جستجوی مقالات مرتبط با کلیدواژه « land use » در نشریات گروه « منابع طبیعی »

Shrubs with diverse ecological functions cover a large area of arid and semi-arid lands. Evaluation of changes in soil properties in shrublands can be effective in understanding the ecological relationships of these biomes and their nutritional status for land management. In this research, the spatial changes of soil fertility characteristics based on patch structure and open spaces between patches were studied in pure shrubs including Artemisia sieberi, Scariola orientalis and Astragalus myriacanthus types located in the ari lands of the central plateau of Iran. The evaluation of soil yield characteristics and soil quality was investigated by selecting the reference open space between the patches and recording the morphological characteristics of the patches to study the relationship between them. The results showed that the properties of organic matter, nitrogen, phosphorus and soil quality index (SQI) had the most significant changes between the type of shrubland and in the space between patches in each type (P<0.01). The highest value of the soil quality index was related to the under canopy in A. myriacanthus type and was equal to 0.87, and the lowest value was related to the central point of the open space in A. sieberi type and was equal to 0.22. The functional characteristics of plants such as biomass, height and canopy showed the highest correlation with the spatial distribution of elements and soil fertility factors in the open space areas (P<0.05).

Microclimates are small areas in a general climate zone that have their own unique climatic conditions. Vegetation is one of the essential factors in the structure and function of terrestrial ecosystems and one of the basic links of the vital chain of water-soil-plants and atmosphere. One of the vegetations that has been cultivated in arid and semi-arid areas and is being developed in some of these areas, is pistachio orchards. This research, with the purpose of investigating the impact of pistachio (Pistachio vera L.) orchards on the vegetation of their adjacent rangelands, was performed in the Roshtkhar region of Razavi Khorasan.

First, three areas of pistachio orchards, as three replicates, that were similar in terms of climatic and physical conditions including topography (elevation and slope), soil characteristics (texture, structure, salinity, and depth of groundwater), and vegetation types, were selected. In each area, a pistachio garden was selected that was adjacent to a rangeland at least up to a distance of 100 meters, and after that was located a pistachio garden, abandoned agricultural land, rangeland, or irrigated agriculture. The percentage of canopy cover was measured along a 100-meter transect with 10 plots of 1 square meter by systematic random sampling method.

Results showed significant difference between the pistachio garden and abandoned agricultural land, rangeland, and irrigated agricultural land. Also, the average canopy cover of rangeland between two pistachio gardens was 58.4% greater than other land uses. The lowest canopy (37.4%) was related to the rangeland located between the pistachio garden and abandoned agricultural land. The highest changes in vegetation canopy were related to the pistachio garden- pistachio garden, with a standard deviation of 26.02. Also, the least changes in vegetation canopy were related to the pistachio garden- rangeland with a standard deviation of 18.14.

The results of this research showed the effect of pistachio orchards on the vegetation cover of the neighboring rangelands. The greatest effect is in the case where a rangeland area is located between two vast pistachio orchards. This effect can be caused by the creation of a microclimate resulting from the vegetation cover of pistachio gardens. The existence of these effects, which are caused by the creation of a microclimate due to the development of vegetation in a dry and desert area, can be considered for other areas under vegetation cover and in urban and industrial land uses

Saffron is one of the strategic products of the agricultural sector in Iran’s South Khorasan province, the second largest producer which has a special place in Iran's non-oil exports. Unfortunately, the dispersion of saffron lands and the existence of smallholder units, while increasing costs and reducing yields, have made it difficult to use new technology and implement modern irrigation projects and has reduced the profit, productivity and production efficiency of saffron growers in the region so that in recent years, many saffron growers have gradually devoted saffron lands to other crops. Land consolidation strategy is of great economic and agricultural importance. This strategy can lead to the optimal use of production inputs. The purpose of this study is to investigate the factors affecting the land integration by saffron growers in Ghaenat county in South Khorasan province. In the completed questionnaire, lands were divided into three levels of small, medium and large-scale farms in terms of size. The results showed that the final effects of the variables of number of households, new technology and tools, knowledge of new production methods, existence of risk in production and performance have been effective on the integration of saffron farmers' lands in both medium and large land levels. In level 2 lands with medium scale (between 3 to 5 hectares), the variables of yield, technology and new tools and knowledge of new methods of saffron production have a significant negative, negative and positive effect on the use of medium scale lands, respectively. Level 3 lands (large scale), the effect of two variables on the number of households and the existence of risk in saffron production on land integration and use of large-scale lands have been negative and significant and the three variables of saffron yield per hectare, new technology and tools and Knowledge of new methods of saffron production with sizes of 0.003, 0.16 and 0.06, respectively, has a positive and significant effect on land integration or large-scale land use. Therefore, by increasing the yield of saffron per hectare, new technology and tools and knowledge of new production methods provide better conditions for land integration and large-scale land use. Therefore, it is suggested that by awareness and informing saffron farmers about new technology and tools, as well as by training and acquiring more specialized knowledge in the field of saffron production, farmers from land integration or the use of large-scale lands in order to improve efficiency and productivity will be further supported.

