The rated quality of life in urban areas based on AZP Algorithm, (The Case of Zanjan
City)
Dr. Akbar Asghari Zamani (PhD)
Dept. of Geography and Urban Planning, University of Tabriz,
Shahin Ali Zadeh Zonuzi (Corresponding Author)
M.A. Student, Dept. of Geography and Urban Planning, University of Tabriz
09147581093
Email: [email protected]
Bahman gholiki milan
M.A. Student, Dept. of Geography and Urban Planning, University of Tabriz
Hafez Abdali
M.A. Student, Dept. of Geography and Urban Planning, University of Tabriz
Yaghoob Azimi
M.A. Student, Dept. of Geography and Rural Planning, University of Tabriz
Abstract
In the past decade, with the rapid growth of urbanization and environmental problems caused by
such Environmental Pollution, Traffic, Psychological distress and ets, Quality of life issues
considered by many researchers in psychology, sociology and urban planning, has been
particularly. The purpose of urban development programs in the country, is increasing the quality
of life of all citizens. The first step toward improving the quality of life in urban areas, is identify
and explain the situation in urban areas. This paper is an applied research with a descriptive analytic method. In this study zoning of Zanjan city in terms of quality of life indicators have
been analyzed based on the AZP algorithm. Ten District was formed so that the results reflect
that the pattern of quality of life of Zanjan is distribution pattern. The distribution pattern of
quality of life assessment using the Moran, show normal state the value and distribution of
markers, That is not clustered distribution pattern nor sparse. Among the 10 created districts, the
best condition is related to region that quality of life indicators are averaged over 2038 people
and the worst condition is related to region with 16 people averagely.
Key Words: Quality of life, Districts Zoning, AZP Algorithm, Zanjan City.
Introduction
Quality of urban life including psychological dimensions that takes indicators such as
satisfaction, happiness and security. In some cases, also called social satisfaction. The
environmental aspect is the inclusion of measures such as housing, access to services and
environmental protection. Regarding other aspects including social opportunities, the hopes of
employment, wealth and leisure(Seyfaldini, 2002).
Quality of life as a multidimensional concept and the importance of living in modern societies, in
many scientific fields such as urban planning and design has been penetrated. On topics related
to urban planning, quality of life encompasses a range of indicators. These indicators can be
classified in a large-scale socio-economic and environmental. Infrastructure improvements,
educational, housing, green space and transportation is an indicator of the quality of urban life،In
other words, the quality of life encompasses all aspects of human life in the city(Ghalibaf g et al,
2011, 35).
Quality of life that reflects the level of welfare of the people during the past decade as one of the
main goals of community development, policy director of many countries. "In other words we
can say that the city's quality of life is directly related to the quality. This means that if the
quality of life in the city is good, this is due to the high quality of the environment (Awang,
2009: 161).
So the quality of life of citizens is regarded as one of the elements of sustainable
development(Fahy, 2008: 366).
In general, according to research conducted in the field of quality of life There are two distinct
approaches in different countries. A Scandinavian approach, which is popular in most European
countries And have been emphasized the objective conditions of life and its related indexes And
quality of life is dependent on the satisfaction of basic needs (such as income, employment,
housing, education, etc.) and has emphasized Another approach that is more American approach
to subjective experience and personal expectations of life (eg, job satisfaction, family
satisfaction, a sense of joy, etc. And regarded satisfaction and happiness as the main
indicator(Heydary, 2011,54-55).
Although various interpretations and range of quality of life can be found, but this concept has
not been universally accepted definition . In terms of quality of life, physical and mental wellbeing as a new concept for old people . For others, the term quality of life in general environment
in which people live (eg, pollution and quality of housing) Some people also refer to the
characteristics (such as health and education). . Welfare or the welfare of the people and their
living environment as well as the interpretations that are used to the concept of quality of
life(Rezvani& et al 2009,93).
