Natural Resources, 2011, 2, 28-34
doi:10.4236/nr.2011.21005 Published Online March 2011 (http://www.scirp.org/journal/nr)
Spatial and Dynamic Analysis of Regional
Sustainable Development Using Geographic
Information System and Relative Carrying
Capacity of Resources*
Qi Wang1#, Hua Tang1, Jun Li1, Haihu Ma1, Tianxing Cheng 2, Xiaodan Wang3
1College of Life and Environmental Science, Wenzhou University, Wenzhou, China; 2College of Chemistry and Materials Engineer-
ing, Wenzhou University, Wenzhou, China; 3School of Chemistry and Chemical Engineering, Southwest University, Chongqing,
China Email: #
Received December 13th, 2010; revised January 24th, 2011; accepted January 31st, 2011.
ABSTRACT
Relative carrying capacity of resources is an index to measure sustainable development through carrying capacity.
Case studies of eleven cities in Zhejiang (Hangzhou, Ningbo, Wenzhou, Jiaxing, Huzhou, Shaoxing, Jinhua, Quzhou,
Zhoushan, Taizhou and Lishui) illustrated regional sustainable development approach. In this study, to provide insight
into spatial and dynamic analysis of region sustainable development, we calculated the relative carrying capacity of
land resources and economica l resources and synthetical carrying capacity of resources in differen t cities in Zhejiang,
and geographic informa tion system was carried out. The results showed th at all cities but Hangzhou and Ningbo were
ecologically sustaina ble, and relative carrying capa city of land resources in northern and eastern Zhejiang was larger
than those in southern and western Zhejiang. The sampling years of Wenzhou, Hangzhou and Ningbo contribution rates
of land resource to synthetic carrying capacity were grouped into three stages, and there were two milestones trends
and changes in 1996 and 2004, respectively. This study demonstrated that geograp hic information system and relative
carrying capacity of resources are effective for assessment of region sustainable development, and provide policy
guidelines for decision-making.
Keywords: Geographic Informati o n Syst em, Arcgis, Relative Carrying Capacity of Resources, Regional Sustainable
Development, Contribut i o n R at e
1. Introduction
Sustainable development has been widely recognized as
an effective tool for harmonizing human society and na-
ture. The main research and practice of sustainable de-
velopment concept are focused on efficient use of the
human and economical resources. Assessment of sus-
tainable development for effective regional management
is becoming concern, which included Relative Carrying
Capacity of Resources (RCCR) [1], Ecological Footprint
(EF) [2,3], Index of Sustainable Economic Welfare
(ISEW) [4], Environmental Decision Support System
(EDSS) [5], and Genuine Progress Indicator(GPI) [6].
Wang proposed that carrying capacity of natural reso-
urces was much lower than the carrying capacity of
economy resources of Wenzhou and had been the state of
overload from 1992 to 2004 [1]. Ivan and Anna explored
the determinants of the ecological footprint of commut-
ing municipal variability by using population density,
accessibility, average household income, and job ratio.
Nguyen and Yamamoto reported the estimated total eco-
logical footprint of the world using the new method im-
plied more serious problems associated with over con-
sumption than using results from the original ecological
footprint method.
Geographic information system (GIS) is a useful and
effective tool for spatial features in various fields, par-
ticularly in environmental science. In recent years, it has
been widely studied for geographical distribution and
spatial analysis including particulate waste distribution
*The authors claim that the paper was partly published in Proceeding
of International Conference on Environmental Science and Information
Application Technology in 2009 and exchanged in this conference.

Spatial and Dynamic Analysis of Regional Sustainable Development Using Geographic Information 29
System and Relative Carrying Capacity of Resources
[7], ecological connectivity [8], acute symptoms [9],
paramphistomosis in sheep [10], verotoxin-producing
Escherichia coli [11], etracapsuloides bryosalmonae
infected fishes [12], international epidemiology of lung
cancer [13] variance of intraseasonal variations [14],
PBDEs in human breast milk [15], amino acid muta-
tions [16], and Colletotrichum lindemuthianum [17].
Yokoi and Satomura revealed remarkable differences
ill the geographical distribution, of variance between two
types of intraseasonal variations in daily-mean radar re-
flectivity data ill the western part of the Indochina Pen-
insula [14]. Sudaryanto et al. proposed that concentra-
tions of PBDEs were relatively uniform and the levels
were in the same order as those in Japan and some Euro-
pean countries, but were one or two order lower than
North America by using geographical distribution [15].