In the present study, to investigate the occurrence of land subsidence in Isfahan plain, SNAP8.0 software and radar differential interferometry technique were used. For this purpose, after processing Sentinel-1A images in the period 2019-2015, rate and intensity subsidence maps were prepared in the desired period. Also, changes in groundwater water level in the period 2002-2018, as one of the geodetic factors affecting subsidence, were studied to match the points that have subsidence. Then the output of SNAP software was studied using ArcGIS10.8, with land use layers and average water level changes and Maps of mean subsidence changes, groundwater drop, standard deviation and time of maximum subsidence were prepared. The results show the occurrence of subsidence phenomenon in areas with groundwater decline with urban use, roads and agricultural lands with a maximum rate of 14.2- 20.8 cm in the years 2018-2019. The average change represents the maximum subsidence of 9.6 cm per year, in line with the satellite line of sight, in the urban area. Also, spatial analysis of subsidence hazards at strategic points showed that the study area needs to provide the necessary warnings for the occurrence of subsidence crisis on a larger scale in the future.

 The protection of natural resources, especially land, and their use, has long been considered. It can be said that because land use has undergone many changes over time, these changes have direct and many effects on the ecosystem and the environment and consequently have various consequences, including these consequences that can be used to change land use. The area was affected by the rapid expansion of urbanization and its effects on land-use patterns in the surrounding environment and, finally, land fragmentation in these areas. Accordingly, in many cases, converting land use from its natural state to artificial land use has irreversible consequences. To reduce the consequences, this can be adapted to the land use structure. Land appropriateness refers to matching the capacities of a plot of land and its land use, and the disproportionate allocation of land use and disregard for its changes has many consequences such as socio-economic segregation, environmental depletion, and loss of resources. Decisions in land and resource management should always be guided in a way that does not conflict with the interests of society and the natural environment. In this regard, one of the effective ways to control and minimize the damage and consequences of land use is to adapt its structure so that, based on the characteristics of land resources and their capabilities, the land can be spatially distributed and arranged more rationally. This study aims to identify and zone the appropriateness of land use structure with the existing capabilities in Hamedan and to evaluate the efficiency of the multilayer perceptron neural network method in the field of land use structure optimization in this city.

 In this study, to adapt the land use structure in the city of Hamedan, based on the research background and according to the effective criteria in the field of land use structure, various indicators were selected, including 12 land use indicators, slope, average temperature, and average rainfall. Average humidity, average wind speed, geology, soil type, distance from the river, distance from wells, distance from main roads, and vegetation type. Then, using the field visit, the points with user suitability were registered as educational points. After preparing the layers of the mentioned indicators, these layers were standardized in the software environment of the GIS system. In the next step, the multilayer perceptron neural network uses the after-release algorithm by importing layers affecting the optimization of the land use structure as input and using the middle layer of distance. From appropriate points in terms of land use structure, this network was implemented with the structure of 1-10-12 to adapt the land use structure in Hamedan. From 35% of the total image pixels, the distance from the agricultural proportions as training points falls into three categories the first part (70%) for network training, the second part (15%) for stopping calculations when the error is increasing, and the third part (15%) was used for network verification. Finally, the final land suitability map was drawn. The resulting layer had a value between 0 and 1 which was divided into five land suitability classes. In the present study, after identifying the factors affecting the land use structure and adapting its structure, and preparing each of them, the mentioned layers were standardized. Then, using the field visit, the points with appropriate use were recorded as educational points. Thus, the land use structure was adjusted by the multilayer perceptron neural network model with 58 replications. The results of the neural network validation and the resulting output layer indicate the high accuracy of the network in fitting the land use structure so that the square root mean values of error (RMSE), and absolute error (MAE). Correlation coefficient (R2) in the implementation process of the network is equal to 0.19, 0.21, and 0.89, respectively, indicating the network's high accuracy in implementing the optimizing process. Completely inappropriately divided, and the results showed that most of the areas covered some somewhat suitable and perfectly suitable lands with 32.62 and 28.13% of the total area, respectively.

