The study areas, consisting of the cities of Hanoi, Hartford, Nagoya and Shanghai, were examined using Landsat and ASTER data from 1975 to 2003.. Conversely, the new urban areas of Hanoi
Trang 1Contents lists available atScienceDirect Landscape and Urban Planning
j o u r n a l h o m e p a g e :w w w e l s e v i e r c o m / l o c a t e / l a n d u r b p l a n
A case study on the relation between city planning and urban growth using
remote sensing and spatial metrics
a Department of Earth and Environmental Sciences, Graduate School of Environmental Studies, Nagoya University, Japan
b Department of Geography, Hanoi University of Science, Viet Nam National University, Viet Nam
a r t i c l e i n f o
Article history:
Received 23 February 2010
Received in revised form
23 December 2010
Accepted 28 December 2010
Keywords:
Urbanization
Hanoi
Landsat
Image processing
Spatial metrics
a b s t r a c t
Despite the unprecedented rate of urbanization around the world, information regarding land use plan-ning and management is not updated frequently enough to accurately track this urban change In order to monitor changes in the urban environment, an understanding of the change in patterns of urban develop-ment over time is becoming increasingly important The objective of this study is to explore an approach for combining remote sensing and spatial metrics to monitor urbanization, and investigate the relation-ship between urbanization and urban land use plans The study areas, consisting of the cities of Hanoi, Hartford, Nagoya and Shanghai, were examined using Landsat and ASTER data from 1975 to 2003 In this study a program based on the PLADJ spatial metric was undertaken to produce urban growth maps Then, FRAGSTATS was used to evaluate the characteristics of urban composition The results showed that the urban core of Nagoya changed moderately over time Shanghai had a high population density, and satel-lite towns absorbed potential suburban development Hartford exhibited a spread out pattern of urban development with a high concentration of settlement in the suburb Conversely, the new urban areas
of Hanoi developed rapidly along major transportation routes, resulting in urban development in Hanoi assuming an unusual pattern The combined approach of remote sensing and spatial metrics provides local city planners with valuable information that can be used to better understand the impacts of urban planning policies in urban areas, particularly in Hanoi
© 2011 Elsevier B.V All rights reserved
1 Introduction
The population of the world is on the verge of shifting from
being predominantly rural to urban As of 2008, more than half
of the world’s human population has resided in urban areas, and
by 2030, urban inhabitants will account for approximately 60%
of the world’s population (Waibel, 1995) Urbanization can be
defined as the changes that occur in the territorial and
socio-economic progress of an area, including the general transformation
of land cover/use categories from being non-developed to
devel-oped (Weber, 2001) The rapid growth of the urban population
has occurred in response to increased urban migration as people
search for better jobs and improved living conditions Historically,
urban immigration has increased at rates that have exceed those
of infrastructure development in the destination cities, resulting in
immigrants being unable to find suitable employment
opportuni-ties and subsequently becoming part of the urban poor This rapid
∗ Corresponding author Tel.: +81 52 789 3023; fax: +81 52 789 2523.
E-mail addresses: haialas@yahoo.com (H.M Pham), yasushi@nagoya-u.jp
(Y Yamaguchi), qthanh.bui@gmail.com (T.Q Bui).
increase in urbanization and the concomitant effect that it has on land use means that it is becoming increasingly for city planners to adopt appropriate sustainable land use plans
Planning and managing urban spaces depends on knowledge
of the underlying driving forces, combined with the chronology and impacts of urbanization (Klosterman, 1999) City planners, economists and resource managers therefore need advanced meth-ods and a comprehensive knowledge of the cities under their jurisdiction to make the informed decisions necessary to guide sustainable development in rapidly changing urban environments Remote sensing provides spatially consistent coverage of large areas with both high spatial detail and temporal frequency, which
is useful for examining historical time series (Jensen and Cowen,
1999) Moreover, remote sensing data is effective to monitor the land use change in areas, especially where information on land use management is inconsistent and insufficient For example, recently the economic development in Hanoi impacts the land use change in the suburb occurring rapidly With the current land use map is updated every 5 years, local land use managers have not enough information to monitor land use change of Hanoi There-fore, with increased availability and improved multi-spatial and multi-temporal resolution, remote sensing can now be applied to 0169-2046/$ – see front matter © 2011 Elsevier B.V All rights reserved.
