فصلنامه جغرافیا و پایداری محیط
پیاپی 34 (بهار 1399)

The natural contrast between alluvial and aeolian geomorphic systems on the western margin of the Petergan Playa creates a balanced and stable environmental condition, while human intervention in the one of these systems leads to environmental instability and natural hazard expansion. In this paper, having determined the territory of the alluvial and aeolian landforms, morphology and origin of aeolian shapes have been carried out by stepwise method and the geomorphology of alluvial shapes has been studied and classified using satellite images, aerial photographs and field surveys. The morphotectonic response of alluvial systems in contrast to the aeolian systems has been calculated using neotectonic indices. Finally, using the indices of motion, velocity, contact angle, and variations of the alluvial and aeolian landforms extracted at two different time points from the satellite images, the types of contrast and possible contact between them are determined and analyzed. According to the results, in 10 years about 11.3% of the territory of alluvial landforms has been converted to aeolian ones. Thus, aeolian systems overwhelm the region's alluvial systems. The predominance of aeolian systems has been made by diverting and blocking the flow of water and flowing over the channel shores caused by the movement of sand dunes and in many cases ponds and other channels have been created along the main channel of the river. The permanent alluvial systems in the area show stable and cyclical behavior so that the dominance of alluvial systems decreases to a certain extent during the activity seasons of the aeolian systems. The research findings show that during the 10-year period, only 1.8% of the territory of the aeolian landforms in the region has been converted to alluvial landforms. This type of contrast can be observed along the permanent river of Tajnood which passes through the sand dunes on the eastern slope of Mount Khaje.

 More than 30 percent of the earth surface is covered by deserts. Although there are not many habitants in these places, these lands are mostly privileged spaces for distinctive economic and cultural activities. Development and expansion of dune hills and dune fields are the most obvious form of desertification. Dune fields are not just covered by aeolian landforms, so in present dry regions, interactions between alluvial and aoelian systems are completely obvious. The Petergan Playa drainage basin is approximately 4300 km2 in the vicinity of Afghanistan country which has a cool semi-arid climate. In this area sand dunes and fields are the most widespread. Natural interaction between these two systems in western margin of the Petergan Playa has created a balanced and stable environmental condition, while human intervention in one of these systems leads to environmental instability and expansion of hazardous conditions.

In this study, two groups of geomorphic forms with completely different morphogens are investigated which consist of alluvial and aeolian. The territory of the main alluvial and aeolian landforms in the region are determined, then the study of morphology and origin of aeolian forms have been carried out by stepwise method and the geomorphology of alluvial forms has been studied and classified using satellite images, aerial photographs and field surveys. In this section, based on the computation of geometrical indices of rivers, including: width, depth and ratio of width to depth, the pattern of rivers channel is studied. Morphometric calculations of sand shapes on the riverbed and shoreline and alluvial forms of alluvial fans in the area have also been carried out using aerial photographs, satellite imagery, and field surveys. In this step, considering the role of active morphotectonics in the deformation and displacement of alluvial landforms and finally sand dunes, active morphotectonic indices including: mountainous frontal sinusitis, channel pathway abnormalities and dimensionless hypsometric index have been investigated. Finally, the types of interactions between these two groups of landforms are classified according to the predominance of the activity of the alluvial and aeolian systems at the contact site. Accordingly, only six distinct class types can distinguish how these two types of landforms interact.

According to the results obtained in the period of 10 years, about 11.3 percent of the territory of alluvial landforms has been converted to aeolian ones. Thus, aeolian systems have the most influence on the region's alluvial systems. The predominance of aeolian systems has been made by diverting and blocking the flow of water and flowing over the channel banks caused by the movement of sand dunes; and in many cases ponds and other channels have been created along the main channel of the river. The permanent and temporal alluvial systems in the region have different behavior, interacting to Aeolian systems. These systems could dominate the aeolian systems especially in regions like Ahangaran Mountains because of neotectonical activities. According to the results obtained in a period of 10 years, only 1.8 percent of the aeolian landforms in the region are converted to alluvial landforms. The interactions of permanent rivers in the region show stable and cyclical behavior so that the dominance of alluvial systems decreases to a certain extent during the activity seasons of the aeolian systems. These interactions are observed alongside of the permanent river, Tajnood, which passes through the sand dunes on the eastern slope of Mount Khaje. An overview of the overall balance of transformations found in the activity of sand dunes and alluvial landforms over a period of 10 years indicates that this trend is positive in favor of sand dunes of more than 9.5 km2. Given the purpose of this study in examining the natural trend of desertification processes in the face of desertification, it is observed that the trend of activities of natural desertification factors in the study area is expanding. In the meantime, the trend of natural desertification factors emerging in the form of alluvial landforms relying on tectonic forces is not significant against desertification processes.

