Uncertainty evaluation of the coordinated devel- opment of

J. Geogr. Sci. 2011, 21(6): 1123-1137 DOI: 10.1007/s11442-011-0905-y

© 2011 Science Press Springer-Verlag

Received: 2011-06-03 Accepted: 2011-07-08 Foundation: Humanities and Social Science Foundation of Ministry of Education of PRC, No.11YJCZH201; Natural

Science Foundation of Hunan Province, No.10JJ5017; Social Science Foundation of Hunan Province, No.2010JD19; No.09YBA003

Author: Xiong Ying (1977–), Ph.D and Associate Professor, specialized in the study of regional human settlement envi-ronment. E-mail: [email protected]

www.geogsci.com springerlink.com/content/1009-637X

Uncertainty evaluation of the coordinated devel-opment of urban human settlement environment and economy in Changsha city

XIONG Ying Department of Resources and Environmental Sciences, Changsha University of Science and Technology, Changsha 410004, China

Abstract: The coordinated development of human settlement environment and economy is of vital significance to urban sustainable development and urban ecosystem health. Urban hu-man settlement and economic systems exist in urban ecosystems, which are a structural complexity. Therefore the research is being challenged by some uncertain factors between human settlements and economic systems. However most of the researches were focused on its determinate objective aspects and qualitative analyses while less concern on the quanti-tative evaluation of coordinated development of urban human settlement environment and economy, especially little on its uncertain aspect. At present, the urgent task is to study the coordinated development of urban settlement environment and economy in terms of the effect of uncertainty. This study analyzed the uncertain characteristics, which would be confronted at different stages, such as confirming the index categories, their bound values, and their construction rate, etc. According to the actual urban conditions, many construction principles based on uncertainties are put forward and an indicating system for human settlement and economic evaluation is established. Moreover, the application of fuzzy mathematics presents a new method and a calculation model for the comprehensive assessment of the coordinated development of urban human settlement environment and economy. The application of the method and model in Changsha city of China showed that the assessment results can reflect not only the overall coordination degree of the city, but also the mode of interactive mecha-nism between urban economic system and human settlement environment.

Keywords: urban economic system; urban human settlement environment; uncertainty; fuzzy mathematic；coordinated development; evaluation; Changsha city

1 Introduction

With the rapid development of industrialization and urbanization, the large-scale industrial

1124 Journal of Geographical Sciences

and population agglomeration, the growing problems such as urban environmental pollution, ecological destruction and threatening the health of human have become more serious. How to coordinate with the relationship between urban human settlement environment and eco-nomic development has become a new focus with common concern. At present, urban hu-man settlement environment is becoming one of the hot subjects in the architecture, geog-raphy, environment, planning and so on (Liu et al., 2005).

Since the 1950s, the Greek scholar Doxiadis proposed the concept of “Science of Human Settlement (Ekistics)”, which has been developed rapidly. Currently, the foreign studies about human settlement environment are mainly concentrated in national-level research and practice (Emmanuel, 2005; Grace et al., 2011; Gordon and Idowu, 2009; Spagnolo and Dear, 2003), environmental impact assessment (Haydar and Pediaditi, 2010; Jason, 2011; Ismo, 2006; Luis and Angus, 2011; Obaidullah and Rizwan, 2008), database establishment by GIS and so on (Li et al., 2007; McNeil et al., 2006; Philip, 2009; Tristram et al., 2008; Valavanis et al., 2004). Moreover, some developed countries have established the evaluation system of ecological residential area, such as the U.S. LEED standards, the Netherland Eco-Quantum standards, etc. The study of human settlement environment in China started in the 1980s, the representative researches include “Introduction to Sciences of Human Settlement” by L. Y. Wu (Wu, 2001), human settlement environment in cities and small towns by Y. M. Ning et al. (Ning et al., 1999), comprehensive assessment of urban human settlements and the climate factors of suitable residential environments by X. M. Li (Li and Li., 2005), the eco-settlement by X. J. Zhu (Zhu, 1997), and other studies about urban ecosystem health (Guo et al., 2002; Hu et al., 2005). In recent years, some specific fields have been carried out by lots of scholars, who proposed the index systems of eco-city, settlement environment and urban environment sustainable development (Liu et al., 2001; Wu et al., 2005; Zhao et al., 2009; Huo and Li, 2010; Li et al., 2011). But generally speaking, the researches about the coordinated development between urban human settlement environment and economy are less, and more attention was paid to the qualitative analysis. At the same time the com-plete evaluation system and method have not been established yet.