Trang 2Fig 1 Study areas in the same scale.
monitor and analyze urban expansion and land use changes in a
timely and cost-effective manner
On the other hand, spatial metrics are measurements derived
from the digital analysis of thematic maps to show spatial
hetero-geneity at a specific scale and resolution (Herold et al., 2002) Such
analyses provide quantitative characterizations of the spatial
com-position and configurations of habitat or land cover types, and can
be used to track changes in landscape patterns over time (Henebry
and Goodin, 2002) The combination of remote sensing and spatial
metrics can provide spatially consistent and detailed information
about urban structure and change, permitting more accurate
rep-resentation and understanding of urban growth processes (Deng
et al., 2009)
The objective of this study was to validate the applicability
of spatial metrics for characterizing urbanization in the cities of
Hanoi (Vietnam), Nagoya (Japan), Hartford (Connecticut, USA), and
Shanghai (China) In the previous study, we detected the
expan-sion of Hanoi by using an image classification method (Pham and
Yamaguchi, 2007) The results visually showed the urban change of
Hanoi from 1975 to 2003 However, in order to have a better
under-standing about the history of Hanoi’s development process, the
local land use planners raised the questions of quantifying where
and when the urbanization occurred in the same period We
devel-oped the primary research to new direction, in which the result
not only answered the questions of the local land use planners,
but also provided various examples of urban change patterns as
well as the policies to manage these changes Nagoya, Hartford, and
Shanghai were chosen because of some reasons Firstly, the study
wanted to compare the urban change of Hanoi and other cities in
different countries Secondly, these urban areas developed very fast
in the same period from 1975 to 2003 Moreover, the study areas
have a particular relationship in terms of the topography The rivers
running inside these cities as Red River (Hanoi), Connecticut River
(Hartford), and Hangpu River (Shanghai) separate them to East and
the West parts The successful land use planning of Hartford and
Shanghais will be valuable for Hanoi to solve the gap of the urban
development process between the West and the East of Hanoi due
to the effect of the Red River While the primary focus was on urban
development in Hanoi, we expected that the analysis of
urbaniza-tion patterns in other cities is considered useful not only for Hanoi
but also for Vietnamese policy makers and related officials to have
appropriated local land use plans
The surface land cover maps of the four cities were generated
from satellite images using the classification methods described in
Pham and Yamaguchi (2007)(Section3.1) The ‘percentage of like
adjacencies’ (PLADJ) was then used to quantify urban
fragmenta-tion and to generate urban change pattern maps (Secfragmenta-tion3.2.1)
The statistical program FRAGSTATS (McGarigal, 2002) was used
to perform the PLADJ analysis (Section3.2.2) Finally, the urban growth pattern maps and the FRAGSTATS results were used to ana-lyze urban growth within the context of urban planning (Section
4) The results of this study are expected to assist local officials in their understanding of urban dynamics, and in so doing, promote future sustainable growth
2 Study area and input data
2.1 Study area Hanoi is the capital of the Socialist Republic of Vietnam (Fig 1a)
It is an ancient city located on the banks of the Red River and retains the Old Quarter, which has a history that spans 2000 years and represents the eternal soul of the city Hanoi was originally planned as a grid, with areas small residential houses located along narrow streets In 2005, Hanoi covered approxi-mately 921 km2(the study area covers 400 km2) and the population numbered approximately 3.3 million (Hanoi Statistical Yearbook,
2005) Recently, this high population density in the city centre has received considerable attention given that it is causing con-siderable pressure on the available land (Pham and Yamaguchi,
2007)
