نشریه جغرافیا و برنامه ریزی محیطی
سال سی و یکم شماره 2 (پیاپی 78، تابستان 1399)

To assess environmental changes, monitoring systems and remote sensing satellites provide powerful tools that make the assessment of environmental change trends easier by multi-temporal comparisons. In recent decades, remote sensing data and GIS techniques for various aspects of urban spatial expansion and urban dispersal such as mapping (for expansion pattern), control (for process pattern recognition), measurement and evaluation (for analysis), and modeling (for Expansion simulation) are used. The object-based analysis is one of the emerging advanced techniques in the classification of satellite images. The object-oriented classification uses a segmentation process and a learning algorithm to analyze the spectral, spatial, and textural properties of the pixels. Along with the object-oriented classification method, Google Earth Engine, with extensive support for free satellite data and images, enables the classification and processing of high-speed satellite imagery that can be used in the monitoring and mapping land use.

To assess environmental changes, monitoring systems and remote sensing satellites provide powerful tools that make the assessment of environmental change trends easier by multi-temporal comparisons. In recent decades, remote sensing data and GIS techniques for various aspects of urban spatial expansion and urban dispersal such as mapping (for expansion pattern), control (for process pattern recognition), measurement and evaluation (for analysis), and modeling (for Expansion simulation) are used. The object-based analysis is one of the emerging advanced techniques in the classification of satellite images. The object-oriented classification uses a segmentation process and a learning algorithm to analyze the spectral, spatial, and textural properties of the pixels. Along with the object-oriented classification method, Google Earth Engine, with extensive support for free satellite data and images, enables the classification and processing of high-speed satellite imagery that can be used in the monitoring and mapping land use.

In the present study, the digital data of the Landsat satellite provided by GEE are used. The data do not require pre-processing and initial correction (geometric, radiometric, etc.) and are readily available for processing. Landsat image types (1 to 8) can be summons with any processing level in GEE. In this study, atmospheric correction images of the Surface Reflectance Tier1 are used. This dataset is modified for atmospheric errors and includes OLI / TIRS sensors for Landsat 8. With simple coding patterns in GEE, the images of 1999, 2009, and 2019 are corrected for the processing step. GEE has provided a modern set of pixel-based classification that can be used for monitoring and mapping. By analyzing the corrected image of 1999, 2009, and 2019 and capturing the training samples, the images are classified with the support vector machine algorithms, random forest, and minimum distance. To perform object-oriented analysis and classification, images are segmented using the multiresolution segmentation algorithm in specialized recognition software. Geometric properties of land use classes (including shape, size, texture) are used for segmentation. By analyzing the results of the segmentation of images with different scale parameters, the optimal values ​​of scale, shape, and compression for the images used are obtained. In this study, based on spatial resolution and image quality, four land use and land cover classes were considered in Zanjan urban areas. These classes include built-up, irrigated and urban green areas, dry farming, and rangelands. By selecting the above classes, training samples for multi-temporal images (1999, 2009, and 2019) are prepared. The nearest neighbor algorithm is used to classify images based on the object-oriented method. In this process, the maximum difference index of mean and NDVI vegetation index are also applied for each of the classes to reduce class mixing and improve the classification accuracy of influential parameters such as normalized difference built-up index (ndbi), mean and standard deviation of each band, area, the ratio of length to width, compaction, and brightness. Statistical parameters of kappa coefficients and overall accuracy are used for the accurate assessment of the classified images. To understand the changes in the area, after producing the land use maps and assessing them, the classification methods are used to evaluate the land use changes that occurred in the period 1999 to 2019. 

