INTERIM REPORT 1 : Application Of GIS To Measure The Value Of Green Lungs In Urban Housing Market
June 2013
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TABLE OF CONTENT
LIST OF MAPS ................................................................................................... ii
1. INTRODUCTION ........................................................................................ 1
2. METHODOLOGY ....................................................................................... 3
2.1 Introduction ................................................................................................................................. 3
2.2 Study Area ..................................................................................................................................... 3
2.3 Data Requirement and Database Development ........................................................................... 7
2.4 Hedonic Price Model Development ........................................................................................... 11
2.4.1 Estimation of OLS models .................................................................................................... 11
2.4.2 Detection of spatial autocorrelation .................................................................................... 12
2.4.3 Estimation of spatial hedonic models .................................................................................. 12
2.5 Conclusion .................................................................................................................................. 16
3. GREEN SPACE AND RESIDENTIAL LAND USE ANALYSIS ......... 20
4.1 Introduction ................................................................................................................................ 20
4.2 Land Use Distribution in Kuala Lumpur ...................................................................................... 21
4.3 Land Use Distribution in Petaling District of Selangor ................................................................ 22
4.4 Green space provision in Kuala Lumpur ..................................................................................... 25
4.5 Green space provision in Petaling District of Selangor ............................................................... 29
4.6 Spatial distribution of green space and residential land use in Kuala Lumpur and Petaling
District of Selangor ............................................................................................................................ 33
4.7 Distribution of open recreational spaces by size in Kuala Lumpur and Petaling District of
Selangor ............................................................................................................................................ 37
4.8 Conclusion ................................................................................................................................... 43
4. CURRENT HOUSING MARKET ANALYSIS ...................................... 44
5.1 Introduction ................................................................................................................................ 44
5.3 House prices and green space .................................................................................................... 45
5.6 Conclusion ................................................................................................................................... 50
5. CONCLUSION AND NEXT MILESTONE ............................................ 51
6. BIBLIOGRAPHY ........................................... Error! Bookmark not defined.
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LIST OF MAPS
Map 4. 1: Open recreational area distribution by mukim in Kuala Lumpur and Petaling District of
Selangor ...................................................................................................................................... 32
Map 4. 2: Spatial pattern of green space and residential land use in Kuala Lumpur (2005) ................ 35
Map 4. 3: Spatial pattern of green space and residential land use in Petaling District of Selangor
(2005) .......................................................................................................................................... 36
Map 5. 1: Green space, residential land use, and median house price by house type and mukim in
Kuala Lumpur (Q1 2013) ........................................................................................................... 48
INTERIM REPORT 1 : Application Of GIS To Measure The Value Of Green Lungs In Urban Housing Market
June 2013
1 1. INTRODUCTION
This Interim Report 1 presents the progress and findings of this research as of June 2013 from
the second phase of the study which is the first stage of data collection. Requested
amendment on the 1st Milestone Report previously submitted in January 2013 has also been
taken into account accordingly, namely the addition of local literature on GIS studies in
Section 4: GIS-Based Hedonic Price Model in Measuring the Value of Green Lungs in Urban
Housing Market.
In this second phase of this study, the main research activities were the conduct of site visit to
selected green lungs, which has been decided to solely include recreational parks of different
sizes (hierarchy) and do not include other types of green lungs such as forest reserves, golf
field, river and road reserves, street trees, and others. The focus is on the green lungs that
provide recreational value and function to encourage active and recurrent visits by nearby
residents, rather than merely of value due to its existence or the passive aesthetic value. The
site visit was therefore conducted to assess mainly the recreational quality of parks based on
the availability and quality of supporting facilities (“facilities” criteria), as well as the other
criteria that influence nearby residents tendency to positively value the green lungs, namely
“space”, “nature”, “sensory experience”, and “culture and history”. On top of that, the parks
should be surrounded by residential areas of both landed and stratified types following the
research objectives. After eliminating the unsuitable sites based on the above five (5) quality
criteria, a total of sixteen (16) parks of different hierarchy have been selected as study areas.
The selected case study areas consist of four (4) parks in each of the local authorities area,
namely City Hall of Kuala Lumpur (DBKL), Petaling Jaya City Council (MBPJ), Subang
Jaya Municipal Council (MPSJ), and Shah Alam City Council (MBSA). With the exception
of City Hall of Kuala Lumpur, the other three local authorities are located within the Petaling
District of Selangor.
The main data to be collected in this phase of this study is the residential property transaction
(price) data. The data are to be sorted, filtered, and converted to GIS point format with
associated structural and locational attributes. In particular, the database is to be developed
for transacted houses that are located within the specified buffer from the selected 16
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recreational parks. However, our research group has faced difficulties in obtaining these
transaction data. The requested transaction data has yet to be released as of the writing of this
report, and hence has caused an unavoidable delay in this stage of this research.
An initiative has therefore been taken to perform a preliminary descriptive analysis on the
green lungs and residential land use, as well as the current housing market in terms of prices
and stocks in Kuala Lumpur Federal Territory and Petaling District of Selangor. The purpose
is to explore the possible relationship between the amount of recreational parks provision
and market value of residential property. The data obtained were analysed based on mukim
unit within the respective districts.
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2. METHODOLOGY
2.1 Introduction
This section describes the methodology designed for this study, data requirements, and steps
in developing the spatial hedonic regression model. The methodology involves the
development of residential property database in a Geographic Information System (GIS)
using the ESRITM
ArcGIS package. The database comprises of points data representing
houses location with their accompanying structural, neighbourhood (locational), and
environmental attributes. A range of GIS spatial analysis is performed to generate the
spatially varying locational variables such as accessibility to selected urban amenities and
dis-amenities including green lungs. In particular, a special interest is given to determine
whether the size of, proximity to, and functions served by selected green lungs area bring
significant impacts on the market value of residential property. To explicitly account for the
spatial relationship in the house price data, the spatial weight matrix is generated in GeoDaTM
package and formal spatial statistical tests are performed to determine the proper spatial
regression model (Anselin, 2005).
2.2 Study Area
The study area consists of sixteen recreational parks, four in each local authority (DBKL,
MBPJ, MPSJ, MBSA). The selected recreational parks further have various hierarchies
including national/regional park, city park, local park, and neighbourhood park. A pilot site
visit is carried out to assess the functional quality of the identified parks by the means of
observation of a set of green space quality criteria as shown in Figure 2.1.
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Figure 2. 1: Study area: recreational parks (example) in four Local Authorities
Figure 2. 2: Framework for quality assessment of green lungs (adapted from Greenspace Scotland,
n.d.)
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Five themes have been identified in the quality assessment framework namely ‘space’,
‘nature’, ‘sensory experience’, ‘facilities’, and ‘culture and history’. The framework has been
adapted from the Greenspace Scotland guide on assessing green space quality by site survey
(n.d.), whereby the green space auditing criteria are shown in Figure 2.3.
1. Well located close to a community
Meets requirement for disabled user needs
3. Provide surfaced, high quality paths
4. Connects with other transport modes
5. Allows movement in and between places
6. Accessible entrances in the right places
7. Offers connecting path network & signage
ACCESSIBLE & WELL CONNECTED
(SPACE)
1. Attractive, with a positive image
2. Attractive setting for urban areas
3. Quality materials, equipment & furniture
4. Attractive plants & landscape elements
5. Welcoming boundaries & entrance areas
6. Facilities in clean, safe & usable condition
7. Low levels of litter & adequate bins
8. Well maintained
ATTRACTIVE & APPEALING PLACES
(SENSORY EXPERIENCE)
1. Provides places for a range of outdoor
activities
2. Diverse play, port and recreational
opportunities
3. Providing places for social interaction
4. Appropriate, high quality facilities meeting
needs
5. Appropriate facilities for location & size
6. Carefully sited facilities for a range of ages
7. Adaptable to changing needs and uses
ACTIVE SUPPORTING HEALTH & WELL BEING
(FACILITIES)
1. Contribute positively to biodiversity
2. Large enough to sustain wildlife
populations
3. Offers a diversity of habitats
4. Part of the wider landscape structure &
setting
5. Connects with wider green networks
6. Balance between habitat protection &
access
7. Resource efficient
BIODIVERSE SUPPORTING ECOLOGICAL
NETWORKS (NATURE)
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Figure 2. 3: Green space quality criteria or indicators (Greenspace Scotland, n.d.)
Once the parks have been identified, a buffer area is constructed from the parks area
boundary with buffer distance calculated based on the population catchment for the specific
park’s hierarchy and population density in the mukim where the park is located. For example,
Figure 2.4 illustrates the case of Taman Tasik Kota Kemuning (Local Park) in Petaling Jaya.
The JPBD guideline on open space and recreational area planning identifies population
catchment for this local park as 12,000 to 50,000. Given the population density of mukim of
Damansara where Taman Jaya is located of 3,790 people per km2, assuming a uniform
population distribution, the park’s maximum service area is calculated as 50,000 divided by
3,790 equals to 13.19 km2. Then, assuming a circle service area, the radius of the circle is
calculated as root square of (13.19 km2 x 7/22) giving 2.05 km buffer radius. For each park,
residential property that fall within the constructed buffer of the respective park will be
included in the hedonic regression modelling.
COMMUNITY SUPPORTED (CULTURE & HISTORY)
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Figure 2. 4: Illustration of buffer construction around park boundary and the identification of landed
and stratified residential property within the buffer (park service) area.