RCCR is essential for carrying capacity in order to as-
sess regional sustainable development. At present, quan-
titative studies on the spatial analysis of regional sus-
tainable development based on GIS and RCCR in a given
region are still rare. With the rapid economic develop-
ment, Zhejiang has faced with severe conflicts between
limited natural resources and increasing resource re-
quirements. Therefore, Zhejiang has become a great
challenge for sustainable development over the last dec-
ades.
The present study based on [18] aimed to evaluate
spatial and dynamic difference of regional sustainable
development based on geographic information system
and relative carrying capacity of resources in Zhejiang.
2. Studied Area
Zhejiang is located in the southern part of the Yangtze
River Delta on the southeast coast of China. It covers a
total land area of 101 800 square kilometers. Hills and
mountains account for 70.4 percent of the total area in
the province. The permanent population of the province
reached 51.2 million by the end of 2008, an increase of
1.19% over the previous year. It reserves of stone coal,
alunite, pyrophyllite, and tuff rank the first in China and
the reserves of fluorite rank the second. In addition, rich
deposits of oil and natural gas in the continental shelf are
awaiting exploitation. There are 11 cities under the direct
jurisdiction of Zhejiang provincial government, including
Hangzhou, Ningbo, Wenzhou, Jiaxing, Huzhou, Shaoxing,
Jinhua, Quzhou, Zhoushan, Taizhou and Lishui.
3. Methodology
3.1. Relative Carrying Capacity of Land
Resources
Relative carrying capacity of land resources calculation
equation is as follows:
rll l
CIQ

. (1)
where is relative carrying capacity of land re-
sources, l is the study area cultivated land, l
rl
CQ
I
is the
study area nature resource carrying capacity index,

l
I
00
/
p
l
QQ, and 0
p
Qis reference region population in the
country, is reference region cultivated land in the
country.
0l
Q
3.2. Relative Carrying Capacity of Economy
Resources
Relative carrying capacity of economy resources calcula-
tion equation is as follows:
ree e
CIQ. (2)
where re Cis relative carrying capacity of economy re-
sources, eis the study area economy, Qe
I
is the study
area economy carrying capacity index, 00
/
epe
I
QQ

,
and 0
p
Qis reference region population in the country,
is reference region economy in the country.
0e
Q
3.3. Synthetical Carrying Capacity of Resources
Synthetical carrying capacity of resources calculation
equation is as follows:
12
s
rl re
CWCWC

. (3)
where
s
C
W
is synthetical carrying capacity of resources,
1 is the weight of , and 2is the weight of er.
Here 1 is 0.7 and 2 Wis 0.3 according to actual nature
resources conditions in Zhejiang[1].
Wrl C WC
3.4. Contribution Rate of Land Resource to
Synthetic Carrying Capacity
Contribution rate of land resource to synthetic carrying
capacity calculation equation is as follows:
0.7
Y 100%
rl
l
s
C
C


. (4)
where is contribution rate of land resource to syn-
thetic carrying capacity.
Yl
3.5. Geographic Information System
A GIS can integrate hardware, software, and data for
capturing, managing, analyzing, and displaying all forms
of geographically referenced information and can show
features and feature relationships. The assessment and
calculation data of relative carrying capacity of resources
used in the analysis were drawn from Zhejiang statistical
yearbooks in 2008. The spatial map analysis was per-
formed by the ArcGIS 9.2 for Windows (Environmental al
Systems Research Institute, Inc., USA) software pack-
ages.
Firstly, display Zhejiang province map features and
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Spatial and Dynamic Analysis of Regional Sustainable Development Using Geographic Information 30
System and Relative Carrying Capacity of Resources
create selection layers. Secondly, add data such as calcu-
lated relative carrying capacity of land resources to Zheji-
ang province map. Thirdly, edit geographic data, and se-
lect geographic features. Fourthly, create a summary chart.
Finally, lay out and print the maps of relative carrying
capacity. The units of relative carrying capacity of re-
sources are all ten thousand persons from Figure 1 to
Figure 10 except Figure 6.
The flow chart of the GIS-based method for spatial
analysis of regional sustainable development is shown in
Figure 1.
4. Results and Discussion
Over load population relative to carrying capacity in
Zhejiang is shown in Figure 2.
