Geomorphology
shahram roostaei; Davod Mokhtari; Christineh Jananeh
Abstract
IntroductionSlope instabilities are one of the most distinctive types of geomorphic hazards that are exacerbated by human interference and threaten most of the human installations, especially mountainous highways and impose heavy costs on the government and local residents. Each year, slope instabilities ...
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IntroductionSlope instabilities are one of the most distinctive types of geomorphic hazards that are exacerbated by human interference and threaten most of the human installations, especially mountainous highways and impose heavy costs on the government and local residents. Each year, slope instabilities cause enormous economic damages to highway, railways, power transmission and communication lines, irrigation and watering canals, ore extraction, as well as oil and gas refining installations, infrastructures in cities, factories and industrial centers, dams, artificial and natural lakes, forests, pastures and natural resources, farms, residential areas and villages or threaten them. Nowadays, many instabilities are resulted by human intervention and manipulations. One of the effective human factors in instability occurrence is the construction of highway. Highway construction, especially in mountainous areas, increases the probability of occurrence of various types of instabilities, as it changes the natural balance of the slopes and causes deformations in the land. Each year, lots of casualties and financial losses are imposed by the occurrence of various types of instabilities in the slopes overlooking the highways, which also cause the destruction of many natural resources in the country. However, the construction of roads, highways and freeways is necessary and unavoidable in today’s life.The Tehran-North highway will be the route that connect the Iran’s capital Tehran with the southern shores of the Caspian Sea.Materials and methodsThis contribution aims to study slope instabilities along this highway using logistic regression method. In this regard, layers of 14 effective factors were identified, comprised of elevation classes, slope, aspect, geology, land use, precipitation, distance from fault, river and highway, normalized difference vegetation index (NDVI), climate, slope length (LS), stream power index (SPI) and topographic wetness index (TWI). Consequently, maps of the factors responsible for instabilities were prepared as separate layers in the GIS environment and transferred into the Idrisi software. The whole procedure included: (1) preparation of digital elevation model (DEM), river and fault layers based on the 1:25,000 topographic map of the area, as well as distance maps from rivers and faults, (2) creating slope and aspect maps from DEM, (3) preparation of land use and NDVI maps of the region based on unmatched classification of Landsat 8 image of OLI sensor, (4) preparation of geological map, (5) preparation of precipitation and climate layers based on the information obtained from the meteorological organization, (6) creating LS, SPI and TWI layers based on the DEM, (7) conversion of the distribution data of the regional instabilities using Landsat satellite and Google Earth images, (8) correlating the information layers with the regional instability map and calculating their density per unit area, and (9) performing the logistic regression model using Terrset software.Result and discussionResults obtained by applying logistic regression model showed that the most important factors affecting slope instabilities in the Tehran-Soleghan highway area are distance from fault and climate. 27.14% of the Soleghan highway area possesses medium to high potential for instabilities, within which 86.26% of the instabilities have occurred. Furthermore, 4.57% of the Soleghan highway area shows very high risk in terms of instability occurrence, encompassing 61% of the occurred instabilities. According to the prepared maps, the middle and southern parts and a small section in the north of the Tehran-Soleghan highway area have the highest potential for instability occurrence. The high value of the ROC index and its proximity to the end value of 1 indicates that instabilities strongly correlate with the probability values derived from the logistic regression model. Additionally, the assessment of the instability potential map by the SCAI index showed that there is a high correlation between the prepared risk maps and the occurred instabilities, which have been confirmed by field surveys. The obtained results are in a good agreement with the general opinion that SCAI decreases especially in high and very high risk classes and indicates a high correlation between the prepared risk maps and the occurred instabilities and field surveys in study areas.ConclusionFinally, it can be mentioned that the logistic regression model is suitable for preparing the zonation of the probability of instability occurrence along the edges of the studied highway. As a final conclusion, it can be concluded that in addition to natural factors, the- human-made factors and particularly unsystematic highway construction can play an important role in the instability occurrences on the slopes overlooking the highway and in order to reduce the relative risks and increase the stability of the slopes, it is necessary to avoid manipulating the ecosystem and changing the current land use as much as possible, in addition to policy making for constructions in accordance with geomorphological and geological features of the area.
Urban Planning
Hassan Mahmoudzadeh; Khalil Gholamnia; Saidmohamad Mousavi
Volume 22, Issue 64 , September 2018, , Pages 267-287
Abstract
The uncontrolled development of the city as a kind of risk arises. Drastic changes in land use around and inside the city limits of good land degradation and environmental pollution that can threaten human health and the environment. This research have taken place to predict the development of the City ...
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The uncontrolled development of the city as a kind of risk arises. Drastic changes in land use around and inside the city limits of good land degradation and environmental pollution that can threaten human health and the environment. This research have taken place to predict the development of the City of Sari and surrounding villages and to achieve the perfect result from satellite imagery of Landsat series (years 1365 and 1394) and layers of information such as distance to fault, distance from the river, distance from Energy lines, sensitivity of rock units, distance from roads, urban development modeling with logistic regression model was used. With using ROC the validity of the model was calculated 0.7603 that confirms the model probability results validity to predict urban growth. After mapping, the possibility of urban development and population growth prediction, two scenarios with historical approaches considering the normal development of the Environmental Approach to conserve forest, garden and water levels for the study area up to the year 1404 were defined and accordingly urban development in the direction lands was limited. According to calculations inside the city of sari within an area of 481.88 hectares and a population of over 50,507 people and in a range of 151.36 hectares outside the city a population of over 12805 people in 1404 will be added. According to results, the management needs to necessary urban and rural administrative measures to comply with environmental issues for urban and rural areas that will be added in the next 10 years.