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Spatial-Based Sustainability Assessment of
Urban Neighbourhoods: A Case Study of Johor
Bahru City Council, Malaysia
Azman Ariffin, Haziq Kamal Mukhelas, Abd. Hamid Mar Iman, Ghazali Desa, Izran
Sarrazin Mohammad
Abstract Rapid population growth has caused expansion of many major cities. Cities
begin to expand into new areas as the demand for housing increases, thus, contributing to
demand for a variety of natural and man-made resources for urban communities. However,
it is our responsibility to sustain these resources so that their usage can be prolonged to the
next generation. With sustainability as a goal, the use of indicators for urban monitoring
and regulation is becoming more in demand. There are many non-spatial indicators in the
form of words and statistics developed by local authorities for assessing urban development
sustainability. This paper proposes the use of spatial indicators for the same purpose. The
indicators are derived from the Malaysian Urban Indicators Network (MurniNet) and are
then developed using Analytical Hierarchy Process (AHP) comprising spatial elements of
points, lines, and polygons. The AHP is used to determine the ranking of sustainability of
urban areas. This study selects Johor Bahru City Council (JBCC) administrative area as a
case. The result shows that spatial indicators can contribute to a better visualisation of
sustainability via the production of sustainability map.
__________________________
Azman Ariffin
TropicalMap Research Group, Faculty of Geoinformation and Real Estate, Universiti Teknologi
Malaysia, Malaysia, e-mail: azmanariffin@utm.my
Haziq Kamal Mukhelas
Department of Geoinformation, Faculty of Geoinformation and Real Estate, Universiti Teknologi
Malaysia, Malaysia, e-mail: haziqmukhelas@gmail.com
Abdul Hamid Mar Iman
Environmental Sustainability & Conservation Cluster, Faculty of Earth Sciences, Universiti
Malaysia Kelantan, Jeli, Malaysia, e-mail: hamid.m@umk.edu.my
Ghazali Desa
Department of Geoinformation, Faculty of Geoinformation and Real Estate, Universiti Teknologi
Malaysia, Malaysia, e-mail: ghazalidesa@utm.my
Izran Sarrazin Mohammad
Centre for Real Estate Studies, Faculty of Geoinformation and Real Estate, Universiti
Teknologi Malaysia, Malaysia, e-mail: izran@utm.my
2
1 Introduction
Urban development can be defined as the expansion of urban areas into natural and rural
areas such as deserts, swamps, and forests (Black et al., 2002). As population grows,
socioeconomic needs arise. In particular, population growth in major cities requires city
boundary’s expansion while developers look into the neighbouring areas to build more
housing, recreational, and other facilities. Consequently, demand for a variety of natural
and man-made resources for urban communities increases.
The process of urban expansion requires that planners work closely with other parties to
ensure environmental protection. In this context, sustainable development seeks to establish
a balance between human needs and environmental preservation. Therefore, urban planners
need to consider maintaining sustainable development while expanding and renovating
urban areas. Especially important, much care needs to be taken to integrate the wilderness
with the developing city when an urban area expands into wildlife regions (Litman et al.,
2007). Besides, sustainable urban development should function to curtail city pollution, to
increase the availability of recycling facilities, and to encourage efficient use of alternative
sources of energy.
Urban sustainability needs to be considered from ecological viewpoint and, thus, it needs to
adopt the concepts of footprint, emissions, and energy (Broekhof and van Marwijk, 2012).
Further, to achieve a sustainable city, there are several elements to be considered (Figure 1).
Figure 1 shows that urban sustainability should be considered from environmental,
economic, and social dimensions. Since they are very complex and have different degrees
of importance, an approach is needed to rank them accordingly before they can be used as
indicators for urban development sustainability assessment (Figure 1).