Number of over load population is positive, which
means ecologically unsustainable. On the contrary, num-
ber of over load population is negative, which means
ecologically sustainable. Figure 2 showed that sustain-
able development level of Ningbo was the best, while
that of Wenzhou was the worst because its over load
population relative to carrying capacity is the largest and
all cities but Hangzhou and Ningbo were ecologically
sustainable. The sustainable development level order of
over load population relative to carrying capacity in
Zhejiang was as follows: Ningbo, Hangzhou, Jiaxing,
Shaoxing, Huzhou, Zhoushan, Quzhou, Jinhua, Lishui,
Taizhou and Wenzhou. Spatial sustainable development
level in northern Zhejiang is better than those in southern
Zhejiang.
Spatial map of relative carrying capacity of land re-
sources in Zhejiang is shown in Figure 3.
Figure 3 showed that relative carrying capacity of
land resources in northern and eastern Zhejiang was lar-
ger than those in southern and western Zhejiang, indicat-
ing resources quality in northern and eastern Zhejiang
Select assessmen t indicators
Select region alsustainable
development m ethodology
C alculate r egional
sustainable development level
Generate GIS-based maps
Spatial Analysis
Over load popu lation
R elative carrying
capacity of land
resources
Re lative c arry ing
capacity of economy
resources
S yn th etical carry ing
cap acity of resou rces
contribution rate of
land resource to
synthetic carrying
capacity
Layers
Figure 1. Flow chart of the GIS-based method for spatial
analysis of regional sustainable development.
Figure 2. Spatial map of over load population relative to
carrying capacity in Zhejiang.
better than those in southern and western Zhejiang. Spa-
tial map of relative carrying capacity of economy re-
sources is shown in Figure 4.
Figure 4 showed that relative carrying capacity of
economy resources of Hangzhou, Ningbo and Wenzhou
were larger than other those cities in Zhejiang, indicating
economy development level in Hangzhou, Ningbo and
Wenzhou better than those of other cities in Zhejiang.
Spatial map of synthetical carrying capacity of res-
ources in Zhejiang is presented in Figure 5.
As can be seen in Figure 5, Zhoushan is located in the
northeast of Zhejiang. It’s an important gateway of in-
land place to the outside world and the juncture of water
arteries linking south and north China with the Yangtse
Figure 3. Spatial map of relative carrying capacity of land
resources in Zhejiang.
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Spatial and Dynamic Analysis of Regional Sustainable Development Using Geographic Information 31
System and Relative Carrying Capacity of Resources
Figure 4. Spatial map of relative carrying capacity of eco-
nomy resources in Zhejiang.
River. Quzhou is located in the west of Zhejiang, and is
usually described as “the Artery of Four Provinces, the
Western Gate of Zhejiang” which has rich mineral re-
sources. Lishui is located in the combination of South
Zhejiang and North Fujian mountainous regions. Lishui
is very rich in resources and specialties with the total
amount of five major natural resources ranking top
among the province, i.e. forest, waterpower, agricultural
and byproducts, mineral resources, wild animals and
plants. Figure 5 showed that Zhoushan, Quzhou and
Figure 5. Spatial map of synthetical carrying capacity of
resources in Zhejiang.
Lishui have the lower synthetical carrying capacity of
resources in Zhejiang, whereas Hangzhou and Ningbo
have the higher synthetical carrying capacity of resources
in Zhejiang. The synthetical carrying capacity of re-
sources in Zhejiang from the highest to the lowest was as
follows: Hangzhou, Ningbo, Wenzhou, Shaoxing, Jiax-
ing, Taizhou, Jinhua, Huzhou, Quzhou, Lishui and
Zhoushan. Although Wenzhou had relatively larger syn-
thetical carrying capacity of resources, over load popula-
tion was serious and sustainable development level of
Wenzhou was the worst.
Spatial map of contribution rate of land resource to
synthetic carrying capacity in Zhejiang is presented in
Figure 6.
Figure 6 showed that contribution rates of land re-
source to synthetic carrying capacity in western Zhejiang
were larger than those in eastern Zhejiang except Hang-
zhou. Slower economy, larger contribution rates of land
resource to synthetic carrying capacity. Therefore poli-
cies of nature resource become a crucial factor for
growth of sustainable development in Zhejiang.
Dynamic analysis of regional sustainable development
using geographic information system and relative re-
source carrying capacity was developed for the cases of
Hangzhou, Wenzhou and Ningbo. Dynamic plot of over
load population relative to carrying capacity in Zhejiang
is presented in Figure 7.