 In the present study, after identifying the factors affecting the land use structure and adapting its structure, and preparing each of them, the mentioned layers were standardized. Then, using the field visit, the points with appropriate use were recorded as educational points. Thus, the land use structure was adjusted by the model of a multilayer perceptron neural network with 58 replications. The results of the neural network validation and the resulting output layer indicate the high accuracy of the network in fitting the land use structure so that the square root mean values of error (RMSE), and absolute error (MAE). The correlation coefficient (R2) in the implementation process of the network is equal to 0.19, 0.21, and 0.89, respectively, which indicates the network's high accuracy in the implementation of the optimizing process. Completely inappropriately divided, and the results showed that most of the areas covered some somewhat suitable and perfectly suitable lands with 32.62 and 28.13% of the total area, respectively.

 The results of optimizing land use structure in Hamedan show that most of the area is not suitable for agricultural activities in terms of effective factors. In this area, most urban land uses completely barren and uncultivable lands, lands. There are mountainous, rocky, and low-quality pastures, mainly in the western and southwestern areas of Hamedan. Also, in this area, lands that have been relatively suitable in terms of a proportion are quite suitable in terms of 12 factors in the best conditions for agricultural and horticultural activities and are the best place for developing agricultural activities. Thus, to change the land use conditions towards a more appropriate trend while paying attention to integrated urban-rural planning for Hamedan and its surrounding settlements. It is recommended to pay attention to land use planning rural-urban plans and projects because the rapid expansion of Hamedan and its suburban spaces has created numerous challenges in terms of land suitability. In such a way that about 23.1% of the lands are ready to be transformed into unsuitable and completely unsuitable conditions. In addition, 32.62% of land use is subject to change to semi-suitable conditions. Based on what has been said, controlling, supervising, and directing the constructions and preventing the over-horizontal expansion of the city of Hamedan and its surrounding spaces by urban and rural stakeholders (local management) is proposed to rangeland and agricultural lands. The findings of the study also indicated that the highest area of land in this area is related to somewhat suitable and perfectly suitable land and the lowest area belongs to unsuitable and somewhat unsuitable land. Therefore, it can be said that the city of Hamedan is currently in a semi-suitable situation in terms of land suitability, which can have a more favorable trend in the future with proper planning and policies.

 Irregular and unplanned urban expansion is known as urban sprawl and is characterized by low-density, transport-driven development, spreading out over large swathes of land towards the fringes of established urban centers. It is generally held that morphological modification of the urban landscape results in rising urban temperatures and the urban heat island (UHI) phenomenon. The biophysical properties of the urban space are determinants of the local urban climate. When there is significant alteration such as the replacement of vegetation and evaporating surfaces with impervious surfaces, the surface energy budget experiences fluxes which leads to warming at the local scale. Most scientists believe that the Earth's temperature has been rising since the 19th century. Meanwhile, a phenomenon called heat island in metropolitan areas (UHI) has caused a faster rise in temperature in these micro-climates, and in the coming years, the rapid urbanization trend will also increase the slope of temperature rise in cities. According to statistics provided by the United Nations, by 2025, more than 80% of the world's population will live in cities, and this will worsen the situation as cities become warmer. Surface temperature (LST) is one of the most important environmental parameters that is affected by land use change. The purpose of this study is to analyze the land use change in the two periods of 1987 and 2019, to estimate and study the changes in LST and NDVI in the same period, and to analyze the impact of land use change in LST and NDVI and the relationship between all three parameters.

