Analysis of Erosion and Physical Resilience Factors in the Worn-out Urban Texture of Ilam City

At the beginning of the 21st century, the world has witnessed great natural and unnatural disasters. The Great Hurricane Katrina, the Southeast Asian tsunami, the Bam earthquake, and dozens of similar incidents, large and small, repeatedly remind the world that predictions, solutions, and ways to deal with these disasters are still inadequate. And only a small number of nations in the world learn and apply the science and technology of managing and controlling such disasters. In recent years, disaster relief agencies and organizations have focused most of their work on achieving a disaster resilient community. Therefore, risk reduction programs in the crisis management organization should seek to create and strengthen the characteristics of resilient societies and in the accident management chain, the concept of resilience should be considered and promoting resilience and reducing its risks should be increasingly the agenda of planners and politicians. This study was conducted to investigate the effects of resilience erosion factors in the worn-out urban texture of Ilam city to reduce the effects of natural disasters. Accordingly, this study tries to evaluate the relationship between erosion resilience and the risk of natural disasters and to study the indicators and factors affecting physical resilience.

The present research is based on library and field studies in terms of development and has an applied purpose in terms of descriptive-analytical methodology adopted. To achieve the objectives of the research, indicators were extracted in two sections and 8 categories including material, building age, skeleton, number of floors, granulation and permeability in the physical section and slope, soil type in the erosive section. Then the model of erosion and physical resilience through the colonial competition algorithm (MST minimum cover tree) in Matlab 2016 software environment was presented. And for specialization of the studied indicators in the worn-out texture of Ilam city, the method of tracking analysis tool has been used in the network analysis process in ArcGIS software environment.

In order to investigate the effects of erosion and physical factors, resilience was performed through the tree of minimum condition according to the analysis steps and a comparison matrix of 8 * 8 was prepared and its model was presented. Based on the input of real and directional network input information in the worn-out texture of Ilam city for identifying the resilience status, different effects and patterns were presented according to the eight indicators. The output corresponding to the most optimal scenarios implemented in MATLAB 2016 environment was presented in the format. Based on the existing priorities, there are 8 indicators to study the level of worn-out texture in Ilam city to study the status of resilience. By transferring this data and information to the Arc Gis software environment, we spatialized these indicators. Also, the structure of the first scenarios was used in the local search phase and the next two structures were used in the jump phase. In each structure, after determining the locations and assigning the indicators to this physical context, the optimal paths to achieve the goal were updated through central network analysis and in the ArcGis environment for each source/destination node pair. In each scenario answer, if the path between the source/destination node pair included two scenarios, then one of these scenarios would be selected according to the indicators and constraints in the physical context. The results of this study also showed that among the spatial indices, D and H indices, i.e., building age and permeability, obtained the highest score among the analytical codes. In order to study the spatialization of the existing scenarios for the erosive and physical characteristics of the worn texture of Ilam city, first all the information of Matlab software environment was transferred to GIS environment by reading and correcting the information and finally through Tracking Analyst Tools and Make Tracking Layer tool the existing scenarios and codes were constructed. The status of construction and design of the purpose-built network structure for erosion and physical indicators was presented in such a way that at the level of 8 indicators studied in two parts, the following results were obtained: In the erosion index section, one condition was completely suitable, three conditions were suitable, 5 conditions were moderate and 1 condition was completely unsuitable. In the physical index section, there were one completely suitable condition, three suitable conditions, 5 moderate conditions and 1 completely inappropriate condition. In order to determine the current status of resilience indices in the worn-out texture of Ilam city, after classifying the indices in ArcGis software environment, the type, area and percentage of each index were extracted. According to Table 6, after determining the current status of resilience indices in the area of ​​eroded texture of Ilam city, the percentage and area of ​​each index from high resilience to low resilience were presented in four categories for each index. In the material index, the highest percentage, ie 33.61%, was in the cement block type and had a low resilience status. In the building age index, the highest percentage, ie 47.00%, was in the type over 30 years old and had a very low resilience status. In the skeleton index, the highest percentage, ie 33.57%, was in the concrete type and had a high resilience status. In the index of number of floors, the highest percentage, ie 47.11%, was in the type of one class and the resilience status was very low. In the granulation index, the highest percentage, ie 34.13%, was less than 100 meters and the resilience status was very low. In the permeability index, the highest percentage, ie 62.78%, was less than six meters and the resilience was very low. To investigate the final resilience of worn texture in Ilam city, the amount of physical resilience was shown at the level of 6 indicators, so that at this stage, after aggregation of the mentioned indicators in Arc Gis software environment, the final resilience of the building resilience was classified into very low to very high. They are categorized to plan for natural disasters to deal with any potential crises.

In the present study, after extracting the erosion and physical resilience indices in the eroded texture of Ilam city, indices in two parts and 8 categories including material type, building age, skeleton, number of floors, granulation and permeability in the physical part, slope, and soil were extracted in the erosion section. Then, the priorities in resilience levels from very high resilience to very low resilience were identified in seven categories. The results of the research are as follows: Among the spatial indices, D and H indices, i.e., building age and permeability, obtained the highest score among the analytical codes obtained from scenario writing in the content programming environment in such a way that significant parts of the worn texture of Ilam city are in the range of medium to very low resilience. Also, the central part of the city, which corresponds to the dilapidated fabric of the city, due to the lack of a standard structural system and sustainable materials and the inability of residents to create safe areas indicated low and very low resilience. This situation becomes more visible in the event of natural disasters, and the financial and human losses will be doubled. In addition, the results of spatial differences and the study of spatial resilience comparisons showed that 62% of the eroded texture of ​​Ilam city is in the range of relatively low to very low resilience. Percentage and area of ​​each part of the resilience of the worn-out texture of Ilam city were such that 5.25 had a very high resilience interval, 5.65 had a high resilience interval, 8.70 had a relatively high resilience interval, 18.33 had medium resilience interval, 17.90 had a relatively low resilience interval, 21.03 had a low resilience interval, and 21.14 had a very low resilience interval.