2.3 Data Requirement and Database Development
To develop the spatial regression model four main categories of data are required. They are
house transaction data (including house price, house location, and time of transaction), house
structural attributes data, urban amenities and dis-amenities data that determine locational
attributes such as accessibility to key facilities and environmental quality of the residential
neighbourhood, as well as neighbourhood socio-economic data. House price is modelled as a
function of these structural, neighbourhood (locational), environmental, time, and submarket
variables (Freeman, 1979; Nicholls & Crompton, 2005; Ismail, 2005) as shown in Figure 2.5.
r = 2.05 km
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Figure 2. 5: Hedonic Price Modelling
Source: adapted from Freeman, 1979; Nicholls & Crompton, 2005; Ismail, 2005
Figure 2.6 compiled the housing attributes identified from previous literature on hedonic
studies. The incorporation of those attributes will depend on the information included in the
transaction data, especially with regards to the structural characteristics of the property such
as floor area, lot area, number of bedroom, and so on. As for the neighbourhood and
environmental attributes, facilities mapped in standard street directory maps such as hospital,
school, police station, mosque, and so on will be digitized. Simple straight-line distance from
house points to these facilities can then be calculated and stored as the locational variables
affecting house value. Access to green lungs, namely recreational parks is treated as part of
the environmental attribute of housing quality.
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Age, sqft, basement, elevation, flood,
floor level, pool, no of rooms,
bathrooms, condition (rated), type of
house, type of building, type of floor;
toilet, garbage grinder, hot water, cable
television, elevator, garage, kitchen area,
living room area, terrace, air cond.
Distance to busy road, CBD, shopping centre,
college/university, average school grade, no of
schools, tax rate, hospital, marketplace, gas
station, police, banks, high pollution industry,
public transport, rail road, population density,
age, race; median household income; children in
family, education in family, house vacancy rate,
unemployment rate, moving persons. Viewshed area, view richness, view of
green, streets, buildings, impervious
surface, tree cover (100, 250, 500, 750,
1000m), noise level, air pollution index,
distance and area of water body, golf
course, waste dump, mean greenness.
Month of sale, season.
year, quarterly.
School district, zip code,
census tract.
ENVIRONMENTAL STRUCTURAL
TIME SUBMARKET
NEIGHBOURHOOD
Figure 2. 6: Compilation of housing structural, neighborhood, environmental, time, and submarket attributes from previous studies
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In Malaysia, the residential property transaction data is provided by the Property Valuation
and Service Department (JPPH). As the address information may be incomplete to exactly
pinpoint on the map, the cadastre lot number information is used instead to precisely locate
the houses. Cadastre maps covering the area of interest are to be obtained from the
Department of Survey and Mapping (JUPEM) in MapInfo format. As the facilities digitized
from street directory maps would be in the universal World Geographic Coordinate System
WGS 1984 (based on latitude and longitude), it is necessary to convert the cadastre map
projection to WGS 1984 as well to allow maps overlay.
Figure 2.7 illustrates the database design will be developed in this study. House location is
digitized as point features based on address or land lot number. Transaction information
namely sale price and date are entered in the attribute data. In general, the other attributes can
be divided into two categories: structural and locational attributes. The first data category, the
structural attributes of the residential property include the lot area, structure area, number of
bedroom and bathroom, floor material, construction age, and availability of ancillary facilities
such as swimming pool and garage (Ball, 1973; Fletcher et al., 2000; Li & Brown, 1980;
Carroll et al., 1996; Rodriguez & Sirmans, 1994; Clark & Herrin, 2000; Kain & Quigley,
1970; Forrest et al., 1996; Garrod & Willis, 1992; Chau et al., 2001). However, the inclusion
of these variables relies on secondary data source such as the transaction data from JPPH.
Figure 2. 7: Schematic design of residential property geodatabase for this study
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The second type of housing attributes, the locational attributes consist of accessibility
measure (typically distance) to nearest urban facilities or services such school, hospital,
employment centre (CBD), shopping centre/market, main road, public transport, place or
worship, and especially recreational parks, the interest of this study (McMillan et al., 1992;
So et al., 1996; Clauretie & Neill, 2000; Huh & Kwak, 1997; Carroll et al., 1996; Des Rosiers
et al., 1996; Mok et al., 1995; Tse & Love, 2000; Tyrvainen, 1997). Other than distance to
recreational parks, green lung variables also include the size (area)/quantity and
function(s)/quality of the recreational sites that have been identified from pilot survey.
Additional attributes can be incorporated into the analysis namely the socioeconomic
neighbourhood attributes (Goodman, 1989) and environmental attributes. Neighbourhood
attributes are indicated by the demography of the community sharing the neighbourhood that
determine the social environment in the neighbourhood. The demography can include
income, average school grade, racial composition, social class, and so on (Garrod & Willis,
1992; Richardson et al., 1974; Ketkar, 1992). Environmental attributes use indicators from
secondary environmental data such as air quality, noise level, and so on (Williams, 1991;
Espey & Lopez, 2000). Environmental attributes can also include view from property (Brown
& Pollakowski, 1977; Cassel & Mendelsohn, 1985; Darling, 1973; Gillard, 1981; Mok et al.,
1995; Plattner & Campbell, 1978; Rodriguez & Sirmans, 1994). However, as these
neighbourhood and environmental data are typically not available at small geographical scale,
their inclusion is optional. After all the required independent variables have been generated
and populated into the house database, the hedonic price model can be developed.
2.4 Hedonic Price Model Development
The modelling stage involves three steps. The first step is the estimation of OLS (Ordinary-
Least Square) models. The second step is the exploration and detection of spatial
autocorrelation in the house price data. The third step is the estimation of spatial hedonic
models.
2.4.1 Estimation of OLS models
The OLS models will be developed using the classic regression functionality built in
GeoDaTM
software (Anselin, 2005). To test different functional forms (linear, semi-log, log-
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log), necessary data transformation processes are performed in IBM SPSS package. The
regression models outputs are compared in terms of the R2, adjusted R
2, the sum of squared
residuals, the residual variance, the standard error estimate, and F statistic. The regression
output also reports the measures of multicollinearity (condition number), non-normality
(Jarque-Bera), and heteroskedasticity (Breusch-Pagan, Koenker-Bassett, and White)
(Anselin, 2005). The predicted value and residual maps are then created to visualize
underestimation and overestimation (Ismail, 2005).
2.4.2 Detection of spatial autocorrelation
Spatial autocorrelation can be detected visually by mapping the OLS residuals (Hamid, 2002;
Anselin, 1999), and quantitatively using formal spatial statistical tests namely Moran’s I
(Moran, 1950) and Lagrange Multiplier or LM test (Burridge, 1980). The residuals, which
can be positive or negative, are calculated by substracting the value estimated from OLS
models, from the actual value. Positive autocorrelation is present when residuals of the same
sign cluster together. If the examination reveals a pattern of spatial autocorrelation, formal
testing is then run to quantify whether the spatial autocorrelation significantly exists in the
data. Significant Moran’s I z-values (p-value) signal significant spatial autocorrelation
(Anselin, 1995). The Lagrange Multiplier (LM) test statistics are further looked at to
determine the appropriate spatial regression models (Anselin, 2005).
2.4.3 Estimation of spatial hedonic models
Spatial models are generally specified as linear regression models with spatial
interdependence taking the form of a linear additive relationship of observations on
neighbours (Wilhelmsson, 2002). The LM tests are reported for the two alternatives of spatial
regression model, namely the spatial lag model and spatial error model (Anselin, 2005;
Sander and Haight, 2012). Figure 2.8 summarizes the diagnostic process towards a spatial
regression specification. First, the standard LM-Error and LM-Lag test statistics are
considered. If neither rejects the null hypothesis (neither is significant), the OLS model is to
be chosen. If one of the standard LM test statistics rejects the null hypothesis while the other
does not, estimate the alternative spatial regression model that matches the test statistic that
rejects the null. When both standard LM test statistics reject the null hypothesis, consider the
Robust forms of the test statistics (Robust LM-Error and Robust LM-Lag). The choice is then
the one with significant Robust test statistic (Anselin, 2005).
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Both spatial lag and spatial error model require spatial weight matrix as input to model the
spatial autocorrelation explicitly. In GeoDaTM
, there are two methods to generate the spatial
multiplier, namely the contiguity-based spatial weights and distance-based spatial weights
(Anselin, 2005). The contiguity-based method is more suitable for polygon data, and because
houses are modelled as point features in this study, the preferred method is the distance-based
spatial multiplier. The fixed distance band method imposes a “sphere of influence” or moving
window conceptual model of spatial relationships onto the data. Each feature is analysed
within the context of those neighbouring features within some specified critical distance.
GeoDaTM
will calculate the threshold distance which is the minimum distance required to
ensure that each location has at least one neighbour. However, this study will use the distance
band that reflects maximum spatial autocorrelation, the distance where the underlying spatial
processes are most pronounced. The distance is identified by running the spatial
Figure 2. 8: Spatial regression specification decision process (Anselin, 2005)
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autocorrelation tool at multiple distances and subsequently selecting the experimented
distance where the resulting Z score seems to peak (ESRITM
ArcGIS resources).
The results from the spatial hedonic models and OLS models are then compared in terms of
the adjusted R2 and variance whereby higher adjusted R
2 value and lower variance indicate
better estimates, hence a better model to predict house price (Anselin, 2005; Ismail, 2005).
The value of access (distance) to, size of, and functions of green lungs are then interpreted
from the resulting regression coefficients, in terms of their sign, magnitude, and significance
value. Positive coefficient indicates that green lungs contribute positively or are an added
value to the house value, whereas negative coefficient indicates otherwise, green lungs as a
dis-amenity. The magnitude of the green lungs variables coefficient indicates how much is
the green premium or implicit price (Rosen, 1974), that is by how many units of price the
house price increases/decreases given a one unit increase/decrease in green lungs variables.