Nagoya (Fig 1b) is an active business centre in Japan Located on the Pacific coast in the Ch ¯ubu region with the population of over 2.2 million, the city has the greatest concentration of manufacturing industries in the country (http://en.wikipedia.org/wiki/Nagoya) The urban changes in Nagoya are evident in the considerable sub-urban sprawl associated of the city The city is unique in that there are large houses on lots that are generally larger than those found in other urban areas of Japan In this respect, the city appears to have followed the Western model more closely than any of the other large urban centres in Japan (Cox, 2003)
With an urban population of 2 million people, Greater Hardford (Fig 1c) located on the Connecticut River is the largest metropoli-tan area in Connecticut The rapid construction of the highways near the periphery of the city the late 1950s had a direct impact on the development of the city More recently, Hartford has become known as the “Insurance Capital of the World”, since the head-quarters of many of the world’s insurance companies are located there After years of relative stagnation, Hartford has recently begun
to attract new development, especially in the downtown areas (http://en.wikipedia.org/wiki/Greater Hartford)
With the population over 17 million, Shanghai (Fig 1d) is one of the largest and most prosperous cities in China (Haixiao,
2000) The city is located at the mouth of the Yangtze River on
Trang 3China’s eastern coast Since the Chinese government adopted the
economic reforms of 1978, Shanghai has undergone dramatic
eco-nomic growth and the increase in the population density of the
inner city has resulted in extensive pollution of the city
envi-ronment (http://en.wikipedia.org/wiki/Shanghai) One of the most
notable achievements of the city’s urban plan has been the
con-struction of the new Pudong New Area, which is located on the east
of the Hangpu River, because it promotes the development away
from the city centre In order to satisfy the transport demands of an
estimated 70 million visitors to the Shanghai 2010 Expo, a
consid-erable amount of investment is currently being channelled into the
development of a transport infrastructure both within and between
cities in the region
2.2 Data sources
Sets of multi-spectral and multi-temporal satellite data for
Hanoi, Nagoya, Hartford, and Shanghai were obtained for the
years 1975–2003 from the Tropical Rain Forest Information
Cen-tre, Michigan State University, USA (Table 1) Cloud cover was less
than 10% in all images and the visible and near infrared (NIR) bands
used for data processing were rectified geometrically to a common
Universal Transverse Mercator coordinate system
Table 1
Data sources.
Hanoi 1975(MSS), 1984(MSS), 1992(TM), 2001(ASTER), 2003(ETM+) Nagoya 1975(MSS), 1985(TM), 1996(TM), 2002(ETM+)
Hartford 1979(MSS), 1989(TM), 2002(ETM+) Shanghai 1979(MSS), 1989(TM), 2001(ETM+)
3 Methodology
3.1 Urban area detection This study used mid-resolution remote sensing data (ASTER
15 m and LANDSAT 30 m) All the images were then resampled to the spatial resolution of 15 m We decided to resample the data to the spatial resolution of 15 m because of the relationship between the size of a pixel and the average size of houses in Hanoi, Nagoya, and Shanghai With the average size of houses less than 200 m2,
15 m resolution data (one pixel in the image covers 225 m2) was expected to be a suitable resolution to study the urban change in these four cities
However, detection of the edges of urban areas using mid-resolution data, such as ASTER and Landsat imagery produced a mixel problem In this study, the mix-pixel problem arises through
Trang 4the mixing of three components, such as urban, vegetation and
water land use types occurring within a given pixel In order to
resolve this problem, this study applied the classification method
ofPham and Yamaguchi (2007)to classify the urban areas This
classification method is effective because it integrates the results
of the image classification, the soil index, and the NIR band to detect
the urban areas while concurrently resolving the mixel problem
Image classification methods, such as this supervised
maximum-likelihood method, are generally referred to as
conven-tional change detection methods (Duong et al., 2002) While the
obtained results successfully detected the urban area, the
occur-rence of the mixel problem remained In addition, although the
soil index has the advantage of being able to distinguish between
soil and water, it is difficult to differentiate between urban and
fallow areas The soil index used in this study was derived from the
vegetation-soil-water (VSW) index ofYamagata et al (1997) By
