درخت حوزه‌های تخصصی

Purpose - Land subsidence is caused by natural factors and human activities around the world. Fars Province, located in the south of Iran, is subject to land subsidence due to the uncontrolled exploitation of groundwater, causing damages to the population and human settlements and also environmental, social and economic areas. Design/methodology/approach - The present research is descriptive in terms of describing land subsidence in the case study region, whereas it is also analytical as time series analysis techniques based on Radar Interferometry (InSAR) is applied to monitor temporal changes in subsidence in Darab and Fasa Plains, including 470 rural points. Using 8 ENVISAT ASAR images spanning between 2005 and 2010, nine Interferograms were processed. In the study area. Geographic Information System (GIS) is then used to study groundwater level decline at the well locations in a 24-year period (from 1991 to 2015). Findings - The results of the research confirm that there is a significant correlation between groundwater water level decline and land surface subsidence. Time series analysis of the processed Interferograms indicate the mean displacement velocity map, demonstrating the maximum subsidence rate of 25 cm/yr. The InSAR analysis reveal within the study area subsidence rate of 25 cm/year in 24 years period and locally exceeding 30 cm/yr in the last decade. This area of significant subsidence is limited in its spatial extent to the agricultural land and is partly influenced by the large-scale over-exploitation of groundwater resources in the region study. The temporal and areal relationships of subsidence and groundwater level data suggest that a significant part of the observed subsidence in the Darab region is caused by intense groundwater extraction which has led to widespread compaction within the upper parts of the up to 300m. Socioeconomic analysis and the subsidence hazard map show that 105523 people are generally at risk of subsidence, of 65068 who are at high risk. In addition, there are 2679 socioeconomic infrastructures such as public service at risk of damage by land subsidence. Research limitations/implications - Limitation in In SAR data access, especially for long-term data was one of the main limitations in land subsidence research and also in this research. Practical implications - Integrated water resource management and the observed extraction of groundwater could influence the subsidence rate in the regions exposed to land subsidence. Originality/value - This research will be important to provide vulnerability in regions with groundwater overexploitation.

Purpose- This study aimed to determine the constructive components of livable rural communities. To this end, it investigates the status of livability from the viewpoint of rural population in villages of Kashmar County. Design/methodology/approach- This is a descriptive-analytic study. In the first stage, indicators were extracted by reviewing the relevant literature. Then, a questionnaire was developed based on the Likert scale. Using the Cochran formula, 350 samples were selected and were randomly distributed. Finally, the data were analyzed using the SPSS software and employing correlation and Friedman tests. Finding- The results of the Spearman test showed no significant relationship between individual characteristics (age, sex, education) and livability indicators. On the other hand, the results of the Friedman test revealed that villages have higher livability in terms of the environmental dimension than other dimensions. In terms of the social dimension, recreation and leisure time indicator had the highest rank from respondents’ viewpoint (5.50), and other indicators were also effective in varying degrees. Respondents were more satisfied with public space than other indicators. Originality/value - Due to the novelty of the subject in Iran, and since it has received low attention in the relevant global literature, more time is needed to carry out further studies. The results of this study may be useful for rural officials and planners, rural students and researchers.

Purpose- The growing attention to rural development issues has created a strong trend in related scientific communities, as over the last few years one can see the traces of this thinking in many relevant scientific trends. One of the most important relevant subjects was job creation using the resources available in rural areas in line with their industrialization and the emergence of agro-processing industries. Spatial distribution of rural industries, spatial justice and their fair distribution based on the distribution of rural settlements have been among the most important concerns in this field. Therefore, the present study aimed to investigate the distribution of agro-processing industries with a spatial approach in rural areas of Gilan Province.  Design/methodology/approach- This research is an applied one conducted in a descriptive-analytical method. The collected data were analyzed using the average nearest neighbor, multi-distance spatial cluster analysis, mean center and standard deviational ellipse. Results showed that industries in rural areas of Gilan Province have been located in clusters. Finding- That is, their sites were selected with an eye to favorable conditions such as proximity to cities, population centers and markets, access to infrastructure, proximity to political and decision-making centers, access to major roads, access to more raw materials and cheaper agro-processing industries. Such industries are often located in the counties of Rasht, Rudsar, Astar, Talesh, Lahijan, Langrud and Sowmehsara. Therefore, the officials in charge should make plans to establish agro-processing industries in a more scattered and diverse manner in Gilan Province.    

Purpose- This survey research was conducted with the aim of assessing the rural residents' support for tourism development and their effective factors in the tourism target villages in the Central District of Firoozabad County. Design/methodology/approach- The statistical population of this study was resident household heads. Using Bartlett Table, 155 households were studied by simple random sampling method. The data gathering tool was a researcher-made questionnaire which its validity and reliability were confirmed. Findings- Based on the findings, the residents were categorized into two groups of committed supporters and passive supporters according to their support for tourism. The results of the logistic regression model showed that the perception of social, economic and environmental impacts is directly (positively) significantly predictive of the residents' support for tourism development. The highest coefficient of the logistic regression model was related to the perception of social impacts (with a coefficient of 10.661) as compared to the economic impacts (with a coefficient of 8.659) and the environmental (with a coefficient of 7.683). In addition, in 95.5% of the cases, the function can correctly measure levels of support for rural tourism. The accuracy of the model was also confirmed through the ROC curve. Research limitations/implications- Difficulties in completing the questionnaires due to the number of the tourist arrivals and people's occupations, the reluctance of some households to respond because of the distrust resulting from the location of the village in the palace privacy, and the problems encountered in this regard, which were resolved by the researchers' frequent visits to the area and acquiring the villagers' trust. Practical implications- In addition to improving the resident's perceptions of environmental impacts, further attention must be paid to improving the residents' perceptions of economic and social impacts. Originality/value- The development of tourism industry is heavily dependent on the participation and support of local residents. Improving the residents' perceptions of the impacts of tourism will lead to more residents' support for the industry, thereby, be paid more by tourists in the area, and recommend destinations to others and their desire to return to the area.