Geographic Information System (GIS)
Jalal Samia; Manouchehr Ranjbar Shoobi; Amer Nikpour
Abstract
Extended abstract
Introduction
Visiting Mazandaran province could be a fascinating and memorable trip due to its amazing natural touristic attractions such as Caspian Sea and mount Damavand. The three main roads naming Kandovan, Haraz and Firoozkooh can be used to access Mazandaran province. Among ...
Read More
Extended abstract
Introduction
Visiting Mazandaran province could be a fascinating and memorable trip due to its amazing natural touristic attractions such as Caspian Sea and mount Damavand. The three main roads naming Kandovan, Haraz and Firoozkooh can be used to access Mazandaran province. Among them, passing through Kandovan road is fascinating with its beautiful natural landscapes. At the same time, this road is also known as one of the most dangerous roads of Iran due to its mountainous location and the potential occurrence of different types of climatic and geomorphologic hazards. Apart from these dangers, the occurrence of accidents in Kandovan road is one of the main concerns of tourists visiting west parts of Mazandaran province and also the local governments providing relief and rescue services and facilities to injured people. Therefore, it is crucial to identifying the dangerous sections of this road in order to minimize fatalities and socio-economic losses. The purpose of this research is to investigate the spatio-temporal density pattern of road accidents and also to identify accidents clusters along Kandovan road.
Material and methods
To this end, we used road accidents information along Kandovan road, collected by the relief and rescue bases of Red Crescent organization of Mazandaran province in the period of 2016 to 2022. Information like location, date, and the number of death and injuries in the road accidents along this road were used in this research. First, we used GIS, spatial and statistical analyses in order to get insight from road accidents distribution and statistics. In the next step, Kernel Density Estimation – a Geostatitical measure – was used to investigate the general spatial density pattern of road accidents in the period of 2016-2022 and also the spatio-temporal density pattern of road accidents in every year from 2016 to 2022. Furthermore, the hot spot analysis was implemented to the distribution of road accidents in this period in order to find out whether accidents are clustered, dispersed or randomly distributed. Both general spatial pattern and annual spatio-temporal patterns of accidents were investigated using hot spot analysis. With this, accidents clusters reflected as hot spots were identified based on the Getis-Ord Gi*index and the associated Z-score, P-value and Gi-bin statistics. In this context, the number of accident clusters, the length of road in the accident clusters and the percentage of observed accidents in the clusters were computed from 2016 to 2022.
Results and discussion
Results show that 2084 accidents were occurred in the period of 2016-2022 with 9076 injuries and 52 deaths. The most number of accidents was occurred in 2022 following the end of Corona lockdown in 2021. Also, several parts of Kandovan road indicated to contain the highest number of accidents density. Besides, the accident density pattern changes spatially and temporarily with an increasing trend in the number of accidents density from the end year of Corona disease epidemic in 2020. Results from hot spot analysis also identified several accidents clusters along this road in the period of 2016-2022. In this context, road accidents clusters were identified in Zangouleh Bridge, Majlar, Siah bisheh, Knadovan tunnel and Ushen Bridge with average Z-score value of 3.12, average P-value smaller than 0.05 and confidence interval of 90 to 99%. The total length of road in these clusters was more than 14 kilometer which contains around 60 % of the total accidents. The spatio-temporal distribution pattern of accidents clusters and also road lengths in the identified clusters change decreasingly in the period of 2016-2022. The results of this research can be used to investigate the reasons behind the occurrence of road accidents in the high accidents density sections and also in accidents clusters identified along the road. Taking proper preparation and mitigation strategies can be beneficial in proper crisis management of road accidents in order to avoid human causalities and socio-economic losses.
Conclusion
We conclude that kernel density estimation and hot spot analysis are effective geostatistical approaches to investigate the density pattern of road accidents and also to identify accidents clusters. In order to increase the safety of Kandovan road, the factors contributing to accidents occurrence in highly dense accidents sections of road and also in accidents clusters need to be identified, and with implementing proper measures, their effects can be minimized.