combining the two aforementioned supervision methods we were
able to delineate the urban areas and reduce the relative
disadvan-tages associated with each of the methods Based on the results,
the NIR band was then used to mask the contribution of water
bodies by diminishing the contribution of water to urban area
detection Then, manually defined visual interpretation thresholds
were employed to extract the urban areas and to reduce the extent
of the areas that were affected by the mixel problem (Pham and
Yamaguchi, 2007) The results of this integration method were
validated against the reference data sources such as land use maps
published in 2002 for Hanoi and Nagoya Comparison between
the results of classification, and reference data for certain sample
sites was conducted visually and interpreted quantitatively The
mixel problem was thus considerably reduced and the integration
method provided a reliable approach for the detection of urban
areas Finally, the results were classified into three categories:
urban, non-urban and water (Fig 2)
3.2 Spatial metric calculations
3.2.1 The percentage like of adjacency (PLADJ)
Although this study was particularly interested in the
quantita-tive assessment of the spatial characteristics and change patterns
associated with urbanization, these data cannot be extracted
directly from classification results The spatial structure of urban
areas in this study was therefore considered to refer to the spatial
distribution of distinct urban areas on a thematic map Spatial
met-rics can be computed as patch-based indices (e.g size, shape, edge
length, patch, density, fractal dimension) or as pixel-based indices
(e.g contagion) computed for all pixels in a patch A patch refers to a
homogenous region of a specific landscape property, such as a park
or residential zone (Anderson et al., 1976) To measure the degree of
aggregation of patch types, this study used the PLADJ metric
devel-oped byO’Neill et al (1998)to analyze the urban growth maps
generated PLADJ, which is widely used because of its intuitiveness
and computational simplicity (Noda and Yamaguchi, 2008), can be
defined as:
PLADJ=
m
i=1gii
m
i=1
m
where giiis the number of like adjacencies between pixels of patch
type i, gikis the number of adjacencies between pixels of patch
types i and k, and m is the number of pixels in the satellite image
Firstly, a 5× 5-pixel-moving window was used to compute the
percentage of urban fragmentation for the centre cell of the window
(Fig 3) PLADJ moves randomly conditional probabilities through
the pixels in the moving window, with each calculation
involv-ing like adjacencies between four pixels; orthogonal cells were
counted, but diagonal cells were ignored PLADJ equals zero when
Fig 3 Example of counting PLADJ.
a maximum disaggregated pattern occurs in the current class or when there are no like adjacencies, and equals 100 when the com-puted areas cover a single class or all adjacencies are in the same class (maximally contagious) Low PLADJ percentages imply that the extent of fragmentation is high or that there are many individual urban units on the map In order to discriminate between devel-oped (urban) and non-develdevel-oped (non-urban) pixels, a positive PLADJ value was assigned to the centre pixel if it was originally non-developed and conversely, a negative PLADJ value was assigned to the centre pixel if it was originally developed Secondly, to better classify the spatial heterogeneity of urban areas, a PLADJ thresh-old was determined This threshthresh-old was applied to the analysis of each city by visual comparison of the extent of urban fragmenta-tion in built-up areas on the PLADJ map with it in the land use plan map or available reference data source in the same periods Finally, a pixel was considered ‘fragmented’ when its PLADJ value was less than 70%, ‘aggregated’ when its value ranged from 70%
to 99%, and ‘interior’ when its value equalled 100%.Fig 4shows
an example of the PLADJ metric and illustrates the heterogeneity
of urban patches in southern Hanoi The interior developed area, which appears homogeneous (yellow) in the central region, is the urban core The aggregated (developed) area connects the urban core to the suburban areas
Fig 4 Urban heterogeneity in southern Hanoi in 2003 calculated by PLADJ.
Trang 5Fig 5 Urban growth pattern maps of Hanoi, Nagoya, Hartford, and Shanghai.