Urban human settlement environment and economic systems exist in urban ecosystem, which is the natural-social-economic complex system. Because of the complexity, there are lots of uncertainty factors. Although the uncertainty theory in environmental science, ecol-ogy, economics and social science have been widely used (Dominique et al., 1999; Zou and Guo, 2001; Cheng and Guo, 2001; Zeng et al., 2006), it has not been given sufficient con-sideration on the coordinating research between urban human settlement environment and economic development. Therefore, under the influences of uncertainty factors, it is one of the difficult researches on how to establish the evaluation system, and how to evaluate the coordinated development status between the two systems by using what methods. Particu-larly the theory and practice of urban human settlement environment are still at the explora-tory stage at present, so strengthening researches in these fields are urgently needed to ad-dress the problems in academic circles. This study attempts to analyze the uncertainty of the coordinated development evaluation between urban human settlement environment and economy, and carries out empirical research for discussing the evaluation system and method to reduce the uncertainty, which is to promote the subjects development of human settlement environment and urban sustainable development.

XIONG Ying: Uncertainty evaluation of the coordinated development of urban human settlement environment 1125

2 Uncertainty analysis of the coordinating evaluation system of urban human settlement environment and economy

The coordinating evaluation uncertainty of urban human settlement environment and eco-nomic systems includes two aspects: 1) research object with itself uncertainty, including the inherent and the external caused by human; 2) the uncertainty of evaluation system, which is the thesis in this study, mainly including the establishment of evaluation index system, the data acquisition process and results and so on.

2.1 Uncertainty analysis of data acquisition and result

The uncertainties in data acquisition process mainly include the lacking of data, experience or historical accumulation data, and the process of data collection. The uncertainties above may be caused by sampling randomness and data analysis. The evaluation result uncertainty mainly comes from the present uncertainty analysis. Because of the uncertainties of data acquisition, present analysis, establishment system, and the limitation of human cognitive abilities, it inevitably leads to uncertainties in handling the actual problems and results analysis. Therefore, it needs to establish the optimization evaluation models and theories so as to reduce the effects of uncertainties.

2.2 Uncertainty analysis in evaluation index system

Actually, uncertainties include parameter internal uncertainty and uncertainty among pa-rameters (Jiao et al., 2004). As for the coordinating evaluation index system of urban human settlement environment and economy, the uncertainties not only exist in the parameters in-ternal, but also between parameters and the whole system. Therefore, the coordinating evaluation should use models or mathematics methods to make single index systematic, and take parameter uncertainty as a research priority. At the same time, the index system is a complete organic whole, rather than a simple combination of indicators. So the coordinating evaluation index system between urban human settlement environment and economy should be a complex system which consists of natural-social-economic system. However, it is dif-ficult to achieve uniform standards with the complexity of index system establishment.

2.3 Uncertainty analysis in quantitative evaluation

After evaluation index system established, it needs to quantify the threshold value and index weight (contribution). However there is no uniform method to quantify the evaluation index. Commonly used methods (Yang, 2001; Dangiel, 2002) at home include the national standard values, the overseas standard values with good value characteristics in some regions, the reference values of the domestic cities by trend extrapolation, and the standard values tem-porarily replaced with other similar indicators and so on. But the methods above can easily bring subjective differences, which lead to uncertainty problems. Another reason of uncer-tainty comes from the trend extrapolation process. At the same time, according to the status values of other cities by trend extrapolation, it will result in extrapolation parameters uncer-tainties on account of the influences of large number of complex factors (Wayne, 2002) such as external random disturbances, measurement errors, differences in subjective judgments. At present, the methods usually use the analytic hierarchy process (AHP), expert evaluation


and the two methods above combination to quantify the weight of each index. However, these methods have their own more subjective. For example, determining the indexes weights, the experts of different awareness and the national policies may often affect their opinions. Hence, the uncertainty of determining each index weight is obvious.

3 Evaluation principles and methods

3.1 Establishment principles of evaluation index system

Urban human settlement environment and economic system is a complex system, which concerns with social, environmental, economic and cultural factors. In order to synthetically reflect the relationship between the urban human settlement environment and economic sub-systems, it is necessary to establish the composite indexes with their respective main factors. That is a scientific and standardized evaluation index system. Selecting and designing the evaluation index system should not only follow the objective, scientific, integrated, repre-sentative and other universal principles, but also the people-oriented, hierarchical, regional, comparable and dynamic principles (Li et al., 2005; Wang, 2005; Xu and Zhang, 2001).