In this study, Landsat 8 satellite images were used from the OLI sensor to extract the land use map and vegetation index, and the TIRS sensor was used to extract ground surface temperature for 2019 also Landsat 5 OLI sensor image was used to prepare land use map and vegetation index. Using visible, near-infrared, and infrared bands, the TM sensor was used to extract the surface temperature using thermal bands for 1987. Ecognition software was used to classify the object. Error matrices and related statistics (overall accuracy, kappa coefficient, user and Producer accuracy of each class) were used to evaluate the classification accuracy. Finally, Pearson correlation analysis was used to analyze the correlation between LST and NDVI, and the Contribution index was used to evaluate the impact of land use on surface temperature.

 Investigating land use changes and their relationship with land surface temperature and vegetation index requires determining the type of land use and accurate estimation of land surface temperature and vegetation index. Preparing a satisfied land use map using Landsat satellite images and applying the object classification method Oriented has a relatively high accuracy. The accuracy of land use map classification in 1987, 82.5, and in 2019, 96.1 shows the high accuracy of the land use classification method and land use map. The study of land use changes in 1987 and 2019 in the Givi Chay catchment showed that rangeland use with an area of 1224.18 and 10469.59 square kilometers is the dominant land use, while in 1987, residential use with an area of 66.63 square kilometers and in 2019, water use with an area of 3.77 square kilometers had the lowest area. Also, the most modified use of rangeland use was dryland agriculture (181 square kilometers), which indicates the destruction of rangelands. The results of surface temperature during the 33-year period were evaluated which showed that the average surface temperature in 1987 from 28.39 °C to 38.86 °C and in 2019 from 34.35 °C to 46.62. The temperature has increased so that the average temperature of the whole study area in 33 years has increased by about 7.11 degrees Celsius. This indicates the urban development in the study area. The highest temperature recorded in both periods belongs to dryland agricultural use (38.86 and 46.62 ° C, respectively), which indicates the concentration of heat in these areas. Dryness and harvest at this time can be the main cause of high temperatures of this use. Garden, forest, and water uses showed lower surface temperatures in both periods than other uses. Vegetation areas due to evapotranspiration have a temperature-moderating role and have areas with a minimum temperature in both periods. Water use also has a great effect on reducing the temperature due to its high heat capacity. The use of residential areas compared to rainfed and pasture agricultural uses showed a lower temperature, which can be due to the existence of parks, and gardens that cause evaporation and cooling of the city, as well as factors such as roofing, felt in The reflection of radiant energy has a great share. Rangeland use had high temperatures (36.57 and 44.81 °C, respectively) in both years under study. The reason for the high temperature of this land, according to the study season, which is late June and early July, is an increase in areas free of vegetation or vegetation that is small and scattered. There was also a large negative correlation between LST and NDVI in the two study periods. Rainfed and rangeland agriculture with higher LST have lower NDVI, while vegetation and water have higher NDVI. Aquatic agricultural use, which was mostly observed in the areas around the Givi Chai River, showed lower temperatures due to the presence of moisture and evapotranspiration due to vegetation density. In the study area, suburban areas (gardens) and irrigated arable lands along the Givi Chai River and forests have the highest amount of vegetation index (NDVI) due to their relatively high green biomass, while irrigated areas, rainfed lands, Residential areas, and pastures have the lowest vegetation index. The results of vegetation index analysis for each land use class showed that forests, rainfed agriculture, and rangelands with the highest LST values and the lowest NDVI values while the lowest LST values and higher NDVI values were observed in forest and garden classes. Replacement of vegetation and forests with residential areas causes the conversion of wet soils to impenetrable surfaces, which leads to reduced surface evaporation. Absorbed solar radiation is converted to heat and reflected with higher values of LST. Increased vegetation has reduced the earth's surface temperature, and this is due to the fact that more vegetation leads to more evapotranspiration and transfer of part of the temperature and cooling of the earth's surface. Finally, the calculation of the participation index for each land use class in 1987 and 2019 showed that dryland agricultural use in 1987 and rangeland use in 2019 had the largest share in increasing surface temperature in the study area. According to the time of the selected images, the main reason for this participation can also be attributed to the time of harvest of dryland agricultural products and drying of pastures.

 The results confirm the increase in surface temperature between different land use classes. Rangeland and dry agricultural uses showed higher LST values compared to forests and irrigated agriculture and water areas. High-temperature areas also had low NDVI values. Conversely, low-temperature areas such as vegetation and water had higher NDVI values. In addition, a high negative correlation was observed between LST and NDVI in both study periods. It has also been shown that rangeland and irrigated agriculture have a positive effect on LST, while forests and water have a cooling or moderating effect.