Chronological study of the depositional interaction between alluvial and aeolian systems which are created in certain landforms in the surface of the ground, presents the condition and the trend of regional landscape considering the geomorphological and ecological characteristics. Interactions between alluvial and aeolian systems and the process of sediment transition between these two systems in the studied region result in changes of one system or both systems. Climate changes in relation to the interaction of these systems can create conditions to dominate alluvial systems which can also change the condition to favor Aeolian systems. Meanwhile, tectonic changes play a role in increasing the alluvial systems' capabilities over aeolian systems. In some limited cases, the dominance of alluvial systems in the region over aeolian ones is the result of alluvial system empowerment based on tectonic changes in the region.

Lightning is one of the most severe weather hazards that will cause significant economic, social and environmental damage each year. The prediction of a lightning is a very difficult task due to the spatial and temporal expansion of weather either physically or dynamically. Therefore, timely forecasting of lightning and evaluation of the best data mining model is effective in reducing damage. In this research, the data of the years 2012_2018 of the Meteorological Station of Rasht were used, including dependent variable of occurrence and non-occurrence of lightning during 7 years and independent variables of factors affecting lightning including temperature, relative humidity, cloudy, wind speed, wind direction, pressure air and Previous day's lightning. After preprocessing and processing data, data mining models including Classification & Regression Tree (CART), Chi-squared Automatic Interaction Detector (CHAID), Induction of Decision Trees (C5) and neural networks Radial Basis Function (RBF), Multi Layer Perceptron (MLP) and Support Vector Machine (SVM) were used in Spss Modeler Ver 20 software. The results of the models were compared with the Comparative Criteria and the Receiver operating characteristic (ROC) curve. According to the results of the models, the probability of lightning occurrence is higher in the months of May, June and July than in other months and the rate of occurrence from spring to winter has a decreasing trend, while in winter it is at least. CHAID tree with a specificity rate of 0.794 and a minimum false positive rate of 0.205 and the SVM model with a correct prediction of 0.773 and an error rate of 0.475 and precision of 0.855 have optimum performance compared with other models. 

Lightning is the ionization of the atmosphere due to the increased potential difference between the cloud and earth and the rapid discharge of electricity in the form of light and sound waves. Increasing the intensity of Lightning lead to thunderstorms, heavy rain, floods and tornadoes. Rasht is the largest rice-growing city in the country and produces 11% of the required rice in country. In recent years, lightning accidents such as rice stalk sleeping and the risk of paddy disease, roads blocked due to floods, traffic congestion, damage to buildings and the falling bridge and mortality from the electric shock have doubled the importance of predicting lightning in the future. The main purpose of this study was to use recorded ground data from the occurrence and non-occurrence of lightning (binary data) and the effect of related meteorological parameters (temperature, relative humidity, cloudy, wind speed, wind direction, pressure air and previous day's lightning) to estimate the probability of lightning occurrence in future using data mining (trees and neural network models) and evaluate and determine the optimal model to reduce future damage.                                                                                              

In this study, binary data of lightning and atmospheric parameters (temperature, relative humidity, cloudy, wind speed, wind direction, pressure air and previous day's lightning) were obtained from Rasht Meteorological Station during the years 2012-2018. Then according to Eq. (1) the data were normalized between zero and one and data classes were balanced using RUS and ROS algorithms in Rapid Miner software. Xn=X-Xmin / Xmax-Xmin  Eq. (1)the process of changing variables with determination of statistical properties and correlation was performed using SPSS software to reduce the errors. Finally, SPSS Modeler software was used to predict occurrence and non-occurrence of lightning in future using by CART, CHAID, C5 trees and Multi Layer Perceptron (MLP), Radial Basis Function (RBF) and Support Vector Machine (SVM). In this research, the training data set contains 70% of the data and testing data set contains 30% of the data. Then, based on the relations (2 – 9) the results of the models output were evaluated with interpolation matrix, comparative criteria and ROC curve.                
 Eq. (2) Accuracy=TP+TN/ TP+TN+FP+FN
Precision=TP / TP+FP Eq. (3)
Sensitivity=TP / TP+FN Eq. (4)                                                    
Harmonic Mean=2*P*S / P+SEq. (5)                                     
Specificity=TN / TN+FPEq. (6)
False Positive Rate= FP / FP+TNEq. (7)
False Negative Rate= FN / FN+TPEq. (8)
RMSE= √1/N Ʃ(P-O)2Eq. (9)
Where, O signifies the observed value, P denotes the predicted value, TN indicates the true negative rate, FP indicates the false positive rate, FN shows the false negative rate, TP shows the true positive rate and N signifies the number of data.   