In monetary terms, the coefficients tell by how much (RM) house value increases/decreases
for every area unit (e.g. m2) increase in green lungs size, or every distance unit (e.g. m)
decrease in distance between house location and green lungs location.
All in all, Figure 2.9 summarizes the steps taken throughout the methodology for this study,
from data collection and preparation to the spatial hedonic regression modelling of house
price as the function of housing attributes. The data preparation and integration will be
carried out in ESRI ArcGISTM
. ArcGISTM
spatial analyst is used to calculate spatial variables
such as distance between locations. The prepared datasets are then imported to GeoDaTM
in
which the Ordinary Least Square linear regression analysis is performed. Together, ESRI
ArcGISTM
and GeoDaTM
Exploratory Spatial Data Analysis tools are used to investigate the
spatial autocorrelation in house price data and OLS model residuals (Anselin et al., 2002).
Subsequently, distance-based spatial weight matrix is generated in GeoDaTM
using the
distance band that maximizes spatial autocorrelation. The appropriate spatial regression
model—either Spatial Lag or Autoregressive Model (SAR), Spatial Error Model (SEM), or
General Spatial Model (SAC)—is determined using the decision algorithm is Figure 2.8
before (Anselin, 2003; 2004; 2005). Before specifying the selected spatial regression model,
datasets are imported in SPSSTM
to eliminate correlated independent variables (to deal with
multicollinearity issue) and execute necessary data transformation to specify non-linear
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hedonic models, such as log-log model, semi-log model, and Box-Cox transformation (Milon
et al., 1984). The results of different models tested are then compared and the one with best
estimates will be used as the basis to interpret green lungs hedonic price or implicit value that
they contribute towards the nearby residential property value.
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2.5 Conclusion
This section has elaborated the methodology for this study including the study area selection
and residential property sampling, the data requirement and the GIS database to be
developed, and the processes of estimating the hedonic and spatial hedonic regression
models. The presented methodology can be modified accordingly depending on availability
of data on housing structural, neighbourhood, and environmental attributes.
Figure 2. 9: Overall Methodology Design and Work Flow
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.
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Table 3.1: Location of 16 Case Study Recreation Parks and Buffer Distance from Park Boundary
No LA Park Name WGS1984 Coordinate Service Area (km
2) Buffer Distance (km)
Lat (o) Long (
o) Min Max Min Max
1
DBKL
Taman Tasik Titiwangsa 3.178615 101.706618 9.32 - 1.72 -
2 Taman Tasik Bandar Sri Permaisuri 3.099774 101.720090 8.67 - 1.66 -
3 Taman Metropolitan Kepong 3.223881 101.645610 8.19 - 1.61 -
4 Taman Desa Parkcity 3.186603 101.629606 1.97 8.19 0.40 0.79
5
MBPJ
Taman Jaya 3.105277 101.648602 12.74 - 2.01 -
6 Taman Aman 3.102847 101.625515 3.06 12.74 0.49 0.99
7 Taman Bandaran Kelana Jaya 3.099028 101.596132 13.19 - 2.05 -
8 Taman Ara Damansara 3.120007 101.585121 3.17 13.19 0.50 1.00
9
MPSJ
Taman Tasik Subang Ria Park 3.080653 101.599615 3.17 13.19 1.00 2.05
10 Taman Kejiranan USJ 4 3.048452 101.575088 0.79 3.17 0.50 1.00
11 Taman Wawasan 3.033081 101.625421 2.56 10.67 0.45 0.90
12 Taman Kejiranan SS19/1 3.074855 101.577993 0.79 3.17 0.50 1.00
13
MBSA
Taman Tasik Shah Alam 3.071892 101.514320 13.19 - 2.05 -
14 Taman Botani Negara Shah Alam 3.102489 101.514991 Whole Region 3.51 -
15 Taman Tasik Kota Kemuning 3.001350 101.536986 3.17 13.19 2.05 -
16 Taman Kejiranan Bukit Jelutong U8 3.102534 101.532835 0.79 3.17 0.50 1.00
Source: Site Visit, February 2013
1 TBNSA is a regional park to serve the whole region. The minimum population catchment of 50,000 people (City Park) is used.
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Figure 3.1: Map of 16 Selected Recreational Parks and Buffer Zones within which the residential property values are to be
investigated
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20 3. GREEN SPACE AND RESIDENTIAL LAND USE ANALYSIS
4.1 Introduction
This section describes the land use zoning in the Federal Territory of Kuala Lumpur and
Petaling District of Selangor where the four local authorities under study (Kuala Lumpur City
Hall, Petaling Jaya City Council, Shah Alam City Council, and Subang Jaya Municipal
Council) are located. The land use data have been provided by Kuala Lumpur City Hall and
Petaling District local authority. Following the objective of this research, emphasize was
given to residential land use and ‘green space’ land use such as open space, recreational area,
forest, and agriculture. The two land use maps do not use the same land use categories (Table
4.1). Following the description of land use distribution, calculations were made at mukim
geographical area unit for green space coverage in terms of acreage per person and as
percentage from total mukim area, using population data from the latest 2010 Population and
Housing Census. The results serve to depict the general condition of green space provision to
be assessed against the National Physical Plan (2005) target of 20 m2 per dweller. In addition,
the ratio of green space area to residential area could give insight into the interplay between
housing development and green space preservation. The analysis continued in the fifth
section of this report—the housing market analysis—where the question of whether
residential property in a mukim which has a larger green cover enjoys higher market value.
Table 4. 1: Land use zoning categories in Kuala Lumpur and Petaling District of Selangor
No Kuala Lumpur Land Use Types No Petaling Land Use Types
1 Industry 1 Industry
2 Institution 2 Institution
3 Recreation area /Open area 3 Open land and recreation
4 Open area
5 Religious use
6 Residential 4 Residential
7 Commercial 5 Business and services
8 Cemetery
9 Train (LRT)
6 Transportation 10 Train (KTM)
11 Electrical Line Reserve
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12 Terminal
13 Public Facilities 7 Infrastruktur dan Utiliti
14 Community/Social Facilities
15 Agriculture, Fishery, Forestry 8 Forest
9 Agriculture
16 School
17 Squatter
18 River 10 Water body
Source: Kuala Lumpur City Hall (2005); Petaling local authority (2005)
Table 4.1 shows that in the Kuala Lumpur land use data, two land use types can be
categorized as green space, namely the ‘kawasan rekreasi/kawasan lapang’ (‘recreational
area/open area’) and ‘pertanian, perikanan, perhutanan’ (‘agriculture, fishery, forestry’).
Whereas in the Petaling land use data, green space includes three categories, namely ‘tanah
lapang dan rekreasi’ (‘open space and recreation’), ‘hutan’ (‘forest’), and ‘pertanian’
(‘agriculture’). Both land use data have ‘kediaman’ (‘residential’) category. Later, it is shown
that the Petaling land use categories are further broken down into sub-classes.
4.2 Land Use Distribution in Kuala Lumpur
Table 4.2 shows the distribution of land use in Kuala Lumpur. Residential area covers around
28 per cent of the city land while recreation/open space covers around 9 per cent of the land.
Interestingly, a significant amount of land (24.6 per cent) was zoned as ‘open space’ which
does not function as recreational sites. A very small proportion of the city area (0.13 per cent)
was zoned as ‘agriculture, fishery, and forestry’.
Table 4. 2: Distribution of Land Use in Kuala Lumpur, 2005
Kuala Lumpur Land Use Distribution, 2005
No Land Use Type Area (m2) Area (%)
1 Industry 5,505,991.47 2.83
2 Institution 16,824,964.38 8.64
3
Recreation/Open Area
(Kawasan Rekreasi/Kawasan
Lapang)
17,443,683.27 8.96
4 Open Area (Kawasan Lapang) 47,910,934.56 24.60
5 Religious Use 1,150,912.78 0.59
6 Residential 54,488,632.08 27.98
7 Commercial 10,715,355.64 5.50
8 Cemetery 2,654,986.59 1.36
9 Train (LRT) 39,952.49 0.02
10 Train (Keretapi Tanah Melayu) 1,211,016.51 0.62
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11 Electrical Line Reserve 3,034,203.53 1.56
12 Terminal 1,641,733.94 0.84
13 Public Facilities (Kemudahan
Awam) 3,833,975.92 1.97
14 Social Facilities (Kemudahan
Masyarakat) 452,390.09 0.23
15 Agriculture, Fishery, Forestry 246,948.54 0.13
16 School 10,262,790.81 5.27
17 Squatter 9,173,984.04 4.71
18 River 8,132,004.22 4.18
19 Unknown 2,347.54 0.001
Total Area 194,726,808.4 100.00
Source: Kuala Lumpur City Hall (2005); Petaling District local authority (2005)
Figure 4. 1: Land use distribution in Kuala Lumpur as percentage from total area, 2005
Source: Kuala Lumpur City Hall, 2005
4.3 Land Use Distribution in Petaling District of Selangor
The land use data provided by Petaling District local authority of Selangor contains a more
detailed land use classification. Although having only ten broad classes (in the attribute field
‘semasa’ or ‘current’), these classes are further broken down in the attribute fields ‘aktiviti’
2.83
8.64
8.96
24.6
0.59
27.98
5.5
1.36
0.02
0.62
1.56
0.84
1.97
0.23 0.13
5.27
4.71 4.18
0.001
Land use distribution (%) in Kuala Lumpur (2005)
IndustryInstitutionRecreation/Open AreaOpen AreaReligious UseResidentialCommercialCemeteryTrain (LRT)Train (KTM)Electrical Line ReserveTerminalPublic FacilitiesSocial FacilitiesAgriculture, Fishery, ForestrySchoolSquatterRiverUnknown
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(‘activity’) and ‘aktiviti2/nama’ (‘activity2/name’). Table 4.3 and Figure 4.2 summarises the
land uses in Petaling District. Table 4.4 breaks down the general land use categories into their
sub-classes.