Distribution utilities contributed to the quality of life of residents in urban areas, so the quality of
life of citizens in urban areas is very important. Therefore, given the importance of quality of
life, the aim of this study was to examine this issue in the area of the city is using AZP algorithm.
In other words, this study sought to identify the scope of the quality of life in the city. In this
way, issues such as zoning, defining stub areas, and zoning covers and in the sources noted. In
order to study and analyze the quality of life in urban areas is considered fundamental
assumption zanjan and In this research is to study and prove it. The main hypothesis of this
study is that it seems In the city of Tabriz in terms of quality of life measures, there was a split
between those areas.
Background Research and Theoretical Investigations
Researchers from different subfields of practical life have been studied since the 1930s. Each of
these researchers have attempted to study the different geographical areas such as cities, states
and nations that have developed on the basis of quality of life measures(Wish,1986).
Beside this group of researchers, WHO, UN, UNDP, international organizations such as the
desired measures have offered either in relation to quality of life. Until now, the sciences have
failed to have a multidimensional approach combines the characteristics of the physical and
social environment to evaluate the design( Van Kamp et al,2003).
Recent studies in the literature on quality of life, shows that a specific conceptual framework
associated with the satisfaction of and There is not a system designed to measure environmental
quality and related aspects and trends( Van Kamp et al,2003).
Algorithm associated with AZP, was developed first by the open Shu, and then
increases(Openshou,1995)
In fact, this algorithm was developed to reduce the problem of variable space(Openshou,1977).
This is the first study in the field of urban planning has been used in the present study.
Research Methodology
The approach used in this study as an exploratory approach combining basic units in the regions
and exchanging these units،Because in many studies, has worked exploitation this methodology.(
Openshou& et al,1979)
And the efforts of researchers at the University of Southampton, UK Hampton software is
developed for solving the problem(Ralfes & et al,2009).
Clustering methods in the same way as zoning techniques are combined with spatial constraints
or boundaries area(Duque et al, 2007).
Following the initial spatial units are combined in the form of regions, districts, clusters so as to
optimize some objective function. The diversity of existing approaches on the issue of zoning in
this area makes it difficult to provide a clear definition However, some features can be noted that
there are many approaches.
All procedures are performed Composition Action geographic areas in a number of areas
simultaneously optimize a particular function. Within a region must be geographically connected
areas (spatial coherence constraints)
No
area
should
be
larger
Each area can only be allocated to a region.
than
the
number
of
areas.
Each
area
must
be
at
least
one
area.
Another characteristic feature of this method is monitoring them. In this respect, we need some
basic knowledge about the composition of such number of areas, the criteria used to combine ,
The objective function (number of times for all, up to a maximum heterogeneity within regions
and maximum homogeneity between regions, within regions compactness or continuity) And
have limited spatial coherence (Duque et al, 2007). Figure 1 shows the existing approaches in
this area:
The algorithm is used in this study for automatic zoning or AZP method that was developed first
by the open shu, and consequently improved(Openshou & et al,1995).
In fact, this algorithm was developed to reduce the problem of variable space(Openshou,1977).
The problem of the automatic classification are described and put forward the proposed
solutions. The basic spatial units can be defined as the smallest toll on the published data (such
as census block data center) And form part of the composition of one or more of the basic units
of spatial. The partition is defined as a set of areas that cover the entire study area, We can x1,
x2, ..., xN of the N n-dimensional vector representing the spatial units called base;
Matrix C (Matrix Vzn¬Hay location) is N * N matrix where each element of it. If the basic
spatial units i and j in the vicinity of the (border) or in or otherwise be subjected to unit area
The aim of combining the N-vector of X in K (as 1,2, ..., K have been identified) that cover the
study
area
in
a
way
that
is
1≤K≤N-1.