 In recent decades, with the acceleration of urbanization and the growth of migration to cities, the physical structure of cities has undergone extensive changes. To implement these changes, regardless of the ecological capacities and requirements of sustainable urban development, cities are facing many challenges. One of these challenges is determining the appropriate areas for the physical expansion of the city for the establishment of urban development. One of the most reliable methods to determine the appropriate directions and areas for urban development by considering environmental conditions and characteristics is the land suitability assessment. Such an assessment greatly contributes to sustainable land use and solving environmental problems caused by rapid urban development. Land suitability assessment aims to identify the most appropriate spatial pattern for future land uses considering the ecological potential of the area. Since many criteria need to be considered and analyzed in the selection of appropriate lands for urban development, it is necessary to use the most effective techniques to identify the best locations for future urban expansion. The Geographic Information System is such a technique, having its most useful application in the land suitability assessment method. In setting the importance of the criteria used and computing the weights of factors, GIS tools must be integrated with other methods to improve the results. Given that, the present study attempted to evaluate the land suitability to determine suitable areas for the establishment of urban development of Bam city through the integration of the Multi-Criteria Decision-Making approach, Fuzzy Logic, and Geographic Information System.

 To achieve the objectives of this study, with the help of a group of experts, and an extensive review of the related literature, all the criteria and sub-criteria essential to the establishment of urban development were identified as the first step. To this end, a questionnaire was designed and distributed among the group of experts and they were asked to express their opinions on the identified criteria and sub-criteria. To determine the required sample size and population, Morgan’s sampling table was employed. Consequently, 9 criteria and 13 sub-criteria were selected for the land suitability assessment in this study.Multi-Criteria Decision-Making method and Expert-Choice software were used to compare and weigh the previously determined criteria and sub-criteria. As the next step, all the data layers were standardized by the fuzzy logic method using ArcGIS software. The scale of the maps used in this research is 1:100000 and the resolution of digital layers is 90×90 meters. After assigning calculated weights to each data layer, they were overlaid using the Weighted Linear Combination method and fuzzy sum technique.

The results from MCDM analysis revealed that three sub-criteria namely distance from major faults, distance from drinking water wells, and soil texture had the highest weights among other factors at 0.235, 0.117, and 0.114, respectively. The inconsistency calculated for the pairwise comparison in this study was 0.07, which is below the 0.1 thresholds. Analysis of the final raster suitability map, resulting from overlaying data layers, showed that the highest and the lowest pixel values were 0.481 and 0.07, respectively. To perform a more accurate analysis, the final suitability map was classified into four suitability classes (medium, low, very low, and undevelopable) indicating that 24% of the studied area equivalent to 189965.2 hectares, categorized as having medium suitability, 34% low equivalent to 268854.3 hectares, 22% very low equivalent to 178695.7 hectares, and 20% undevelopable equivalent to 160762/3 hectares for the establishment of urban development. The medium suitable areas are mainly located in the east, northwest, and to a lesser extent in the center, mostly away from the major fault lines, while the areas of very low suitability and undevelopable are mainly located in the west and south of the area studied. Due to their proximityto protected areas, mountainous, fault lines, and hills, these areas do not demonstrate the appropriate suitability for the establishment of urban development.

 This study was conducted to identify and determine suitable areas for the establishment of urban development in Bam city using a combination of the Multi-Criteria Decision-Making approach, Geographic Information System, and Fuzzy Logic technique. All the criteria and sub-criteria, used to conduct this study, have been determined using a questionnaire and considering the environmental conditions and socio-economic characteristics of the studied area. As a result, 9 criteria including water resources, climate, topography, geology, soil, areas under the Department of Environment Management, roads, population centers, and land use, and 13 sub-criteria including distance from surface and groundwater resources, climate, wind speed, slope, altitude, distance from the main faults, geology, soil texture, distance from protected areas, distance from roads, distance from built-up urban areas and land use were selected for this study. Expert Choice and ArcGIS software were employed for pairwise comparison and standardization and overlaying data layers. It was found that 24% of the studied area equivalent to 189965.2 hectares can be categorized as medium suitability for the establishment of urban development. Based on the final results, it is concluded that the integration of the Multi-Criteria Decision-Making approach, Fuzzy Logic, and Geographic Information System can provide sufficient tools to determine the areas suitable for urban development and present a detailed analysis of these areas according to the characteristics of the area for future planning.