Table 4. 3: : Distribution of Land Use in Petaling District of Selangor by Types (2005)
Petaling District (Selangor) land use, field ‘Semasa’
No Land Use Type Area (m2) Area (%)
1 Water body 8,142,614.95 1.69
2 Forest 44,336,033.91 9.18
3 Industry 30,994,434.95 6.42
4 Infrastructure and Utility 9,669,493.34 2.00
5 Institution 48,120,452.24 9.96
6 Residential 68,040,997.06 14.09
7 Transportation 94,573,558.04 19.58
8 Business and Services 11,451,615.49 2.37
9 Agriculture 31,148,795.49 6.45
10 Open space and recreation 136,562,767.76 28.27
Total 483,040,763.23 100.00
Source: Petaling District local authority, 2005
Figure 4. 2: Land use distribution in Petaling District of Selangor (2005)
Source: Petaling District local authority, 2005
1.69
9.18
6.42
2.00
9.96
14.09
19.58
2.37
6.45
28.27
Land use distribution (%) in Petaling District of Selangor (2005)
Badan Air
Hutan
Industri
Infrastruktur dan Utiliti
Institusi
Kediaman
Pengangkutan
Perniagaan dan Perkhidmatan
Pertanian
Tanah Lapang dan Rekreasi
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Table 4. 4: Distribution of Land Use in Petaling District of Selangor by Types and Activities (2005)
GTPetaling_region_Kertau; field ‘Aktiviti’, ‘Aktiviti2’, and ‘Nama’
No Land Use Type Activity Activity2/Name Area (m2) Area (%)
1
Infrastructure and
utility
Water Supply Water Supply Pump
House 859,595.38 0.18
2 Electric Supply Electrical Tower 2,301,493.19 0.48
3 Gas Supply Gas Pipe Line PGU
1 909,822.72 0.19
4 Toxid Waste Disposal Treatment Pond-
Clinical 13,657.26 0.00
5 Soild Waste Disposal Rubbish Bin – Solid
Waster 543,800.89 0.11
6 Sewerage Pump Station
Network 1,715,896.6 0.36
7 Irrigation and drainage Sanitation Pond 3,288,926.52 0.68
8 Telecommunication Ibu Sawat Building 36,300.78 0.01
9
Industry
Heavy Single Industry 26,446,537.71 5.48
10 Medium Single Industry 2,783,688.05 0.58
11 Light Terrace Industry 1,632,189.79 0.34
12 Service Terrace Industry 48,551.17 0.01
13 Terrace Industry 83,468.23 0.02
14 Water Body
Artificial Ex-mining 2,674,800.46 0.55
15 Natural River 5,467,814.49 1.13
16 Forest Land Forest State Forest Reserve 44,336,033.91 9.18
17
Institution
Religious Church 6,223,810.53 1.29
18 Government Use Museum 1,149,356.7 0.24
19 Security Fire Station 3,328,189.21 0.69
20 Health Hospital 234,591.39 0.05
21 Other Social Facilities Hall (Balai JKK) 326,672.41 0.07
22 Education Higher Education
Institution 34,676,535.75 7.18
23 Cemetery 2,018,714.18 0.42
24 Welfare House House for the
Disabled 162,582.07 0.03
25
Transportation
Rail Others 122,374.39 0.03
26 Transport Facilities Lorry Depot/Heavy
Vehicle 3,825,730.51 0.79
27 Road Others (Street
Divider) 90,625,453.14 18.76
28 Open Space and
Recreation
Sport and Recreation
Facilities 7,625,197.57 1.58
29 Bare Land 104,299,926.82 21.59
30 Open Land Regional/State Parks 24,637,643.37 5.10
31
Agriculture
Denied Land 702,849.87 0.15
32 Palm Oil Small Farm 29,193,614.25 6.04
33 Other Agricultural
Activities Banana 1,229,796.6 0.25
34 Livestock Pig Farm 22,534.77 0.00
35 Business and
Services Business and Services
Various (Bangunan
Darul Ehsan) 11,451,615.49 2.37
36
Residential
Village Housing 20,190,982.96 4.18
37 Planned Housing Terrace Houses 47,824,487.37 9.90
25,526.73 0.01
Total 483,040,763.23 100.00
Source: Petaling District local authority, 2005
An initial look reveals a surprising 28 per cent, more than a quarter proportion of the land
area is devoted for ‘tanah lapang dan rekreasi’ (‘open space and recreation’). However, this
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interpretation is misleading because unlike in land use in Kuala Lumpur, the ‘open space and
recreation’ class also includes open space that bares undeveloped land with no recreational or
aesthetical function. In fact, as shown in Table 4.4, 21.59 per cent of the Petaling area are
merely ‘tanah kosong’ or ‘empty land’, while a mere 5.10 per cent is actually ‘taman
wilayah/negeri’ (‘regional/state parks’) and 1.58 per cent serves as ‘kemudahan sukan dan
rekreasi’ (‘sports and recreational facilities’). Other green space land uses are ‘hutan’
(‘forest’) and ‘pertanian’ (‘agriculture’) which take 9 per cent and 6.45 per cent of the land,
respectively.
Also a highly urbanised and densely populated area in the Klang Valley where the Petaling
Jaya, Shah Alam, and Subang Jaya are situated, residential area accounts for 14 per cent of
the district area. Interestingly, 4.18 per cent of the district area that is zoned for housing are
designated for ‘perumahan kampung’ or ‘traditional/rural houses’, while 9.90 per cent (or
roughly 70 per cent of the residential area) are ‘rumah teres’ (‘terrace houses’). This reflects
the availability of land resources in Petaling for landed houses development, a situation in
contrast to the saturated Kuala Lumpur where development is going vertical characterised by
apartment, flat, and condominium types of shelter. Table 4.4 also shows a greater proportion
of conservation forest (‘hutan simpan negeri’) in Petaling at around 9 per cent.
4.4 Green space provision in Kuala Lumpur
Table 4.5 highlights the residential and green open space land use in Kuala Lumpur, analysed
at mukim area unit to indicate the geographical distribution. The population data obtained
from the latest 2010 Population and Housing Census (Malaysia Department of Statistics,
2011) are integrated to assess the adequacy of the green space provision for the urban
residents, also analysed at mukim level. Unfortunately, the land use data is not provided for
the mukim of Bandar Petaling Jaya area.
The Federal Territory of Kuala Lumpur under the administration of Kuala Lumpur City Hall
has its area sub-divided into eight mukim, namely Ampang, Bandar Kuala Lumpur, Batu,
Cheras, Kuala Lumpur, Petaling, Setapak, and Ulu Kelang. Based on GIS area calculation on
the map of mukim administrative boundary in Kuala Lumpur, mukim of Kuala Lumpur has
the largest administrative area of 60 km2, followed by mukim of Batu (52.6 km
2), Petaling
(44.9 km2), Bandar Kuala Lumpur (47.3 km
2), and Setapak (28.99 km
2). Mukim of Ampang,
Cheras, and Ulu Kelang have relatively smaller areas.
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The focus of this research is to assess the value of specific green space type namely
recreational parks. In terms of percentage from total mukim area, mukim of Kuala Lumpur
has the largest open recreational space (‘kawasan rekreasi/kawasan lapang’) at 11.21 per cent.
In general, the distribution of open recreational space by mukim is quite even, although
mukim of Kuala Lumpur, mukim of Bandar Kuala Lumpur, mukim of Petaling, and mukim
of Ulu Kelang have more open recreational area (more than 6 per cent of respective mukim
area), while mukim of Ampang, Batu, Cheras, and Setapak maintain open recreational space
less than 5 per cent of mukim area.
Looking at distribution of residential area, mukim of Setapak and Ampang have more than 30
per cent of their area zoned for residential use. Around 20-26 per cent residential area were
gazetted in mukim of Bandar Kuala Lumpur, mukim of Kuala Lumpur, and Ulu Kelang. The
other mukim have more than 15 per cent residential area. In terms of population density, four
mukim located in the eastern periphery of Kuala Lumpur (Ampang, Cheras, Setapak, and Ulu
Kelang) recorded more than 10,000 people per km2 in 2010, whereas the other mukim were
inhabited by around 5,000 to 6,500 dwellers. Expectedly, the four more densely populated
mukim also recorded higher living quarter density at more than 2,500 living quarters per km2,
and similarly greater number of households every km2.
Population density calculated as number of people per km2 residential area (instead of mukim
area) gives a more meaningful measurement of residential density. Density calculated this
way is even higher because it only considers residential area to accommodate the population.
Mukim of Cheras covers the smallest administrative area and consequently smallest
residential area. As a result, residential density (people per km2 residential area) is far higher
than other mukim, at almost 90,000 residents per km2 residential area. Similarly, residential
area in mukim of Ulu Kelang contains more people (above 40,000) for every km2 due to this
reason. Mukim of Ampang, Batu, Petaling, and Setapak have more than 30,000 people,
whereas mukim of Bandar Kuala Lumpur and mukim of Kuala Lumpur have less than 25,000
people, in one km2 residential area on average. The related indicators of household density in
residential area and living quarter density in residential area more or less display similar
population distribution as more people indirectly translates to more households and more
living quarters.