Based on the above analysis of evaluation system uncertainties, it is also necessary to consider the principle of flexibility (Jiao et al., 2004) when establishing index system. And that the indexes are divided into two aspects of elastic elements and non-elastic elements in accordance with the characteristics of habitat environment and economic systems. The main differences between the two aspects are that the former refers to the elements of instability in the evaluation process, as well as accurately determining the elements by non-human factors, and some of the indicators which can not be quantified or qualitative indicators, such as improvement degree of human settlement environment, convenient transportation index, happiness index and policies preferential degree, etc. Elastic elements can cause multi-changes of the evaluation system, and these elements are mainly presented as the un-certainty features. The latter are relatively stable elements and these show the rigidity or the main problems which influence the urban sustainable development. And these elements are the strictly control factors by man-made measures, which it is necessary to determine the quantitative indexes and standards for the purpose of realizing sustainable development and urban planning and construction. For example, the urban per capita land index, the treatment standards of city three wastes, the green land standards of residential environment construc-tion, etc. There are differences in the choice of two kinds of indicators. As to non-elastic index, it should be selected in detail. In contrary, it should be widely selected to flexibility index. The evaluating methods of linear or nonlinear are more common for the two kinds of indexes. But the non-elastic elements more focus on single goal evaluation (Wang et al., 2004), or refer to some evaluating standards (Song et al., 1999). The research methods of elastic uncertainties mainly include sensitivity analysis, gray system analysis, fuzzy mathe-matics, cybernetics, transfer function method and so on (Lv and Wang, 1996; Zeng et al., 2006).

3.2 Idea of evaluation and method

3.2.1 Basic ideas

At present, the qualitative and quantitative researches on the uncertainties of urban human settlement environment and economic system have made some progress. However, facing


with the system complexity, the fuzziness and uncertainty of the system are paid less atten-tions, and some researches only aim at one aspect of the uncertainties (Zou and Guo, 2001; Chen and Guo, 2001; Wang et al., 2004). On concern of the research methods, most of evaluation methods are evolved from traditional deterministic methods, and the methods are also focused on the single objective models, so it can not reflect the system dynamics, com-plexity and uncertainty. Moreover, it can not form the identification methods to reflect the development and evolution systems. And it is difficult to identify the status of the systems according to the decision-maker experience and qualitative judgment. So this research com-bines fuzzy mathematics with traditional evaluation method, and establishes the synthetic evaluation index system with consideration of the system’s certainty and uncertainty. Using principal component analysis (PCA) is to reduce or eliminate the influence of single system evaluation uncertainty. At the same time establishing the fuzzy intervals of system develop-ment stage by introducing interval variables is to identify the evolution fuzzy mode of the two systems. Based on this it can analyze the coordination situations of urban human set-tlement environment and economic systems, so as to realize the synthetic evaluation under the uncertainty influence.

3.2.2 Synthetic assessment of each system

In order to quantitatively evaluate the coordination between urban human settlement envi-ronment and economic systems, the first important task is to obtain the evaluation value of each system. Due to the complexity and uncertainty of the two systems, it will lead to the fuzzy evaluation result and even to contradiction. For the sake of eliminating these effects and reducing human factors, the principal component analysis is considered to be applied to evaluate the two systems coordination. This method is of the outstanding characteristics in objectively determining the original index weight, so as to improve the accuracy and reli-ability of the evaluation results, and eliminate or reduce the uncertainty influence. Specific steps are as follows:

(1) On the basis of the coordinated development theories and according to the designing indexes, the original data of the systems are arranged. If En and Sn, respectively represent economy and human settlement environment sub-systems, then the data matrix can be con-structed by selecting the n year’s original data.

11 12 1

21 22 2

1 2

...

...;

... ... ... ......

a

an

n n na

E E EE E E

E

E E E

=

11 12 1

21 22 2

1 2

...

...;

... ... ... ......

a

an

n n na

S S SS S S

S

S S S

=

12 1

21 2

1 2

1 ...

1 ...( , ) ;

... ... ...... 1

p

p

p p

R R

R RR i j

wR R

=

(2) Standardizing the indexes data, and constructing the correlation coefficients matrix Rij. All the factors are processed by these standardized formulas. Xij= (Tij – Tj) / S (1) Rij = S

ij / S iSj (2) where Tij is the original data of j index, Xij is the standardized data, Tj is the average of j in-dex in the selected period, S is the standard deviation of indicator and Sij is the covariance between different indicators.

