sure_gisproject_interim1_excerpt

INTERIM REPORT 1 : Application Of GIS To Measure The Value Of Green Lungs In Urban Housing Market

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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


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


June 2013

23

(‘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)


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


June 2013

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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


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


June 2013

25

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.


June 2013

26

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


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



Living quarters density (2010) per km2

2,851 1,554 1,873 3,618 1,645 2,071 2,814 3,121



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


June 2013

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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


June 2013

30

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


1,285 3,790 4,686 3,628 3,924


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


334 965 1,241 1,011 965




347 1,086 1,375 1,130 1,046



Open space (parks) (m2) per inhabitant 16.77 26.39 9.40 8.69 Data incomplete


June 2013

32

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


June 2013

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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


June 2013

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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.


June 2013

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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


2/person, 8.89%


2

Mukim Batu____________ Pop density: 6,106/km

2


2/person, 3.87%


2

Mukim Cheras__________ Pop density: 12,972/km

2


2/person, 3.30%


2

Mukim Ulu Kelang______ Pop density: 10,759/km

2


2/person, 6.37%


2

Mukim Kuala Lumpur_____ Pop density: 5,768/km

2


2/person, 11.21%


2

Mukim Setapak_________ Pop density: 10,117/km

2


2/person, 2.33%


2

Mukim Petaling_________ Pop density: 4,686/km

2

Open space (parks): 9.40 m

2/person, 4.40%


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


2/person, 4.40%


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


2/person, 2.16%

Residential area: 4.84% LQ density: 347/km

2

Mukim Damansara_______ Pop density: 3,790/km

2


2/person, 10.00%


2

Mukim Sungai Buloh____ Pop density: 3,628/km

2


2/person, 3.15%


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)


June 2013

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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,


June 2013

39

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


June 2013

40

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


June 2013

46

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


June 2013

47

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


June 2013

50

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.

sure_gisproject_interim1_excerpt

Documents

green space provision

kuala lumpur

land use distribution

petaling district of

residential land use

value of green lungs

urban housing market

estimation of ols models