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With regards to open green space, of which focus is given to green space that functions as
recreational (‘kawasan rekreasi/kawasan lapang’), the three mukim with larger administrative
area (mukim of Bandar Kuala Lumpur, mukim of Kuala Lumpur, and mukim of Petaling)
have more abundant open recreational area of more than 3 km2 (or equivalently more than 7
per cent of mukim area) in their respective mukim. Mukim of Batu is an exceptional case, the
second largest mukim but having only almost 4 per cent of open recreational area. Mukim of
Setapak and Cheras have the less open recreational area of not more than 3.30 per cent.
Evaluated as provision for the population, the simple analysis in Table 4.5 reveals that all
mukim in Kuala Lumpur failed to provide the targeted 20 m2 per inhabitant of open
recreational area, although mukim of Kuala Lumpur almost meets the standard with 19.43 m2
per person. Mukim of Cheras and Setapak are especially experiencing serious lacking of open
recreational space with less than 3 m2 provided for every person, on average. A person in
Mukim of Ampang, Batu, and Ulu Kelang enjoys less than 7 m2 open recreational area.
Mukim of Kuala Lumpur provides a decent 16.6 m2 of such space for every person, while
half of the targeted provision is satisfied by mukim of Petaling with 10.8 m2 per person.
A useful indicator of provision of open recreational space for residential area is also given in
Table 4.5 as a simple ratio between open recreational area and residential area. Mukim of
Bandar Kuala Lumpur, Kuala Lumpur, and Petaling provide more than 0.4 m2 (or in other
words, 40 per cent of residential area) open recreational space in every 1 m2 residential area,
although further information of the recreational area distribution relative to residential area is
needed to give a more accurate picture. Mukim of Batu, Cheras, and Ulu Kelang on the other
hand provide half of that (0.2 m2 open recreational space) for every 1 m
2 residential area.
Mukim of Setapak not only has the smallest open recreational space per person, but also the
smallest open recreational space of a mere 0.07 m2 per m
2 residential area.
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Table 4. 5: Green space provision by mukim in Kuala Lumpur. Source: Kuala Lumpur City Hall (2005); Department of Statistics Malaysia (2011)
Land Use (m2)
Mukim in WPKL
Ampang Bandar Kuala
Lumpur Batu Cheras
Kuala
Lumpur Petaling Setapak
Ulu
Kelang
Recreation Area/Open Space 189,598.5 4,207,812 2,037,445 30,974.16 6,726,595 3,163,925 676,226.5 156,796.3
Open Area 232,048 3,562,305 15,441,819 331,903.4 9,534,633 11,394,851 5,083,369 1,131,571
Agriculture, Fishery, Forestry 4,438.74 44,726.59 19,548.84 0 169,614.2 5,818.95 0 0
Residential 125,3945 10,218,239 9,989,513 135,612.9 15,067,279 7,324,248 9,105,323 627,912.9
River and water body 179,834.1 1,782,258 2,515,033 54,272.5 1,123,369 1,418,847 915,255.1 7,771.21
Selected Indicators
Mukim area (km2) 4.15 47.34 52.6 0.94 60.02 44.91 28.99 2.46
Population number (2010) 43,522 253,817 321,164 12,194 346,211 292,095 293,280 26,467
Households number (2010) 11,356 65,858 86,371 3,085 91,623 78,488 75,346 7,060
Living quarters (2010) 11,832 73,551 98,543 3,401 98,729 93,009 81,583 7,677
Population density (2010) person/km2
10,487 5,362 6,106 12,972 5,768 6,504 10,117 10,759
Population density (2010) person/km2
residential area 34,708 24,840 32,150 89,918 22,978 39,881 32,210 42,151
Residential as % from mukim area 30.22 21.58 18.99 14.43 25.10 16.31 31.41 25.52
Household density (2010) per km2
2,736 1,391 1,642 3,282 1,527 1,748 2,599 2,870
Household density (2010) per km2
residential area 9,056 6,445 8,646 22,749 6,081 10,716 8,275 11,244
Living quarters density (2010) per km2
2,851 1,554 1,873 3,618 1,645 2,071 2,814 3,121
Living quarters density (2010) per km2
residential area 9,436 7,198 9,865 25,079 6,553 12,699 8,960 12,226
Recreation/Open Space (m2) per
inhabitant 4.36 16.58 6.34 2.54 19.43 10.83 2.31 5.92
Recreation/Open Space as % from mukim
area 4.57 8.89 3.87 3.30 11.21 7.05 2.33 6.37
Recreation/Open Space : Residential Area 0.15 0.41 0.20 0.23 0.45 0.43 0.07 0.25
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4.5 Green space provision in Petaling District of Selangor
The administration of the Petaling District of Selangor is divided into five mukim, namely
mukim of Bukit Raja, Damansara, Petaling, Sungai Buloh, and Bandar Petaling Jaya. Table
4.6 shows the green space indicators by mukim in Petaling District of Selangor. Mukim of
Bandar Petaling Jaya has the smallest area of 15 km2 and the largest mukim area is for
mukim of Damansara (136 km2). In terms of population density, in general Petaling District
of Selangor is less densely populated compared to the Federal Territory of Kuala Lumpur,
with less than 5,000 people per km2 as of 2010. The population is densest in mukim of
Petaling with 4,686 people per km2, and least dense in mukim of Bukit Raja with 1,285
people per km2. The population density in the other three mukim (Damansara, Sungai Buloh,
and Bandar Petaling Jaya) is roughly the same around 3,600 to 4,000 people per km2.
One possible reason for lowest population density in mukim of Bukit Raja is that it also has
the smallest residential area (4.8 per cent), less than a third of residential area in the other
mukim in Petaling. Mukim of Damansara, Petaling, and Sungai Buloh each has more than 15
per cent residential area. Mukim of Bukit Raja has a density of by around 300 households and
living quarters per km2, while more than 1,000 living quarters have been registered for the
other four mukim in the 2010 census.
When it comes to residential density (number of people divided by residential land use area),
all the four mukim actually experience a very high residential density with 22,000 to 27,000
residents of more than 6,000 households living in around 7,000 living quarters every km2
residential area. This shows that residential density calculated this way better reflects the
extent population density scenario as mukim in Petaling have lower proportion of residential
land use and still more space for development given their larger administrative area in
comparison to Kuala Lumpur.
In terms of green space, Petaling District land use have several categories related to
recreational use namely ‘kemudahan sukan dan rekreasi’ (‘sports and recreational facilities’),
‘tanah lapang (taman wilayah/negeri’) or ‘open space (‘regional/state parks’), and ‘hutan
darat (hutan simpan negeri)’ or ‘land forest (‘state forest reserves’). Unlike in Kuala Lumpur,
mukim of Petaling still maintains a significant forest reserve, especially the Shah Alam
National Botanical Garden (TBNSA) in the least populated mukim of Bukit Raja where
forest reserves area per person has reached 240 m2 per person—covering 30 per cent of
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mukim of Batu area. Mukim of Sungai Buloh has 15 per cent (42 m2 per person) of forest
reserves, while mukim of Damansara and Petaling has around 20 m2 forest per person.
However, the interest of this research is more on the regional/state parks which serve more
direct recreational function to nearby residents, with higher access encouraging more frequent
uses.
Mukim of Damansara provides the largest area for regional/state parks (10 per cent) and
hence the highest provision of these recreational parks (26.39 m2 per person) in Petaling
District of Selangor. In mukim of Bukit Raja, although having the smallest land proportion
devoted for recreational (regional/state) parks, its low population density allows for the
provision of 16.77 m2 recreational parks, the second largest in the district. Mukim of Petaling
and Sungai Buloh both provide 9.40 m2 and 8.69 m
2 parks per person. These figures show
that except for mukim of Damansara, the other mukim have also not met the 20 m2 NPP
target. However, this is disregarding the forest reserves which can partially function as public
recreational area like in the case of TBNSA where a portion of the forest is open for cycling
and nature sightseeing.
Finally, the ratio of recreational (regional/state) parks area to residential area varies
considerably by mukim. From the mukim with wider parks area per unit of residential area
are mukim of Damansara with 64 m2
parks per 100 m2 residential area, followed by mukim of
Bukit Raja (45 m2), Petaling (24 m
2), and lastly Sungai Buloh (19 m
2).
All in all, Map 4.1 shows green space (open recreational space/parks in particular) acreage (in
square meter) per person by mukim in Kuala Lumpur and Petaling District of Selangor.
Mukim in darker brown provide more recreational areas to their residents. It can be clearly
seen that only mukim of Damansara appears to provide adequate open recreational space of
more than 20 m2 per person. Mukim of Setapak on the other hand is the least provided, with
less than 3 m2.
