Kuwait
Saudi Arabia UAE 20.9 81% Oman
Cameroon Congo 9.9 9.5 Zambia 25% Gabon Angola Malawi 9.3 MozamBotswana bique
Rio de Janeiro 12.2
Iraq 20.3 67%
7.6 DR Congo Rwanda 20.2 33% BurundiTanzania
Namibia
Uzbekistan 10.1 Kyrgyzstan Turkmenistan 37%
Iran 48.4 68%
Jordan
China 559.2
Kazakhstan 8.6
Tehran 12.1 Azerbaijan
Georgia Armenia
Turkey 51.1 68%
Israel
Uganda
Beijing 12.7
Mongolia
Moldova
Austria Hungary
CAR
Sao Paulo 20.4
Shanghai 17.3
Ukraine 30.9 Czech 68% Republic Slovakia
Nigeria 68.6 50%
Benin
Moscow 13.4
Poland 23.9 62%
Tunisia
Cuba 8.5 Jamaica
Netherlands 13.3 81%
France 46.9 77%
At the beginning of the 20th century, the world's urban population was only 220 million, mainly in the west
Russia 103.6 73%
Estonia Latvia Lithuania
London 12.0
US 246.2
LA 17.9
UK 54.0 90%
Sweden Finland 7.6
Osaka 16.6
Philippines 55.0 64%
Indonesia 114.1 50%
Jakarta 14.9
Tokyo 33.4
Manila 15.4
Papua New Guinea Melanesia
E Timor
Australia 18.3 89%
New Zealand
Urban growth, 2005—2010
3.2%
2.8%
13.5
2.4% 1.7%
Africa
Arab States
Asia
Latin America & Caribbean
1.3%
1.3%
Oceania
North America
0.1% Europe
-0.4%
Eastern Europe
3,307,950,000 The world’s urban population — from a total of 6,615.9 million
SOURCE: UNFPA GRAPHIC: PAUL SCRUTON
Source: http://www.guardian.co.uk/environment/2007/jun/28/climatechange.conservation THESIS
02
3. Slum generation The Millennium Development Goals, created by the United Nations, reported that the share of the urban population living in slums in the developing world has declined significantly over the past 10 years (see the Figure). However, in absolute terms, the number of slum dwellers in the developing world is actually growing, and will continue to rise in the near future. According to the United Nations (UN), the slum population of the world will grow to 2 billion in the next 20 years if no preventive measures are taken (UN-HABITAT, 2003). The UN has listed the Baan Mankong Program (BMP) in Thailand as one of the few unique and sustainable examples of participatory slum upgrading programs.
Figure3. Population living in urban slums and proportion of urban population living in slums, 1990-2010 Population in slums Percentage of urban population living in slums 900,000
50
46.1 42.8 39.3
Populaiton in slums (Millions)
600,000
THESIS
35.7
40 34.3
32.7
30
20
300,000
10
0
0 1990
1995
2000
2005
2007
Proportion of urban population in slums (Percentage)
60
2010
03
4. Research questions This paper evaluates how successful the BMP is, and makes recommendations for the future of the slum upgrading program in Thailand. In order to achieve these goals, the research questions are:
1) What are the gaps between the initial goals of BMP and the current situation? 2) Why have differences occurred between the plan and reality both in quality and quantity? 3) How can a further slum upgrading program be developed from the BMP?
5. Methodology Slum definition
The problem with measuring slums begins with the lack of an agreed definition. As a result, enumeration of slums has not yet been incorporated within mainstream monitoring instruments, such as national population censuses, demographic and health surveys, and global surveys. The UN itself has developed indicators and thresholds for defining slums for evaluate slum. This research uses the UN slum indicator to evaluate the physical condition of slums in the analyses portion.
Case study method
This paper uses the single (embedded) case study method as the research methodology for analyzing both the macro level analyses of how many projects have been implemented in a certain periods, and the micro level analyses of how a target community improves through the program.
THESIS
04
Table. Indicators and thresholds for defining slums
Source: UN-HABITAT, 2003 THESIS
05
6. Baan Mankong Program Baan Monkong Program (BMP) is one of two slum upgrading programs under the Thai government’s policy to provide One Million Housing Units within 5 years between 2003 and 2007. Baan Mankong has set a goal of improving housing, in terms of living and tenure security for 300,000 households in 2,000 poor communities in 200 Thai cities within five years. BMP channels government funds, in the form of infrastructure subsidies and soft housing loans, directly to poor communities. The main difference from conventional programs of delivering housing units to individual poor families is that the BMP encourages existing slum communities to form co-ops to develop their housing in a collective way. This method is designed to discourage speculators from buying off individual housing units from the poor and selling them out to higher income groups (CODI, “History,” 2011). Each community can choose one of five types of upgrading, which can be chosen by the community to fit their best practices.