Fig. 1. The classic dimensions of sustainable development (source: Tanguay et al. 2010)
In 2004, the Malaysian government has taken an initiative, based on the Eight Malaysia
Plan, to develop a set of indicators that can be used to measure sustainable urban
development, called Malaysian Urban Indicators Network (MurniNet) (Marzukhi et al.,
3
2011). However, these indicators, extracted from several planning sectors, are non-spatial
indicators although they can be used for evaluating urban development. We propose the use
of spatial indicators for the same purpose. Spatial indicators with sufficient spatial
information and geographic visualisation can be useful for local sustainable planning,
supporting decision-making in the planning process, and helping policy makers to identify
‘unsustainable’ actions in the planning areas (Broekhof and van Marwijk, 2012). As a
result, areas of urban development can be mapped as sustainable, semi-sustainable, or non-
sustainable.
Geographic visualization plays an important role in any spatial rating to ensure reliable and
consistent outcome. Rating using non-spatial indicators usually results in statistics that can
only be viewed as words and numbers; its usefulness in the spatial context is quite limited.
On the other hand, spatial indicators can be a more meaningful way of generating spatial
information thus assisting users on decision making and enhancing policy by perfect
viewing of sustainable urban development with multi-layered information included at one
time. Broekhof and van Marwijk (2012) have argued that maps can give valuable
information to develop sustainable policies at the local scale.
This study attempts to improve the approach to assessing sustainable urban development
adopted by MurniNet. In particular, this study attempts to demonstrate how spatial
information can be generated to assess urban development sustainability. In all, this study
proposes the incorporation of spatial indicators to help the local authority and policy
makers to assess urban development sustainability in a more visualized manner.
2. Assessment of Sustainable Urban Development
Sustainability
The literature on through-time urban sustainability assessment techniques conducted using
built-environment quality evaluation framework (BEQUEST) reveals several methods
available for sustainability assessment of urban activities (Deakin et al, 2002; Ugwu and
Haupt, 2005). Three of them are Environmental in General (EIG), Life Cycle Assessment
(LCA), and Sustainability Indicator Assessment (SIA) methods. Out of these three, the SIA
method is most widely used by local authorities around the world. This is because the SIA
method seeks to achieve integration of all issues of sustainability compared to the other two
which focus solely on environment and socioeconomic aspects, respectively. In general,
SIA method employs a wide range of indicators to characterize the different dimensions or
aspects of urban development. Therefore, the assessment of sustainability is actually
considered as an assessment of indicators by which people can track their progress towards
sustainability.
2.1 The Study Area
The study area, Johor Bahru City Council (JBCC), covers an administrative region of 220
km2 with a total population of 552,026 people. JBCC is divided into 16 planning blocks
according to the Johor Bahru Local Plan for 2020 as shown in Figure 2. These are Daerah
4
Sentral, Tasek Utara/Teluk Danga, Pelangi, Pasir Pelangi, Tampoi, Larkin, Majidee, Teluk
Tebrau, Permas Jaya, Rinting, Kempas, Kangkar Tebrau, Pandan/Taman Molek, Bandar
Dato’ Onn/Setia Tropika, Mount Austin/Taman Daya and Tebrau.
Fig. 2. 16 Zones in MBJB
2.2 Sustainability Indicator Assessment (SIA) Method
An indicator is a measurement to be met, an effect obtained via a gauge of quality or a
context variable (European Commission, 2008). An indicator produces measured
information with a purpose to help researchers concerned with public interventions to
communicate, negotiate, or make decisions. In the process of urban sustainability
assessment, there is a need for measureable indicators and several approaches of assessment
based on these indicators have been developed (Shen et al., 2011).
However, assembling information for all-embracing indicators is not what urban
sustainability assessment is all about. Rather, a selective analysis of indicators which are
more fundamental in essence and more likely to produce the most accurate information
about the status of practice should be focused (Shen et al., 2011). The United Nations
Statistical Institute for Asia and Pacific (2007) stated that an indicator must be SMART (i.e.
Specific, Measureable, Achievable, Relevant, and Time-related). This can help in effective
data management and avoiding data exaggeration of irrelevant selected indicators and, thus,
contribute to cost-effective assessment of urban development sustainability.