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Table 4. 6: Green space provision by mukim in Petaling District of Selangor
Land Use (m2)
Mukim in Petaling District of Selangor
Bukit Raja Damansara Petaling Sungai Buloh Bandar Petaling Jaya
Sport and recreation facilities 0 3,796,343.42 1,748,856.78 2,765,129.95
Data incomplete
Open land (regional/state park) 1,977,070.87 13,636,155.4 5,670,035.13 4,049,865.09
Land forest (State forest reserve) 28,348,699.03 10,325,088.58 12,178,510.28 19,622,119.76
Village housing 2,570,344.57 3,034,943.68 6,828,754.25 9,888,627.03
Planned housing (terrace) 1,854,902.14 18,310,172.92 16,934,612.64 11,107,504.98
Planned housing (others) 12,499.96 0 13,026.77 0
Total residential 4,437,746.67 21,345,116.6 23,776,393.66 20,996,132.01
Ex-mining 29,634.82 779,946.46 1,704,111.73 161,107.45
Natural water body (river) 3,048,264.12 2,700,447.65 1,616,101.8 388,180.03
Selected Indicators
Mukim area (km2) 91.72 136.34 128.78 128.48 15.64
Population number (2010) 117,869 516,666 603,430 4,66163 61,367
Households number (2010) 30,596 131,528 159,779 129,871 15,088
Living quarters (2010) 31,834 148,023 177,064 145,180 16,363
Population density (2010) person/km2
1,285 3,790 4,686 3,628 3,924
Population density (2010) person/km2
residential area 26,561 24,205 25,379 22,202 26,561
Residential as % from mukim area 4.84 15.66 18.46 16.34 Data incomplete
Household density (2010) per km2
334 965 1,241 1,011 965
Household density (2010) per km2
residential area 6,894 6,162 6,720 6,185 6,894
Living quarters density (2010) per km2
347 1,086 1,375 1,130 1,046
Living quarters density (2010) per km2
residential area 7,173 6,935 7,447 6,915 7,173
Open space (parks) (m2) per inhabitant 16.77 26.39 9.40 8.69 Data incomplete
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Open space (parks) as % from mukim
area 2.16 10.00 4.40 3.15
Open space (parks) : residential area 0.45 0.64 0.24 0.19
Land forest (m2) per inhabitant 240.51 19.98 20.18 42.09
Land forest as % from mukim area 30.91 7.57 9.46 15.27
Land forest : residential area 6.39 0.48 0.51 0.93
Source: Petaling District Government (2005); Department of Statistics Malaysia (2011)
Map 4. 1: Open recreational area distribution by mukim in Kuala Lumpur and Petaling District of Selangor
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4.6 Spatial distribution of green space and residential land use in Kuala Lumpur and
Petaling District of Selangor
Map 4.2 and 4.3 display the distribution and spatial pattern of green space and residential
land use in Kuala Lumpur and Petaling District of Selangor. A few useful indicators are also
provided for each mukim on the open space (recreation), population density, and residential
area.
The residential area is color-coded pink, and clearly takes up a large proportion (28 per cent)
of the Kuala Lumpur land (Map 4.2). Mukim of Setapak, Ampang, Ulu Kelang, Kuala
Lumpur, and Bandar Kuala Lumpur have more than one-fifth area zoned for residential. The
distributional pattern of residential development tends to be generally widespread, especially
in mukim of Batu, Setapak, and Petaling. However, some ‘empty spots’ designated for other
land uses can be observed in the centre of mukim of Bandar Kuala Lumpur, northwest part of
mukim of Kuala Lumpur (southeast of Taman Rimba Kiara), and east part of mukim of
Petaling.
Several land use types that can be considered green space are also mapped, namely the
recreation area/open space (green), agriculture/fishery/forestry (yellow), open undeveloped
land (grey), and water body (blue). However, this study will focus on the foremost category,
that is the value of green recreational areas in the urban housing market. This is because the
other categories are not the land developed to serve recreational function, and hence do not
encourage visit by nearby residents. The recreation area/open space performs this function
and hence generates an added value to nearby residential property.
Focusing on open recreational area (green areas in map 4.2), overall there is limited open
recreational area in Kuala Lumpur. The largest green land use is located in western part of
mukim of Kuala Lumpur, which is Taman Rimba Bukit Kiara. Compact residential areas can
be seen surrounding this forested park on its west and east. A large area identified as open
undeveloped land (‘kawasan lapang’). Moving southeast to the middle part of mukim of
Kuala Lumpur, in mukim of Bandar Kuala Lumpur, several fragmented medium size green
patches can be observed. Eastern part of mukim of Bandar Kuala Lumpur is where the Royal
Selangor Golf Club is located. Moving from east to west, can be seen the KLCC Park, Bukit
Nanas Forest Reserve, and Lake Garden. Meanwhile on its north is the Titiwangsa Lake. In
mukim of Batu, the green areas surrounding lakes can be found in the northern part, which is
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the Taman Metropolitan Kepong. Small green patches in between residential areas are
distributed across mukim of Setapak. The most southern mukim of Petaling also has a cluster
of open recreational areas and open undeveloped land in it southern part, which is the Bukit
Jalil International Park. On the east side is the Sungai Besi Forest Reserve.
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Map 4.2: Spatial pattern of green space and residential land use in Kuala Lumpur (2005)
Mukim Ampang________ Pop density: 10,487/km
2
Open space (recreation): 4.36 m
2/person, 4.57%
Residential area: 30.22% LQ density: 2,851/km
2
Mukim Bandar Kuala Lumpur Pop density: 5,362/km
2
Open space (recreation): 16.58 m
2/person, 8.89%
Residential area: 21.58% LQ density: 1,554/km
2
Mukim Batu____________ Pop density: 6,106/km
2
Open space (recreation): 6.34 m
2/person, 3.87%
Residential area: 18.99% LQ density: 1,873/km
2
Mukim Cheras__________ Pop density: 12,972/km
2
Open space (recreation): 2.54 m
2/person, 3.30%
Residential area: 14.43% LQ density: 3,618/km
2
Mukim Ulu Kelang______ Pop density: 10,759/km
2
Open space (recreation): 5.92 m
2/person, 6.37%
Residential area: 25.52% LQ density: 3,121/km
2
Mukim Kuala Lumpur_____ Pop density: 5,768/km
2
Open space (recreation): 19.43 m
2/person, 11.21%
Residential area: 25.10% LQ density: 1,645/km
2
Mukim Setapak_________ Pop density: 10,117/km
2
Open space (recreation): 2.31 m
2/person, 2.33%
Residential area: 31.41% LQ density: 2,814/km
2
Mukim Petaling_________ Pop density: 4,686/km
2
Open space (parks): 9.40 m
2/person, 4.40%
Residential area: 18.46% LQ density: 1,374/km
2
Taman
Metropolitan
Kepong
Taman Rimba
Bukit Kiara
Titiwangsa Lake
Lake Garden
Bukit Nanas Forest Reserve
KLCC Park
Royal Selangor
Golf Club
Tasik Permaisuri
Desa Water Park
Sungai Besi Forest
Reserve Bukit Jalil
Recreational Park
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Mukim Petaling_________ Pop density: 4,686/km
2
Open space (parks): 9.40 m
2/person, 4.40%
Residential area: 18.46% LQ density: 1,374/km
2
Mukim Bandar Petaling Jaya Pop density: 3,924/km
2
Open space (parks): No Data Residential area: No Data LQ density: 1,046/km
2
Mukim Bukit Raja_______ Pop density: 1,285/km
2
Open space (parks): 16.77 m
2/person, 2.16%
Residential area: 4.84% LQ density: 347/km
2
Mukim Damansara_______ Pop density: 3,790/km
2
Open space (parks): 26.39 m
2/person, 10.00%
Residential area: 15.66% LQ density: 1,085/km
2
Mukim Sungai Buloh____ Pop density: 3,628/km
2
Open space (parks): 8.69 m
2/person, 3.15%
Residential area: 16.34% LQ density: 1,129/km
2
N
Taman Botani
Negara Shah Alam
Taman Tasik Shah Alam
Taman Bandaran
Kelana Jaya
Taman Subang Ria
Park
Map 4. 3: Spatial pattern of green space and residential land use in Petaling District of Selangor (2005)
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Map 4.3 above shows the spatial distribution of green space and residential zones in Petaling
District of Selangor (unfortunately, land use for mukim of Bandar Petaling Jaya is not
provided). Residential areas (in pink) spread widely across mukim of Petaling, but less spread
in mukim of Damansara and Sungai Buloh. Unlike Kuala Lumpur, residential areas take
lower proportion of land in Petaling District, as indicated by the lower residential area
percentage in the accompanying boxes. The open space and recreation land use consists of
three sub-classes namely regional/state parks (in green), sports and recreational facilities (in
red), and open undeveloped land (in grey). This study focuses on the first category, which
functions as both urban greenery and recreational areas. Other green spaces drawn in the map
4.3 are the forest, agriculture, and water body.
It can be clearly seen that mukim of Damansara provides the most amount of open
recreational parks (10 per cent) of medium and small sizes, fragmented and distributed in
between residential areas. The largest of it, to the northeast direction from the middle, is the
Taman Bandaran Kelana Jaya. Far on the west part of mukim of Damansara is Taman Tasik
Shah Alam. Like in Kuala Lumpur, many recreational parks are developed surrounding ex-
mining ponds/lakes, to enhance the naturalness aspects. In mukim of Petaling and Sungai
Buloh, small open recreational spaces are visibly scattered within the residential
complex/neighbourhood. For the other green spaces, very large forest and agriculture areas
cover almost entirely mukim Bukit Raja. They extend to mukim of Bukit Raja’s boundary
with mukim of Sungai Buloh, east part of mukim of Sungai Buloh and in the middle of
mukim of Petaling. Adjacent and north of the agriculture area in the west of mukim of Sungai
Buloh can be observed compact residential areas.
4.7 Distribution of open recreational spaces by size in Kuala Lumpur and Petaling
District of Selangor
A functional open recreational area should be interconnected, and JPBD has stated in their 10
per cent open space guideline for development to avoid incidental open space, with
recommended minimum open space size of 0.1 Ha (1000 m2). However, on the other hand,
open spaces need to be distributed evenly to ensure them being accessible from residential
areas all everywhere, especially in a large area. Therefore, the distribution of open space in
terms of size and number of patches can indicate a finer distribution of open recreational
space in an area.
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In this section, the area of open space has been classified into 8 classes, following the JPBD
guideline on the size of open space based on hierarchy (Table 4.7). Although a particular
open space can be classified as park based on size of a certain hierarchy, further verification
is needed to check if the open space is really developed and maintained as a functional park
by the local authorities or private developers.