Figure 7 showed that the number of over load popula-
tion declined rapidly from 1993 to 2004, and increased
rapidly from 2004 to 2005, and keep calm 2005 to 2007
Figure 6. Spatial map of contribution rates of land resource
to synthetic carrying capacity i n Z h ejiang.
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Spatial and Dynamic Analysis of Regional Sustainable Development Using Geographic Information 32
System and Relative Carrying Capacity of Resources
-300
-200
-100
0
100
200
300
400
500
1992199419961998200020022004 20062008
Year
Overload population
Wenzhou
Hangzhou
Ningbo
Figure 7. Dynamic plot of over load population relative to
carrying capacity in Zh ejiang.
in Zhejiang such as Hangzhou, Wenzhou and Ningbo.
The three cities of Zhejiang province such as Wenzhou,
Hangzhou and Ningbo have experienced significant
structural changes due to the incessant growth in the
number of urban population.
The over load population of Wenzhou varied from 2
196 thousand person to 3 291 thousand person during
1993 to 2007 with an average value of 2 793 thousand
person. The over load population of Hangzhou and Ningbo
varied from −127 and 138 thousand person to −2 012 and
−2 189 thousand person during 1993 to 2007 with an av-
erage value of −912 and −1 033 thousand person, respec-
tively, indicating Hangzhou and Ningbo non over load
level of sustainable development from 1993 to 2007.
Dynamic plot of relative carrying capacity of land re-
sources in Zhejiang is presented in Figure 8.
Figure 8 showed that relative carrying capacity of land
resources in Zhejiang remained essentially constant from
1993 to 1995, while it increased with steady steps from
1996 to 2007. The order of relative carrying capacity of
land resources from higher to lower as followed: Ningbo,
Hangzhou and Wenzhou. The prevention and control land
resource of Wenzhou was still severe.
Dynamic plot of relative carrying capacity of economy
100
140
180
220
260
300
1992 19941996 1998 2000200220042006 2008Year
Relative carrying capacity of
land resources
Wenzhou
Hangzhou
Nin
g
bo
Figure 8. Dynamic plot of relative carrying capacity of land
resources in Zhejiang.
resources in Zhejiang is presented in Figure 9.
Figure 9 showed that relative carrying capacity of
economy resources increased steadily from 1993 to 2004,
whereas it remained essentially constant from 2005 to
2007.
The order of relative carrying capacity of economy
resources from higher to lower as followed: Hangzhou,
Ningbo and Wenzhou.
Dynamic plot of synthetical carrying capacity of re-
sources in Zhejiang is presented in Figure 10.
Figure 10 showed that synthetical carrying capacity of
resources was increased steadily from 1993 to 2004,
whereas remained essentially constant from 2005 to
2007.
The sampling years of Wenzhou, Hangzhou and
Ningbo synthetical carrying capacity of resources were
grouped into two stages. The order of synthetical carry-
ing capacity of resources from higher to lower as followed:
Hangzhou, Ningbo and Wenzhou.
Synthetical carrying capacity of resources in Zhejiang
increased with increasing relative carrying capacity of
economy resources in Zhejiang, and Synthetical carrying
capacity of resources declined with declining relative
carrying capacity of economy resources.
Dynamic plot of contribution rates of land resource to
synthetic carrying capacity in Zhejiang is presented in
Figure 11.
Figure 11 showed that sampling years of Wenzhou,
Hangzhou and Ningbo contribution rates of land resource
to synthetic carrying capacity were grouped into three
stages, and there were two milestones in the contribution
rates of land resource to synthetic carrying capacity
temporal trends and changes, which year were 1996 and
2004. The contribution rates of land resource to synthetic
carrying capacity increased suddenly from 1993 to 1996,
and increased steadily from 1996 to 2004, whereas it
remained essentially constant from 2005 to 2007.
0
500
1000
1500
2000
2500
3000
1992 1994 1996 1998 2000 2002 2004 2006 2008Year
R
e
l
at
i
ve carry
i
ng capac
i
ty o
f
economy resources
Wenzhou
Hangzhou
Nin
g
bo
Figure 9. Dynamic plot of relative carrying capacity of
economy resources in Zhejiang.
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Spatial and Dynamic Analysis of Regional Sustainable Development Using Geographic Information 33
System and Relative Carrying Capacity of Resources
200
300
400
500
600
700
800
900
1992 1994 1996 1998 20002002 2004 2006 2008Year
Synthetical carrying capacity
of resources
Wenzhou
Hangzhou
Nin
g
bo
Figure 10. Dynamic plot of synthetical carrying capacity of
resources in Zhejiang.
