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Volume 2, Issue 2 (7-2015)
With the development of economy and social services, increased need to reduce risks, control risks and other important measures in order to provide program management and follow-up plans vulnerability, Having the right information and understanding the current situation in the field is essential for prevention and planning measures, Therefore, research on risk reduction and knowledge of threats in the Arangeh region is essential, as one of the areas tourist attraction regions in Karaj's catchment area.
Geomorphology of River studies landforms and processes of river and predict changes using models and field studies and laboratory. And new analytical tools and techniques, growing and expanding with the help of river engineering.
This eventually leads to gain new capabilities in the field of river management, landscape restoration, risks and geomorphological studies ancient river.
In most cases geomorphological processes that are created by river systems, are causing environmental hazards of natural and human environments. In this paper, we have investigated the risks of geomorphic processes, especially risks of flooding and river flooding and is calculated for the maximum flood discharge for subarea also. In this article, it has been found that most of the flood will be calculated based on the map of the geomorphology of the area and the discharge sub basin. The purpose of this study, is assessing damages caused by the flood risks in the area. It is obvious that the results of this study will enable the pre-crisis phase of the crisis management system and can help to tourism and physical planning in the area.
Arangeh basin is an area of 10,090 hectares and a maximum height of 3665, at least 1637 m and average height of 2689 m. Arangeh area have an annual precipitation about 785 mm. Arangeh watershed is located within the northern city of Karaj, 15 km Karaj Branch, Karaj Dam east side of the river and inferiors (Amir Kabir).
In this study, to analyze the flood in the basin, a variety of sources are used including surveys of library data and documents, topographic base map scale of 1: 25,000 geological map of 1: 100000 taken from the ground geological, climatic data obtained from meteorological Organization, hydrological data obtained from regional water Alborz Landsat satellite image.Also field visits, the use of GPS and GIS software Arc GIS Version 10 was main parts of the survey.
The calculated concentration time by Krpych method to estimate the flood of data base, then estimate is based on a regional analysis of runoff and peak discharge of flood.
According to Hydrogeomorphic properties basin unit (sub-21) has the maximum flood discharge which is mostly covered by alluvium and located on the ground impermeable siltstone, waterways due to morphological features steep, mountainous dominant morphology, concentration time low basin, poverty and lack of vegetation (about 15 and 50 cubic meters per second in the 50 and 100-year return period). Other sub-basin with high flood discharge of sub No. 3, 5,7,9,12,14 and 16 are in Central, East, North, East and South of the basin villages.
Many parts of the Arangeh basin has slopes of more than 60%, which is an important factor in the effect of runoff, reducing the time of concentration, poor soil and vegetation and is an important factor aggravating flood risk and erosion. The presence of vegetation in these areas can have an important effect in obstructing runoff, reduce the rate of runoff, reducing flooding and consequently the reduction of soil erosion. We can largely control the flood basin watershed management practices and proper management range in the above units.
Volume 9, Issue 1 (5-2022)
Investigation of Construction Wastes Release in Roadside Using AHP
Introduction
Although construction waste is an integral part of municipal waste, due to the differences between this waste and waste and environmental issues, a suitable model should be designed for optimal productivity and acquisition of resources. The increasing volume of urban materials and rubbish, especially the rubbish from the destruction of their construction and worn-out urban textures, has created many problems in large cities, as well as environmental problems that have arisen due to unprincipled and unprofessional disposal of these materials. Has attracted these materials. Research shows that the amount of this waste is equal to 10 to 15% of the total materials used in construction operations. This amount is much higher than what is estimated by the estimators.
Data and research method
In Iran and other developing countries, construction and construction waste is a major part of municipal waste, which in addition to high costs for its disposal, also has adverse consequences on the environment. The volume of this garbage is so much that now this issue has become a social and environmental problem not only in Iran but also in developed countries due to the limitation of natural resources and preservation of national capital for future generations as well as environmental protection And it is necessary because with proper management and efficient planning and reducing the volume of construction waste, not only the waste of natural resources and national capital is prevented, but also additional and ancillary costs are reduced and it is economically beneficial.