Area,
which
is
awarded
Array W category defined as follows:
Each unit of the base space can be allocated to each area. If no other unit in the area is not
owned or j in the matrix C is adjacent to at least one of the members area. Finally, it is assumed
that a model with m independent variables was applied to the data:
The objective function Defined to measure the performance of each of the possible
combinations of base units in the area based on the model and the predefined. As a result, can be
expected by optimizing this function, the optimal scheduling. The function is a scalar function of
the independent variable and fixed variable. An example of function-is a measure of goodness of
fit of a model. As a result of the optimization function can be achieved by a combination of parts
that minimize effect MAUP. It involves finding optimum combination for zoning is constant so
that:
Usually dependence between p and the data generated by different compounds. The
interactions between parameters of the model and the various partition that is characteristic of the
intrinsic spatial modeling.
Under this option, the general form of the problem of optimal scheduling is as follows:
While that is. Due to the linear parameter estimation techniques, along with constant changes
also altered the P-W compounds. Which can result in extremely complex. In conventional
studies, where the independent variable for fixed amounts and only once-was estimated. Here
again estimated for every change in ingredients . . Solving this problem in the context of the
zoning system can be created by combining the model to optimize (Openshou,1977).
Solution by the open shu and Rao (1995) presented a more tangible form are as follows:
The basic algorithm is the basic unit of N input (census block, neighborhood layout, counties,
etc.) starts. The basic units are a1 through aN. . Implementation process includes the following
steps:
Step One: Create an initial random combinations of basic units of input into output zone Z1 to
ZM M so that all of the parts are connected together And if M <N is true, and each unit is
assigned to only one area. Objective function value is calculated for the initial composition.
Second stage: a District (zm) of primary random set is randomly selected and then a list of all
the basic units which have a common border But not covered within that area, provided that it
has named B, and its members aB1 aBn. Figure 2 z5 area has been selected as zm and have all
adjacent basic units of B List.
Third stage: the first one was randomly selected from list B (aB12) are distinct.
Step Fourth Regional which is the unit belongs to the set (z7) and comes with a clear zq.
Step Fifth If other units are connected wholly owned zq start the sixth stage. Otherwise, ) is
returned the basic unit of the Regional Selective owned it (z7 and the process begins again for
the third stage. In Figure 2 aB12 separate from zq does not disappear connection or the within
continuity .
Step Sixth aB12 units assigned to the zm and the objective function value is computed for this
new compound.
Step Seventh: If the calculated value of the objective function is greater than that of the first
stage starts eighth stage , Otherwise the classification is done before it is returned to the initial
state, the algorithm starts from the third stage.
Eighth step: Now that improves the objective function B list has expanded to include all adjacent
primary units are selected zm aB12 belonging to B will be added to the list. If an empty list is not
returned to third stage, otherwise the ninth stage begins .
The ninth stage: When you list all the primary units surrounding area comes zm finished second
stage is performed.
Step Ten: first to eighth steps until convergence algorithm that improves the objective function
value is less than a specified tolerance, will be implemented.
Figure (1) the algorithm AZP. (Ralfs and others, 2009)
First stage
Secend stage
Third stage and fourth stage,
the fifth and sixth
The seventh and eighth stages
This algorithm is implemented in a local search process in the primary units,and Registration
change these units until obtaining the best value for the objective function. While the list of
global search algorithms to perform all movements are created for the M zone, and choose the
best of them. This type of search is less efficient than AZP because of the large number of
formats zoning designation of the primary unit must be assessed.(Openshou & et al,1995).