(3) Calculating the characteristic root and eigenvector of the correlation matrix. The characteristic root of matrix Rij is λ1≥λ2≥λ3≥λ4≥…λp≥0, and the corresponding or-


thonormal eigenvector is C1, C2, …, Cp, Ci = Ci1 , Ci2, …, Ci. (4) Calculating the variance contribution of each indicator and the cumulative contribu-

tion rate. According to the cumulative contribution rate, the principal component number is selected, then the principal component scores and synthetic scores can be calculated. Gener-ally, the cumulative contribution rate of principal components is more than 85% which ba-sically reflects the main message of the original variables. Therefore, the pre-j indicators are selected as the main components, and the principal components scores are obtained. Zj=Cj1X1+Cj2X2+Cj3X3+ … +CjiXi (3)

1

n

n j njn

l w z=

=∑ (4)

where Zj is the j principal component score, Cj1, Cj2, Cj3,…Cji are the loading rates of the j principal component, and X1, X2, X3,…, Xi are the normalized index values. Then the com-prehensive evaluation score of index system for each year can be calculated by using for-mula (4). In this formula, Ln is the n-year comprehensive evaluation of each index, w is the contribution rate of the j principal component and Znj is the score of the j principal compo-nent in the n-year. 3.2.3 Modes of interaction and evolution between urban human settlement environment and economic systems Urban human settlement environment system and economic system exist in urban ecosystem, which has the feature of being open, and there are material, energy flows between the sys-tems, so the systems interacting will show lag behind or advanced features in a certain pe-riod (Li et al., 2006). Under the effects of uncertainty factors, the development modes be-tween human settlement environment and economic systems usually produce four basic stages (Figure 1). That is, the coordination mode of economic and environment systems ( ), Ⅰ

the mode of environment system lagging behind economic system (Ⅱ), the backward mode of economic system and environment system (Ⅲ), and the mode of economic system lag-ging behind environment system ( ). Ⅳ The x-axis represents the development level of economy, and y-axis represents the intensity of environmental protection (Figure 1). Actu-ally modeⅠ is the ideal harmonious development, of which the economic development is at high level, and the investment of environmental protection is very large. Mode Ⅱ is with a high level of economic development, but neglecting the environmental protection, so in this mode the development is at the expense of human settlement environment. Therefore, mode Ⅱ is not desirable. Mode Ⅲ is at lower level of economic development, and the investment of environmental protection is very low, so this mode is most non-desirable, and at the same time the development situation of human settlement environment and economy presents backward level. Mode pays Ⅳ great attention to the investment of environmental protection, but less to economic development, so this mode is not desirable. Of course, the interaction evolution of urban economic and environment systems can show the uncertainty characteris-tics with gradual advance and mutation. That is to say, the mode can be transformed under the influences of some policies adjustment, for example, implementing the leaping develop-ment strategy, accelerating the economic development and increasing investment of envi-ronmental protection. Under the above effects the evolution mode of the systems can be di-rectly transformed from mode to mode , which Ⅲ Ⅰ represents the mutation advance status.


Figure 1 Mode of interactive mechanism between urban economic development and human settlement envi-ronment

How to determine the evolution development mode of the two systems, there is a way to introduce interval variables so as to identify the development stage, which can eliminate or reduce the uncertainty influences. The development mode of urban human settlement envi-ronment system S(x) and economic system E(y) can be reflected by calculating their respec-tive comprehensive values. That is, if the evaluation value of S(x) is higher than that of E(y), it shows that the economic development is lagging behind the environmental protection level, so the evolution state is in mode . When the value of Ⅳ S(x) is equal to the E(y), it reflects the synchronous development for the systems, which means the state is in coordination mode . When the value of Ⅰ S(x) is less than that of E(y), it reflects that the development level of human settlement environment lags behind the economic development, so the sys-tems evolution state is in mode Ⅱ. If the values of S(x) and E(y) are all in declining, which indicates the evolution state is in mode Ⅲ. Certainly, the comprehensive value only reflects the relative level of the whole evaluation rather than the absolute level. That is, the values are negative or positive. When the value is negative, it shows that the annual level of devel-opment is less than the average level.

3.2.4 Coordination calculation method based on uncertainty mathematical models

Uncertainty mathematical methods include the stochastic mathematics method and the fuzzy mathematics method (Zeng et al., 2006). The stochastic mathematics has been widely ap-plied in the fields of ecology, economics, environmental science and social science, and a large number of random models were established such as stochastic prediction model, sto-chastic simulation model, stochastic evaluation model and so on. The fuzzy mathematics describes the uncertainty information by the creation of fuzzy models. At present, the fuzzy comprehensive evaluation, the fuzzy decision analysis and the fuzzy planning have a very wide range of application in all disciplines, and in future the research fields will focus on the fuzzy measure and the fuzzy logic methods. The coordination uncertainty of urban human settlement environment and economic systems can be revealed by using the fuzzy mathe-matical model.

