Shi Xu. Guizhou University of Finance and Economics

Transcription

1 doi: / Analysis on Quality Evaluation of Ecological Environment in Medium-sized and Small Towns based on BP Neural Network Abstract Shi Xu Guizhou University of Finance and Economics This paper studies the establishment of the quality evaluation index system for the ecological environment in medium-sized and small towns as well as evaluation methods. It attempts to establish an ecological environment quality evaluation index system suitable for medium-sized and small towns and determine reasonable weights and appropriate evaluation methods to offer reference for the establishment of a national quality evaluation system for the ecological environment in medium-sized and small towns and provide information for the effective management and rational construction of ecological environment. This paper takes Town A as an example. It performs in-depth analysis on the establishment of the ecological environment quality index system and rating of the ecological environment quality for this town, and obtains the spatial distribution pattern of the ecological environment quality. Through research on the grade distribution pattern of single factors that affect the ecological environment quality and the correlation with ecological environment quality grades, we find that the socio-economic factor affects the ecological environment quality the most, followed by the environmental level, and that natural resources plays the smallest role. These conclusions are consistent with the actual situation, which has further proved the practicability and reliability of the index system and evaluation methods obtained in this research. Keywords: medium-sized and small towns; ecological environment quality evaluation; evaluation index; analytic hierarchy process; BP neural network 1. INTRODUCTION With the fast growth of social economy and the rapid progress of urbanization, the ecological environmental issues have become increasingly prominent (Wu, 2012). Now as the new rural construction is ongoing and the urban circle keeps expanding, the quality evaluation of ecological environment in small towns is trending nowadays and has also become a new subject for research (Wu and Huang,2009). Accordingly, researches have been conducted on the quality evaluation index system for the ecological environment in small towns, weight determination and evaluation methods (Li et al.,2011; Corti et al.,2013). However, currently there is still no unified standard for the quality evaluation index system for the ecological environment in small towns (Wang et al., 2006), and researches are a bit weak on how to establish such a system and how to determine the weights (Taffetaniet al.,2009). Medium-sized and small towns are the political, economic and cultural center of rural areas, the bridge between urban and rural areas and the key base for intensive development of township enterprises, materials distribution, rural scientific and technological promotion and cultural education (Larsson and Hanberger, 2016). With the rapid development of small towns, ecological environmental issues have become increasing prominent (Vries et al.,2004). However, currently there is still no unified standard for the quality evaluation index system for the ecological environment in small towns, and researches are a bit weak on how to establish such a system and how to determine the weights (Starrett,1987). 204