Since there are different statistics on the area, distribution, and density of Zagros forests, continuous monitoring and evaluation of these forests are facing implementation problems. The available statistics and information from Zagros forests are not effective in the management decisions of these forests due to many reasons such as their preparation in the traditional way or their oldness. In this research, a high-accuracy map of canopy density and distribution of Zagros forests as well as the determination of other land uses have been prepared using Sentinel-2 images of 2019 in the south of West Azarbaijan province. The image classifications were performed with the supervised method and ML and SVM algorithms in the ENVI 5.3 software environment. The Bing and Google Earth images were used to prepare the ground truth map to evaluate the accuracy of the output maps. In this research, the five non-forest land uses including ranges, gardens, agriculture, water sources, and barren and residential lands were classified. The results showed that the maximum likelihood algorithm with an overall accuracy of 87.3% and a kappa coefficient of 0.74 was the most accurate in preparing the canopy density map. The available statistics showed that the state of forest cover in the province is not in a favorable condition and the area of Zagros forest in the province is equal to 60200.55 ha, which is equivalent to about 90% of the updated statistics of the forests, rangelands, and watershed management organization of the country (67235,91 ha) in 2020. It can be stated that Sentinel-2 data has an acceptable efficiency in terms of accuracy and cost for preparing the canopy density and distribution map of forest areas and preparing the land use map.

Background and Objective:

 One of the issues that occur due to groundwater abstraction is land subsidence. This situation is now reported in many arid and semi-arid regions of Iran, especially in Yazd province. In addition, in recent decades, heterogeneous development of agricultural lands and uncontrolled extraction of groundwater from the reservoirs of Herat and Marvast aquifers in Yazd province have caused the occurrence of land subsidence around agricultural lands. The rising metal wall of deep wells and the horizontal cracks on the ground directly indicate the degree of subsidence. It is necessary to identify and identify areas that are prone to subsidence due to the risk and danger to life. On the other hand, we must note that The effects of subsidence may be accelerated by other natural activities in the area such as volcanic activity, earthquakes and landslides, and due to the seismicity of many areas of our country, attention to this phenomenon is of particular importance. Today, one of the most accurate and cost-effective methods for detecting ground surface movements is the radar interference technique. By comparing the phases of two radar images taken from the same area at two different times, this method will be able to determine changes in the earth's surface with accuracy and spatial resolution in centimetres and even millimetres in that time interval. In this article, for the first time, we tried to monitor the subsidence of land subsidence in Herat and Marva's aquifers by using Sentinel-1 satellite images and open source software. In this research, we try to achieve the following goals by using the time series data of the Sentinel-1 sensor, which has not been used in the study of subsidence of the studied areas. The aim of this study is to implement the technique of interferometry with permanent distributors using the integrated SNAP2StaMPS package. Another goal can be to estimate the subsidence rate by processing a set of Sentinel-1 sensor images in the period 20/02/2017 to 10/02/2019, approximately two years of time series. The ultimate goal was to investigate the data potential of this sensor in time series analysis and monitoring of changes due to land subsidence.

Materials and Methods :

Herat and Marvast aquifers, in fact, the study areas in this study include Herat and Marvast aquifers located in Yazd province. Herat and Marvast aquifers are geologically part of the Zagros (ophiolite, radiolarite) and Sanandaj-Sirjan zones. The study areas are located in the 2nd-degree catchment area of Abargoo and Sirjan deserts with code 44 and an area equal to 57125 square kilometres. In this study, 24 data related to Sentinel-1 sensor were processed in one-dimensional mixed image level, high pass, VV polarization and segment number 93 related over a period of approximately two years in both study areas. In general, most of the process of processing and analyzing the time series of interferometers with permanent distributors (PSI) in this paper was done by two open source software, Snap and Stamps. Finally, to automate the single-reference interferometry steps, a set of code written in the Python programming language called SNAP2StaMPS was used, which is well designed based on the graphs of the Snap software.

