Seyed Komeil Salehi, Ms Habibeh Nabizadeh, D.r Amineh Anjem Shoa,
Volume 0, Issue 0 (3-1921)
Abstract
The purpose of this study was to investigate the factors affecting the increase in attractiveness of tourism purposes in Tehran. The present research is descriptive-analytical in terms of purpose and method. The data collection tool is a question and interview. The statistical population of the study includes experts and experts in the field of tourism, which was selected using Cochran formula and simple random sampling method, 210 tourism experts were selected as samples. Descriptive tests and logistic regression test were used to analyze the data. The results of this study indicate that from 210 active in Tourism in Tehran, 91 people believed in 43.3%, with attractiveness of tourist destinations in Tehran at high level, 29% believed that the level of charm at the appropriate level and only 27% He believed that the attractiveness of tourist destinations in Tehran is at a low level. The results in the field of effective factors on increasing the attractiveness of intentions due to tourism development also showed that among the four factors intended, respectively, factors of 1) innovative business opportunities with impact coefficients (613/0), 2) assets Natural / cultural and historical city with a coefficient of impact (0.577), 3) Development of tourism infrastructure with an impact coefficient (0.497) and 4) urban development agent with an impact coefficient (0.473) had the most effects on increasing attractiveness Due to tourism development in Tehran.
Alireza Rahimi, Nader Nazemi, Jamaleddin Honarvar,
Volume 21, Issue 60 (3-2021)
Abstract
Energy plays a major role in providing welfare of urban and rural households, and reforming energy consumption patterns, in addition to price balancing, requires recognition and acts of cultural and social variables affecting the pattern of consumption and savings. Considering the importance of saving electricity and its relation with consumer behavior, in this study, the difference in urban and rural communities was investigated in terms of effective factors on energy savings. The present research is descriptive-analytical in terms of purpose and method. The data-gathering tool and information collection and interviews with urban and rural households in Poledokhtar city. The statistical population includes urban and rural households in Poledokhtar Township (N= 30012). Using Cochran formula and simple random sampling method, 379 households (244 urban households and 135 rural households) were selected. In the data analysis section, analysis of variance and logistic regression tests were used. The results showed that there is a significant difference between the factors and indicators affecting power saving in rural and urban areas. The individual agent and the factor of behavior management and purchasing, while the factor is the most important factor in saving households in rural areas, primarily influence power saving in urban areas.
Mr Shokrollah Kiani, Mr Ahmad Mazidi, Mr Seyed Zein Al-Abedin Hosseini,
Volume 24, Issue 74 (12-2024)
Abstract
Subsidence is an environmental phenomenon caused by the gradual subsidence or sudden subsidence of the earthchr('39')s surface. The phenomenon of subsidence in residential, industrial and agricultural areas can cause catastrophic damage. In most parts of Iran, there is a high correlation between land subsidence and the decrease of groundwater level and consequently the density of soil layers. In this study, using two time series of radar images with artificial apertures from Sentinel sensors belonging to 2014 and 2019, the amount of subsidence in Damaneh plain (Frieden city) was calculated. Wells were studied in the period 2014 to 2019, the results of the study of the correlation between land subsidence with changes in groundwater level at the level of 95% was significant. In the continuation of the research, using the logistic regression model, the subsidence trend in the study area was predicted and a subsidence probability map was prepared and created as a dependent variable for the logistic regression model. The independent variables used included altitude, slope, slope direction, geology, distance from the road, distance from the river, land use, distance from the village, groundwater level, piezometric wells. The output of the model is subsidence risk zoning map which was created in five classes. The accuracy and validation of the logistic regression model was evaluated using the system performance characteristic curve and the accuracy (0.89) was obtained. The good accuracy of the logistic regression model in producing the probability map Subsidence is in the study area. In the output of the model, it was found that the area of 1980 hectares, equivalent to 7.9%, has a very severe subsidence that has put the situation in a dangerous situation and the need for control and management to reduce this destructive effect.