Table 4. 7: Size of open recreational space based on open space and recreation hierarchy in JPBD
guideline
No Area (m2) Area (Ha) Hierarchy
1 Less than 1,000 Less than 0.1 Minimum open space size 0.1 Ha
2 1,000 - 1,999 0.1 - 0.2 Recreational Yard
3 2,000 - 5,999 0.2 - 0.6 Playground
4 6,000 - 11,999 0.6 - 1.2 Playing Field
5 12,000 - 79,999 1.2 - 8 Neighbourhood Park
6 80,000 - 399,999 8 - 40 Local Park
7 400,000 - 999,999 40 - 100 City Park
8 More than 999,999 More than 100 Regional Park and National Park
The distribution of open recreational spaces by size and mukim following the area
classification in Table 4.7, in Kuala Lumpur and Petaling District of Selangor is shown in
Table 4.8. A useful indicator of number of open recreational land patches of size greater than
0.1 Ha per 100 Ha residential area has also been computed by mukim. It is noted that this
indicator ignores the relative distribution of the open recreational space to residential areas.
However, Map 4.2 and 4.3 above indicate that open recreational spaces are distributed in
many places within residential area/park or housing clusters.
Based on Table 4.8, mukim of Ampang and Cheras have the least number of open
recreational land patches (less than 20) as they have also among the least total area of open
recreational space. However, mukim of Ulu Kelang also has even less open recreational area
coverage than mukim of Ampang, but it has the largest number of patches, mostly of size less
than 0.1 Ha which are not likely functional as recreational parks, despite its mukim area is
only 2.46 km2. Here, for every 100 Ha residential area, there are on average 25 open
recreational patches, the largest number of open space in Kuala Lumpur. Still with regards to
number of open recreational patches greater than 0.1 Ha relative to residential area coverage,
mukim of Cheras and Petaling also have roughly more of such space (more than 20 patches in
100 Ha residential area), mukim of Batu have 17 patches over 100 Ha residential zones,
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mukim of Bandar Kuala Lumpur and Setapak 13 patches, and lastly mukim of Ampang has
the least with 19 patches.
With the exception of mukim of Ulu Kelang, the four mukim with larger total area of open
recreational space ranging from 204 Ha to 673 Ha (Bandar Kuala Lumpur, Batu, Kuala
Lumpur, and Petaling) also have more open recreational patches of more than 230 patches.
Most of the patches are of size less than 0.1 Ha in mukim of Bandar Kuala Lumpur and
Petaling. In general, in all mukim in Kuala Lumpur, many of the open recreational patches
are less than 8 Ha in area.
Since this study is interested to capture the value of open recreational spaces large enough to
provide adequate recreational facilities and facilitate diverse activities for surrounding
residents, focus is given to the open recreational space with area 1.2 Ha and above. In
planning terms, these parks have the hierarchy of neighbourhood park and higher (local, city,
regional, and national park). Many open recreational space the size of neighbourhood park
can be found in mukim of Bandar Kuala Lumpur and mukim of Kuala Lumpur, whereas very
few are available in mukim of Ampang, Cheras, and Ulu Kelang. For open recreational space
the size of local park (8-40 Ha), at least four patches are provided in mukim of Kuala
Lumpur, Petaling, Batu, and Bandar Kuala Lumpur (Table 4.8), one in mukim of Ampang,
and none in the other mukim. One city park (40-100 Ha) can be seen in the land use data in
mukim of Bandar Kuala Lumpur and Batu, two in Petaling, and none in the rest of the
mukim. Open recreational space larger than 100 Ha are available only in mukim of Bandar
Kuala Lumpur (1 patch) and mukim of Kuala Lumpur (2 patches).
In Petaling District of Selangor, mukim Damansara has the highest amount of open
recreational space in terms of total area, and consequently the largest number of open
recreational patches. Out of the 1,312 patches, as many as 201 patches are of the size of
neighbourhood park (1.2-8 Ha), 23 of local park size (8-40 Ha), 1 city park (40-100 Ha), and
2 parks with size more than 100 Ha thus falling into the category of regional and national
park. With regards to residential area, 39 open recreational areas are available for every 100
Ha residential area, the highest provision in Petaling District. Mukim of Bukit Raja is the
least provided, with 150 land patches identified as open recreational spaces totalling up at
197.71 Ha, and on average 18 patches larger than 0.1 Ha for 100 Ha residential areas. Mukim
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of Sungai Buloh and Petaling on the other hand provide 20 and 25, respectively, open
recreational patches larger than 0.1 Ha.
Playground-size open recreational spaces are largely provided in mukim of Damansara (279
patches), Petaling (262 patches), and Sungai Buloh (150 patches). There is also a good
provision of neighbourhood park-size areas in mukim of Petaling (88 patches) and Sungai
Buloh (87 patches). Unlike mukim of Damansara, less than 5 local park-size open
recreational areas can be found in the other mukim. There is one city park-size patch each in
mukim of Bukit Raja and Damansara and none in the other two mukim (Petaling and Sungai
Buloh). Other than the two in mukim of Damansara, only one patch sized more than 100 Ha
is available, which is in mukim of Petaling.
Figure 4.3 until 4.10 plots the distribution of open recreational space (parks) by size of
individual open space patch in Kuala Lumpur, using the 2005 land use data. Figure 4.11 until
4.14 plots the distribution in Petaling District of Selangor.
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Table 4. 8: Distribution of open recreational spaces by size and mukim in Kuala Lumpur and Petaling District of Selangor
Area
(Ha) Hierarchy*
No. of patches in each mukim in Kuala Lumpur No. of patches in each mukim in Petaling District of
Selangor
Am-
pang
Bandar
Kuala
Lumpur
Batu Che-
ras
Kuala
Lumpur
Peta-
ling
Seta-
pak
Ulu
Kelang
Bukit
Raja
Daman-
sara Petaling
Sungai
Buloh
Bandar
Petaling
Jaya
Less than
0.1
Minimum open space
size 0.1 Ha 9 101 69 11 68 79 71 1000 69 488 246 361 NA
0.1 - 0.2 Recreational Yard 2 39 48 1 56 39 27 2 17 164 136 87 NA
0.2 - 0.6 Playground 4 37 86 0 71 57 59 8 30 279 262 150 NA
0.6 - 1.2 Playing Field 1 15 17 1 34 30 20 2 10 154 112 95 NA
1.2 - 8 Neighbourhood Park 2 30 12 1 28 19 13 4 19 201 88 87 NA
8 - 40 Local Park 1 6 5 0 4 4 0 0 4 23 2 3 NA
40 - 100 City Park 0 1 1 0 0 2 0 0 1 1 0 0 NA
More
than 100
Regional Park and
National Park 0 1 0 0 2 0 0 0 0 2 1 0 NA
Total no. of patches 19 230 238 14 263 230 190 1016 150 1312 847 783 NA
Total area of open recreation (Ha) 18.96 420.78 203.74 3.10 672.66 316.39 67.62 15.68 197.71 1363.62 567.00 404.99 NA
Mukim area (km2) 4.15 47.34 52.6 0.94 60.02 44.91 28.99 2.46 91.72 136.34 128.78 128.48 15.64
Residential area (Ha) 125.39 1021.82 998.95 13.56 1506.73 732.42 910.53 62.79 443.77 2134.51 2377.64 2099.61 NA
No. of patches**/ 100 Ha
residential area 8 13 17 22 13 21 13 25 18 39 25 20 NA
* Although based on the size the open recreational space can be categorized in a certain open space hierarchy, there is no way to tell that the space is really developed and
maintained by local authorities as a functional green park.
** Excluding the patches of size less than 0.1 Ha
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Figure 4. 3: Open recreational space distribution in mukim of Ampang, Kuala Lumpur (2005)
Figure 4. 4: Open recreational space (parks) distribution in mukim of Bukit Raja, Petaling District of
Selangor (2005)
Number of patches: 19
Minimum area: 19.05 m2
Maximum area: 108648.45 m2
Mean area: 9978.87 m2
Number of patches: 150
Minimum area: 0.83 m2
Maximum area: 426813.61 m2
Mean area: 13180.47 m2
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4.8 Conclusion
This section has presented a preliminary analysis on the green space and residential land use
in Kuala Lumpur and Petaling District of Selangor. This section has achieved the objectives
namely to calculate the provision of green space of the interest to this study, to investigate the
spatial pattern of open recreational spaces and residential areas, and to analyse the
distribution of those spaces in terms of size, in Kuala Lumpur Federal Territory and Petaling
District of Selangor. The analysis has been made at mukim level, as the population data and
residential property market report data have also been available at mukim level of
disaggregation. Next section will discuss the current housing market in Kuala Lumpur
Federal Territory and Petaling District of Selangor, whereby the findings from this section in
terms of green recreational areas provision will be analysed together with housing stock and
price data. The combined analysis attempts to explore possible relationship that may be
captured at mukim level, that is whether more amount open recreational spaces increase
residential property value in an area.
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4. CURRENT HOUSING MARKET ANALYSIS
5.1 Introduction
This section draws current market data from the latest Residential Property Stock Report for
first quarter 2013 published by the National Property Information Center (NAPIC or JPPH).
A descriptive analysis of existing stocks (supply) and house price by area and house types is
presented to give a general picture of the current housing market scenario in Kuala Lumpur
and Petaling District of Selangor. The existing stocks consist of all completed units (both
vacant and occupied) as of the end of the review period. Existing stock is chosen for
reporting to reflect current supply of completed units rather than future planned supply such
as approved units or units under construction. The median house price calculated from the
sample transactions performed in the reporting period is selected for price comparison
between areas, instead of mean house price which might be distorted by extreme values.