Lightning is one of the most important environmental hazards. Data mining technique is a suitable method to predict lightning. The results show that prediction using data mining technique is possible and effective. Based on the results, the probability of lightning occurrence is the highest in spring (May and June) and summer (July); it is minimized in winter and has a decreasing trend. Therefore, the probability of lightning occurrence in the future is higher than non-occurrence of lightning. Besides, among the three tree, CART, CHAID and C5, the CART and C5 trees had less satisfactory indices lacking the highest accuracy and precision in predicting lightning in future. Whereas the CHAID tree in 0.76 cases made a correct prediction with 0.85 precision and predicted the occurrence of lightning rate to be 0.54, which is very similar to the real value 0.62, and among the network artificial models Support Vector Machine (SVM) model with maximum utility with prediction of 0.77 accuracy and precision of 0.85 and prediction of 0.60 probability of lightning occurrence have priority and superiority than Radial Basis Function (RBF) and Multi-Layer Perceptron (MLP) models. According to the classification and Area Under Roc Curve (AUC) among the trees, the CHAID tree with 0.829 value and the Support Vector Machine model with 0.853 value have superiority. The numerical results are obtained and the similarity of this prediction with real values ​​shows that trees and network artificial are effective in predicting the probability of lightning occurring in the future and the CHAID tree and Support Vector Machine model have optimal performance compared with other models showing better predictability.                                                                                                         

According to the results of the model outputs, it was found that the probability of lightning occurring in Rasht city is very high. The models show the probability of lightning occurring in April has the same trend but the maximum lightning occurred in spring (May and June) due to unstable weather conditions and summer (July) is more than autumn and winter. Besides it has a decreasing trend, from spring to winter which is minimized in winter. From the evaluation of the CHIAD tree and the Support Vector Machine model, the Support Vector Machine model with a slight difference in utility indices of accuracy = 0.773, precision = 0.855, harmonic mean = 0.813, root mean square error = 0.475.  False negative rate = 0.198 was identified as the optimal model in predicting lightning in future and with respect to reliable outputs with maximum accuracy, precision and least prediction error, the Support Vector Machine model has a good performance which can be used to forecast the probability of  lightning occurrencein Rasht City. Also, according to the results of the models, the effective parameters to occurrence of lightning in order of Importance are previous day's lightning, temperature, pressure air, relative humidity and cloudy; other parameters are less important. Using data mining techniques and predictingprobability of lightning occurrence in future use by Support Vector Machine model, as a model with most accurate and precision, provides more accurate meteorology and the more effective actions to reduce future damage.

Soil salinity and soil salinization as one of the problems facing agriculture and natural resources are of great importance which needs to be prevented with proper knowledge. In this regard, it is important to obtain information about soil salinity and vegetation, such as their amount and distribution. The use of satellite data enables extensive study of soil salinity and vegetation. Since vegetation in most arid and semi-arid regions is strongly influenced by soil properties such as salinity, therefore, this study investigated the effects of Interceptor Drain on soil salinity and vegetation changes using remote sensing capabilities in a 15-year interval. Results showed that construction Interceptor Drain in Salt Marsh Qazvin plain had no effect on soil salinity changes and vegetation cover. According to the results of correlation test between measured soil elements and satellite image bands, bands 5 and 7 were highly correlated with soil SAR (Sodium Adsorption Ratio) index prior to drainage construction and thus, the two bands after drainage construction had a significant correlation with soil EC (Electrical Conductivity) index. In fact, indices including red and infrared bands showed a significant relationship with soil salinity parameters. Also the results of correlation test of remote sensing indices and ground data in the salinity area showed that SI (Salinity Index) index had a highly significant correlation with soil salinity data.

One of the methods of salinity monitoring is ground-based data, which can be time-consuming and costly, especially if large-scale monitoring is performed over multiple time periods. Using Remote Sensing method and georeferenced and laboratory data, soil salinity changes over time can be monitored. The spectral reflectance of a variety of salts at the soil surface has been studied in several studies which has been used as a direct indicator in remote sensing. However, when the soil moisture is high or the salt layer is not visible at the soil surface or the salt is mixed with other soil components, the direct salinity detection approach will become more complex. However, vegetation and saline-friendly plants can be used as a sign of soil salinity for indirect detection and identification of saline areas based on spectral reflectance of plants. The purpose of the present study was to investigate the trend of soil salinity and vegetation changes using remote sensing capabilities in two intervals before and after construction of Interceptor Drain in Salt Marsh Qazvin plain. Therefore, the trends of soil salinity and vegetation changes over a 15-year period have been studied.