2 Therefore, during the large-scale urbanization in China, how to effectively protect the ecological environment in small towns, promote the mutual development of social economy and ecological environmental protection and help small towns maintain efficient, sustainable, healthy and stable development is one of the most important researches in the implementation of sustainable development strategies in the current stage and also a new subject for environmental protection in China (Vrščaj et al., 2008). This paper starts with the study on how to determine the quality evaluation index system for the ecological environment in small towns. By taking the ecological environment evaluation indexes for Town A as an example, this paper tries to build an ecological environment quality evaluation index system suitable for Town A and determine reasonable weights and appropriate evaluation methods to serve as a reference for the establishment of ecological environment evaluation systems for medium-sized and small towns and the researches on evaluation methods and provide scientific basis for ecological environment management, engineering, standard setting, planning and construction. 2. ESTABLISHMENT OF ENVIRONMENT QUALITY EVALUATION SYSTEM 2.1 Profile of Town A Town A is located in flat terrain, with convenient transportation. Within the whole town, there are 8 villages, 1 farm and 1 station, and 106 villager groups. As of the end of the year, the total population was 32, 700 people, with a birth rate of 0.62% and a family planning rate of 94.7%. Town A covers an area of 68kM 2, of which the cultivated area is 2, ha. In 2015, Town A achieved GDP of RMB 1, 406 million Yuan and received financial revenue of RMB 60, 148, 600 Yuan, an annual growth of 14.1%. By taking various measures to attract investment, Town A introduced 4 industrial projects throughout the year. Within the town, there are 19, 000mu of aquaculture areas, 4, 000mu of orchards and nearly 20, 000mu of other operating areas. These land resources are expected to further develop towards suburban high-efficiency agricultural bases, pollution-free agricultural and sideline product bases and flower and tree nursery bases so as to increase agricultural industrialization 2.2 Data collection and processing Data used in this research are mainly collected through field surveys, public questionnaire surveys and remote sensing surveys. Data of the research area are collected according to the index system consisting of pre-selected indexes, which are mainly from the administrative map of Town A with a scale of 1:10000, the topographic map of Town A with a scale of 1:10000 and the present land use map of Town A with a scale of 1:10000; annual accounts of Town A for , field survey data and questionnaire statistics. For comparison purposes, indexes of different dimensions need to be unified with a standardized method, and qualitative indexes need to be quantified by some data processing method and based on experience and then standardized. A linear dimensionless method (Reffat and Harkness,2001) should be used in data standardization. The calculation formula is as follows: Z ij =X ij /S j (i=1, 2, 3, n; j=1, 2, 3, m) (1) Where, X ij is the raw data obtained from the statistics of various indexes; S j is the optimal value of index j; n is the number of areas under evaluation; m is the number of evaluation indexes. Ecological environment quality evaluation indexes can be divided into development indexes 205

3 (positive indexes) and constraint indexes (negative indexes) (Wang et al, 2007). After being standardized, the positive index Z ij represents the proportion of X ij in the optimal value S j. The larger the proportion is, the better the environment quality will be; and if the value is very close to 1, this ecological environment index is optimal. Negative indexes (expressed as X i, of which, n sample values are X 1, X 2, X n ) can be converted to positive indexes using the following formula: X i =1/X i (2) This paper mainly adopts the frequency statistics (Li, N., Chen, Y., Yang, P., & Yu, H, 2014), theory and practice analysis (Guo et al., 2006), Telfi expert consultation (Meiet al.,2005) and correlation analysis to screen the pre-selected indexes and choose the evaluation indexes (Wang, 2012) for each system. The detailed process is as follows (see Figure 1). Figure 1. Evaluation index screening process Through strict and careful screening and comparison, 29 indexes were finally retained, mainly distributed on three levels: regional natural resources, environmental level and socio-economic level. After consultation with experts and by reference to literature, the ecological environment quality index system for Town A is summarized in the following chart (see Figure 2): Figure 2. The structure of the evaluation index system of ecological environment quality stone town 206

4 2.2 Explanations of main evaluation indexes (1) Regional natural resources In this index subsystem, there are three sub-indexes, namely water resource, land resource and biological resource. Water resource is measured by abundance/deficiency, and land resource is measured mainly by cultivated land resource and the guarantee conditions for its utilization, which include cultivated land per capita, irrigation guarantee rate and residential land per capita. (2) Regional environmental level The regional environmental level index mainly focuses on the pollution of the atmospheric, acoustic, water, land and agricultural environment, including regional air pollution index (API), ambient noise level, water environment, land environment and agricultural environment. (3) Regional socio-economic level The regional socio-economic level index focuses on demographic situation, economic conditions, infrastructures and utilities and traffic conditions. Demographic situation includes population density, education level of residents, family planning rate and labor resources. Economic conditions reflect regional peasants sources of income, poverty and wealth and regional economic growth pattern. Infrastructures and utilities indexes include the completeness of utilities and clean energy popularity rate, which reflects the completeness of utilities and the regional energy consumption pattern. Traffic conditions mainly include road accessibility and highway network density, indicating the geographic conditions and traffic convenience of the administrative village. 3. QUALITY EVALUATION OF ECOLOGICAL ENVIRONMENT IN TOWN A 3.1 Analysis by the index method Determining the ecological environment quality status in Town A by the analytic hierarchy process (AHP) is actually multiplying the comprehensive weight determined by AHP with the standardized present value of the ecological environment quality in Town A to determine the ecological environment quality index of each administrative village (Lou and Mu,2013). The evaluation model is as follows: EQI i Qij Wj (2) Where, EQI i stands for the environmental quality index with village as the unit; Q ij stands for the j-th index of the i-th unit village; W j stands for the weight of the j-th index value. After calculation of ecological environment quality indexes, the results of the villages (B-H) are listed in Table 1. Table 1.The ecological environment quality index t of each administrative village of town A Village name B Village C Village D Village E Village F village G village H Village EQI The differences between the ecological environment quality indexes of villages are not 207