After the classification of Landsat 5 and 8 satellite images, land use maps of 1999, 2009, and 2019 are prepared using object-oriented and pixel-based methods. Since in this study the parameters and characteristics of mean and standard deviation of bands, NDBI, NDVI indices, etc. are used to improve the results of the algorithm nearest neighbor object-oriented method, the results of image classification accuracy assessment show that the object-oriented method is weaker in separating rangelands and built-up in 1999 and 2009 than the support vector machine classification method. However, the object-oriented classification results for 2019 show the best performance of all the utilized classification algorithms. Due to the better results of the support vector machine classification method for 1999 and 2009 and the object-oriented method for 2019, the results of these methods are used in the assessment of land use changes in the study area. According to the results, significant changes have occurred in the region from 1999 to 2019. During this period, the land (mainly Zanjan) showed an increase of 5036 hectares. Also, the results show that Zanjan has grown and expanded into rangelands and dry farming in the suburbs over the period 1999 to 2019.

Comparing the results of classifier accuracy assessment, the nearest neighbor object-oriented classification algorithm for 2019 showed better performance in terms of kappa coefficient and overall accuracy than other algorithms. Also, by comparing the results of the assessment of the classification maps of 1999 and 2009, the support vector machine algorithm showed the best performance compared to other classification algorithms in the study area. The support vector machine was the basis for the assessment of changes. Based on the results of land use changes assessment, in recent years, significant land use changes have occurred around Zanjan city. The reason for the increased land area in Zanjan in 2019 (26.12%) is the increase of population and the development of new settlements in the suburbs, and consequently, the reduction of agricultural rangelands.

The climatic history of Chaharmahal and Bakhtiari province in the Central Zagros region shows a huge amount of snowfall in the cold season. In recent years, the tendency of precipitation from snow to rain has increased in autumns and winters and wintertime snowfall has decreased compared to the long-term average of the province, while sometimes springtime snowfall can be seen in the province. In spring, dynamic systems that stimulate atmospheric instability are still present in the region, and sometimes the combination of dynamic-thermodynamic conditions causes heavy rainfalls. In the present study, the dynamic and thermodynamic conditions for three springtime snowfalls were analyzed and the effective moisture sources in springtime snowfall were obtained.
 

Precipitation and temperature values in synoptic stations of Chaharmahal and Bakhtiari province in the period of 2000 to 2018 were provided by the Meteorological Organization. To select abnormal springtime precipitation, the anomaly of temperature, precipitation, and geopotential height at the level of 500-hPa were analyzed. The ERA5 analysis of the data from ECMWF with a horizontal resolution of 0.25° was used to calculate moisture flux, perceptible water and vorticity advection, the monthly anomaly of precipitation, height and temperature of 500-hPa, and instability indices. To analyze the causes of snowfall in spring and also to investigate the sources of moisture, the monthly anomalies of rainfall, the temperature at a height of 2 meters above the ground and height, and temperature of 500-hPa level were compared to the 30-year average (1981-2010). In a dynamic study, vorticity advection at the level of 500-hPa was measured. To identify the trajectory of atmospheric moisture, moisture flux at the level of 850-hPa and perceptible water were calculated. To investigate the thermodynamic conditions and atmospheric instability, Skew-T diagram and atmospheric instability indices including KI, TT, PW, and CAPE were used at Shahrekord station at 00 UTC on the day of snowfall.