The study area is located in a part of Qazvin province, 150 km northwest of Tehran and the major cities adjacent to the area in Qazvin are Takestan  in the west, Abike in the north and Dansfahan in the southwest. Due to the geological conditions of the bedrock and deposition of sediments and groundwater discharge from Qazvin and Hashtgerd Plains, the marsh has been formed which has become saline due to years of severe evaporation. Most saline species have little growth in the salinity range and only in the months when rainfall increases and it is moderately saline, the plants with moderate to low salinity resistance and with a low vegetative period have a short time. Then, with increasing salinity, the soil is seated and dried; only saline-resistant plants in this area survive for the remainder of the year.In this study, spatial and temporal variations of vegetation and soil salinity were investigated using Landsat 7 satellite images. After calculating salinity and vegetation indices, the spatial variability map of soil salinity and vegetation index was prepared. In this study, Landsat satellite images during years 2004 to 2018 were used to study the trends of soil salinity and vegetation changes in Salt Marsh Qazvin plain. After analyzing the remote sensing indices in the study area, the data from satellite images and georeferenced data were compared. The soil salinity and vegetation indices used in the study included 6 soil salinity indices and 5 vegetation indices. The soil samples used in this study were related to 99 observation wells dug in the Proximity of Interceptor Drain of Salt Marsh Qazvin plain during 2010 and 2012.

According to the results of correlation test between measured elements in soil and satellite image bands, bands 5 and 7 were highly correlated with soil SAR index before drainage construction, and thus two bands after drainage construction, with soil EC index. The use of different soil salinity and vegetation index equations gives the results the differential preferences to achieve adequate soil salinity and vegetation index estimation on a large scale using remote sensing data. The evaluation of different soil salinity indices was based on the Statistical test. Statistical test results comparing mean at seasonal variations scale showed that remotely sensed indices related to soil salinity monitoring including BI, SI, SI1, SI2 and SI3 indices showed significant response to seasonal changes in surface soil condition. On the other hand, indices related to monitoring of vegetation status showed a significant difference in vegetation status from spring to summer. The results of correlation test of remote sensing indices and ground data expressed that in the salinity range of SI index there was a significant correlation with soil salinity data. Mean correlation results demonstrated that GVI had a high negative correlation with all salinity indices, but there was less correlation between salinity and other vegetation indices. The satellite images used in this study indicated the highest correlation with soil salinity in the dry months of the year and the correlation between the two factors was reduced in the months with precipitation. Soil salinity estimation based on SI index has been investigated in several cases which revealed that this index is accurate in estimating surface soil salinity in arid and semi-arid regions.

The present study showed that Interceptor Drain of Salt Marsh Qazvin plain had no effect on soil salinity and vegetation changes in the region, so none of the 11 indices derived from satellite images had significant changes in the period before and after drainage. In other words, soil salinity and percentage of vegetation in the Salt Marsh Qazvin plain have not changed significantly over a period of 15 years. However, due to the dryness of the area and the lack of rainfall as well as the incidence of drought, the fresh water content for natural leaching of adjacent drainage lands is limited and the drainage increases the intensity of groundwater flow and reduces soil salinity by creating a hydraulic gradient. Strengthening of vegetation in the area is affected by drainage. As the Qazvin Plain is one of the agricultural hubs of the country, hence the expansion of saline lands is one of the biggest threats to agriculture in the region. Since deep soil salinity status is one of the important factors in the establishment of vegetation in the region, studies combining remote sensing method, geophysical data and simulation models can lead to a better understanding of the status of the area.

Conservation planning needs to identify the perceptions of local communities about the distribution of uses. Required areas for supporting welfare of these communities within and around protected areas is called community use zone. Based on theoretical foundations and given that every place has value or values for local communities, it is possible to identify local values by combining participatory approach and explicit spatial approach. The aim of this study is to identify community use zone in Dena district and in the vicinity of the Dena protected area. In this regard, ethnography is applied by practices such as semi-open questionnaire, field observation and literature review and then is complemented by participatory mapping. Collecting data of local values (Subsistence, economic, cultural and conservative) is continued until the information saturation. Participants marked these hotspots of providing services on four basic maps. After digitizing the data, the spatial overlapping of these areas has been investigated. Community use zone is designated by counting the overlaps of subsistence, economic, and cultural values. Most of this zone is around rivers, roads and settlements. Within the Dena preserved area is influenced by economic and cultural uses. The conservative value identified outside the protected area requires participatory conservation planning, too. Dual-value and three-valued area in the community use zone should be a priority in educational planning and financial supporting for sustainable use. Future programs in Dena district should be focused on such actions: Prevention from firing and cultivating in the forests, prevention from land use change, increasing irrigation efficiency, proper cultivation management, prevention from irregular harvesting medicinal and edible plants, and prevention from illegal hunting of wildlife. Applying the method of this research provides a common language for the dialogue between conservation and community uses. It also provides the ground of training, empowering and attracting the participation of local communities and learning from them.