5 significant; therefore, they need to be technically processed to look more significant. In this paper, we deduct a fixed value 0.4 from all index values, and adjust them to ecological environment quality scores and grades. Table 2. The ecological environment quality level of each administrative village of stone town Village name B Village C Village D Village E Village F village G village H Village Score Grade Analysis by clustering method Calculation model for principal component comprehensive score (Liu,2012): F= ZX ZX ZX 3- O.oll201ZX ZX ZX ZX ZX ZX 9 +0.O157512ZX 9 +0.ll97263ZX ZX lZX ZX ZX ZX X ZX ZX ZX ZX IO9863lX ZX 23 -O X ZX lZX ZX ZX ZX 29. From this, the principal component comprehensive score of each administrative village in Town A can be obtained, as listed in Table 3. Table 3.The ecological environment quality level of each administrative village of stone town Village name B Village C Village D Village E Village F village G village H Village Score Grade Results show that the quality of ecological environment in Town A is rated by 5 grades. In the first group, B are of Grade 3; in the second group, C and D are of Grade 2; the third group consists of G, which is of Grade 4; the fourth group consists of E, which is of Grade 1; and the fifth group consists of F and H, which is of Grade Pattern recognition method based on BP artificial neural network Evaluating and rating ecological environment quality using BP artificial neural network is mainly performing pattern recognition (Yan et al., 2011). We completed network simulation training according to y 2 =sim(net, jcz), and the simulation results are shown in Table 4. Table 4. Simulation results Village name B Village C Village D Village E Village F village G village H Village Score Grade Judged from the distribution of ecological environment quality in Town A determined by the above method, results of principal component-cluster analysis are completely consistent with the results of BP neural network simulation, and basically consistent with the experts analytical results. The principal component-cluster analysis and BP neural network 208

6 simulation results are more in line with the actual distribution pattern of ecological environment quality in Town A. Therefore, these two models are more suitable for the quality evaluation of ecological environment in Town A and the evaluation results are more accurate. In Town A, the ecological environment quality grade decreases progressively from the center to the east, west, south and north. The ecological environment quality of F in the center is the weakest; that of G is also rather weak; that of B and H is average; that of C and D in the west of the town is good, and that of E is the best. 3.4 Spatial distribution characteristics of single factors to ecological environment quality in Town A The distribution of ecological environment quality in Town A has a certain pattern, and it is worth us exploring the factors behind this pattern. This research starts with the determination process of the ecological environment quality in Town A and tries to trace it back to the reasons behind these results. As the ecological environment quality in Town A is evaluated on 3 levels, we perform analysis from these 3 levels. We adopt the comprehensive index method to study the spatial distribution characteristics of single factors to the ecological environment quality in Town A based on the weight determined by BP neural network (Li et al.,2014). (1) Comparison of natural resources between villages Spatial data displayed by ARCMAP clearly show the spatial distribution of natural resources and the distribution pattern in Town A. We should further analyze these results together with the comprehensive analysis results (see Figure 3) Figure 3.The sketch of natural resource index value The indexes in the histogram in Figure 3 show that the grade of natural resources in each village is basically consistent with that of the ecological environment quality in this village, except that the grades of natural resources in B and H are quite different from those of the ecological environment quality in other villages. By comparison of various indexes in Figure 3, it can be seen that the following indexes play bigger roles in the rating of natural resources: cultivated per capita, irrigation guarantee rate and water resource abundance/deficiency. (2) Comparison of environmental levels of villages Spatial data displayed by ARCMAP clearly show the spatial distribution of environmental level and the distribution pattern in Town A (see Figure 4). 209