Snowfall is a climatic feature of Chaharmahal and Bakhtiari province that also occurs in spring, but in recent years, due to warmer weather and reduced snowfall in winter, snowfall in spring seems somewhat unexpected. Precipitation is one of the quantities whose prediction of location and intensity is associated with uncertainty. Therefore, in this study, for more accurate prediction, the moisture sources, and the dynamic and thermodynamic conditions of spring snowfall in the province were investigated. To select unusual springtime precipitation, anomalies of temperature, precipitation, and geopotential height at 500-hPa were examined. As a result, snowfalls were selected in the spring of 2004, 2009, and 2016, which were different from normal compared to the long-term 30-year average.Examination of the dynamic conditions of the mentioned systems showed that at the level of 500-hPa with the formation of a deep trough in the eastern Mediterranean to the Red Sea, the location of the study area in the east of this trough has caused instability and upward movements. In addition, there is a positive vorticity at the level of 500-hPa. Given that these conditions have occurred for all three systems, it can be concluded that the occurrence of snowfall in spring is due to a dynamic process. It is noteworthy that in April 2016, when the amount of snow was more than the other two cases, the trough formed in the area was much deeper than the other two ones, and the vorticity advection was higher. Analysis of the quantities of moisture flux and perceptible water showed that these systems supplied their moisture from the Arabian Sea, the southern Red Sea, the Sea of Oman, and the northern Indian Ocean. The sources of moisture for precipitation in the region are mainly the Arabian Sea, the Red Sea, the Sea of Oman, and the North Indian Ocean are located more than 2000 km far from the southwest of Iran.Moisture flux continues from a few days before the operation of the system with south and the southwest winds from the Arabian Sea and south of the Red Sea to the southwest of Iran. In addition, the amount of perceptible water on the day of the event increases sharply. Temperature analysis showed that the decrease in temperature on the days of the phenomenon was more severe than the previous days and compared to the climatic average, and the coldness of the entire air column illustrates snowfall in spring. Examination of climatic conditions including anomaly analysis of precipitation showed that their values in all cases were much higher than the long-term and the normal average of the region, and is consistent with prominent temperature and height anomalies at the level of 500-hPa. 15 to 30 decameter drop in height and more than 1° drop in temperature were observed at this level compared to the long term. Cooling of the atmospheric column due to the process of evaporation or melting along the path and especially in the adjacent layers of the earth's surface has an important role in precipitation in snow form. Examination of the values of instability indices in Shahrekord station also showed that these indices were prominent in the hours before the event and intensified the activity and convective cooling of the system.

The results showed that the sources of moisture for precipitation in the region are mainly the Red Sea, Arabian Sea, Oman Sea, and the North Indian Ocean, which were associated with a positive vorticity advection. Examination of thermodynamic conditions also showed that the instability indices in the hours before the onset of precipitation were favorable and intensified the convective activity of the systems. Convection cooling along with a severe decrease in temperature has shifted rain to snow. A significant decrease in temperature compared to the long-term average and the atmospheric cold column justifies the snowfall occurrence in spring.

One of the processes that has been able to create the largest unit of form in geomorphology is the process of karstification. In many cases, the processes are not able to create a landscape or other units, but the karstization process has formed in different scales and one of the frameworks in geomorphology is related to these landscapes (Nojavan, et al., 2017, p. 99). The karst areas provide good opportunities for researchers to study the relationships and evolution of human societies. The recognition of past climatic relations, cave sedimentology, and the possibility of pollen studies, etc. can determine this issue on past human societies and identities. In dealing with various geomorphic units, humans have adapted to the environment according to the capabilities of the environment. According to this issue, the impact of karst landscapes on the realm of human societies and their distribution can be expressed. Karst areas in the past and present have a great impact on improving the condition of water resources and creating a suitable and beautiful visual landscape in the areas. Among these areas, we can mention the karst spring of Gharbalbiz in Yazd. It is noteworthy that this region has an ancient civilization and culture.The importance of recognition of karst areas lies in the way they are exploited. Karst areas are very important to the development of the civilian core.  Regarding the forms of civilization in the past, it has been argued that the distribution and settlement of the population on Earth depend on the levels that have created the right conditions for the creation of the civilian core. The isohyetal maps of karst areas in Iran show that most of them are located on the Zagros Mountains, the Azerbaijani plateau, the northern regions of Iran, the Alborz Mountains, northeastern Iran (Khorasan), and a limited number of other highlands. Currently, 25 percent of the world's population uses karst water sources for drinking (Gillison, 2003, p. 23). The development and expansion of human resource centers depend on the size of karst resources in a region. Karst waters are able to move more than 1,000 kilometers inland and can be used in other regions such as western Iran (Limestone caves in Kalhorud, Asadabad, etc.). Human distribution and urban development are mainly in the western patterns of Iran in the Zagros. The purpose of this study is to investigate the effect of karst and non-karst systems onhabitat patterns index in the Romeshkan region according to environmental conditions.