The order of synthetical carrying capacity of resources
from higher to lower as followed: Wenzhou, Ningbo and
Hangzhou.
In order to achieve “double-win” of economy and en-
vironment, the local government should take into con-
siderations in developing circular economy including
construction of eco industrial park (EIP).
Thus, the city’s policies of sustainable development in
the future should aim at emphasis on strengthening
population and nature resources management, upgrading
industrial structure, and raising the utilization efficiency
of resources based on different regional situations.
5. Conclusions
Relative carrying capacity of land resources in northern
and eastern Zhejiang was larger than those in southern
and western Zhejiang. Zhoushan, Quzhou and Lishui
have the lower synthetical carrying capacity of resources
in Zhejiang, whereas Hangzhou and Ningbo have the
higher synthetical carrying capacity of resources in Zhe-
jiang. The contribution rates of land resource to syn-
thetic carrying capacity in western Zhejiang were more
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
1992 19941996 19982000 20022004 20062008Year
C
ontr
ib
ut
i
on rates o
f
l
an
d
resource to synthetic carrying
capacity
Wenzhou
Hangzhou
Nin
g
bo
Figure 11. Dynamic plot of contribution rates of land re-
source to synthetic carrying capacity in Zhejiang.
than those in eastern Zhejiang except Hangzhou.
Hangzhou and Ningbo were not over load level of Sus-
tainable development, whereas Wenzhou was seriously over
load of that from 1993 to 2007. Synthetical carrying ca-
pacity of resources increased with increasing relative
carrying capacity of economy resources in Zhejiang such
as Wenzhou, Hangzhou and Ningbo and vice versa.
The geographic information system and regional rela-
tive carrying capacity of resources are useful tools to
measure urban sustainable development and provide pol-
icy guidelines for decision-making.
6. Acknowledgements
This work was supported in part by a grant from Wen-
zhou Major soft science Bidding Notices Foundation
(R20060004), the grant from Wenzhou Soft Science
Project (R20100119).
REFERENCES
[1] Q. Wang, “Dynamics Analysis on the Relative Carrying
Capacity of Resources of Wenzhou,” Proceeding Chinese
Control Conference (2008CCC), IEEE Press, July 2008,
pp. 738-742 (in Chinese).
doi:10.1109/CHICC.2008.4604990
[2] I. Muniz and A. Galindo, “Urban Form and the Ecologi-
cal Footprint of Commuting. The Case of Barcelona,”
Ecological Economics, Vol. 55, No. 4, 2005, pp. 499-514.
doi:10.1016/j.ecolecon.2004.12.008
[3] H. X. Nguyen and R. Yamamoto, “Modification of Eco-
logical Footprint Evaluation Method to Include
Non-Renewable Resource Consumption Using Thermo-
dynamic Approach,” Resources Conservation and Recy-
cling, Vol. 51, No. 4, 2007, pp. 870-884.
doi:10.1016/j.resconrec.2007.01.004
[4] M. Mundayand and A. Roberts, “Developing Approaches
to Measuring and Monitoring Sustainable Development
in Wales: A Review,” Regional Studies, Vol. 40, No. 5,
2006, pp. 535-554.
doi:10.1080/00343400600757726
[5] G. H. Huang, X. S. Qin, W. Sun, X. H. Nie and Y. P. Li,
“An Optimisation-Based Environmental Decision Sup-
port System for Sustainable Development in a Rural Area
in China,” Civil Engineering and Environmental Systems,
Vol. 26, No. 1, 2009, pp. 65-83.
doi:10.1080/10286600802003732
[6] N. Hanley, I. Moffatt, R. Faichney and M. Wilson,
“Measuring Sustainability: A Time Series of Alternative
Indicators for Scotland,” Ecological Economics, Vol. 28,
No. 1, 1999, pp. 55-73.
doi:10.1016/S0921-8009(98)00027-5
[7] O. M. Perez, T. C. Telfer, M. C. M. Beveridge and L. G.
