جستجوی مقالات مرتبط با کلیدواژه « مدل تخریب » در نشریات گروه « محیط زیست »

Protected areas in the country requires monitoring and protection measures due to reduced quality. Therefore, in this regard, degradation model could be applied by quantifying human activities The aim of this study was environmental impact assessment of development in Bagh-e Shadi protected area using the degradation model in 2020.

 To implement this model in the study area, first the area was divided into 406 pixels with a scale of 1: 50,000 and dimensions of 500 x 500 cm. Using existing maps, field observation and experts' opinions, 8 factors of degradation model in the whole region were identified and their severity was determined.

The results showed that among the identified degradation factors, tourism activities had the most degradation in the protected area of Bagh-e Shadi. Then, the ecological vulnerability of the area was calculated using slope, direction, altitude, climate, soil depth, vegetation density, temperature, rainfall, land use with GIS tools and classified according to severity. After calculating the physiological density, the degradation coefficient was calculated in each of the pixels and was classified into 6 classes and 3 categories based on fuzzy theory.  Then all networks are compared in terms of severity and extent of degradation and the whole region was divided into three zones: prone to further development, in need of reconstruction and in need of protective measures.Discussion and

 The results showed that in terms of land quality, 27.83% of the region is in the category of prone to further development (second categories), 35.22% in the requires reconstruction categories, 29.31% in the categories requires protective measures 64.7% are in the floor in need of protection measures (first categories).

In terms of natural structure and geographical location, our land has major constraints on the biological and sustainable production of biological systems, and most of its biomes are forests that naturally have fragile biological systems and, if exploited outside their capability, they are simply exposed to destruction. Therefore, due to the multifunctional nature of forests, it is necessary to assess the environmental impacts of forest management plans. The main purpose of the present study is to evaluate the impacts of forest activities as well as planning to minimize and prevent negative environmental impacts and maximize the positive environmental impacts of the Lirehsara forest management plan using the destruction model approach. In this regard, environmental degradation modeling was performed to determine the environmental impacts of forestry activities in the Mashalak Forest. In this study, compartments were selected as the impact unit. After determining the degradation factors, 14 identified factors were included in the model and the final destruction map was created. The results of the degradation model showed that the study area was divided into four zones of potential development, requiring restoration 1 and 2 and requiring conservation measures. Accordingly, 49.70% of the study area was in degradation class 1 and susceptible to development, 35.15% and 9.78% in degradation class 2 and 3, respectively, in need of restoration and 5.3% in degradation class 5 and in need of protection measures. According to the results of this study, it is recommended that protection measures and further development in the area be prioritized and remedial measures for forest protection should be considered. One of these measures could be the elimination of the destructive factor of the mine and the other non-accumulation of waste in the forest.