In order to visualise change patterns based on the PLADJ metric
results, this study utilised the landscape transformation scheme
presented by Forman (1995) Using this method, three urban
growth patterns were adopted to describe and map urban sprawl:
infill, expansion, and outlying The infill pattern is mostly
encoun-tered inside the existing developed areas, while the expansion
pattern dominates the urban fringe The outlying pattern tends to
occur some distance from the existing developed areas
The result is a series of maps illustrating the changes in the urban
structure of four cities from 1975 to 2003, which are discussed
fur-ther in Section4(Fig 5) These maps provide valuable reference
information for city planners because they can be used to illustrate
the historical evolution of a particular urban area However, for
scientific purposes, information derived solely from urban change maps does not adequately explain the forces driving urbanization and additional information is required to link the spatial structure
of a city with the urban change process
3.2.2 Metric parameters
In this study, six class-level spatial metrics in the FRAGSTATS spatial analysis program (McGarigal, 2002) were selected to char-acterize the urban composition features of a particular urban class (Table 2) Different spatial metrics in FRAGSTATS provide different information on urban growth The class area (CA) metric describes the growth of urban areas The number of urban patches (NP) mea-sures the extent of subdivisions of urban areas NP is high when urban expansion remains constant but fragmentation increases The edge density (ED) is a measure of total length of edges of the urban patches The largest patch index (LPI) is the percentage of land occupied by a defined urban area as a function of the total urban area in a region LPI is 100 when the entire urban class con-sists of a single urban patch The mean nearest neighbour distance (MNN) is a measure of the open space between individual urban patches MNN is low when the distance between urban patches is high The area weighted mean patch fractal dimension (AWMPFD)
is a measure of patch shape complexity If the patches are more complex and fragmented, the parameter increases to a higher frac-tal dimension In this study, the increase in the number of individual patches (NP) due to the expansion of the urban area was closely correlated to the increase in the length of the urban boundary (ED) The MNN measures distance between the individual urban patches and decreases if these urban patches coalesce The largest patch index (LPI) increases when urban areas become more aggregated and integrated with the urban cores.Fig 6shows the variations in these parameters during the development of the four cities over the last 30 years (1975–2003) The original metric values of the class area (CA) and the length of the urban boundary (ED) were divided
by 1000 so that they would fit on the scale of the y-axis
4 Result and discussion
The urban land use plan for Shanghai was designed to trans-form the city from being mono-centric to a multi-centric metropolis
in order to decentralize the population and economic activities (Haixiao, 2000) As reported by Haixiao, satellite towns have been planned so that the suburbs will absorb the development poten-tial of the central city of Shanghai As can be seen inFig 2, the satellite towns of Shanghai have had a significant impact on the progress of urban growth and urbanization in the city Based on the slight increase in the NP (Fig 6), the development of Shanghai over the period 1979–1989 was characterized by moderate growth
of the urban patches While the central urban area changed slowly, there was a rapid increase in size of the satellite towns (Fig 2b4) This observation suggests that, by restricting the development of existing urban areas, the government promoted the development
of metropolitan areas on the city fringe Furthermore, the mass transport lines that were constructed to link the satellite towns
to the urban core from 1989 to 2001 may have been a key fac-tor contributing to the rapid expansion of the urban areas in the region The spatial characteristics of the urban areas of Shanghai had become increasingly complex by 2001, which correlated with peak LPI and low MNN values (Fig 6) However, the peak in the AWMPFD observed in 2001 indicated an increase in the fragmenta-tion of the urban areas, possibly due to the existence of open spaces inside the urbanized areas In addition, the dramatic increase in the LPI values implies increased development of the urban areas situ-ated to the east of the Hangpu River (Fig 5) The new area of Pudong was also observed to expand rapidly from 1989 to 2001 (Fig 5)
At the time, a large number of local inhabitants were displaced
Trang 6Table 2
Description of the spatial metrics used in this study ( McGarigal, 2002 ).
CA-Class area CA equals the sum of the areas (m 2 ) of all urban patches, divided
by 10,000 (to convert to hectares).
Hectare CA > 0, no limit NP-Number of urban patches NP equals the number of urban patches in the landscape None NP ≥ 1, no limit ED-Edge density ED equals the sum of length (m) of all edge segment involving the
urban patch type, divided by the total landscape area (m 2 ), multiplied by 10,000 (to convert to hectares).