In this study, the method of synoptic analysis was used. The method of comparing karstic and non-karstic areas was used in terms of how the settlements are distributed. To achieve the objectives of the research, geological maps 1: 250,000, topographic maps 1: 50,000, DEM 15 meters, and Google Earth images were used and the maps were drawn in the Global Mapper and Arc Gis10.5 software environment. After collecting the data, different layers of information were prepared including topographic, geological, karst, scattered caves and karst springs, summer settlements, rural, and urban areas. Each of these layers was matched with the karst areas of the region. Then, descriptive information related to layer overlap was extracted from Arc Gis10.5 software.

Romeshkan is one of the cities of Lorestan province. In terms of geomorphology, it is one of the intermountain plains of the Central Zagros, which is located in the southwest of Lorestan and the northwest of Ilam province. Analysis of Geomorphology and Civilization of the Romeshkan Plain:According to the studied sources and theories of analytical geomorphology of Iran, the Romeshkan plain is one of the inland areas. In this regard, it can be said that it is one of the holes of Iran in the cold and wet Quaternary period. Due to the dissolution in the northwestern parts, its water is drained and it is not possible to trap water at the moment (Safari, 2013, p. 56-57). Oberlander (1956) refers to waterway patterns along with a focal point as evidence of the existence of these lakes. The presence of ancient hills in the bed and margins of these holes is evidence of this claim. In most of these hills, evidence of pottery fragments and remnants of pottery kilns have been found. The presence of such artifacts shows that the shores of the lake were a place of civilization and that the quality of water was far more favorable than during the warmer periods.

The existence of numerous challenges and problems in rural areas has forced geographers to do their research to solve these challenges. It can be said that one of the effective pillars in achieving rural development is the way decisions and policies are made. Futures studies are used to write about the future and possible changes in national, regional, and organizational contexts to respond to change. This study sought to explain the effective indicators in policy-making for rural regions management of Kerman province to help make more accurate decisions for the future of villages and policy-making appropriate to these indicators. In this regard, the main question was: What are the most effective indicators in policy-making for the management of rural areas of Kerman province in the future? The research method in this study was descriptive-analytical. The study followed a systematic and structural view with the method of futures studies and the use of MICMAC software. The results showed that the current policy-making system for the management of rural areas in Kerman province cannot be considered stable and desirable. The most influential indicators in policy-making for the management of rural areas of Kerman province were the environment (score 986), rurality (score 918), economy (score 884), and culture of rural people (score 850). Also, the indicators of the environment (score 952), economy (score 952), the sustainability of policies (score 884) were the most dependent factors. For better policy-making and optimal management of rural areas of the province in the future, strategic variables should be considered including environmental variables as an effective factor and the resulting form of policies, rurality or environmental-social identity, the economic identity of the village, the impact, and economic goals of policies, respectively. It is also possible to develop and sustain the rural management system of the province by manipulating and improving the variables of the economy, the role of the government, and increasing the participation of the people.

