عنوان مقاله [English]
Urban development and land use pattern changes have far-reaching environmental effects. Increasing the size and number of cities in the future Human activities such as changing land uses, consuming more resources and emitting pollutants have negative effects on the functioning and structure of the urban system and disrupt the circulation of materials and energy. Population growth, different social and economic conditions of cities, providing high quality housing in cities, fragmentation, destruction of natural habitats due to urban development, while becoming one of the major challenges for managers and planners, It has forced cities to withstand pressures beyond the carrying capacity of environmental refinement and reabsorption capacity. Urban carrying capacity refers to the amount of population or development that can continue in an area without any impact in the area that is too acceptable.
This article tries to look at the city of Karaj as a system that has been disrupted due to human intervention, structure, function and processes, and through the correct identification of pressure forces, resources and reservoirs and analysis of their status. To study and monitor the pressures resulting from development in urban regressed systems and by monitoring the indicators of pressure on the urban environment, the stability of the city in the form of load number index and finally in the process of planning and environmental management the life of Karaj city should be used. The study of the Total Load Numbers (TLN) obtained in the districts of Karaj shows that none of the urban districts at the time of the study, according to the 18 indicators, is in the range of the optimal total load number. district 1 of Karaj city had high-to-very high range.
In this study, in order to evaluate the pressure on the urban environment in the city of Karaj, after reviewing information sources and frost documents and preparing existing maps, a number of effective indicators based on weighting analysis and calculating the coefficient of importance of indicators using the method entropy and SMART FILTER were determined. Then, the loading numbers were calculated for each of the indicators in the degrees of carrying capacity and the mapping of these indicators was done in GIS and in each of the areas based on these loading numbers. Finally, the zoning and status of each area of Karaj was determined based on environmental pressure and loading number model (Figure 1).
In this research, using the PSIR framework, in addition to structuring information, it is possible to determine important relationships as well as achieve a comprehensive understanding of environmental problems and finally to achieve practical and environmental management solutions. Therefore, effective indicators in the context of pressure-status-effect-response are selected to assess the state of the urban environment (table 3).
In order to create a model of loading number from the city board, each of the indicators, in case of minimum allowed (desirable) and maximum allowed or allowed (threshold) is classified into 6 categories and according to the amount and intensity of the index within the allowed limit Winning is given to them to the degree that is called the degree of carrying capacity (DCC) (table 1).
In this model, indicators are placed in 6 categories called "Degree of Carrying Capacity (DCC)".
In order to calculate the degree of carrying capacity of the indicators, the standards, base values and tariffs for each indicator have been used, which have been calculated for the group of selected indicators, including status, pressure and effects indicators (table 2).
In order to compile the spatial model of urban board capacity based on PSIR framework, the indicators are selected using Smart Filter and entropy methods and their importance coefficient is determined. Table 3 shows the importance coefficients of indicators.
After determining the importance coefficients of indicators by the importance coefficient matrix, DCC of each indicator was multiplied by its IC. The resulting number represents the pressure on the urban ecosystem based on the concept of carrying capacity. It also indicates the priority of pressure indicators called the load number (LN). LN= DCC x IC
To evaluate the total carrying capacity of 18 pressure indictors, the carrying capacity table and the total pressure number of 18 indicators were used (Table 4).
After determining the DCC and LN of 18 indicators in Karaj, the total load number of these indicators was calculated (Table 6) and the LN maps were prepared (Figure 3, 7). This maps shows the distribution of pressure in different areas of Karaj and is an appropriate tool to investigate and locate critical points and to compare the overall situation in different areas. The total load numbers of the studied zones in the areas of Karaj city and the areas with the highest number of loads were identified and prioritized. Then. In each region, the priority of each indicator in creating pressure was examined (table 5).
After calculating the values of the load numbers of each indicator in the study zones, district 1 with the loading number of 312.845, which is in the 3rd to 4th group of the carrying capacity of the total loading number degree, has the highest amount of loading number, the highest of which in the group of indicators is equal to 236.18 and belongs to the indicators, The situation. Then the pressure indices with loading number 47.88 and in the third place are the effect indices with loading number 28.785.
The results of this study show that the city of Karaj exceeds the desired environmental level with high pressure on the urban carrying capacity and reveals the need for management and planning to reduce the pressure on the land in the urban areas of Karaj.
It should be noted that obtaining the final loading number means a very high pressure and is within the threshold of all indicators, which seems unbearable to achieve, placing the loading number in this range can indicate a high and threshold of most Indicators and requires special attention to the situation of the land in the area whose loading number is mentioned in the range.
According to the load number model studied in this study, the applicability of this model in all urban areas is shown and it is easy to compare the load numbers from each urban area to compare the environmental pressure on the urban ecosystem.