Metres per Hectare ED ≥ 0, no limit
LPI-Largest patch index LPI equals the area (m 2 ) of the largest patch of the corresponding
patch type divided by total area covered by urban land type (m 2 ), multiplied by 100 (to convert to percentage).
Percent 0 < LPI ≤ 100
MNN-Euclidean mean nearest neighbour distance MNN equals the distance (m) mean value over all urban patches to
the nearest neighbouring urban patch.
Metres MNN > 0, no limit AWMPFD-Area weighted mean patch fractal dimension Area weight mean value of the fractal dimension values of all
urban patches, the fractal dimension of a patch equals two times the logarithm of patch perimeter (m) divided by the logarithm of patch area (m 2 ).
None 1 ≤ AWMPFD ≤ 2
and farmland (non-developed areas) was converted to urban use;
however, the improved infrastructure and transportation improved
urban living standards which contrasted with that in the central
part of the city
The urban structure of Hartford follows the Concentric Zone
Model (Robson, 1969) The urban areas were classified to zones,
such as the Central Business District (in the central part of the city),
Transitional Zone, Working Class Zone, Residential Zone, and
Com-muter Zone The Transitional Zone includes factories, Working Class
Zone includes single family tenements, Residential Zone includes
single family homes, yards and garages, and the Commuter Zone
consists of the suburbs As opposed to focussing on the expansion
of satellite towns (as in Shanghai), urbanization in Hartford was
characterized by the outlying pattern from 1975 to 1989 (Fig 5),
with pronounced urban development occurring on both sides of
the Connecticut River Most of this new development activity arose
through the conversion of vacant land along the periphery of the
city near the major transportation routes and far away from the
city centre The rapid development of this outlying development
pattern around the city led to an increase in the size of the urban
area, which is illustrated by an increase in the both the CA and the
ED The new urban areas subsequently expanded along the major
transportation lines toward the city centre, such that the centre
assumed a more compact shape in 1989 with LPI peaking in 2002
From 1989 onward, the rate of urbanization in Hartford started
declining, which has NP value that was decreasing Although the
urban growth of Hartford declined and the developed areas became
more compact, outlying development occurred in the suburbs;
this urban development occurring beyond the existing urban areas
explains why the minimum distance between the urban patches
had decreased drastically by 2002
In contrast to Shanghai and Hartford, the rate urbanization in
Nagoya was moderate over time, with most urban change
occur-ring along the urban foccur-ringe (Fig 5) In Japan, urban growth is subject
to the City Planning Act which was promulgated in 1968 The Act
categorises urban areas as one of two types: urbanization
promo-tion zones, consisting of existing urban areas or areas that have
already been earmarked for development in the next 10 years, and
urbanization control zones, consisting of areas such as farmland
where urbanization should be constrained (Saizen et al., 2006) This
land use plan was expected to create a comfortable and functional
urban environment while controlling suburban sprawl through the
promoting the ordered development of urban areas From 1975 to
1985, the urban areas expanded on both sides of the Kiso River in
the western areas of the city While urban development usually
occurs through the conversion of farmland or forest to residential
use, the urban development in Nagoya was restricted by the
appli-cation of the City Planning Act which prohibits the conversion of
agricultural land in the urbanization control zone The expansion and occurrence of outlying development in the western areas of the city resulted in the size of the urban area increasing, which was indicated by a peak in the CA in conjunction with an increase in the ED The urban growth of Nagoya started declining from 1985; instead, from 1985 to 1996, urbanization shifted to the eastern part of the city In other words, renewed urban development in Nagoya occurred in areas that were already urbanized In addition, the pattern of urban development in Nagoya created open spaces surrounded by developed urban areas The occurrence of this infill development is thought to have arisen in response to the prob-lems caused by the patterns of urban expansion preceding 2002 The LPI peak observed in 2002 correlated with a decrease in the