Sustainability indicators are essential in the overall assessment of progress towards
sustainable development. They are useful for measuring and monitoring the state of the
environment by considering a manageable number of variables or characteristics (McLaren
and Simonovic 1999). Several studies at the urban, regional, and national levels have
5
compiled extensive lists of sustainability indicators (Foxon et al. 2002; Hellström et al.
2000; Alberti 1996; Maclaren 1996). Based on these indicators, a number of assessment
methods have been developed which attempt to simplify the holistic assessment of urban
sustainability. These methods rely on key interactions and feedback mechanisms between
infrastructure and the surrounding environmental, economic, and social systems and use
sustainability criteria and indicators to understand and quantify the resulting interacting
effects. From a methodological standpoint, SIA method is recognised as a useful integrative
approach to evaluating a multi-dimensional situation and assessment outcome.
2.3 Sustainable Urban Development Indicators
In Malaysia, the Department of Town and Country Planning, Ministry of Housing and
Local Government Malaysia has developed a system for assessing the sustainability of a
city and region called MurniNet. The goal of this system is to assess the sustainability of
Malaysian cities according to Malaysian Urban Indicators. There are eight dimensions with
21 themes that are further subdivided into 36 urban indicators and are used as overall
sustainability indicators of a city. These indicators can be re-grouped into three categories,
namely non-spatial, spatial, and mixed indicators.
3 Determination of Spatial Indicators
The selection of spatial indicators is based on several criteria including their reliability and
effectiveness in providing sufficient information. These criteria must include three pillars of
sustainability, namely economy, environment, and social (see Fig. 1). As mentioned earlier,
the indicators must be “SMART”. However, in this study, these indicators are filtered by
selecting only those that contain spatial elements and mapable data.
There were nine spatial indicators selected to be used in this study. The first three indicators
are selected from the economic sustainability dimension. The first indicator represents
public transportation terminals and stations. The second indicator represents attraction areas
and recreational centres and the last indicator from this dimension represents grade ‘A’
business. All the indicators are represented as points.
Environmental sustainability is the next dimension in assessing urban development
sustainability and it is made up of three indicators. All of these indicators are represented in
polygons where the first indicator represents flood prone areas. The second indicator
represents provision of public open spaces and the last indicator represents residential areas
getting centralized sewerage services.
The last dimension is social sustainability whose first indicator is accessibility to
community facilities represented in points and polygons. The next indicator is happiness
index that indicates population’s satisfaction about their daily life and surroundings. The
last indicator is related to demography, in particular, the total population of each zone.
6
3.1 The Scoring System
The urban sustainability assessment scoring system is extracted the MurniNet system itself.
The system uses various weightage scores for each dimension and theme according to the
predetermined specification. The spatial indicators scoring system shown in Table 1 is
adopted in this study to determine the sustainability of the JBCC’s planning blocks.
Table 1. Spatial indicators formula
7
3.2 Analytical Hierarchy Process for Sustainability Assessment
Analytical hierarchy process (AHP) is a multi-criteria decision-making (MCDM)
technique. Underlying MCDM principle is that a decision has to be made by means of
analyzing a set of criteria. Saaty (1980) has developed AHP which models a hierarchical
decision problem framework consisting of multi-level criteria having unidirectional
relationships. AHP works with such a hierarchy that can combine both subjective
(intangible) and objective (tangible) criteria.
After finalizing the selected spatial indicators, the hierarchical decision model is then
developed. The decision model of this study is broken up into three major levels, namely
goal, objective, and design criteria. Goal is the topmost level which describes the decision
problem. This study attempts to work out the most sustainable urban development and
therefore, the topmost level is to ‘‘select the most sustainable area’’. The objectives of
sustainability assessment comprise three aspects: economic, environmental, and social. In
order to identify the priorities of three sustainable development objectives in the second
level, and the relative importance of different design criteria in the third level, a series of
pairwise comparisons have to be performed. The elements in both levels are then weighted.
By using pairwise comparisons, the relative importance of one criterion over another can be
expressed by ranking them using AHP’s nine-point scale of importance as shown in Tables
2, 3, 4, 5, 6, 7, 8, and 9.
