1. College of Resources and Environmental Science, Hunan Normal University, Changsha 410081, China 2. Key Laboratory of Geographic Big Data Development and Application,Hunan Normal University, Changsha 410081, China
Understanding the regional differentiation regularities and causes of quality of life in rural areas is not only the new content of rural geography for a new era, but also the inherent requirement of the scientific implementation of the rural revitalization strategy. Taking 101 counties (cities, districts) of Hunan province as the research unit, this paper proposes a assessment indicator system of quality of life in rural areas consisting of six dimensions. Then, using the entropy method, exploratory spatial data analysis and geo-detector, we elaborate spatial pattern characteristics and influencing factors of quality of life in rural areas of the province. Our results suggest the following: (1) The spatial distribution pattern of quality of life indicates that the overall feature is high to low from the east to west and descends from east to west. (2) From the perspective of the spatial correlation pattern, obviously, the spatial pattern of High-High area and Low-Low area present a pattern of agglomeration. High-High area is mainly located in Changsha-Zhuzhou-Xiangtan urban agglomeration and its adjacent counties, while Low-Low area is mainly in western Hunan. (3) The primary factors influencing quality of life are per capita GDP, urbanization level, distance from provincial capital, and elevation. The secondary factors are the slope, the proportion of secondary and tertiary industries, the proportion of non-agricultural labor in rural areas, and total power of agricultural machinery. To realize rural revitalization and improve the quality of life in rural areas, we should give priority to rural industrial and economic revitalization based on eco-environmental protection, actively strengthen the interconnection between regions and enhance the modernization of infrastructure and public service facilities in rural areas.
. 湖南乡村生活质量的空间格局及其影响因素[J]. 地理研究,
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TANG Chengli et al
. Spatial pattern and influencing factors of quality of lifein rural areas of Hunan province[J]. GEOGRAPHICAL RESEARCH,
2018, 37(12): 2475-2489.
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International practice applies several urban indicators for sustainable cities (Monocle's Quality of Life Survey, Quality of Life Index (QLI), Indicators for Sustainability, European Green City Index, City Blueprint and others). These urban indicators can serve in performing integrated monitoring, assessing and recommending objectives sought by cities by different quantitative and qualitative aspects. Some of these tools can be applied to assessing a city's quality of life. One of the goals of this article is to compare several alternative methods for assessing a city's quality of life and their accuracies. A comparison was performed of the QLI and INVAR methods while conducting an analysis of comparable data from the 2012 2016 surveys on the Quality of Life in European Cities. Upon establishing the rankings of European cities by their quality of life with the assistance of the QLI and INVAR methods, an estimation of correspondence of results obtained by both methods and sensitivity analysis were performed based on a quantitative tool proposed in this paper. The obtained values of such criteria revealed a good level of congruity between the ranks obtained by employing both methods. The sensitivity analysis indicated that the results yielded by both the QLI and INVAR methods for rating the quality of life in European cities per the ever-fluctuating 2012 2016 data were similar. In other words, there was little difference between these methods for city ranking. This research also provides the INVAR method and its abilities to supplement the QLI with new functions: quantitative recommendations for cities under analysis by the indicators under analysis, optimization of indicators with consideration of indicators achieved in the quality of life area, and establishment of the values of the indicators under analysis permitting the city under analysis to raise its rating to the desired level.
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