Results and Discussion:

 One of the results of interferometric processing based on the innovative SNAP2StaMPS algorithm in this research was the production of interference maps from which the topographic phase has been omitted. Other results of the standard deviation scatter index for the average displacement map of both Herat and Marva's aquifers were 4.19 and 3.65 mm per year, respectively. Also, the main results of this study are the estimation of the average displacement map of the Herat aquifer between -40.33 to 11.46 mm per year and for Marva's aquifer between-39.79 to 10.63 mm per year in terms of satellite visibility during the study period (2017 to 2019). For this purpose, areas were randomly selected and areas based on subsidence field evidence in both study areas were selected. Hajiabad Naseri and, 6) Marvast city, related to the Marvast aquifer can be named. In this paper, due to the lack of specialized tools to evaluate and validate the only way to review the results, its compliance with ground subsidence evidence, time series diagrams and hydrograph of the aquifer unit. According to the hydrograph results of Herat and Marvast alluvial aquifers, the groundwater level in the Herat aquifer has decreased by about 5.5 meters during the 8-year period from 2011 to 2019, based on data from 28 observation wells. This hydrograph shows a drop of groundwater of about 7 meters over an eight-year period. The time series results obtained from the interferometry of the images used in this paper show the slope of the fitting line, which actually shows the amount of displacement (up or down), indicating a downward trend in the second area (white aqueduct of Herat aquifer) and Fifth (Shuran aqueduct from Marvast aquifer) shows its amount equal to about 5 and 7 cm, respectively. These results have a significant relationship with the hydrograph of the unit of both aquifers.

Conclusion :

In this study, for the first time, to estimate the rate of subsidence in Herat and Marvast aquifers in Yazd province, the technique of interferometry with permanent dispersants was used using Sentinel-1 sensor data and SNAP2StaMPS open source package. Also, the potential of Stamps and SNAP software for radar interferometry processing was investigated, and also the details of the implementation of the Step to Stamps software package were shown. In general, based on the processed outputs of this package and the results of validation, it is possible to understand the ability of the automated method presented in this study to monitor subsidence and use this algorithm in other study areas.

One of the main tasks of planners in rural region is to allocate land to different uses according to the function and the impact of each function on each other. The aim of this study is to investigate usage progression of rural fields. The research method is descriptive and analytical, which has been studied using a map and a questionnaire. In this land study, conversion function have been studied in four villages: Jozghan, Hosseini, Soran and Kohjeh of Kuhsangi village, during the last 20 years. Which has examined land usage changes around the villages by preparing a map in ENVI and ARC MAP software. In addition, to investigate the conversions within the rural ground and evaluate the compatibility of these changes through a questionnaire that was fulfilled by 60 endemic persons using purposive random sampling and analyzed using SPSS software. The results show that in the first 10 years of the research, the highest growth of land usage conversion occurred in residential use and the least change was in non-vegetation land and in residential usage, rangeland was with the least change in usage in the second 10 years of research unlike to others in the first 10 years. Also, by evaluating the conversion indicator of compatibility indicator with using the three components of public security, village vision and environment, the results are as follows: according to the public security and village vision, residential-religious usage are more compatible than other usages and due to environment, Greenbelt is more compatible than other usages

In recent decades, land use change due to environmental and human factors has caused serious effects on the environment and the economy in Golestan province. On the other hand, wide rangelands and natural areas have been cultivated without observing ecological and scientific principles or have been exploited for special purposes and changing to other uses, while many of these lands are do not have the potential to become new land uses and they have a high potential for erosion, as a result of which we will see soil erosion, especially in sloping lands and the creation of destroyer floods. Therefore, it is necessary and essential to be aware of the type and manner of use and its possible changes over time, which will be important for planning and policy-making in the country. The aim of this study was to detection the land use changes in Golestan province during the years 1986 to 2019 and to predict the land use status of the region for 2050 using the Land Change Modeling (LCM) approach.

In order to monitor the trend of land use changes in the study area, Landsat 5 and 8 satellites (TM and OLI sensors for 1986, 2001, and 2019) were used. Interpretation and processing of satellite data were performed in ENVI software. The necessary pre-processing was performed on the images. First, the images were mosaic together and then cut according to the province boundary. In order to identify and separate the phenomena from each other, a false color image was created. Then, the supervised classification method with the maximum likelihood method was used. At this stage, five classes, including rangeland, agriculture, forestry, residential, and water areas were defined. Land use maps for 1986, 2001, and 2019 were prepared. Integration of land cover maps related to 1986, 2001, and 2019 was used as input of LCM model and digital elevation model (DEM) maps and road and stream layers to analyze area changes and prediction of land use changes of 2050. After the necessary analyzes in order to detect land use changes between the intended time periods, change maps and land use transfers were prepared. Finally, the amount of decrease and increase in each land use, the amount of net changes, the net change from other land uses to the desired class, areas without change and transfer from each land use to another land in different land cover classes in the form of maps and charts were prepared and analyzed.