Evaluating the coordination of urban human settlement environment and economic de-velopment based on uncertainty mathematical model is to determine the coordination fuzzy


level between the systems. That is to say, it is to determine the coordinated development values with bad or good degrees (fuzzy coordination degrees) between the two systems in a certain period. By using the concepts of subordinate degree in fuzzy mathematics, the fuzzy synthetic evaluation degrees between the two systems are carried out in this study. Firstly, establishing the coordination degree function V(i,j) (Li and Li, 2005), and the formula is as follows: V(i/j)=exp[– (F – F’)2/S2] (5) where V(i/j) is the relative coordination degree between the system i and j, F is the actual value of the system j to system i, F’ is the coordination value of the system j to i, and S2 is the variance of the system i.

Under the ideal coordination state, the urban human settlement environment and the eco-nomic systems is on the synchronous development according to the significance of coordi-nated development and regression analysis. Namely, if the value of the system i is K, corre-spondingly the value of the system j is also K. But the complete synchronization between the two systems is very rare in actual processes. Therefore it can be considered that when the regression coefficient is from 0.8 to l, the development mode of the two systems is identified in a coordination status (Li and Li, 2005). As a result, the value of F’ can be determined. When the index of human settlement environment system is K, accordingly the value of economic development system is (0.8–1) K. So it can assess the coordination degree be-tween the systems by using the coordination function V (i,j). The calculation formula is de-scribed by formula (6). V = [min{V(i/j),V(j/i)} / max{V(i/j,),V(j/i)}] (6) where V is the coordination indexes of the two systems, V(i/j) is the coordination degree of system i to j, and V(j/i) is the coordination degree of system j to i. The formula (6) shows that, if the values of V(i/j) and V(j/i) are closer, the value of V is larger, which indicates the coordination degree of the two systems is higher. Conversely, if the difference of V(i/j) and V(j/i) is larger, the V value is smaller, it indicates the coordination degree of development of the two systems is lower. When the value of V is equal to 1, it means the development state of the two systems is in perfect coordination. In order to preliminarily reflect the coordina-tion degree between the two systems, the fuzzy coordination degree and the classification criteria (Figure 1) are established in the study by using the fuzzy membership degree.

Table 1 Fuzzy coordination degree’s division and standard

Uncoordination degree Coordination degree Degree

V1 V2 V3 V4 V5 V6 V7 V8 V9 V10

Fuzzy grade Most serious

More serious Serious Slight Critical Nearly Primary Medium Better Best

Standard 0– 0.100

0.101–0.200

0.201–0.300

0.301– 0.400

0.401–0.500

0.501– 0.600

0.601–0.700

0.701– 0.800

0.801– 0.900

0.901– 1.000

4 The case study of Changsha city

4.1 Study area

The study area is Changsha city. Changsha city is the capital of Hunan Province, central-China, located in the eastern part of the province, spanning over 111°53'–114°15'E and


27°51'–28°40'N (Figure 2). Changsha city, situated at the conjoint region of the Yangtze River economic zone and South China economic circle, is the political, economic, cultural and communication center of Hunan Province and in the meantime the nuclear city of the economic union of three cities of Changsha, Zhuzhou and Xiangtan, so it has an outstanding locational advantage (Zhou and He, 2006). It is composed of five districts (Furong, Tianxin, Yuelu, Kaifu and Yuhua), three counties (Changsha county, Wangcheng county and Ningxiang county) and Liuyang city, with a total area of 11,819.5 km2. Changsha city is a low hilly region with its elevation descending from south to north, varying from 23.5 to 1607.9 m (Li et al., 2007). A subtropical monsoon climate gives Changsha city an annual rainfall of 1483.6 mm. Screened by Yuelu Mountain, belted with Xiangjiang River, the city is distinguished with its Hu–Xiang culture, civilization arose from the Dongting Lake and Xiangjiang River. Recently Changsha city has taken on a new look with its system func-tioning well, its size expanding and its economy developing. In 2009, the urban part had a population of 2,409,500. The built-up land covered an area of 242.8 km2. GDP of the urban part reached 225.014 billion yuan with per capita GDP of 93,386 yuan.

Figure 2 Location of Changsha City Note: 1. Yuelu District; 2. Tianxin District; 3. Yuhua District; 4. Furong District; 5. Kaifu District

4.2 Establishment of the evaluation index system

Based on the above analysis, and taking Changsha as a study area, aiming at the regional development situations, the study puts forward the evaluation index systems of the urban human settlement environment and the economic systems (Figure 3). According to the es-tablishment principles of evaluation index system, and using analytic hierarchy process (AHP) and fuzzy comprehensive evaluation methods, the two indexes systems of urban hu-man settlement environment and economy are divided into three levels. The evaluation in-dex system of the urban human settlement environment is established, including five major groups of human living conditions, urban eco-environment, public infrastructure, social sta-bility, and cultural and education life with a total of 22 individual indicators. The evaluation


Figure 3 The evaluation index system of the urban human settlement environment and economic development


index system of the economic development consists of four major groups including eco-nomic strength, industrial structure, economic extraversion and residents’ income and consumption with a total of 17 individual indicators.