Conservation planning needs to identify local community' perceptions about the distribution of uses. Required areas for supporting welfare of these communities within and around protected areas called community use zone. Given that Local communities value every place, it is possible to identify local values by combinatory and complementary methods. The concepts and methods of planning and managing protected areas and their surroundings have two main approaches: Area-oriented and process-oriented approach. The area-oriented approach is based on the science-based top-down land use planning experience and mapping with geographic tools has led to conflicts with Conservation which because of the ignorance of local communities. The most advanced method of this approach is the use of spatial information to make decision through ecosystem services mapping. The process-oriented approach includes soft social methods to create opportunities for dialogue, participation, adaptation and agreement, but its results do not lead to explicit spatial boundaries and regions, such as participatory rural appraisal and community-based conservation. Therefore, increasing the effectiveness of conservation planning requires the development of combinatory practices of the two approaches (area-oriented and process-oriented). In this regard, there are two confirmatory theories: The "Cartography, ethics & social theory" argues that the absence of social values in the content of the mapping has caused the mapping to be distanced from the democratic and human form of geographical knowledge. Also, "Cartographic semiosis" is a theory that knows map performance beyond description and representation and in communication and prescription form by deconstructing in the mapping and registering of place values. Such a map is a social product that finds institutional legitimacy by considering the perspectives of local communities. The aim of this study is to identify community use zone in Dena district and in the vicinity of the Dena protected area.

In this research, ethnography is applied by practices such as semi-open questionnaire, field observation and literature review which is then complemented by participatory mapping. Participants (some residents of settlements in Dena district) have been selected and collaborated voluntarily and by trying to balance the age, gender and population ratio of the settlements, during spring and summer of 1398 SH. Collecting data of local values (Subsistence, economic, cultural and conservative) is continued until the information saturation. Participants marked these hotspots of providing services on four basic maps. After digitizing the data, the spatial overlapping of these areas has been investigated.Community use zone is designated by counting the overlaps of subsistence, economic, and cultural values.

Parts of the Dena preserved area are affected by economic and cultural uses  which is especially noticeable around the Sisakht town. The conservative value identified outside the preserved area requires participatory conservation planning.  Local value overlapping shows the conservative local value depicted by the participants has no spatial overlap with other mapped values. Also, the largest overlap was between cultural and economic values and then subsistence and economic values. The overlap of economic and subsistence values was related to adjacency livelihood activities to income generating activities. Besides, the overlap of economic and cultural values is mostly related to the conventional livelihood of tourism revenue and the attractions of culturally valuable areas. The community use zone includes value areas which respectively have three types, two types or one type of three subsistence, economic and cultural values. The major distribution of this zone is close to and concentrated on the areas which have noticeable natural and human built features. In other words, the major surface of community use zone is at an altitude below 2500 meters and around rivers, roads and settlements. Dual-value and three-valued area in the community use zone should be given priority in educational planning and financial supporting in order to sustainable use. Future educational and participatory programs in Dena district should be focused on such actions:Prevention from firing and cultivating in the forests, prevention from land use change in gardens, increasing irrigation efficiency, proper cultivation management and waste control, prevention from irregular harvesting medicinal and edible plants, and prevention from trapping and illegal hunting of wildlife.

Applying the method of this research for other districts provides a common language for the dialogue between conservation and community uses. It also provides the training and empowering ground and attracting participation of local communities and learning from them. Such recognition can help reduce the scope of conflicts, increase compliance with conservation, strengthen the motivation for continued participation in conservation and finally make the resilience of land use allocation decisions between development and conservation.

The Urban Heat Island (UHI) describes the temperature difference between urban and rural temperatures. Finding urban heat island mitigation strategies is of great importance, given expected influences on human health and air quality. This study presents numerical simulations over a summer period to investigate the impact of urban heat island control measures on Tehran urban air quality. The WRF-Chem Chemical Mesoscale Model is used to investigate the effect of increasing urban vegetation and highly reflective surfaces on the concentration of primary pollutants (CO, NO) as well as secondary pollutants (O3) in urban canyons. In order to account for the heterogeneity of urban areas, a multi-layered urban canopy model is coupled with WRF-Chem. Using this canopy model at its broad range requires introducing several urban user classes in WRF-Chem. Tehran metropolis is considered to simulate designed experiments in the summer of 2016. The selected reduction measures in the simulations are able to reduce the urban temperature by about 1-3 degrees Celsius and average daily ozone concentration by 5 to 10 percent. The modeling results also presented secondary negative effects on urban air quality, which is strongly related to the reduction of vertical mixing in the urban boundary layer. The simulation results show a 1 to 20% increase in the primary pollutants (NO and CO). Despite the daily average decrease in ozone concentration, highly reflective surfaces due to severe short-wavelength radiation that accelerates photochemical reactions can lead to an increase in the peak ozone concentration by up to 9% at noon hours.