Amer Nikpour; Hamid Amoniya; Sahele Shokri
Abstract
Extended Abstract
Introduction
Sprawl is the process of rapid population growth and spreading of urban developments on undeveloped land near a city with a direct impact on the spatial development which in recent years has become one of the major challenges of cities around the world. Growing population ...
Read More
Extended Abstract
Introduction
Sprawl is the process of rapid population growth and spreading of urban developments on undeveloped land near a city with a direct impact on the spatial development which in recent years has become one of the major challenges of cities around the world. Growing population trend and substantial changes in land use have made scientific and accurate planning a vital requirement for the management of this phenomenon. Accurate planning can help managers and spatial planners achieve sustainable urban and rural development. The present study seeks to enhance understanding about spatio-temporal processes of urban growth and development in Babolsar, identify general factors affecting the formation and spatio-temporal changes of the city and also inform managers and decision makers of the trends and growth patterns to help them in accurate planning, designing and managing. In order to achieve these goals, detailed information about the physical structure of the region in different time periods are collected, changes and spatial dispersion of the study area are observed, and information about the physical growth of the city is also obtained.
Material and Methods
The present study applies descriptive-analytical method to examine population growth and physical expansion of the city. After selecting the geographical area, satellite images captured in 1990, 2000, 2010 and 2020 were obtained from the US Geological Survey (USGS) web site. To calculate Shannon's entropy, the study area was divided into 25 regions based on the distance from central core of the city. Then, total area of each region and each zone (marked in each region for each period) were calculated. Thus, the necessary information was prepared to determine the trend of physical expansion and development of Babolsar city from 1990 to 2020. Shannon's entropy model not only has no limitation regarding the number of areas, but also has a high level of flexibility regarding the types of divisions used for the study area.
Results and discussion
These maps show that Babolsar has always grown both spatially and demographically from 1990 to 2020. The relative entropy of Shannon was calculated for each period and each region, and resulting coefficients show that not only is the rate of sprawl high in Babolsar, but it has always exhibited a sharply increasing trend during the last three decades especially from 2010 to 2020. Since examining expansion and dispersion require a careful consideration of population changes and trends, population of the study area was calculated for each year and its relationship with sprawl was examined. Findings indicate that sprawl has increased along with population increase. According to Holdern model and results obtained in the present study, population is the most important factor affecting physical growth of Babolsar city. It has played an especially powerful role from 1990 to 2000. Three main patterns of spatial development and sprawl can be identified in Babolsar: 1) strip or linear growth pattern spreading the city along the main transportation artery further away from the urban core. 2) Leapfrog development pattern which occurs when developers skip over land to obtain cheaper land further away from cities and thus create separately, singularly, discontinuously developed settlements. 3) Continuous low-density pattern developed due to excessive use of land for urban purposes along the outskirts surrounding the city. Gradual development in this pattern support infrastructure such as water, and energy and road network.
Conclusion
Studies indicate that sprawl in Babolsar city has had destructive effects on the environment and high quality agricultural lands around urban and rural settlements. Especial attention of Iranian society to its northern culture and the concept of "pleasure utopia" which has been assigned to the Southern Coast of the Caspian Sea are considered to be the most important reasons for urban sprawl in this city and other similar cities. Rapid increase in the number of villas built by indigenous and non-indigenous people has resulted in the destruction of high quality agricultural land and irreparable socio-economic damages. Currently, real estate trading, even in the villages of northern region, has not only intensified the sprawl, but also has changed and dissolved the traditional land use systems turning previous land owners into janitors. Other influential factors affecting sprawl in Babolsar and similar cities in the northern region of Iran include inefficient government policies in land and housing section, failure to meet the goals of urban and rural projects, population growth, real estate trade, development and construction codes incompatible with the realities of society, ambiguity in the laws and regulations governing construction within the legal limits of cities, lack of protection for government-owned land and properties, lack of proper supervision in construction projects.