Section 5.2 presents housing market trend in Kuala Lumpur, followed by section 5.3 on
Petaling District of Selangor. This section is then concluded with analysis relating house
prices and results of green space provision analysis from section 4.
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5.3 House prices and green space
Table 5.5 shows the results from Section 4, an analysis on open recreational space provision to see whether mukim with more open recreational
space enjoys a higher market value for residential property, taking only the case in Kuala Lumpur as the house price data for Petaling District of
Selangor is not disaggregated by mukim in the NAPIC Residential Property Stock Report. Three major and highly valued types of houses are
selected, namely 2-2 ½ storey terrace, detach, and condominium/apartment. Mukim of Kuala Lumpur with the most amount of open recreational
space (11.21 per cent of mukim area; 19.43 m2 per person; 45 m
2 for every 100 m
2 residential area) somehow experience the highest market value
(median price) for the two landed houses of 2-2 ½ storey terrace and detach. However, this expected positive relationship between availability of
open recreational areas and house prices does not apply for all other mukim where property prices can also be higher in mukim with minimum
provision of open recreational areas. For example, median price of 2-2 ½ storey terrace is higher in mukim of Ampang with 4.36 m2 open
recreational space per person, than in mukim of Bandar Kuala Lumpur with 16.58 m2 open recreational space per person, or than in mukim of
Petaling (10.83 m2 per person).
Table 5. 1: Median house price (Q1 2013) and open recreational parks provision in Kuala Lumpur by mukim
Mukim in Kuala
Lumpur
Median house price (Q1 2013) Open recreational parks provision
2-2 1/2 Storey
Terrace Detach
Condominium/
Apartment
Percentage from
mukim area m
2 per person
Open recreational
space : residential
area
Mukim Ampang 830,000 ND 390,000 4.57 4.36 0.15
Mukim Bandar Kuala
Lumpur/Section 1-100 730,000 2,594,000 464,500 8.89 16.58 0.41
Mukim Batu 400,000 244,000 625,000 3.87 6.34 0.2
Mukim Cheras 443,000 ND ND 3.3 2.54 0.23
Mukim Kuala Lumpur 1,154,000 4,650,000 430,000 11.21 19.43 0.45
Mukim Petaling 634,000 2,932,500 275,000 7.05 10.83 0.43
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Mukim Setapak 437,500 3,080,000 342,500 2.33 2.31 0.07
Mukim Ulu Kelang ND ND ND 6.37 5.92 0.25
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Similarly for condominium/apartment, median price in the better provided mukim (in terms
of open recreational area) of Kuala Lumpur is lower than in mukim Batu. Mukim of Batu
only has 3.87 per cent open recreational space, but the condominium/apartment price in
mukim of Batu is RM625,000 compared to RM430,000 in mukim of Kuala Lumpur.
However, arguably this direct comparison is too coarse analysis as the factor of location and
accessibility from houses to the open recreational parks is not taken into account.
Map 5.1 presents the land use map for residential and green space in Kuala Lumpur and the
trend of (median) house price by mukim. The graphical representation can be used to further
visualize the relationship between availability and quantity of open recreational areas and
house price analysed at mukim level. Mukim of Ampang, Ulu Kelang, and Cheras are
excluded given their small administrative areas, hence assumed to contribute a small segment
of housing market in Kuala Lumpur. Looking at the 2-3 storey terrace median prices, median
price is highest in mukim of Kuala Lumpur (RM1.154 millions) where the largest green
recreational areas are visible (quantified as 11.21 per cent of mukim area). However,
comparing between mukim of Batu and Setapak, 2-3 storey terrace price is higher in mukim
of Setapak (RM437.5 millions) than in mukim of Batu (RM400 millions) although the green
coverage in the map appears to be larger in mukim of Batu. Detached house in mukim of
Setapak is also somehow more expensive (RM3.080 millions) than in the mukim of Kuala
Lumpur (RM2.594 millions) and mukim of Petaling (RM2.933 millions) even though more
green recreational areas are available in the latter two mukim. The value of green space
contributing to house value is therefore not clearly manifested through such a broad mukim-
level analysis and comparison.
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GREEN SPACE, RESIDENTIAL LAND USE (2005), AND MEDIAN HOUSE PRICE (Q1 2013) BY TYPE AND MUKIM
Map 5. 1: Green space, residential land use, and median house price by house type and mukim in Kuala Lumpur (Q1 2013)
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Table 5. 2: Median house price (Q1 2013) and distribution of open recreational spaces by size, by mukim in Kuala Lumpur
Area (Ha) Hierarchy*
No. of patches in each mukim in Kuala Lumpur
Am-pang Bandar Kuala
Lumpur Batu Cheras
Kuala
Lumpur Peta-ling Setapak
Ulu
Kelang
Less than 0.1 Minimum open space size
0.1 Ha 9 101 69 11 68 79 71 1000
0.1 - 0.2 Recreational Yard 2 39 48 1 56 39 27 2
0.2 - 0.6 Playground 4 37 86 0 71 57 59 8
0.6 - 1.2 Playing Field 1 15 17 1 34 30 20 2
1.2 - 8 Neighbourhood Park 2 30 12 1 28 19 13 4
8 - 40 Local Park 1 6 5 0 4 4 0 0
40 - 100 City Park 0 1 1 0 0 2 0 0
More than 100 Regional Park and National
Park 0 1 0 0 2 0 0 0
Median House
Price
2-2 ½ Storey Terrace 830,000 730,000 400,000 443,000 1,154,000 634,000 437,500 ND
Detach ND 2,594,000 244,000 ND 4,650,000 2,932,500 3,080,000 ND
Condominium/Apartment 390,000 464,500 625,000 ND 430,000 275,000 342,500 ND
Table 5.6 presents a further analysis on the possible relationship between the availability of open recreational spaces and house price in Kuala
Lumpur. Mukim of Kuala Lumpur, where the median price for both 2-2 ½ storey terrace house and detached house is the highest, does have more
open recreational patches of large size. In particular, it has 28 (second largest number among the mukim) neighbourhood –sized recreational spaces,
4 local park-sized open spaces, and 2 (the highest number among the mukim) regional park-sized open spaces. However, mukim of Bandar Kuala
Lumpur which are provided with even more neighbourhood park-sized (30 patches) and local park-sized open recreational spaces (6 patches), and
an additional 1 city park reported a much lower market value for 2-2 ½ storey terrace at RM730,000. This value is even lower than the value for the
same house type in the less provided mukim of Ampang (RM830,000), with only 2 neighbourhood parks and 1 local park. In the
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condominium/apartment sector, market value is the highest in mukim of Batu (median price
RM625,000), which has been shown to have not more open recreational spaces than, for
example, mukim of Petaling where the reported median price is the lowest (RM275,000). In
particular, mukim Petaling has 7 more neighbourhood parks, 1 more city park, and 13 more
playing fields, although less 1 local park and less 26 playgrounds. Therefore, no clear and
generalised conclusion can be made on the influence of distribution of open recreational
spaces by size in a mukim and the residential property market value in that mukim.
5.6 Conclusion
This section has presented the current trend of housing market in Kuala Lumpur and Petaling
District of Selangor in terms of market median price and existing housing stock by the types
of the residential property. Further, the findings on green space provision in Section 4 has
been linked to the house price data to examine the question on whether market value for
residential property tends to be higher in mukim with better provision of green open
recreational areas. It has been found that there is no clear relationship between green space
provision and house value at mukim level, indicating that this type of analysis should be
performed at a finer scale and take into account the more important factor of the condition
and relative location of the green areas to the residential areas. This will be covered in the
main analysis of this study which is the development of spatial hedonic model that will
incorporate the proximity to green spaces as one of the factors that influence house prices. As
stated in the introduction, this analysis has not been possible to be undertaken at this stage as
the required house price data are still being collected.
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5. CONCLUSION AND NEXT MILESTONE
This interim report 1 has achieved the objectives to provide an insight into the green lungs
and residential area distribution as well as the current residential property market in the
Federal Territory of Kuala Lumpur and in Petaling District of Selangor. The main purpose
has been to investigate the role that green lungs play in influencing the market value of
residential properties, both landed and stratified housing. The descriptive and simple
comparative analysis has been carried out at mukim administrative unit or geographical
aggregation level. The analysis utilised the It was found that the relationship between green
lungs in terms of size-distribution and the overall provision of recreational parks, and the
residential property value is not a clear-cut one and hence no generalisation can be made at
mukim level with sufficient evidence. This preliminary finding suggests that the green
premium is highly localised and therefore, the value is highly dependent on the relative
location or distance from the residential properties and the recreational parks. With regards to
this, this interim report 1 has also presented the successful completion of selecting
considerably good quality recreational parks (of various hierarchy) that are of value to nearby
residential properties and residents. In general, all mukim in the Federal Territory of Kuala
Lumpur and Petaling District of Selangor (with the exception of mukim Damansara in
Petaling, Selangor) underprovide open recreational parks as per the National Physical Plan
target of 20 m2 per dweller. This finding suggests the importance of related implication of
this study to create awareness among the property developers and government agencies of the
value of these environmental amenities. This is expected to lead to more active initiatives to
preserve green lungs in the increasingly urbanised Klang Valley region.
The next stage of this research is the collection and preparation of residential property
transaction data. The transacted properties are to be selected based on the selected sixteen
(16) case study parks and their catchment buffer areas. The locations of properties are
georeferenced based on their address and cadastre lot number information using the cadastre
map to be obtained from the Department of Survey and Mapping (JUPEM). The housing
attributes associated with each property are inserted into the database. Key public facilities,
services, and urban amenities are to be digitized from scanned street directory maps. The
residential property database can then be developed in a Geographic Information System.