Sudden flash floods are generated by severe storms with high peak discharge (Abraham, 1984, p. 163) and are generally due to complex interactions between topographical, geological, geomorphological, and hydrological conditions (Abu Zaydou et al., 2016, 56). The flash flood is a complex phenomenon, whose prediction is very difficult (Cao et al., 2016, p. 2). The flash flood results in severe material damage and even human casualties and extreme erosion (Farhan & Iid, 2017, p. 718). It is the result of the activity of two groups of different parameters. The first group has meteorological features that vary in space and time, and the second group includes constant parameters including geomorphological and geological conditions (Josef et al., 2011, p. 755). The morphometric characteristics of drainage basins are significantly correlated with hydrological parameters (Maysa 2006, p. 1238) and the possibility of estimating their hydrologic behavior. Physiographic factors such as gradient, soil texture, land use, and rock permeability have different hydrological responses to precipitation occurrences in different basins. This affects the formation and characteristics of a sudden flood (Tinco et al., 2018, 595). Qasr-e Shirin Basin, due to the outcrops of Marne and Chile formations, geomorphologically, is an eroded area with a drainage network that is relatively dense and is susceptible to flash flood events due to heavy rainfalls. So far, there has not been any study to assess the risk of flash flood events in this basin since the assessment and zoning of the flash flood event in this basin is necessary. The purpose of this study is to assess and categorize the risk of flash flooding based on the morphometric and physiographic characteristics of Qasr-e Shirin Basin.
 

In this study, two methods of standardization of morphometric parameters and the FFPI model have been used. In the first method, 11 morphometric parameters were used to calculate the degree of risk. These parameters are calculated according to Equations (1) and (2).Equation1 :              HD =
Equation2 :              HD =
The MFFPI model uses six physiographic parameters to capture the potential hazard of a sudden flood. Each of these parameters has its weight and is classified into five classes. The weight of each parameter is multiplied in each of the five sub-parameters and the final score of each layer is calculated (Tinco et al., 2018, p. 596). In the next step, the six-layer layers are assembled in the Raster Calculator and the final map of the potential flood event is calculated (Tinco et al., 2018, p. 507). The layers of the topographic slope (S), flow accumulation (Fa), and amplitude curvature (Pc) are extracted from a 10-meter DEM. Lithology layer (L) from Geological map 1: 250,000 Qasr-e Shirin sheet, Land Use layer (LU) from modified land-use plan of Kermanshah province with 1: 100000 scale, and soil texture layer from 1: 250000 map of Kermanshah province. 

The studied basin has six sub-basins and the drainage network model in Qasr-e Shirin basin and sub-basins is dendritic. In the standardization method, the total sum of the degree values of the eleven morphometric parameters showed that Qasr-e Shirin Basin and sub-basins 1, 2, and 3 have a high potential hazard. Sub-basin 4 has a high potential hazard and sub-basins 5 and 6 have a potential low risk of flash floods. According to the final map, the Falling Flood Potential (FFPI) of Qasr-e Shirin Basin has the extremes of high, medium, low, and very low levels of flash floods. The highest and the lowest risky areas of flash floods have 33.63% and 9.86% of the basin area, respectively. Areas with very low and low risk of flood occurrences correspond to the highlands of the basin, high mountain ranges, and river valleys prevailing on the river bed. Areas with high potential risk and a large number of flash floods are in line with the erosion plain and hill.

Calculating the risk according to eleven parameters showed that 83.3% of the area of Qasr-e Shirin basin had a high risk, 9.5% had a potential hazard, 7.2% had a potentially hazardous risk. In fact, 93% of the area of the Qasr-e-Shirin Basin had a potential high and severe risk of flash floods. According to the second method, about 60% of the area of Qasr-e Shirin Basin had a high potential hazard, about 20% had had a moderate potential, and about 20% of the basin area had a potentially hazardous and very low potential. A review of the map from the MFFPI model showed that the high heterogeneity of this map was influenced by the heterogeneity of slope parameters, directional direction, and flow density. The comparison of the results of the two models suggested that most of the area of the Qasr-e Shirin basin had a potentially high risk of occurrence of a flash flood. The degree of risk method, which is based on the measurement of eleven linear, shape, and ergonomic morphometric parameters, presented the potential risk of a flash flood event for the entire basin. Since the drainage network is responsible for the discharge of the flood, the results had a high degree of accuracy in assessing the risk of a flash flood event in the whole basin. But the MFFPI model used the effective physiographic parameters for creating floods in flood risk zoning and it identified high-risk areas within the basin. Finally, it can be admitted that the results of the two methods, despite differences like the parameters used, are complementary to each other. Based on the results of these models, the Qasr-e Shirin Basin had a high potential hazard in the event of a sudden flood event and the city of Qasr-e Shirin is in a very high-risk zone. Therefore, the Qasr-e Shirin Basin requires the implementation of protective projects and flood control.