Because of The local search algorithm to solve the problem may be a problem and can not solve
the problem. On the other hand, the ability to solve the problem is reduced by increasing the ratio
N / M and irregularity in the size and shape of the primary units. The main issue is the issue of
zoning, the objective function is defined; Because that is the kind of restrictions we impose on
the data. Zoning systems are the discoverer of spatial patterns and pattern discovery depends on
the Optimal objective function. AZP algorithm has the ability to exercise any function. For
example we can Mentioned functions that can be extracted directly from the data (Sum of
squared deviations from the mean area) or functions that reflect the goodness of fit of the model
is applied to data. (Linear regression model fitting, the performance of spatial interactions
models). It is very important ability optimize any function because of creating this algorithm
there are three goals. : 1) identify the combination of statistical data and various models by
maximizing and minimizing the amount of variables or parameters of the model are
systematically changing the objective function. 2) To confirm that the effects of MAUP is
intrinsic and results of all studies influences on the combined .3) Above all, the foundation and
basis for the development of new approaches to solving this problem is to combine the data. In
many studies, the hexagonal lattice is used as the basic unit for combining the original data ،
Because every once in a hexagonal grid can be re-established as the exact same coordinates
because the its boundaries do not change over time. On the other hand it is extremely important
to select the base unit to avoid bias in the data fusion in larger spatial units(Sable & et al, 2012).
Figure (2) the basis units for the combined data obtained based on the hexagonal lattice
Drawing: The authors
To select parameters in this step, it can be noted that, taking into account criteria such as the
availability of information, the appropriateness of the methods of planning, comprehensiveness,
and all of the inclusion, selection of indicators were in table (1) are mentioned . . Parameters
involved in quality of life after combined digital land use layer (the layer effects Spot) and
blocks of data (in the form of a layer of surface effects) in a hexagonal lattice with the analysis
of overlaps (Intersect) summarized and connecting the summary of the hexagonal grid, was
calculated for each cell. Principal components analysis deals with eexplanation the structure of
the variance covariance a linear combination of the original variables. The overall objectives are:
Reduce the size of the data and their interpretation (niromand, 1378, p 431). Principal
component analysis in order to maximize the sum of squares between them. Weights assigned
depends to the indicators by the first factor, the correlation between indicators, so that the index
is more correlated with other indicators also belongs in the upper weight (Kalantary, 1391 .: 64).
Principal component analysis is used in two cases: reducing the number of indicators and
determining importance.
Table (1) table of indicators used in relation to Zoning quality of life in zanjan city
The following indicators
Indicators
Access to health center, ownership of land for housing, the
Physical
rental housing, private housing rates, the average area of
the residential components, building type of materials,
quality of construction, type of communications network
infrastructure, health care centers, number of schools
Literacy rate, illiteracy rate, sports facilities, arts and
Social
cultural facilities
Employment rates, unemployment rates, average land Economic
prices, The amount income
Source: Detailed plan for zanjan city, the role of Consulting Engineers, 1390
Solidarity within the area can be measured intra-class correlation directly from this regional .
Which equals:
M is the number of surface units, the average value per units surface area per unit value of g, the
proportion of the variable in the class (for primary level) k and k belong to the same level of g is
the loop variable(Sable & et al, 2012).
This indicator shows the proportion of variance between groups to the variance within a set.
Studies have shown that if the IAC> 0.5, the homogeneity within regions is desired) Kvkyng and
others, 2011: Grid and Anandr, 2009). Another criteria is that the compression ratio of the square
of the area of the region will be achieved. The following:
and A is the area of K q. This amounts to an area of a circle is equal to 1. Finally, using Moran's
I statistic for spatial distribution of components was investigated. Moran statistic values between
+1 and -1 is variable. Value of -1 indicates a scattered distribution pattern of +1 and 0 indicating
equal distribution of cluster distribution is random.
Figure (3) the classification of AZP algorithm based on the land use map of zanjan city
Drawing: The authors
Figure (4) zoning map of zanjan city in terms of quality of life scales
Drawing: The authors
The survey was addressed to the Zoning quality of life scales in zanjan city, as in the map
number (3) is shown in zanjan 10 city districts that are homogeneous in terms of quality of life
scales in the no. 4 shows the spatial structure of the region. . The underlying assumption is that
the index is created in the areas where the quality of life in zanjan city, how have been
distributed, and how many people are on average of the indices, which is the best Regional there
is an average of the indices are in 2038, and the Regional worst case is that the indices are an
average of 16 people. It also uses the Average Nearest Neighbor tool in ARC GIS to assess the
distribution and deployment zones created in the city was discussed in Figure 5 shows a graph
indicating a pattern of areas that create areas of AZP algorithm, which drew a diagram of the Z
Score 912.861 is produced, indicating a cluster of over-the-regions is created.
