Constructing Formulation of Affordable Green Home for Middle Income Group

A.R. Musa, N. M. Tawil*, S. M. Sood, A. I. Che-Ani, N. Hamzah, H. Basri

Universiti Kebangsaan Malaysia, 43600 UKM, Bangi, Selangor, MALAYSIA

2nd International Building Control Conference 2011

Abstract

The purpose of this research is to develop a new affordable and sustainable green home which focusing on affordability of young generation to have their own house in early age of working. When housing affordability is measured by rent-income ratios based on annual income, affordability must be correlated with income. Moreover, housing will appear to be less affordable for the very young and very old; it will appear to be more affordable to households at the peak of their lifetime income profiles (Quigley J.M & Raphael. S (2004).

This research then appraises the costing of materials for commercial housing development as possible avenue for cost reduction in the house price. Another element is the management of materials at construction site. It is hoped that out of this research a Commercially Affordable Sustainable House (CASH) module could be developed and later implemented for meeting the country’s housing needs and becoming an environmentally responsible country at the same time.

Framework

The observation, interviews and survey is used in the collecting data method. Data mining with individual and group interviews in this research are considered as a convenient way to collect data. This method allows each person to respond to question, then asking questions, exchanging comments according to his/her experiences and points of view. The interviews and survey used the form of questionnaire. In this research exploring existing cost data is needed to formulate financial for Housing construction. Thus, the approval and the collaboration with local authority is very important.

The first part of this research is to collect data regarding to the critical construction process in housing project management and factors influencing the house price in Langat District. The survey will used to collect data on house price and household income to get the price to income ratio, this data mining will involve INSPEN, MHLA and stakeholder, Second part of the collecting data method is using interview to define categories of factors with the developers and CIDB. By using this technique, the researcher could identify the main aspects, categories, indicators, and parameters to develop simulation on costing of construction for affordable sustainable housing scheme and housing price index for the university township.

Second part of this research is to identifying factors to reduce cost by analyze unnecessary content or over specification from the housing project and propose a framework provides a suitable checklist for the cost management of CASH（commercial affordable sustainable house） in both formal and informal housing sector of the economy.

One of this work aims to present a mathematical programming approach to solve imprecise housing cost problems with fuzzy goal and fuzzy cost coefficients. It will designed to minimize total project costs with reference to direct costs, indirect costs, contractual penalty costs, duration of activities and the constraint of available budget. Few models for costing and housing analysis such as hedonic models, fuzzy programming will be use to develop CASH.

Third part of this research is to identify the best system and design of rainwater harvesting-system by using literature review method. This stage will explore the existing house and proposes house design that is suitable for incorporating in rainwater-harvesting system. Towards the end, with the integrated an architect, QS, Property Finance, Finance, BS, GBI, Project Management, this research will identifying new construction and material system, new management tool, new system of unburden CASH and factors to reduce overall cost for CASH.

Conclusion

The concern of this research is to design towards the development of critical construction processes in housing project management for developing affordable and sustainable housing scheme. it is well known in Malaysia the difficulty in ownership of housing especially for middle income category. Thus, this research is useful to help housing construction in determining which element that can help in reducing the price of new houses. Furthermore, green element if beeing introduce, may give significant effect in long run of life span and life cycle of the building. Researcher of this group will try to formulate the best solution in order to help middle income buyers for nation development.

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The Impact of Urbanization Policy on Land Use Change: A Scenario Analysis

Cities 28 (2011) 147–159

Yuzhe Wua, Xiaoling Zhang, Liyin Shen

Resumed by Pindo Tutuko

Abstract

The rapid urbanization has led to extensive land use change particularly in those developing countries.

This paper introduces a dynamic systems based method for assessing the impacts of urbanization policy on land use change with reference to the urbanization practice in China. Four typical policy scenarios are identified in implementing urbanization in China, including 

1. Balanced development driven by planning
2. Uneven development driven by planning
3. Balanced development driven by market
4. Uneven development driven by market and their impacts on land use change.

They are analyzed through a dynamic system model. 

Introduction

• Urbanization has increased in transport provision and development of regional economies. Increased demand for urban land has led to a diversification of land use patterns (for example, industrial, residential, and infrastructure uses, as well as ecological conservation).
• The number of mega-cities (>1 million population) increased from 13 in 1978 to 56 in 2007 (National Bureau of Statistics of China, 2007).
• Land use change is closely related to the socio-economic and ecological environment.
• A large a mount of agricultural land to be developed as construction land.