Ross, “Geographical Information Systems (GIS) as a
Simple Tool to Aid Modelling of Particulate Waste Dis-
tribution at Marine Fish Cage Sites,” Estuarine Coastal
C opyright © 2011 SciRes. NR

Spatial and Dynamic Analysis of Regional Sustainable Development Using Geographic Information
System and Relative Carrying Capacity of Resources
34
and Shelf Science, Vol. 54, No. 4, 2002, pp. 761-768.
doi:10.1006/ecss.2001.0870
[8] J. Marulli and J. M. Mallarach, “A GIS Methodology for
Assessing Ecological Connectivity: Application to the
Barcelona Metropolitan Area,” Landscape and Urban
Planning, Vol. 71, No. 2-4, 2005, pp. 243-262.
doi:10.1016/S0169-2046(04)00079-9
[9] K. Radon, A. Rosenberger, V. Ehrenstein, M. Hoopmann,
I. Basting, H. Todt, J. Reichert, H. Dressel, M. Schmid, R.
Suchenwirth and D. Nowak, “Geographical Distribution
of Acute Symptoms after a Train Collision Involving
Epichlorohydrin Exposure,” Environmental Research,
Vol. 102, No. 1, 2006, pp. 46-51.
doi:10.1016/j.envres.2006.01.010
[10] G. Cringoli, R. Taddei, L. Rinaldi, V. Veneziano, V.
Musella, C. Cascone, G. Sibilio and J. B. Malone, “Use of
Remote Sensing and Geographical Information Systems
to Identify Environmental Features that Influence the
Distribution of Paramphistomosis in Sheep from the
Southern Italian Apennines,” Veterinary Parasitology,
Vol. 122, No. 1, 2004, pp. 15-26.
doi:10.1016/j.vetpar.2004.03.011
[11] T. Kistemann, S. Zimmer, I. Vagsholm and Y. Andersson,
“GIS-Supported Investigation of Human EHEC and Cat-
tle VTEC O157 Infections in Sweden: Geographical Dis-
tribution, Spatial Variation and Possible Risk Factors,”
Epidemiology and Infection, Vol. 132, No. 3, 2004, pp.
495-505. doi:10.1017/S0950268803001729
[12] T. Wahli, D. Bernet, H. Segner and H. Schmidt-Postha-
us, “Role of Altitude and Water Temperature as Regulat-
ing Factors for the Geographical Distribution of Tetra-
capsuloides Bryosalmonae Infected Fishes in Switzer-
land,” Journal of Fish Biology, Vol. 73, No. 9, 2008, pp.
2184-2197.
doi:10.1111/j.1095-8649.2008.02054.x
[13] D. R. Youlden, S. M. Cramb and P. D. Baade, “The In-
ternational Epidemiology of Lung Cancer-Geographical
Distribution and Secular Trends,” Journal of Thoracic
Oncology, Vol. 3, No. 8, 2008, pp. 819-831.
doi:10.1097/JTO.0b013e31818020eb
[14] S. Yokoi and T. Satomura, “Geographical Distribution of
Variance of Intraseasonal Variations in Western Indo-
china as Revealed from Radar Reflectivity Data,” Journal
of Climate, Vol. 21, No. 19, 2008, pp. 5154-5161.
doi:10.1175/2008JCLI2153.1
[15] A. Sudaryanto, N. Kajiwara, S. Takahashi, Muawanah
and S. Tanabe, “Geographical Distribution and Accumu-
lation Features of Pbdes in Human Breast Milk from In-
donesia,” Environmental Pollution, Vol. 151, No. 1, 2008,
pp. 130-138.
doi:10.1016/j.envpol.2007.02.016
[16] K. Rungsihirunrat, C. H. Sibley, M. Mungthin and K.
Na-Bangchang, “Geographical Distribution of Amino
Acid Mutations in Plasmodium Vivax DHFR and DHPS
from Malaria Endemic Areas of Thailand,” American
Journal of Tropical Medicine and Hygiene, Vol. 78, No.
3, 2008, pp. 462-467.
[17] G. A. Bardas, O. Koutita and K. Tzavella-Klonari, “Geo-
Graphical Distribution, Pathotype Characterization, and
Molecular Diversity of Colletotrichum Lindemuthianum
in Greece and Resistance of Greek Bean Cultivars,” Plant
Disease, Vol. 91, No. 11, 2007, pp. 1379-1385.
doi:10.1094/PDIS-91-11-1379
[18] Q. Wang, H. H. Ma, Q. Ke, C. H. Wang and X. D. Wang,
“Spatial Analysis of Regional Sustainable Development
Based on Geographic Information System and Relative
Carrying Capacity of Resources,” Environmental Science
and Information Application Technology. International
Conference on ESIAT 2009, Vol. 1, 2009, pp.437-440.