Map No. (5) Location and land use maps in terms of quality of life measures Low density
areas and crowded
Drawing: The authors
According to Chart No. 5. Position indicator and low-density and crowded land use areas and is
growing in terms of quality of life measures According to Figure 5, the area that is best in terms
of quality of life measures is located in the central part of zanjan city. And in fact been in a
position to distribute and distribution of services and facilities in good condition because it is one
of the older parts of Zanjan. , And the arteries of communication and per capita residential and
service is good condition And one count of Zanjan affluent areas, but due to the low density of
Figure 5 in terms of quality of life measures are not in good condition and The range is located
on the outskirts of town is like a worn-out tissues and biological complexes in this area most of
the informal settlements And For this reason, the service is poor municipalities and other
stakeholders in the area and the area of industrial and workshop applications is more inclusive. ,
An area that is growing in Figure 5 shows the position of the city of Zanjan is located in an area
where a new town was built And more middle-class society in its place. And even though some
of these areas are located in distressed areas But most of these parts are new towns that are
becoming the underlying infrastructure and services is growing. That value z-score obtained is
very high :912.8, which represents a very dense and scattered pattern of distribution established
in areas of the city is based on indicators of quality of life.
Figure (5) distribution areas graph are created using algorithms AZP
Drawing: The authors
Figure (6) results from the zoning Moran base AZP
(employment rates, literacy rates and land prices)
Drawing: The authors
Research continues to evaluate the distribution and dispersion of indicators that represent created
the quality of life in areas that is used from the Moran statistic. That chart above shows the
distribution pattern of the scales of the graphs Khv a series of numbers to headers z-score and zscore obtained p- value That much closer to the number one distribution is Random phenomena
And no matter how the number is closer to0 is the cluster distribution phenomena, but the zscore obtained is closer to a number greater than one. Phenomena are more dispersed and more
dispersed distribution situations and the p-value indicates a significant amount of statistical
analysis is that the value is the value obtained is closer to 0. And is smaller than 0.05. Statistical
analysis of the phenomena under study is significantly higher than the value obtained is greater
than the level of analysis is significant. That z-score obtained for indicators such as employment
rates, literacy rates and land prices and to arrange 0.518- 0.553- and 0.560- that all indexes are
created in areas not cluster and were not distributed, but they are balanced and random.
Conclusions
This study showed that the new method can be used to solve problems systematically, within the
space of the hidden patterns of social, economic and physical That are representative and show
the satisfaction and quality of life in the city's. The zoning method can detect spatial patterns of
surface and spatial analysis seems to have been an efficient tool to help planners and
geographers. The present study examined the zoning for the city, which in terms of quality of life
indicators among the 10 districts created by the region in terms of quality of life, these indicators
are averaged over 2038 people And the worst part is out of 16 of these indicators and patterns are
created in areas of zanjan city by using AZP algorithm is a cluster. Then be explored to assess
the distribution pattern zones created using Azp algorithms That distribution pattern and spatial
correlation dense areas were created And continue to investigate the distribution pattern
indicators used in the study were evaluated using the Moran statistic That measures are not
clustered distribution pattern was rather sparse, but also a random. In fact, the z-score obtained
for some quality of life measures employment rates, literacy rates, land prices are respectively 0.56 and -0.51 and 0.05, which indicates a relatively balanced distribution pattern in the
distribution of indicators. It is recommended that future studies are also discussed other aspects
of zoning and the ability to measure them Until can be the best method to determine areas of
program-planning zoning in terms of quality of life scales in urban living affect persons So as not
Until All supplies and services to the people of the city concentrated in certain spots and some
areas are in denial. All citizens have equal access to all amenities and to prevent the creation of a
class should be the top priority of sustainable development and urban planners.
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