Significant emission of heat from human activities and overheating of synthetic surfaces over natural surfaces leads to urban heat island formation. The average annual temperature in central areas of a large city is at least about 1-3 ° C above the surrounding area. On calm nights, city centers can experience temperatures as high as 12 ° C. In addition to the health problems caused by rising temperatures, the effect of increasing rates of photochemical reactions, which in turn worsens indoor air quality, is also of particular importance (Oke, 1982). Specific measures such as the use of green roofs or facades and materials with high reflectivity are able to reduce the intensity of the urban heat island. The purpose of this study is to use the WRF-Chem model, coupled with urban parameterization schemes, to investigate the dynamical and chemical processes when applying conventional reduction strategies. The study area is the urban area of ​​Tehran as one of the most polluted cities in Iran.

To show the three-dimensional structure of urban areas, the urban parameterization plan was used along with the Noha land surface model. In order to show the heterogeneity of urban land levels and to use urban modeling with its full expansion, the main urban class (1) in the WRF / Chem model was divided into 3 subclasses (31-33). The range of the model for the internal nest was 103 by 79 network cells with a horizontal resolution of 1.33 km. In order to identify morphological features for each class of Tehran urban area, the characteristics of roads and buildings (building height, street width, albedo level, vegetation, etc.) as well as thermodynamic properties and roughness characteristics within the model were updated. The simulation period was July 17 to July 23, 2016, a period of thermal stress in Tehran that could be considered as a special period for future weather conditions in Tehran. The basic mode (control) was simulated along with urban planning strategies such as increasing urban vegetation (park), increasing building surface whiteness (albedo), and changing building density (density) for further study.

During the study of simulation sensitivity, different meteorological and pollution parameters of the simulated air in the default mode were compared with the average observations of the three urban metering stations. The correlation between simulations and observations, except for CO, was greater than 0.5, and the model performed well in reproducing various parameters. Comparing the results of simulations with observational data, it can be stated that the model generally simulates the hourly changes of meteorological variables well, but more or less estimates the concentration of air pollutants during the simulation period (Grossman and Sobert and Clark, 2013). One reason for the comparison method is that simulation outputs are extracted at the beginning of each hour, while measurements are reported as average or average daily (Akbari et al., 2001). To investigate the effect of different reduction strategies, the effect of each strategy on the concentration of different pollutants was simulated. On average, the air temperature decreases by 3.37 degrees Celsius and 1.7 degrees Celsius, respectively, for the albedo and park scenario. In relation to the primary pollutants CO, SO2 or NOx, the positive effect of reduced temperature is reversed. This was particularly the case for a scenario in which the whiteness of the roof and walls of buildings increased (the relative increase in primary contaminants by up to 20%). An increase in ozone concentration of up to 9% for the Albido scenario was found around 1300 hours, which could be due to a further increase in ceiling and wall surface whitening from 0.2 to 0.7 (Takabayashi and Moriyama, 2007), which is 67% higher than the increase in use. It was done by two other studies (Taha, 2008 and 1997-A) and on the other hand, the maximum decrease in air temperature in Tehran urban area was 2.170 C, which is about 0.83 33 2.83 33 C lower than the decrease. The temperature was reported by Taha (2008).

Simulation experiments were designed and studied to evaluate urban thermal island control strategies that could have an adverse effect on urban air quality. The selected measures showed positive and negative effects on the concentration and dispersion of pollutants. Albido's strategies and urban vegetation are able to improve air quality, followed by a daily decrease in the average concentration of ozone. Also, lowering the temperature has a significant effect on the dynamic structure of the urban boundary layer. Reduction of turbulent kinetic energy (TKE) due to lower temperatures leads to a decrease in turbulence mixing rate and a decrease in the height of the mixing layer, which leads to higher surface concentrations of primary contaminants. This case study provides simulation for a city in certain climatic conditions, because for cities with different sizes, locations, population densities, emission conditions, or different meteorological conditions, similar actions may have different effects on air quality. In urban planning, the social effects of parks on increasing the well-being of citizens should also be considered

The forests of the Zagros are one of the most important and fundamental treasures of the country, which plays a key role in providing water and soil resources in this region.The geographical distribution of different plant communities is dramatically dependent on climatic conditions. Changes in climatic elements, such as precipitation, can cause long-term and short-term reactions of various plant colonie. The main purpose of this study is to reveal the spatial changeability of Lorestan forest NDVI index in response to rainfall changes. The vegetation index of Lorestan was detected using Landsat 8 and 5 imageries during 2000-2017. The monthly and annual rainfall also has been obtained using accumulated monthly rainfall of 9 synoptic stations of Lorestan province. The Pearson correlation matrix has been used to analyze the relationship between annual variation of forest cover area and qnnual rainfall index. The results showed that the EVI> 0.4 threshold can be considered as the threshold of the province's forest cover. The correlation analysis showed that the 18-year time series of forest cover, was correlated with the spatial distribution of annual rainfall in Lorestan Province by 0.72 that is significant in 0.95 confidence level (P_value=0.05). Spatial analysis of the implementation of the greenness estimator model showed that the rainfall threshold of oak greenery (EVI> 0.4) was equal to 320 mm, above which the EVI index increased by 0.88 for each millimeter of rainfall growth of the studied oaks.