4.3 Analysis of the results

4.3.1 Evaluation value and change

From the integrated evaluation scores (Table 2), the scores of urban human settlement envi-ronment and economic systems as a whole are in a growing tendency from 1997 to 2008. The scores of urban human settlement environment increased from –9.276 to 23.655 during this period. At the same time the scores of economy increased from –10.619 to 27.829. This reflects the study area is under the improving development status. As for the development speeds both of the systems are rather fast, but the developing speed of economic system is higher than that of human settlement environment, and the speed ratio of the two systems is 1:0.79. This also reflects the coordinated development of the two systems is not uniform, although the development of the two systems is simultaneous. Table 2 The synthesized index of human settlement environment and economic system in Changsha

Year Human settlements system evaluation score S(x)

Economic system evaluation score E(y)

Coordination value Coordination grade

1997 –9.276 –10.619 0.543 primary

1998 –7.652 –8.874 0.582 primary

1999 –5.307 –6.453 0.560 primary

2000 –2.468 –3.275 0.614 primary

2001 –1.154 –0.293 0.625 primary

2002 4.536 5.112 0.746 medium

2003 6.385 8.364 0.643 primary

2004 9.471 13.098 0.659 primary

2005 12.259 15.717 0.711 medium

2006 15.100 18.875 0.729 medium

2007 18.087 21.790 0.757 medium

2008 23.655 27.829 0.775 medium

4.3.2 Analysis of inter-system coordination

From the coordination grades (Table 2), the evolution development mode of the two systems is approach to the coordination mode. The coordination degrees of the two systems in Changsha city are in the basically harmonious development status as a whole, but the coor-dination levels are not higher, only in the preliminary or intermediate grade. Although the coordination grade in 2002 had risen to the intermediate level, the status quickly fell back to the preliminary level in 2003. It shows that the quality of coordination grade is not high, and the stability is not strong. Since 2005 the coordination grade has been maintained the inter-mediate level. Specifically speaking, the coordination degrees are not high before the year of 2000, and the scores of S(x) are higher than that of E(y). It shows that the economic devel-opment lags behind the environment development level, so the coordination status is in the


mode of economic system lagging behind environment system. Since 2000, the coordinated development degrees have been increased, but the scores of S(x) are less than that of E(y), which illustrates the urban economic development speed is more quickly in this period, and the evolution status is in the mode of environment system lagging behind economic system. Viewing from the evolution trends (Figure 4), although the composite values of the two sys-tems during 1997 to 2001 are in a growing tendency, the coordinated development status is at lower level, at the same time the evolution spatial distribution is in the outer layer (the numbers of 1, 2, 3 respectively represents the modes of ,Ⅰ Ⅱ, Ⅲ). But the distribution is close to the inner layer during 2002 to 2008 (the change from mode Ⅲ to Ⅱ and ).Ⅰ

Figure 4 The coordination index of human settlement and economy and the change of development mode

Actually, the coordination values from 2001 to 2008 are higher than that of the years from 1997 to 2000. It reflects that significant changes in the economy and human settlement en-vironment of Changsha took place after 2000, and the evaluation results are basically con-sistent with the actual situations, which shows that using the method to evaluate the coordi-nation values can well reflect the objective realities. Since 2000 due to the implementation of the strategy on economic restructuring, especially accelerating the regional industrializa-tion process, the economic development, residents’ income and consumption of Changsha have been improved obviously. At the same time, the investment of regional environmental protection and construction has been increased, and the environment improvement has been paid more attention. For example, the urban infrastructure constructions and reforms have been carried out, which include the construction of Xiangjiang River Scenic Belt, the main roads reconstructions in old urban district, and the commercial street reconstructions and so on. Moreover, increasing the investment of the housing renovation and real estate industry, and reconstructing the new residences with comfortable and healthy environment, the qual-ity of urban human settlement environment is improved greatly. However relative to the rapid economic development, the improvement speed of urban human settlement environ-ment is slightly backward (after 2005 the speed difference is appreciably decreased). At the same time, pollution was caused due to the rapid economic development and the advancing industrialization, which influences the environmental quality improvement to a certain ex-tent.


5 Conclusion and discussion

1) Urban human settlement environment system and urban economic system exist in the urban ecosystem, which is the social-economic-natural synthetic system. Because of the complexity, there are lots of uncertainty factors. Although the researches of urban human settlement environment have made great progress, it has not given sufficient consideration on the integrated study on urban human settlement environment and economic development. This paper attempts to analyze the uncertainties of the coordination evaluation of urban hu-man settlement environment and economic systems, and put forward the establishment prin-ciples of evaluation index system based on the uncertainty characteristics. By introducing the fuzzy mathematics method, the study proposes a set of comprehensive evaluation method and model based on uncertainty. And taking Changsha city as a study area, this method is applied to evaluate the coordination status between urban human settlement envi-ronment and economic development. The results are basically consistent with the actual situations, so it shows that using the method to the evaluation can well objectively reflect the regional realities.