NP and AWMPFD, indicating that the rate of urbanization slowed down and became more homogeneous In the urban growth map (Fig 5), it can be seen that almost all of the vacant land earmarked for future development in the city of Nagoya is used, implying that the urban growth of Nagoya is likely to decrease in the future All four of the cities examined in this study have rivers flow-ing through their city centres Due to the marked difference in socio-economic conditions, the urbanization of Hanoi is consider-ably different from that observed in Hartford, Nagoya and Shanghai The land use plan in Hanoi followed the Hanoi Land Use Master Plan, which was officially promulgated in June 1998 According to the plan, urban areas will be developed in Concentric Belts, with
a priority on the areas to the west, south-west, and north of the Red River by 2020 (http://www.hanoi.gov.vn/) The urban growth under the Hanoi Land Use Master Plan has been influenced by economic development We can see inFig 2that before the “Doi Moi” economic reforms of 1986, there was no noticeable urban sprawl in Hanoi “Doi Moi” is the name given to the economic reforms initiated in Vietnam in 1986 for a “socialist-oriented mar-ket economy (http://en.wikipedia.org/wiki/Doi Moi) In 1975, the urban area was small and fragmented (Fig 2), which is corrobo-rated by the small LPI and NP values (Fig 6) By 1984, the NP had increased slightly in concert with an increase in the AWMPFD, indi-cating that this was when Hanoi’s urban areas started to diffuse outward Since the launch of the “Doi Moi” reforms and the adop-tion of a market-oriented economy in 1986, the economy of the city has undergone remarkable changes, including an increase in the population of the city by approximately 500,000 people from
1984 to 1992 (Hanoi Statistical Yearbook, 2005) and an expansion
of urban land use by 21,000 ha (Pham and Yamaguchi, 2007) More-over, the majority of new immigrants lived in densely populated informal settlements adjacent to industrial zones, transport hubs, and major markets along the city fringes Within the context of offi-cial housing policy, these areas were considered to be illegal urban areas (Do, 2007).Fig 2b1 and c1 shows urban development in the
Trang 71
10
100
1000
10000
Hartford
1
10
100
1000
10000
Hanoi Hanoi
Nagoya
1
10
100
1000
10000
1
10
100
1000
10000
Shanghai Shanghai
Fig 6 Fluctuation of six spatial parameters using FRAGSTATS (refer toTable 2 for
parameter descriptions).
urban centres over time, the 1984 and 1992 maps show that urban
expansion has occurred in two directions, one to the west and a
lin-ear branch-type to the south While expansion to the west was the
predominant trend, the construction of the first national highway
to the south of the city resulted in the linear expansion of the city to
the south In both cases, there was an increase in the development
of urbanized patches occurred some distance from the urban core; a
rise in the ED and a corresponding decrease in MNN confirmed this
trend At this time, the urbanization of Hanoi was also characterized
by the development of urban areas along newly constructed roads
and highways The area of the inner city transportation
infrastruc-ture increased from approximately 3000 ha in 1975 to 5000 ha in
1992 (Pham and Yamaguchi, 2007), implying that new road
con-struction was a powerful catalyst for the urbanization to the west
and south of the city The rate of urbanization decreased after 1992 due to the economic recession in Vietnam and the 1997 economic crisis in Southeast Asia (Berg et al., 2003) Even so, despite the eco-nomic recession, approximately 700,000 immigrants moved to the city at this time Indeed, the peak observed in the value of NP in
2001 indicates a steady expansion in the size of the urban areas
in Hanoi In order to promote decentralization of the city centre, numerous apartment buildings were constructed in the suburbs Taken together, 20,000 ha of agricultural land and water bodies areas were converted to urban use (Pham and Yamaguchi, 2007) and the urban areas continued to expand along highways to the south and south-west of the city The decline in the MNN value
at this time reflected an increase in both the size and the extent
of fragmentation of the urban area, and the observed peak in the AWMPFD and ED indexes in 2001 support this trend (Fig 6) Despite the observed decrease in the rate of urbanization since 2001, the urban core coalesced with the various fragmented urban patches
to form a homogenous urban patch in 2003
