Explaining Environmental Livability of Rural Settlements around Rasht Metropolis

Document Type : Research Paper

Authors

1 Ph.D. Student in Geography and Rural Planning, Rasht Branch, Islamic Azad University, Rasht, Iran

2 Assistant Professor, Department of Geography, Rasht Branch, Islamic Azad University, Rasht, Iran

3 Professor, Department of Geography, Rasht Branch, Islamic Azad University, Rasht, Iran

Abstract

Introduction
Today livability is regarded as an introduction to sustainable development. A great deal of attention is paid to assessment and evaluation in the field of planning and policy for rural settlements. Livability includes various dimensions such as environmental, socio-cultural, economic, institutional-management, and physical ones. Achieving a livable habitat requires each dimension to be evaluated and improved. Therefore, the goal of this paper is to explain environmental livability of villages around Rasht metropolis. The research is an applied one, employing a descriptive-analytical method and collecting its data via documentary resources and field studies. The statistical population of this research contains the villages around the Rasht metropolis. To assess environmental livability, the paper uses five recognized components, namely green space, pollution (environmental quality), visual quality, landscape and rural perspective, and resilience (28 items). For so doing, it gathers the required information by getting help from villagers and rural managers, thus identifying the study scope.
Methodology
In this study Dehyars and living household supervisors were selected through random sampling to respond to the designed questionnaires. It assessed the questionnaire’s validity, by using previous studies as well as the approval of experts in the field of rural studies. As for assessing the questionnaires’ reliability, it employed Cronbach's alpha method. The results (0.731) confirmed the questionnaire’s reliability for conducting the research. Once the questionnaire’s results were ensured, it got designed to collect information and analyze the descriptive statistics and then for inferential statistics, create an index. For this purpose, the items were first rounded and then, due to the fact that a correct comparison of the items required same value indicators, the negative ones became positive in value. For this convertion from negative to positive, the items had to be either reduced to a constant or reversed, which in case of the present study, the latter was true. To complete the indexation process one should fix scale differences and get numeric information. For this purpose, the research employed standardization method, then to weigh the indicators. Weight assessment used judgments’ opinion method, wherein a questionnaire was filled for each village by well-known experts. There, each component was given a value between one and ten. Afterwards, the average weights were obtained and then the numbers were considered within the range of 1-3, where 3 had the highest weight. Finally, the weight was achieved. Applied scaled-up indexes and mean and standard deviation of the indicators got calculated and further research steps utilized these indicators to carry out quantitative operations.
Result and Discussion
Results show the manner and quality of waste collection from the village surface with an average of 3.85, natural beauty eye with an average of 3.78, and air pollution (no air pollution was intended as the score changed from negative to positive) with an average of 3.36 had the highest average, while enjoyment and quality of children's play space with an average of 0.09, presence of a sewage disposal system with an average of 1.77, and the quality of wastewater collection with an average of 2.10 had the lowest average. The high average showed respondents’ satisfaction as well as the possibility of greater impact on rural viability. To determine the effect of the independent variable (environmental dimension) on the dependent one (livability), bivariate regression (simple linear regression) was used with the same method. Test results showed that the amount of determination coefficient statistics (variance explained by the set of variables) was equal to 0.593, meaning that 59.3% of the variation in livability could be explained by the environmental dimension. This reflected the impact of this dimension. F statistic was 50.935, being meaningful up to one thousandth, and representing the dependence of livability on this dimension. In other words, environmental indicators had an impact on livability. In the following, by examining the results of the indexation, it could be found out that among the studied indicators, resilience index, with a score of 9.49, was the highest and green area index, with a score of 3.137, was the lowest. Highest score of livability in the environmental dimension belonged to Alman Village, whereas the lowest was observed in Karchovandan village. Finally, there were the Leveled villages, studied in five levels, namely very desirable, desirable, moderate, undesirable, and very undesirable.
Conclusion
With the help of field surveys and documentation and by identifying environmental components and items in rural settlements around Rasht metropolis, it was found that villagers were satisfied by the type and quality of waste collection from the village surface, beautiful natural eye, and non-contamination more than other components. In contrast, they were not satisfied with enjoyment and quality of children's play space, sewage disposal system, and collection quality of sewage. After identifying the items and collecting the data, indicative steps were taken and with the help of a single sample T test it was identified that indicators could be generalized to the whole society and then with the help of regression analysis the effect of environmental dimension on livability was shown. By using the mean of indexes, resilience had the most and greenhouse had the least effective indices, with Alman village having the highest livability rate and Karchovandan village, the lowest. Afterwards, the studied villages were ranked at five levels of livability, based on their average score. According to these levels, the villages of Talamseshanbe, Alman, and Bijarbane belonged to very desirable livability level (6.60-7.17); Kasar and Pirkolachah to desirable (6.04-6.60); Fashtam, Gilpordesar, Pasikhan, Piledarbon, Garfam, Shekarestalkh, and Pachkenar to moderate (5.47-6.04); Dareposht, Keshalvarzal, Varazgah, Koleshtaleshan, Kheshtmasjed, Balakoyakh, Roknsara, Lachegorab, Shalkoh, Kizhdeh, Bijarpas, Kisarvarzal, Vishkavarzal, Pasvishe, Tazeabad, Siaestalkh, Komakol, and Mangode to undesirable (4.91-5.47); and Rodborde, Tarazkoh, Tochipaybast, Karchovandan, Gorabvarzal, Ravajir, and Vishkamatir to very undesirable (4.91-5.47).

Keywords

Main Subjects


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Volume 53, Issue 1
April 2021
Pages 1-22
  • Receive Date: 09 January 2019
  • Revise Date: 11 July 2019
  • Accept Date: 11 July 2019
  • First Publish Date: 21 March 2021