The geographical distribution of different plant communities is dramatically dependent on climatic conditions. Changes in climatic elements, such as precipitation, can cause long-term and short-term reactions of various plant colonies (Wang et al., 2017). The relationship between vegetation and climatic factors is so close that many researchers, including Coupon, have classified their climate systems based on the overall structure of plant communities (Guard and Prince, 1995). Climatic conditions and vegetation in each region have a two-way, intertwined relationship. In fact, climatic conditions determine the spatial distribution of species, growth period, phenological needs and even natural selection. On the other hand, they create a vegetative cover of a balanced microclimate in the heart of the region general climate, which sometimes differs significantly from the original climate. Borhan et al., 2015).

In this study, two categories of data were used. The first category of data, including the monthly rainfall data of the province during the oak tree growth period (i.e. periods when the average minimum temperature did not fall below 10C is presented. The source of this data was the monthly record of stationary precipitation during the statistical period of 2000-2017 by 9 synoptic stations of the province and the networked precipitation of GPCC climate base. The second group of data used in this study is related to the vegetation index, which was obtained from three red, infrared and blue bands of LANDSAT satellite on a monthly basis for the statistical period of 2000-2018. The Pearson spatial correlation model was used at the confidence level of 0.95 (P-value = 0.05) to analyze the relationship between spatial changes in the forest cover areas of Lorestan province and spatial distribution of precipitation based on annual and monthly scales.

In this study, forest areas, which were obtained by using threshold (EVI> 0.4), showed that the greenery of oaks in Lorestan province was the highest in peak mode (September) on an intra-year scale with rains 3 to 5 months ago. Such a delay has been observed in many other researches, including the work of Sedighifar et al. (2019), which examined the temporal and spatial response of the Hyrcanian forests of Mazandaran province to the climatic characteristics of the region, including precipitation. Secondly, the threshold of oak greenery in Lorestan province, which has been calculated using experimental sampling, has been 320 mm of rainfall, which indicates that the experimental greenery obtained is generally observed in areas where annual rainfall is more than 320 mm per year. The fitted model indicated that on an annual precipitation scale, an increase in each millimeter of precipitation (above 320 mm at the precipitation limit) would increase the EVI index by 0.88, a ratio of 0.46 to the confidence level. 0.95 has been significant. In terms of spatial changes in precipitation, the results showed that precipitation changes in oak habitats could significantly change the area of ​​oak green thresholds, so that according to the fitted linear model, each millimeter of precipitation changes in oak habitats (320 precipitation threshold). Millimeters will lead to a change of 1724 km in the area of ​​these areas with greenery above 0.4.

In this study, it was observed that precipitation of 5 months before the September of each year, ie precipitation from April to June, is the main controller of the greenness of healthy trees in the oak forests of the province. On the other hand, it was determined that the greenery threshold of these forests is 320 mm of annual rainfall. However, in some habitats, forest ash is also seen below this precipitation level. Due to this dependence of the province oak forests on precipitation, the increasing trend of anomalies and irregularities of precipitation is increasing in the future and the temporal and spatial changes of precipitation in the province will have an increasing trend provided that the continuation of the current management process and failure to take protective measures against the oak forests of the province, the process of destruction of these forests has intensified and in the near future the level of these forests in Lorestan province will greatly reduce.

Land subsidence, as one of the natural and geological hazards, can be caused by human activities such as long-term discharge of groundwater and traditional irrigation farming. In the last two decades, climate change and successive droughts, unsustainable management of water resources and overexploitation of groundwater as well as population growth have caused land subsidence in Shahriar plain in the west of Tehran province. The present study aims to monitor and estimate land subsidence using Interferometric Synthetic Aperture Radar (InSAR) approach. Moreover, it tries to investigate the relationship between groundwater level and subsidence rate. Therefore, the time series of the ENVISAT-ASAR satellite images from 2003 to 2010 were used. The Small BAseline Subset (SBAS) algorithm was applied to analyze the time series of land surface displacement and to generate the mean displacement velocity map. The findings from time series analysis of InSAR data indicate a continuous subsidence occurrence in the agricultural lands of the region. The mean velocity of deformation along the satellite line of sight (LOS) in the time period of study, shows the displacement at an average rate of -10 cm / year and a maximum rate of -27 cm / year in the Shahriar plain in the west of Tehran province. Over this time period, groundwater level decreases about 0.5 to 1.5 m in the aquifer storage at 12 observational wells located in the study area. The overall correlation between changes in groundwater level and subsidence rate was estimated circa 89.45 percent, which indicates a strong relationship between subsidence and groundwater exploitation in the region.