Existing challenges in arid regions have caused climatic and environmental problems such as low rain, winds with high speed and intensity as well as lack of vegetation. These problems happen by destroying and transporting particles leading to the influx of sand flowing into agricultural lands and residential centers. This is one of the most concerns of residents in the arid and desert region of the country. Because, it causes a lot of life and financial losses, the move of sands, and the formation of sand dunes are influenced by interactions between wind flow, the site of deposition, and the morphology of the sedimentation site that gives rise to wind landforms. The vegetation cover plays an important role in determining the morphology and dynamicsby influencing transportation conditions and trapping the sand carried by the winds. This process takes the form of creating a wind vision during a natural reaction, with the creation of the Nebaka phenomenon. The phenomenon appears in desert areas to neutralize wind erosion stress. Accordingly, the presence of vegetation is a prerequisite for Nebakas and controlling the flow of sand flows in arid and desert areas due to the specific climatic conditions in these areas. Numerous studies have been conducted to investigate the effect of vegetation factors on Nebaka formation. The volume of Nebakas is influenced by the vegetative form. The volume of its constituents is different from each other. Vegetation factors have played an important role in the development of Nebakas. Studies have shown that the vegetation cover has the main role in the formation and development of Nebakas so that vegetation reduces sediment replacement and limits its source. Among the critical areas that are referred to as the main focus of wind erosion, the Sistan region has always been affected by wind erosion. The present study was conducted with the aim of investigating the effect of vegetation restoration on morphometric components of Nebaka and its effect on sand dunes stabilization in the Nimroz area of Sistan province.

To achieve the purpose of the present study, after floodwater spreading and forestry operations in the Nimroz area of Sistan during 2003, parameters of Nebaka including Nebaka high, Nebaka base diameter, Nebaka volume, vegetation cover, plant height, wind direction, and back to the wind in 45 Nebakas to the Tamarix species were measured at different time intervals in a 16-year period by restoration vegetation and installing 5 linear transects with a length of 50 m randomly in the area. Then, by measuring the morphometric properties of Nebakas, the correlation of morphometric components was investigated using correlation analysis and multivariate regression analysis.

In the correlation analysis regarding the morphometric characteristics of Nebaka, the findings showed that a significant correlation (at the level of 0.99) of the plant characteristics such as vegetation cover and high plant parameters such as Nebaka high, Nebaka base diameter, Nebaka volume, wind direction, and back to the wind. The multiple regression analysis approved 92.9 percentage of the volume changes of the Nebaka with the vegetation cover. Investigating the amount of sediment stabilized in the Nebaka also showed that increasing vegetation wills increased the volume of Nebaka in such a way that with increasing vegetation, the volume of Nebakas on average increased from .0.53m3 in 2008 to 15.69m3 in 2018 with the amount of stabilized sediments increased from 184.97 ton to 879.79 ton. The statistical comparison of the measured data showed that there is a significant difference (at the level of 0.01) between the mean stabilized sediments in Nebakas during the research process. According to the results of the study, the restoration of vegetation in the study area shows a good background for the formation of Nebakas. As a result, a considerable amount of sands has stabilized in these Nebakas.

In this study, the role of wind activity in the formation and development of Nebaka areas where wind power was low was confirmed. Based on the result of this research, a significant amount of wind sediments has been stabilized in Nebakas. As a result, the Sistan area is always affected by wind erosion and the problem of sand dunes. The method of restoring vegetation by doing flood and forestry plans in susceptible areas is effective to stabilize the sand with the creation of the Nebaka phenomenon in the study area. Re-vegetation in the study area has provided a good basis for the creation of Nebakas in the region.