2) The coordination evaluation method in this study is a beneficial exploration under the current weak research fields. Application of the method and model can not only reflect the overall coordination degree of the study area, but also distinguish the evolution mode be-tween the urban human settlement environment and economic systems. But due to the in-fluence of complexity and uncertainty of the two systems, the research field may not be inadequate comprehensive in the evaluation process, and some indexes are not involved. At the same time, establishing the evaluation model and the coordination fuzzy grade can only preliminarily reflect the coordinated development level of urban residential environment and economy, etc. Therefore, it is necessary to improve the evaluation methods in the future so as to increase the results accuracy.

3) In addition, there is a close connection between urban human settlement environmental system and economic system, so strengthening the forecast and early warning for the two systems will helpful to reveal these internal relations and development, which can better detect the interaction regularity between the human settlement environment and economic systems, and promote the coordinated development of the two systems.

References

Cheng B, Guo H C, 2001. An optimization approach and its application for environmental planning of tourism city (I) Inexact multi-objective programming mode. Acta Scientiae Circumstantiae, 21(2): 238–242. (in Chi-nese)

Dangiel G, 2002. Extrapolation in risk assessment: improving the quantification of uncertainty, and improving in formation to reduce the uncertainty. Human and Ecological Risk assessment, 8(1): 177–192.

Dominique G, Bern A, Pierre P et al., 1999. Comparing two methods for addressing gun certainty in risk assess-ments. Journal of Environmental Engineering, 125(7): 660–666.

Emmanuel R, 2005. Thermal comfort implications of urbanization in a warm-humid city: The Colombo Metro-politan Region (CMR), Sri Lanka. Building and Environment, 40(12): 1591–1601.

Feng Z M, Yang Y Z, Zhang D et al., 2009. Natural environment suitability for human settlements in China based on GIS. Journal of Geographical Sciences, 19(4): 437–446.

Haydar F, Pediaditi K, 2010. Evaluation of the environmental impact assessment system in Syria. Environmental


Impact Assessment Review, 30(6): 363–370. Hu T L, Yang Z F, Heng M C et al., 2005. An urban ecosystem health assessment method and its application.

Acta Scientiae Circumatantiae, 25(2): 269–274. (in Chinese) Hu X Y, Liu Q, Zhang D, 2008. Urban habitat environment construction and ecological leisure demonstration

area planning. Economic Geography, 28(4): 565–568. (in Chinese) Huo Z, LI Y G, 2010. Study on the suitability evaluation of the human settlements environment in Dianchi Lake

Basin based on GIS. Research of Soil and Water Conservation, 17(1): 159–162. (in Chinese) Ismo Pölönen, 2006. Quality control and the substantive influence of environmental impact assessment in Finland.

Environmental Impact Assessment Review, 26(5): 481–491. Gordon M, Idowu A, 2009. Climate change, related hazards and human settlements. Current Opinion in Envi-

ronmental Sustainability, 1(2): 179–186. Grace M, Leonie S, Clive M et al., 2011. Land cover change under unplanned human settlements: A study of the

Chyulu Hills squatters, Kenya. Landscape and Urban Planning, 99(2): 154–165. Guo X R, Yang J R, Mao X Q, 2002. Primary studies on urban ecosystem health assessment. China Environ-

mental Science, 22(6): 525–529. (in Chinese) Jason Phillips, 2011. The conceptual development of a geocybernetic relationship between sustainable develop-

ment and environmental impact assessment. Applied Geography, 31(3): 969–979. Jiao S, Zeng G M, He L, 2004. Study on the uncertainty of the index system of eco-city planning. Journal of Hu-

nan University (Natural Sciences), 31(1): 75–90. (in Chinese) Li X M, Li W N, 2005. Quantitative analysis about coordinating development of environment of urban human

settlements and economy in Dalian since the 1990’s. Economic Geography, 25(3): 383 –386. (in Chinese) Li Yu, Ai H, Feng F et al., 2006. Advance in research of small town environment in 1990’s. Progress in Geog-

raphy, 25(1): 90–101. (in Chinese) Li Y C, Liu C X, Zhang H et al., 2011. Evaluation on the human settlements environment suitability in the Three

Gorges Reservoir Area of Chongqing based on RS and GIS. Journal of Geographical Sciences, 21(2): 346–358.