Land subsidence, as a natural phenomenon, is defined as the gradual subsidence or abrupt sinking of the ground surface due to the subsurface material’s compression. One of the common causes of the land subsidence formation is the overexploitation of underground aquifers. The occurrence of land subsidence due to groundwater extraction from aquifers has been studied in several researches and documented in various regions of the world. This phenomenon is known as a global problem and leads to many environmental consequences such as damaging human structures like buildings, streets, bridges and power lines, creating holes on the earth surface, intensifying floods and flooding and reduction of aquifer capacity for water storage and ultimately it poses social and economic risks for human societies. In regions with bounded groundwater aquifers, groundwater discharge causes the reduction of pore pressure and subsequently sedimentary layers are compacted and condensed. This process leads to the downward movement of the ground surface and so-called land subsidence. Surface deformation is often measured using Interferometric Synthetic Aperture Radar (InSAR) technique. Generally, InSAR technique measures the phase difference of radar waves caused by the deformation created on the earth surface in time interval between two satellite pass.

In this study, radar interferometry techniques were used to monitor, estimate and analyze time series of land displacement in the west of Tehran province. Based on the historical archive and free accessibility, ENVISAT images were identified as the best dataset to estimate the land subsidence. Therefore, the level 2 time series data product (IMS) of ENVISAT-ASAR sensor related to frame number of 2889 from descending track of 149 were acquired. The time series selection of SAR data was determined according to the availability of well depth data. In the first step, the radar interferometry method was applied by analysing all possible differential interferograms with respect to temporal and spatial baselines to detect deformation signals (in particular, land subsidence). In the next step, by selecting a set of optimal generated interferograms regarding spatial and temporal baseline and using the SBAS algorithm, the land surface displacement time series were evaluated and the mean displacement velocity map for the region was produced.

The results of using InSAR approach indicate some subsidence event in the eastern part of Shahriar and northwest and west of Eslamshahr with mean velocity of -10 cm per year. Also, the estimated maximum subsidence rate in this region is -27 cm per year. The results of time series analysis, using the SBAS algorithm, showed that the subsidence signals before 2005 occurred at a faster rate compared to the 2005 to 2010. Groundwater level data of study area for the period of 2003 to 2010 generally represents drop in groundwater levels. Due to the slope and elevation (topographic status), the wells located in the northern part of the study area are much deeper than those in the southern part. Besides, the trend of water level decline in this area has not always been descending and sometimes the water level has increased limitedly at certain times. The results indicate that the water level decline has been more severe in the north and west than in the south and east part of region. The results of correlation analysis between changes in groundwater level and land subsidence indicate a high correlation between land subsidence signals and groundwater extraction with an average estimate of 89.45%. The lowest correlation was observed in well No. 2 with a correlation of 52.11%. The highest correlation of 99.96% was observed in well No. 7. The poor correlation between water depth in observational wells and land surface subsidence signals is related to the geological properties of the area and the type of soil which ultimately causes a time delay between groundwater exploitation and subsidence signals. The results also indicate that an average subsidence of 5 to 12 cm have been occurred per 1 meter drop in groundwater level. The results of previous studies related to InSAR processing in Shahriar plain were examined to confirm the accuracy of the obtained results. The results of the time series analysis of land displacement signals to extract the spatial-temporal pattern of the region's subsidence, despite minor differences, are very similar to the results of other studies in the same region. Minor discrepancies in the estimated subsidence rate (sometimes up to 3 cm per year) can be attributed to the type of applied algorithm and radar images, as well as the considered time period.

Having recognized land subsidence phenomenon in the current study, time series images were estimated using InSAR technique in the west of Tehran province. Then, the relationship between subsidence rate and groundwater level changes in the area was investigated. The high correlation indicated that the main cause of the subsidence in this area was the overexploitation of groundwater. Also, the conformity of the spatial patterns of subsidence signals to agricultural lands in the study area indicates the relationship between subsidence event and land use. In this study, for the first time with a deeper look, the relationship between land subsidence and water underground level changes in observational wells was evaluated separately. Due to the observation of nonlinear patterns in relation to the correlation analysis between subsidence and groundwater levels in some areas of the study area, it is suggested that the geological structures of each well be separately examined and compared with the amount of subsidence in future research.