The adoption of the “Doi Moi” reforms marked a remark-able change in the progress of urbanization in Hanoi However, compared to the cities of Hartford, Nagoya, and Shanghai, the urbanization of Hanoi has also produced several problems In the newly urbanized areas, the new transportation routes (the develop-ment zones around the city) and apartdevelop-ment buildings were planned very close to existing urban areas and are an average of 10 km away from the city centre This is considerably closer than the new urban areas of Hartford and Shanghai, which were located on the out-skirts of existing urban areas, 20 km and 40 km from the city centre, respectively (Fig 2) The development of new urban areas far from the main city centre not only attracts people to the suburbs, but also increases the long-term development potential In Hanoi, the new urban areas were quickly assimilated into the old urban cen-tre by the rapid and unexpected economic growth that followed the “Doi Moi” reforms Secondly, the areas of Hanoi to the east of the Red River remained relatively less developed In addition, urban growth in Hanoi has primarily occurred along the major transporta-tion routes on the western side of the Red River, which has resulted
in an increase in the price of land The resettling of inhabitants and extension of transportation routes inside the existing urban areas has also been difficult For example, in order to construct a new one-kilometre road from O Cho Dua Street to Hoang Cau Street in the Dong Da district, the government had to compensate local habi-tants a total of 4 million US dollars to make space for the road (Hiep,
2009) Taken together, these problems illustrate the importance of developing adequate land use plans for Hanoi to cope with rapid urban development
5 Conclusions
The integration of remote sensing and spatial metrics provides
an innovative method for analyzing urban growth patterns In this study, a detailed analysis of urban growth in Hanoi, Hartford, Nagoya, and Shanghai over a 30-year period was performed and the results were presented using urban change maps Several previous studies using remotely sensed data to detect urban change did not consider the problem of mixed pixels, resulting in the loss of spa-tial information However, in this study, the accuracy of urban area classification was improved by applying the classification method developed byPham and Yamaguchi (2007) Using these results, we were able to examine the changes in the urban land use of four cities over time In 2003, the urban areas of Hanoi and Shanghai under-went considerable expansion into the suburban areas, whereas the direction of urbanization in Hartford seemed to occur from the periphery of the city toward the city centre Interestingly, the spa-tial characteristics of the urban areas around Nagoya varied only slightly over time
Trang 8The results of this study show the relationship between certain
changes of spatial metric parameters and a particular type of city
planning.Fig 6clearly highlights this conclusion The
establish-ment of the urbanization control zones of Nagoya’s land use plan
was reflected by slight change of spatial metrics over time On the
other hand, the establishment of satellite towns around the
exist-ing city centre of Hanoi and Shanghai resulted in the border of the
cities getting larger, which was demonstrated by an increase in ED
and LPI The rapid development of Residential Zone in the suburb
of Hartford contributed to a sudden increase in CA
The land use master plans of each city are important for guiding
their future urban expansion We demonstrated that the legislative
instruments related to land use in urban areas have a significant
affect on the patterns and nature of urbanization; this was
particu-larly apparent in contrasting urban development scenarios in Hanoi
and Nagoya In Nagoya, the existence of a well-defined master plan
with its provisions for urban control and promotion zones resulted
in only minor changes in the city fringe In contrast, urban
devel-opment in Hanoi was less orderly, occurring mainly on the western
side of the Red River and along major transportation routes As a
consequence, this pattern of development resulted in the illegal
conversion of vacant and agricultural land to land for urban use
Improving the current land use plan and promulgating appropriate
land management legislation is thus considered to be vital for the
future development of Hanoi
It is proposed that the methods presented in this study could
be applied to the acquisition of the comprehensive information
required for making informed land use management decisions In
addition, it is hoped that the findings presented here will be useful
for decision-makers and that they will contribute to an increased
understanding of the urban dynamics and development of future
sustainable land use plans, especially in Hanoi We believe that
the combination of remote sensing and spatial metrics is an
effi-cient method for studying urban change Future research will focus
on improving the accuracy of the proposed method to avoid the
requirement for assigning the thresholds for PLADJ analysis based
on personal empirical interpretations
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