Research Method

• The system dynamics method, the model contains urbanization, social, economic, environmental and land use subsystems.
• System dynamics (SD) was created in the form of a computer simulation model, comprising five modules of world population, industrialization, pollution, food production and resource depletion - to forecast the exhaustion of the world resources.

Study Area

The year 2002 marked the opening of the highway from Jinyun County to Hangzhou, the capital of Zhejiang Province – greatly improving access to the Jinyun County. The urbanization level has also been accelerated, with an urban population of 33.1% of the total population in 2000 increasing to 46.3% by 2007

The SD model for land use change

The first stage in constructing an SD model is to define the system boundary.

It have a boundary comprised of urbanization (U), social (S), economic (E), environmental (EN), and land use (LU) subsystems.

Economic development levels in urban areas are generally higher than that in rural areas (income in urban areas is higher than in rural areas). Results in the continuous movement of the rural population to metropolitan areas.

Framework

• Dynamic modeling flow chart of land use change system in the perspective of urbanization.
• The urbanization process curve (a) curve ‘S’ and (b) standard pattern based on curve ‘S’.
• The key variables and their interactions:To determine the validity of the logic of the SD model, suitability of the proposed preliminary variables and terminology.
• Key variables for the subsystem-urbanization (U)
• Policy scenarios for the urbanization process; This describes the process of urbanization with its initial slow development followed by rapid growth, smooth development, and finally saturation.

The Four Policy Scenario

Lishui, Jinyun comprises a rural County, while Liandou is an urbanized centre within the City. The two alternative urbanization policies of balanced development and unevenly coordinated development can be adopted by Lishui City in allocating urban land use and that will affect the urban development of Jinyun County. If a balanced development is adopted, more urban land use quota will be allocated to each of the eight counties including Jinyun County, thus increasing the urban land use quota per capita for Jinyun County.

Urbanization system-Urbanization Policy-Land use system

The Government assumes an important role in the process of urbanization by adopting planning policies.

The question now is how to simulate these four policy modes? In the urbanization system, a policy decision process, the urbanization policy subsystem is used. Also, several factors determine the policy modes.

 Simulation of policy scenarios
Data for the simulation process and model validation

• The data for 1996 were used as the initial value to test the model and the variation between the simulated and actual values were defined as errors.

Simulation results

• By using the validated SD model of land use change, a comprehensive simulation was conducted to demonstrate the impacts of the four scenarios in Jinyun County. The 2004 data were set as the initial value of model.

The following conclusions

1. All four policy scenarios cause reduction in agricultural land use from year 2004 to year 2020. This reduction rate is significant before 2010. However, the reduction impacts of policies 1 and 2 are less than that from policies 3 and 4 after the year 2010.
2. All the four policy scenarios result in increased urban construction land from 2004 to 2020. 

However, it is interesting to note that policies 3 and 4 cause much higher increase rates policies 1 and 2. 

• In terms of the changes in open land use, all the four policy modes result in an increase in this type of land use before 2010, but with it decreasing after 2010. 
• Nevertheless, the influences of policies 1 and 2 on the reduction of open land use are less than those of policies 3 and 4.

Summary

• The simulation results indicate that the amount of agricultural land will follow a downward trend, urban construction land will continue to increase, and open land will rise before the year 2010 but decrease afterwards.
• With market-driven policies (Scenario 3 and Scenario 4), urban construction land area tends to grow until 2010, while the agricultural land and open land areas have a decreasing trend there after. 
• Considering the impact of the planning-driven policies (Scenario 1 or Scenario 2), due to the rigid requirements of China’s arable land protection policy, a minimum amount of agricultural land needs to be maintained. The urban construction land areas grow slowly by the year 2010 and open land decreases slightly after the year 2010. 
• The land use is expected to change over the next 10 years.

Conclusion

• Urbanization is one of the major driving forces contributing to land use change. 
• Particularly in developing countries where changes in land use are expected to be driven by urbanization policy. 
• In particular, urban construction land use is anticipated to expand continually with an increasing urban population.
• The optimization of land resource allocation, particularly for urban construction, is vital to improved welfare and achieving sustainable development. 
• The method presented in this paper aims to help decision makers to predict the likely consequences of their decisions, thus enabling adjustments to be made before policy implementation. 
• SD model can be used to monitor the land use change and act as a decision-making tool for assisting the development of urbanization policy.

Source: The impact of urbanization policy on land use change: A scenario analysis