8
Table 2. Scale of importance
AHP Scale of Importance for pairwise
comparison
Numeric
Rating
Extreme Importance
9
Very strong to extremely
8
Very strong Importance
7
Strongly to very strong
6
Strong Importance
5
Moderately to Strong
4
Moderate Importance
3
Equally to Moderately
2
Equal Importance
1
Table 3. Pairwise comparison
EcS
EnS
ScS
EcS
1/1
3/1
1/2
EnS
1/3
1/2
3/1
ScS
2/1
1/3
1/1
The fractions are converted into decimals to acquire pairwise matrix. A short computational
way to obtain the ranking is to raise the pairwise matrix to powers that are successively
squared each time. The row sums are then calculated and normalized.
Table 4. . Pairwise matrix
EcS
EnS
ScS
EcS
1
3
0.5
EnS
0.3
1
3
ScS
2
0.3
1
[AB]i,j = Ai,1B1,j + Ai,2B2,j + . . . + Ai,nBn,j =
jr
n
rri BA ,
1,
(1)
Table 5. The first Eigenvector
EcS
EnS
ScS
Normalized
Eigenvector
EcS
2.9999
6.16665
10
19.16655
0.3929
EnS
6.6666
2.9998
6.16665
15.83305
0.3246
ScS
4.111089
6.6666
2.9999
13.77759
0.2825
Total
48.77719
1
9
Table 6. Pairwise Comparison of objectives level
EcS
EnS
ScS
Normalized
Eigenvector
EcS
91.2155
103.6585
98.0166
292.8906
0.3761
EnS
65.3433
91.2200
103.6641
260.2273
0.3341
ScS
69.1056
65.3493
91.2209
225.6757
0.2898
Total
778.7935
1
Table 7. Eigenvector of the objectives level
Objectives
Eigenvector
Economic Sustainability(EcS)
0.3761
Environmental Sustainability(EnS)
0.3341
Social Sustainability(ScS)
0.2898
From the computed eigenvector, the relative criteria are ranked as follows:
EcS
0.3761
The most important criterion
EnS
0.3341
The second most important criterion
ScS
0.2898
The least important criterion
The steps were then implemented for the next level which is design criteria level where it
includes all the spatial indicators from environment, economic and social dimensions.
Then, the criteria are ranked in a descending order from most important to least important.
Economic sustainability indicators are represented by the numbers of integrated terminals
and stations for public transportations (TS), numbers of attraction areas and recreational
centres (TR) and percentage of grade ‘A’ business premises (GA).
Table 8. Pairwise comparison of economic sustainability
TS
TR
GA
TS
1
1/3
2
TR
3
1
4
GA
1/2
1/4
1
Table 9. Iterated eigenvector solution
TS
TR
GA
Normalized
Eigen Vector
TS
27.5301
10.4746
48.1068
86.1115
0.2380
TR
72.34
27.5301
126.42
226.2901
0.6254
GA
15.8025
6.0134
27.62
49.4359
0.1366
Total
361.8375
1
TS
0.2380
The second most important criterion
TR
0.6254
The most important criterion
GA
0.1366
The least important criterion
10
Environmental sustainability indicators are represented by the percentage of population
living in areas prone to flooding (FA), provision of public open space ratio compared to
1000 population (OS) and percentage of centralized sewerage (CS).
Table 10. Pairwise comparison of environmental sustainability
FA
OS
CS
FA
1
4
3
OS
0.25
1
3
CS
1/3
1/3
1
Table 11. Iterated eigenvector solution
FA
OS
CS
Normalized
Eigen Vector
FA
35.7488
89.4002
168.1425
293.2915
0.6218
OS
13.9403
35.7002
67.1175
116.7580
0.2476
CS
7.3990
18.5200
35.6590
61.5780
0.1306
Total
471.6275
1
FA
0.6218
The most important criterion
OS
0.2476
The second most important criterion
CS
0.1306
The least important criterion
Social sustainability indicators are represented by the percentage of residential areas within
400 meters from community facilities (AF), happiness index (HI), and demography (DM).