Li Z W, Zeng G M, Zhang H, 2007. The Integrated eco-environment assessment of the red soil hilly region based on GIS. Ecological Modelling, 202(3/4): 540–546.

Liu P, Wang R S, Tan H S, 2001. Approach of the method of ecological design on the environment of urban human settlement. Acta Ecologica Sinica, 21(6): 998–1002. (in Chinese)

Liu Q P, Lin Z S, Feng N H, 2005. Evaluation on the spatial differences of urban settlement environment of Jiangsu Province. Areal Research and Development, 24(5): 30–33. (in Chinese)

Luis E S, Angus M S, 2011. Learning about knowledge management for improving environmental impact as-sessment in a government agency: The Western Australian experience. Journal of Environmental Management, 92(9): 2260–2271.

Lv Y L, Wang R S, 1996. Simulating method of urban ecosystem: sensitivity model and its improvement. Acta Ecologica Sinica, 16(3): 308–313. (in Chinese)

McNeil B E, Martell R E, Read J M, 2006. GIS and biogeochemical models for examining the legacy of forest disturbance in the Adirondack Park, NY, USA. Ecological Modelling, 195: 281–295.

Ning Y M, Zha Z Q, 1999. A study of evaluation and optimization for human settlement in the metropolitan areas: Take Shanghai for Example. City Planning Review, 23(6): 15–20. (in Chinese)

Obaidullah N, Rizwan H, 2008. Evaluation of environmental impact assessment system in Pakistan. Environ-mental Impact Assessment Review, 28(8): 562–571.

Philip J, 2009. Arnold III. Settlement and subsistence among the Early Formative Gulf Olmec. Journal of An-thropological Archaeology, 28(4): 397–411.

Song Y C, Qi R H, You W H et al., 1999. A study on indices system and assessment criterion of eco-city. Urban Environment and Urban Ecology, 12(5): 16–19. (in Chinese)

Spagnolo J, Dear R D, 2003. A field study of thermal comfort in outdoor and semi-outdoor environments in sub-tropical Sydney Australia. Building and Environment, 38(5): 721–738.


Tristram R K, Katherine A A, Lee J A et al., 2008. Basin-scale reconstruction of the geological context of human settlement: An example from the lower Mississippi Valley, USA. Quaternary Science Reviews, 27(11/12), 1255–1270.

Valavanis V D, Georgakarakos S, Kapantagakis A et al., 2004. A GIS environmental modelling approach to es-sential fish habitat designation. Ecological Modelling, 178: 417–427.

Wang J H, Liu Y C, Guo H C, 2004. Strategic environmental assessment on regional development plans based on an inexact multi-objective method. Acta Scientiae Circumstantiae, 24(5): 922–929. (in Chinese)

Wang R S, 2001. A transition of urban human settlement planning towards eco-integrity, naturalizing, low cost and humanity orientation. Urban Environment and Urban Ecology, 14(3): 1–5. (in Chinese)

Wayne G L, 2002. Uncertainty in the extrapolation from individual effects to impacts upon landscapes. Human and Ecological Risk Assessment, 8(1): 193–204.

Wu B, 2010. The evaluation of coordinated development between human settlement environment and economy in rapid urbanization area. Yunnan Geographic Environment Research, 22 (2): 54–58. (in Chinese)

Wu L Y, 2001. Introduction to Sciences of Human Settlements. Beijing: China Architecture & Building Press. (in Chinese)

Wu Q, Wang R S, Li H Q et al., 2005. The indices and the evaluation method of eco-city. Acta Ecologica Sinica, 25(8): 2090–2095. (in Chinese)

Yang J S, 2001. Study on the frame theory of eco-city. Urban Environment and Urban Ecology, 14 (5): 59–61. (in Chinese)

Zeng G M, Jiao S, Huang G H et al., 2006. Analysis of the uncertainties in urban ecological planning. Journal of Hunan University (Natural Sciences), 33(1): 102–105. (in Chinese)

Zhao Y D, Zhang H, Chen X P, 2009. Evaluation of city inhabitable environment quality by objective index sys-tem. Journal of Arid Land Resources and Environment, 23 (4): 1–5. (in Chinese)

Zhou G H, He Y H, 2006. Characteristics and influencing factors of urban land expansion in Changsha. Acta Geographica Sinica, 61(11): 1171–1180. (in Chinese)

Zhu X J, 1997. Discussion on the composition of residential park. Urban Planning Forum, (2): 1–4. (in Chinese) Zou R, Guo H C, 2001. An inexact environmental planning method for economic development zone and its ap-

plication. Acta Scientiae Circumstantiae, 21(1): 101–106. (in Chinese)

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Uncertainty evaluation of the coordinated devel- opment of