Hosein Nazmfar; Ali Eshghei Char Borj; Saide Alavi; Ali Jasaraty
Abstract
Abstract[1]
Road accidents and casualties are one of the main causes of death worldwide, which has imposed a lot of economic costs on the economies of the countries.Four human, vehicle, road and environment factors are involved in the road accidents, among which, the environmental and climatic factors ...
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Abstract[1]
Road accidents and casualties are one of the main causes of death worldwide, which has imposed a lot of economic costs on the economies of the countries.Four human, vehicle, road and environment factors are involved in the road accidents, among which, the environmental and climatic factors account for a significant share.The components of "frost, humidity and temperature" are among the most effective climatic factors that play a major role in road accidents.Therefore, the present study has been conducted to analyze the distribution of road accidents leading to death with climatic approach in different seasons of the year using Geographic Information System (GIS) in Ardabil province.The research method is descriptive-analytic.ترجمهSince the crash is a spatial phenomenon and Arc GIS analyses are also location-based, GIS and Kriging's interpolation method have been used for analysis.In this research, road accidents in Ardebil province in different seasons of the year and considering the climatic factors of freezing, temperature and humidity in the time period from 1389 to 1393 have been studied.The results of this study show that out of 762 accidents, 35% happened in summer, 25.75% in the spring, 24.55% in autumn and 14.7% in winter.The comparison of the diagram of accidents leading to deaths based on the months of the year, with the diagram of days of frost in Ardebil province indicates that road accidents in Ardebil province during the freezing months are lower due to the reduced traffic of tourists' vehicles compared to non-frosty months. Most of the accidents have occurred with a moisture content of 69-72% in terms of humidity, and at very low temperatures of 8 degrees Celsius and very high temperature of 16 degrees Celsius in terms of temperature.
Keywords:Road Accidents, Climatic Factors, GIS, Ardebil
[1] - به دلیل کیفیت نامناسب ترجمه (چکیده مبسوط انگلیسیِ دریافتی) نشریه، به ناچار اقدام به ترجمه مجدد متن مختصر چکیده فارسی و انتشار آن به جای چکیده مبسوط انگلیسی نموده است.
Ali Ahmadabadi; Amanollah Fathnia; Saeed Rajaei
Abstract
Abstract[1]
Vegetation cover has a high relationship with climatic conditions. Identification of the seasonal variation of plant growth to determine the response of ecosystems to climate change in seasonal and inter-annual time scales is decisive.To present a prediction model, 7 climatic elements including ...
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Abstract[1]
Vegetation cover has a high relationship with climatic conditions. Identification of the seasonal variation of plant growth to determine the response of ecosystems to climate change in seasonal and inter-annual time scales is decisive.To present a prediction model, 7 climatic elements including precipitation, temperature and relative humidity (maximum, average and minimum) for a 20 year period (1987-2006) were converted into spatial data in 141 synoptic and climatological stations. The combination of maximum monthly NDVI values from NOAA-AVHRR images was extracted in the same period. Then climatic elements and NDVI entered the multivariate linear regression as independent variable and dependent variable respectively. The results showed that the highest correlation coefficient between climatic elements and the amount of NDVI was 0.82 and happens in May that is the peak of greenery. The least correlation in winter is due to the lack of sufficient tree growth. Taking into account the random error, the annual correlation coefficient of the model amount with computational mode is more than 93/0. In total, the computational value of May and June for 2004 and 2005 is close to the correlation coefficient of the model, but in the winter months, the correlation coefficient decreases due to lack of greenness.In 2006, there was less prediction due to more severe dryness in the late spring (June). In winter, the role of temperature control is more than rainfall and relative humidity, but with increasing temperature and decreasing precipitation and relative humidity, the role of precipitation and relative humidity becomes positive and temperature becomes negative from the beginning of May. In the autumn, the role of precipitation decreases and the temperature is increased.
[1] - به دلیل کیفیت نامناسب متن چکیده مبسوط انگلیسیِ ارائه شده توسط نویسنده مسئول مقاله، نشریه به ناچار اقدام به ترجمه مجدد متن چکیده فارسی و انتشار آن به جای چکیده مبسوط انگلیسی نموده است.