Table 12. Pairwise comparison of social sustainability
AF
HI
DM
AF
1
4
3
HI
1/4
1
1/3
DM
1/3
3
1
Table 13. Iterated eigenvector solution
AF
0.6149
The most important criterion
HI
0.1171
The least important criterion
DM
0.2680
The second most important criterion
AF
HI
DM
Normalized
Eigen Vector
AF
29.6126
155.2424
67.6704
252.5254
0.6149
HI
5.6293
29.6126
12.8749
48.1168
0.1171
DM
12.8748
67.6704
29.5228
110.0680
0.2680
Total
410.7102
1
11
Fig. 5. Finalised AHP decision model
The finalised AHP decision model is as shown in Figure 5.
3.3 Sustainability Map
Sustainability maps are produced for each indicator based on the formula prescribed in
MurniNet. These maps represent the sustainability of each planning block according to
spatial indicators. There are three sustainability scores: 1 = ‘not-sustainable’; 2 = ‘semi-
sustainable’; and 3 = ‘sustainable’. The production of the maps is important to assist users
in interpreting the information correctly. The maps are used in the analysis while graphs
and tables created are shown alongside the attributes. With the use of ArcToolbox in
ArcGIS 10.0, proximity analysis is performed for the measurement of various data.
4 Results and Discussion
This section discusses the results from the data analysis. The purpose is to spatially
visualize the assessed sustainability of each JBCC’s planning block. Besides spatial
indicators, the usage of non-spatial indicators is also shown in this section.
12
4.1 Sustainability based on Economic Indicators
Fig. 6. Attraction and recreational centres (Map 1) and Terminals and stations for public
transportations sustainability (Map 2)
Map 1 shows that out of 16 planning blocks only four are classified as sustainable
according to MurniNet standard. These are Teluk Danga, Daerah Sentral, Pelangi and
Larkin. Two planning blocks – Tampoi and Pasir Pelangi – have the score of ‘2’ which
means semi-sustainable while the rest of the planning blocks are considered not sustainable.
Map 2 shows that only Daerah Sentral is considered sustainable. Larkin and Permas Jaya
are categorized as semi-sustainable. Overall, the results show that the southern region of the
study area is economically sustainable.
4.2 Sustainability based on Environmental Indicators
Fig. 7. Population living in areas prone to flooding sustainability (Map 3) and Provision of
public open space ratio compared to 1000 population sustainability (Map 4)
Figure 7 shows that all the planning blocks are sustainable. Map 3 shows that the highest
percentage of flood-prone area – Kangkar Tebrau – is only five percent, followed by Teluk
Danga (0.28 %) and Teluk Tebrau (0.07%). Map 4 shows the planning blocks that achieve
sustainability on the public open space ratio, namely Tebrau, Bandar Dato’ Onn/Setia
Map 1
Map 2
Map 3
Map 4
13
Tropika, Mount Austin/Taman Daya, Pandan/Taman Molek, Tampoi and Tasek
Utara/Teluk Danga. Each of them has more than 1.5 hectares of public open space. Rinting,
Pasir Pelangi, Permas Jaya and Kempas are categorized as semi-sustainable planning
blocks while the rest of the planning blocks are not sustainable. Six areas are classified as
environmentally sustainable by achieving the highest score on both indicators. These are
Bandar Dato’ Onn/Setia Tropika, Mount Austin/Taman Daya, Pandan/Taman Molek,
Tampoi and Tasek Utara/Teluk Danga.
4.3 Sustainability based on Social Indicators
Fig. 8. Population in MBJB, Accessibility from residential areas to community facilities,
and Happiness index sustainability map
In Figure 8, Map 5 shows the population of JBCC with a total of 555,026 people. The most
populated area with a total of 70,141 people is Tebrau followed by Bandar Dato’ Onn and
Setia Tropika with a total of 60,279 people. Pasir Pelangi is the least populated area with
only 7,852 people. The map also shows that Tebrau is the largest area with a total size
27.24 km2.