THESIS
06
7. Results During the expected target period from January 2003 to March 2008, the BMP’s 512 projects involving 1,010 communities were approved. These communities were located in 226 cities in 76 different provinces, and affected 53, 976 families (CODI Monthly Report, March 2008). The program, which has upgraded 1546 communities and 90,000 households by January 2011, is still progressing towards reaching its initial target.
Figure5. Number of projects implemented through the BMP
project 900 800 700 600 500
t_project
400 300 200 100
0
2003 2004 2005 2006 2007 2008 2009 2010 2011
Figure6. Number of communties implemented through the BMP
community 1600 1400 1200 1000
800
t_community
600 400 200
0
2003 2004 2005 2006 2007 2008 2009 2010 2011
Figure7. Number of units implemented through the BMP
unit 90000 80000 70000 60000 50000
t_unit
40000 30000 20000 10000 0
THESIS
2003 2004 2005 2006 2007 2008 2009 2010 2011
07
8. Conclusion Quantity
The CODI initially expected to construct 150 housing units by 2003, 1,500 units by 2004, and 300,000 units by the end of 2007. However, they have only achieved about a third of that goal, which is 90,813 housing units, by January 2011. There were significant differences of speed of implementation in each year. Additionally, although the project is still in progress, its speed of implementation has slowed down since then. The Primary reason of failure to achieve the ambitious goal is due to its financial system. First of all, the government has strong influences on the program. Its finances were strongly affected by the global economy including the world financial crises in 2008. In addition, the unstable government political situation strongly changed the situation. Mr. Thaksin emphasized on the support to the poor, however Ms. Yingluck, the current prime minister, focuses less on them. Secondly, the financial model of the BMP was no longer sustainable after 2008 when the program was suppose to have achieved their initial goals. The reason for this is because the financial model, theoretically, takes 15 years to be able to collect all loans from the recipients. CODI had a budget to implement the program for the first five years from 2003 to 2007, but the organization was forced to slow down the project without a government injection, as they could not collect all the loans within five years. Therefore, they could not allocate the same amount of money to other communities for implementing the projects.
Quality
The newly built living environment created through the BMP showed sufficient improvements. Klong Toey Block 7-12, a community this focused on in this research, has improved significantly in terms of the living conditions that the UN slum indicators specify. Access to water, access to sanitation, building structure, and overcrowding were all addressed. Housing units in the community have access to water and sanitation and built durable structures with sufficient materials. However, the location and land tenure could have been improved more. Although this is not a hazardous place as the UN slum indicator mentions, the site of the community located next to a slum were just across a small path. Although the community has got tenure of its land, they have to move out after the leases are over. The mental condition of the residents is indicative of the preferences they have toward their housings and the financial situation they are facing. According a CODI’s survey many residents show affection towards the new houses. Despite of the high popularity of their housing, more than 35 percent of the residents complained about the size of the land. Therefore, there is room to improve the size of land through more flexible approaches of distribution that are based on needs. Since many residences borrow loans from CODI and other financial institutions, they have to return their loans periodically. Approximately, 35 percent of them have problem of returning their loans. The budget system of the program is suitable for low-income residents who need a little bit more financial supports to build their houses. It is not suitable for the lowest-income residents who need a larger amount of money for building their houses.
THESIS
08
Bibliography ACHR. (2007). Housing by people in Asia. Bangkok: Asian Coalition for Housing Rights Boonyabancha, S. (2005). Baan Mankong: going to scale with ''slum'' and squatter upgrading in Thailand. Environment and Urbanization, 17(1), 21-46. Retrieved from http://eau.sagepub.com/content/17/1/21.full.pdf html CODI. (n.d.). Results: Statistics January 2011. Retrieved from http://www.codi.or.th/housing/results.html CODI. (2004). CODI update. Bangkok: Community Organisations Development Institute CODI. (2012, July). Approve Report Baanmankong Project. Bangkok: Excel spreadsheet at CODI Kaplan, D., Wheeler, J., & Holloway, S. (2008). Urban geography. Danvers: Wiley and Sons Inc. Knox, P. L., & McCarthy, L. M. (2005). Urbanization, an introduction to urban geography. (2 ed.). Upper Saddle River, NJ: Prentice Hall. United Nations. (2010, June 15). The millennium development goals report 2010. Retrieved from http://www.un.org/millenniumgoals/pdf/MDG Report 2010 En r15 -low res 20100615 -.pdf UN-HABITAT. (2003). The challenge of slums - Global report on human settlements 2003. Retrieved from http://www.unhabitat.org/pmss/listItemDetails.aspx?publicationID=1156
THESIS
09