7 Figure 4. The sketch of district circumstance level index value The indexes in the histogram in Figure 4 show that the environmental level of Town A is not quite consistent with the ecological environment quality grades of these villages. By comparison of various indexes in Figure 4, it can be seen that the following indexes are more important to the environmental level: regional air pollution index, hazardous wastewater discharge intensity, regional acoustic environment quality and comprehensive utilization rate of crop straws. (3) Comparison of socio-economic levels of villages Spatial data displayed by ARCMAP clearly show the spatial distribution of socio-economic level and the distribution pattern in Town A (see Figure 5) Figure 5. The sketch of district district society economy index value The indexes in the histogram in Figure 5 show that the socio-economic level of Town A is basically consistent with the ecological environment quality grades of these villages. By comparison of these indexes in Figure 5, it can be seen that the following factors are more important to the socio-economic level: labor resources, road accessibility, road network density, net income of farmers, disposable income of residents, Engel coefficient and education level of residents, etc. Among the three factors, the socio-economic level affects the ecological environment quality the most, followed by the environmental level and the natural resources. Compared with the sustainable development goal for 2016, the comprehensive evaluation index of ecological environment construction in Town A every year from 2010 to 2015 is less than 0.06, indicating that Town A is generally under weakly sustainable development. The resources and environment evaluation indexes are all below 0.06, which means Town A is under weakly sustainable development; the economic evaluation indexes are all below 0.04, meaning Town A is under unsustainable development; and the social evaluation indexes are all below 0.08, meaning Town A is under moderately 210

8 sustainable development. 3.5 Correlation analysis of the ecological environment quality in Town A and single factors In order to figure out the correlation between each single factor and the ecological environment quality index system, we perform correlation analysis on the ecological environment quality in Town A and constraint factors Natural resources Environment level Socioeconomic Composite index Figure 6. Relativity analysis between EQ and single factor Through the correlation analysis on the ecological environment quality in Town A and each single factor (as shown in Figure 6), the economic level of Town A is relatively low, with backward secondary and tertiary industries. Due to poor economy, there are few township enterprises causing pollution, and in recent years, this town has enhanced its effort in the grain for green activities and actively conducted ecological environment construction. The relatively high social score has something to do with the great policy support from the government. Due to poor economy, this town receives little financial revenue, which constrains the environmental infrastructure construction. In summary, the ecological environment construction in Town A still has a long way to go towards sustainable development. To achieve this goal, Town A must promote its resources and environment, economical and social development simultaneously. However, general speaking, the ecological environment construction in Town A is in a good momentum. 4. CONCLUSIONS (1) Through the quality evaluation of the ecological environment in Town A, we have found the spatial distribution pattern of ecological environment quality in this town: the ecological environment quality grade decreases progressively from the center to the east, west, south and north. The ecological environment quality of F in the center is the weakest; that of G is also rather weak; that of B and H is average; that of C and D in the west of the town is good, and that of E is the best. (2) Through research on the grade distribution pattern of single factors that affect the ecological environment quality and the correlation with ecological environment quality grades, we find that the socio-economic factor affects the ecological environment quality the most, followed by the environmental level and then natural resources. (3) Through the analysis in this paper, we can see that the ecological environment construction in Town A still has a long way to go towards sustainable development. To achieve this goal, Town A must promote its resources and environment, economical and social development simultaneously. However, general speaking, the ecological environment construction in Town A is in a good momentum and has large room for improvement. The index system and evaluation methods obtained in this research prove to be practical. 211

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