Map 5
Map 6
Map 7
14
The accessibility from residential areas to community facilities is determined by proximity
analysis. Map 6 shows that Majidee is the only sustainable planning block with 81%
accessibility. Kempas, Tampoi, Larkin, Daerah Sentral, Pelangi, and Mount Austin/Taman
Daya are categorized as semi-sustainable planning blocks with 50%-80% accessibility to
community facilities. Other planning blocks are classified as not sustainable. Map 7 shows
that the majority of respondents are satisfied with their daily life and the surroundings.
Respondents in Teluk Tebrau, Mount Austin/Taman Daya, and Tebrau feel that they are
partially satisfied with the surroundings. Both maps show that the most socially sustainable
area is Majidee which achieves the highest score for both indicators. Kempas, Tampoi,
Larkin, Pelangi, and Daerah Sentral are classified as semi-sustainable with the highest and
second highest scores for both indicators.
4.4 Sustainability Map Using AHP
The eigenvector is calculated to decide on the importance ranking of sustainability
indicators as explained earlier. Each planning block has its own score of sustainability from
each indicator through the index prescribed in the MurniNet. Importance ranking is then
used to assess the sustainability of urban development of the planning blocks within the
JBCC. Based on the indicators’ eigenvalues, economic sustainability is the most important
dimension to determine sustainability of an area followed by environmental sustainability
and social sustainability (Fig. 9).
Fig. 9. Finalised AHP decision model
Figures 10 and 11 show that Daerah Sentral, Tasek Utara/Teluk Danga, Pelangi and Rinting
have the highest score on the most important indicators. For the second most important
indicator, all planning blocks achieved the highest score. Majidee is the only area that has
the highest score for the third highest ranked indicator. For the fourth indicator, all planning
blocks obtained the highest score while for the next highest ranked indicator shows that
Tasek Utara/Teluk Danga, Tampoi, Pandan/Taman Molek, Bandar Dato’ Onn/Setia
Indicators
Ranking
TR
1st
FA
2nd
AF
3rd
DM
4th
OS
5th
TS
6th
GA
7th
CS
8th
HI
9th
15
Tropika, Mount Austin/Taman Daya and Tebrau are sustainable planning blocks. The
indicator of integrated terminals and stations for public transportation is ranked sixth with
Daerah Sentral having the highest sustainability score. The next indicator is the premises
that are awarded grade ‘A’ status. This indicator shows that only Daerah Sentral is
sustainable compared to other planning blocks. It also indicates that business premises in
JBCC, especially the restaurants, do not achieve the standards specified by the Department
of Health JBCC. Figure 10 also shows that all the planning blocks are sustainable on the
basis of existence of centralized sewerage services. This indicator shows that 82.05% of the
residential areas in JBCC are enjoying sufficient level of centralized sewerage services. The
last ranked indicator is the happiness index whereby all planning blocks, except for
Kangkar Tebrau, are categorized as sustainable. [Happiness index stipulates that majority of
the respondents must be satisfied with their daily life and surroundings.] Kangkar Tebrau,
in particular, is found to be not sustainable.
Fig. 10. Graph of overall sustainability score
16
Fig. 11. Sustainable urban development map
5 Conclusion
Sustainability is a broad concept that encompasses many aspects of the social, economic
and environment. The study demonstrates how suitable indicators can be used for the
assessment of sustainable urban development. Proper selections of SMART indicators are
very important. The use of spatial indicators, with sufficient spatial content provided, can
contribute to a better implementation of assessment of areal sustainability. It can also give
more understanding and interpretation of spatial information by producing to-be-seen map.
From the overall assessment, we can see that the majority of planning blocks located near
city centres such as Daerah Sentral, Pelangi, Teluk Danga, Larkin, Majidee and Tampoi are
sustainable because these planning blocks are areas of people’s attraction. This study also
shows how placement of business premises, recreational areas, community facilities and
roads are important to maintain urban sustainability.
Acknowledgments The authors are grateful and acknowledged those who have assisted
and contributed so extensively to this paper. Especially, we would like to thank the Johor
Bahru City Council (MBJB) who has provided us with the data and information to ensure
the successful completion of the manuscript.
17
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