In recent decades, the population of urban areas has increased dramatically and many vegetations have fallen prey to the onslaught of urbanization. Human beings, regardless of the main factors of the environment and its tolerance, have caused excessive destruction of the environment and endangered the survival, growth and health of current and future generations. On the other hand, in recent years, the ecological approach of Landscape in assessing environmental impacts has been greatly welcomed due to the use of the concepts of spatial integrity as the main basis in environmental planning. The processes and phenomena that exist in environmental systems are often dependent on many variables and there are very complex relationships between components that make it very difficult to analyze. This problem always causes errors in the accuracy and precision of model predictions, so examining the performance of networks and finding the best type of neural network to achieve acceptable and more reliable results is one of the priorities and modeling concerns. As a result of using these concepts to evaluate the appearance of the land, while saving time, the evaluation of the outcome of the activity can be determined cumulatively and in the shortest time. Land degradation model is one of the environmental impact assessment methods that quantitatively represents the effects of human activities in region or watershed scale. In fact, the degradation coefficients that are obtained by this model is an index of the damage done by human activity in a region. the main problem is that this model at some stage of implementation, relying on expert judgment and in addition need to extensive field work. so in this study investigated the relationship between land degradation and landscape ecological metrics that are descriptive index of landscape. Understanding this relationship and identifying metrics that have a strong correlation with degradation coefficients, is very effective to investigation feasibility use of these metrics in degradation model in order to future objectivity. The area of Arak city, using the political border map and in ArcGIS 9.3 software environment was 315 networks (networks 5 km 5 km and 25 km2) on the ground, some of which were full network and some incomplete networks. The degradation, ecological vulnerability and physiological density and then, degradation coefficient were determined. In the next stage, landscape metrics using Patch Analyst software based on the land use map was calculated. Finally, the correlation between the degradation coefficient and landscape metrics using the SPSS 17 software was analyzed statistically. After reviewing the described results, metrics with correlation with destruction numbers that were common to all 4 levels of study were determined in each user. The TLA measure was omitted because all networks are the same in all networks and applications because of the same size. Agriculture: NumP, PScov, TE, AWMSI Range: NumP, TE, AWMSI City: NumP, PScov, TE CA, Barren lands: NumP, PScov, TE, MPE, AWMSI CA, In forest use, there were no measured water areas that had a significant correlation with degradation numbers and were common to all 4 levels studied. The results showed that the metrics that were surveyed, two metrics: total edge (TE) and the number of patches (NumP) had the highest correlation coefficient with land degradation. By changing the scale (network size), the result will not change, so it can replace the degradation model. The findings of the degradation model indicate the destructive effects of industrial and transportation activities in Arak. In this research, artificial neural network was also used. ‌Multi-layered non stero peryspector, in comparison with other methods, has a high accuracy and predictive power and modeling of the factors influencing it. Network estimates were evaluated by MAE, RMSE and R2 criteria. In natural resources, due to the confusion and scatter in the data and the flexibility of the feed-through neural network with two hidden layers, data processing usually begins with two hidden layers. Therefore, network training was performed with four neurons in the input layer, three neurons in the first secret layer, one neuron in the second hidden layer and one neuron in the output layer. The network estimates were evaluated by MAE, RMSE and R2 criteria. Comparing the actual volume output with the network output predicted by the network is another way to evaluate the model. As can be seen, the black dots are the measured dots that indicate how much volume has been added. Based on the results obtained from the implementation of the demolition model in Arak city, it was found that destructive activities such as pollution of factories and various industries, "motor vehicles" and domestic, commercial, etc. heating sources, which were observed in most work units, as well as climatic and geographical conditions of the city. Arak (being surrounded on three sides to the mountain, towards the west and southwest winds and adjacent to Miqan desert) are the main causes of destruction. According to the results obtained in Arak, out of a total of 94 work networks, 37 networks need to be reconstructed due to their location within the boundaries of protected areas, and 22 networks due to high physiological density and high intensity of destructive factors. 21 networks are undevelopable due to faults. Existence of powerful and active faults such as Kooshak, Ensrat, Tafresh, Indes, Tabarteh, Talkhab, and Leopard spring are the most important faults in the province, which indicates the potential for earthquake risk in this province. 35 networks have the first to third development priorities. These networks, which are mainly located in the western and southwestern parts of the city, have low physiological densities and are located farther away from the city of Arak, where the severity of destruction is still high. There is no crisis and the future development of the city should be directed to these areas. Industrial growth has created many job opportunities as a result of the migration of large numbers of people from the cities, villages and villages of Markazi province and other provinces to meet the needs of the growing population. Urban and industrial areas are in this direction. Finally, considering what has been said about the natural sensitivity of the region's ecosystem and the results of the destruction model in this city, it seems that with the continuation of the current trend, there is a possibility that the intensity of development and economic activities will exceed the natural capacity of the region. In which case it will be very difficult and even impossible to restore it to its original state; For this reason, it is necessary to implement large-scale development projects that have a great destructive effect.

Land degradation modeling is one of the environmental impact assessment methods that quantitatively represent the effects of human activities. The purpose of applying this model is identifying vulnerability factors and destruction of ecosystems, to prevent further destruction by other project and also to show feasibility of future development to decision markers.

first The study area was partitioned into 94 cells, 1600 ha each and then Fourteen degradation factors were identified along with their intensity using land use map, field observations and expert views. So the determination of ecological susceptibility and physiological density was determined and all cells were classified to 4 categories: recommended for development, zones that require reconstruction, protection and cells hadn't development potential based on fuzzy theory.

The results show that from 94 cells, 22 cells (23.40% of the total area) require reconstruction, 37 cells (39.36% of total area) have no development potential, and 35 cells (37.22% of total area) are recommended for development. 

The effects of destructive activities (which are mainly destructive effects of tourism activities) in the region are obvious, so that destructive activities such as land use change and river pollution to the region on the one hand. They are the main causes of destruction of the 94 cell, 21 cell due to faults and 16 cell due to being in the Binalood protected area, have no development potential. 35 cell are recommended for development in first to third priorities, these cells are in low physiological density area and 22 cell due to high physiological density and severity destructive agents has a high degradation coefficient and need to be reconstructed, and therefore any future development in this area, should be excluded.

Today, most of protected areas in the country require serious monitoring and protection measures due to reduction of quality. Degradation model with quantifying the effects of human activities can be used in monitoring and improving the situation in these areas. To implement this model in Bashgol protected area, the sub watersheds were selected in the area as the impact units. Using maps, field observations and experts’ opinions, 25 destruction factors in the whole area were identified and their intensities were determined, also ecological vulnerability of the area was calculated with GIS tools using geological, physiographic, climatic, vegetation, habitat and other maps (16 factors) and was classified in terms of intensity. After calculating the physiological density, destruction coefficients were calculated in each unit and were classified based on fuzzy theory into 3 categories and 6 classes. The results showed that 8465/51 hectares (34/7%), 12013/44 hectares (49.23%) and 3920 hectares of area (16/07%) are located on the 2nd class prone to development , the 3nd class (need to rehabilitation) and the 5nd class (need to conservation), respectively in terms of the quality of the land. Generally, according to local conditions, without the further development, the objectives of area management must go toward the restoration and protection measures.