Abstract
The construction of new rural communities is an important measure to promote the integration of urban and rural areas. The environmental quality of new rural communities represents the residential suitability of the communities. The evaluation of the environmental quality can help promote the healthy development of new rural communities. The present study combines AHP (Analytic Hierarchy Process) and TOPSIS (Technique for Order Preference by Similarity to an Lead Solution) for the evaluation and ordering of the environmental quality of 28 new rural communities in Henan Province, China. The AHP model containing four hierarchies is constructed: objective hierarchy, principle hierarchy, index hierarchy and factor hierarchy. The principle hierarchy is composed of 3 factors: social environment, material environment and ecological environment; the index hierarchy consists of 7 factors: service environment, civilized environment, planning environment, architectural environment, facility environment, greening environment, sanitation environment; the factor hierarchy consists of 14 factors: life service, health service, education degree, neighborhood relationship, spatial layout, functional layout, architectural style, architectural functions, infrastructure, public facilities, percentage of green open space, leisure and entertainment facilities, garbage treatment rate and wastewater treatment rate. By AHP model, the weight of the factors in every hierarchy is obtained and TOPSIS is employed for the ordering of the environmental quality of the 28 new rural communities. The results show: in the environmental evaluation, spatial layout, functional layout, architectural functions, infrastructure and neighborhood relationship have a relatively higher weight and more importance should be attached to these respects. The ordering of environmental quality of new rural communities has a high discrimination. The five communities with the highest environmental quality (representing 17.8% of the total communities) are R<sub>13</sub>, R<sub>6</sub>, R<sub>24</sub>, R<sub>23</sub> and R<sub>28</sub>. The result can effectively reflect the environmental quality of new rural communities. On the one hand, this result can provide the basis for the transform and restructuring of the existing communities; on the other hand, it can be used as the reference for the quality control of newly-built communities, so that the objectives of new rural community construction will be met.
Highlights
The planned economic system that was once implemented in China for a long period resulted in a dual structure of urban development: urban and rural areas have been confined to be a closed unit
The rural areas are retarded in the economic, social, infrastructure and cultural aspects compared to the cities
In the overall ordering of the factors in factor hierarchy by weight, spatial layout, functional layout, infrastructure, architectural functions and neighborhood relationship have a higher weight, which should be put in an important place in the environmental construction of new rural communities
Summary
The planned economic system that was once implemented in China for a long period resulted in a dual structure of urban development: urban and rural areas have been confined to be a closed unit. The combined application of hierarchical analysis (Melissa et al, 2012) and TOPSIS has a great potential in the environmental quality evaluation of new rural communities. The present study establishes an environmental evaluation model of new rural communities based on AHP-TOPSIS. Establish the evaluation model and judgment criteria: The focus of the construction of new rural areas is five "new": new houses, new facilities, new environment, new peasants and new customs (Zhang, 2011). The factors are selected by experts according to the criteria that the influential factors can reflect the essential requirements of the environmental quality of new rural communities. On the premise of passing the consistency test, the weight of the influential factors in every hierarchy in relation to the immediately upper hierarchy is obtained and the weight of factors with respect to the objective hierarchy (Table 5)
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