In this study, first, the effective criteria in selecting the burial site in the study area are determined. These criteria are reviewed and used by various standards, including standards related to the Environmental Protection Organization, the Ministry of Interior and international standards, as well as by reviewing resources and studies on the process of locating landfills in the country and abroad and by examining the conditions of the region. The study and the influencing factors are compiled in the study area. The layers related to each criterion in the relevant table will be prepared, processed and converted from the relevant organizations. The method of this dissertation is applied-modeling in terms of purpose, because on the one hand, the concepts and rules related to the field of knowledge are carefully analyzed, and on the other hand, the relationships between these concepts and rules are evaluated and determined by experts. In this study, there is a need to use the decision theory method to evaluate and investigate the status of construction waste disposal along roads to increase trust and confidence in decision making.
The data analysis tools of this research are SPSS, Expert Choice and Matlab for conducting the research. In the research process, after data collection, the next step involves data analysis. Cronbach's alpha coefficient was used to evaluate the reliability of the localization tools of the research components. In order to describe the data, the mean and standard deviation of the research data have been used.
The four-step process of multi-criteria decision-making process and fuzzy logic calculations to investigate the dumping of construction debris along roadsides is as follows:
Step 1 - Modeling causal relationships based on similarity to the ideal solution
Step 2 - Parallel comparisons and determining the weight of causal relationships based on the evaluation of decision options between the criteria for assessing the status of construction debris on the sidewalks,
Step 3 - Prioritize Based on Causal Relationships Based on Evaluation of Decision Options
Step 4 - Fuzzy Prioritization and Final Analysis Investigation of Construction Waste Disposal Status
Result and Discussion
The most important results of the study of the dumping of construction debris along the roadsides are that,
1- The most important criterion in the cluster "Environmental factors of construction waste disposal" with code (A), "Soil pollution in the city" with code (AB) with fuzzy network weight of 0.096; And
2- The most important criteria in the cluster "Applications of GIS in urban management of construction debris disposal" with code (B), "Urban green space management" with code (BA) with fuzzy network weight equal to 0.191; And "Urban management related to health" with code (BB) with fuzzy network weight equal to 0.120; Were calculated. on the other hand,
3- The most important criterion in the cluster "Economic factors of construction waste disposal" with code (C), "Construction waste management training cost" with code (CD) with fuzzy network weight equal to 0.123; Prioritized,
conclusion
The results of the present study can be said that, after reviewing the theoretical foundations of the research and reviewing the research background, it was found that due to research gaps in the fields of economic factors of construction waste disposal, GIS applications in urban management, construction waste disposal, environmental factors, Utilization of a combined fuzzy multi-criteria decision-making methodology to investigate the status of construction debris dumping along roadsides; It is possible to realize the innovation of the present research in filling the mentioned research gaps.
Key words: Construction Debris, Civil Waste Management, Multi-Criteria Decision Making, Karaj.
Volume 11, Issue 1 (5-2024)
Nowadays, deep learning as a branch of artificial intelligence acts as an alternative for human with hopeful outcomes. Open Street Map as the biggest open source data is used as a complementary data sources for spatial projects. It is notable that is some advanced counties the accuracy of VGI data is higher than governmental official data. This research aims to use artificial intelligence to produce and subsequently promote completeness of OSM data. Res_UNet architecture was utilized to train landuse categories to the network. The result shows that IoU metric is about 83 percent that implies a high accuracy paradigm. Then, united-based method was used to calculated completeness of OSM data. The unit-based results show that completeness of building blocks, forest, fruits garden and agriculture land are: 3.6, 9.7, 90.4 and 81.88 respectively. It shows the low volunteer participation rate to produce OSM data. On the other side the high accuracy achieved by deep learning leads us to complete OSM data by artificial intelligence instead of human prepared data. The advantage of using machine rather than human may be utilized in undeveloped countries or low density population regions as well as inaccessible areas.
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