The aim of this study was prediction and modeling of land use changes in a period of 33-years in Golestan province. According to the results during this period, the area of ​​the rangelands has decreased a lot, equivalent to 181181.25 hectares. Much of the decline in rangelands is due to its conversion into agricultural, which can be attributed to population growth and the need to expand crop land. The area of ​​forest lands during the mentioned years has decreased from 393018.75 to 349143.75 hectares in 2019, which has shown a decrease of 43875 hectares (2.2%). In general, the destruction of rangeland and forest areas is especially visible in developing countries due to population growth, technological growth and non-compliance with ecological principles and law enforcement. Also, the results of classified maps during the mentioned years show that the highest amount of changes in the region is related to agricultural lands, has increased to 173700 hectares equal to 8.5 % during the same period. The rate of land use changes related to the residential land class has also increased with the increasing trend from 18731.25 hectares in 1986 to 37518.75 hectares in 2019, which has increased by 18787.50 hectares (0.9%) during this period. Rapid growth of population has led to the development of residential and urban areas and the increase in this type of land use with a relatively steep slope, especially in recent years, which can be part of the government's plans for housing construction in the surrounding areas cities. This increase in the class of agricultural lands is more noticeable, especially in the central and eastern regions of the province, and can be a warning alarm for the future. It means that in an imperceptible trend, rangeland and forest lands become rainfed agricultural lands and after a while unprincipled exploitation, eventually become barren and unusable land. On the other hand, this could indicate an increase in population and demand for housing, and consequently securance of the needs of the residents of the region is a threat to rangeland lands which is necessary instead of increasing the agricultural and residential lands and turning rangeland lands into such land uses, the policy of increasing productivity in the agricultural sector should be pursued. About of water areas, it can be said that during this period, it has increased by 1.6% or 3268.75 hectares. This increase in water areas can be partly attributed to heavy rainfall and water intake and even floods in different parts of the province in 2019. Predicting the rate of land use change in 2050 indicates that in the coming years, the area of ​​rangelands and forests will be reduced by 131906.25 and 291600 hectares, respectively, and in contrast to the area of ​​agricultural land and residential areas will increase to 164137.50 and 25313.25 hectares, respectively. Therefore, the adoption of necessary measures and policies to further reduce forest and rangeland will be inevitable.

Understanding of the conditions of different land uses during the coming periods will facilitate planning for the future by creating information in terms of their spatial distribution pattern, but maintaining and creating sustainable conditions for the future both statistically and it is ecologically one of its limitations. These constraints play an important role in the safe use of different land uses in the planning process. Therefore, creating sustainable conditions in the region and modeling it in order to use the natural resources of a region regularly and sustainably is one of the preconditions for achieving upstream visions and documents, including the sustainable development plan.

Modeling and showing the coverage of the land changes, provides a comprehensive view to researchers in various fields, including environmental and natural resources experts. One of the main methods of environmental studies is to study the land cover/use and vegetation area change. In addition to showing spontaneous changes in nature, changes affected by human activities also fall into this category. Human construction has accelerated these changes in line with its development, especially in recent decades. Today, with the development of space-related sciences and remote sensing in general, and the production of more satellite products, it is possible to display the land use of different areas without the need for field visits and easily. The different behavior of the waves received by the satellite sensor from the various phenomena, known as a spectral signature is the basis for cognition and detection of the uses of the map. Such studies in Qom province have also been considered due to the very urban growth trend and the existence of several different types of climates in the not-so-wide area of this province. Qualitative and quantitative study and display of environmental and peripheral changes in Qom province over a period of about 30 years are one of the main objectives of the present study to help identify the trend of changes in different classes and complications and to model these changes in the future. Also, recognizing the changes in the outlook of Qom province, makes possible the ground for future planning.

In the present study, study times and time steps were selected based on changes in climatic/meteorological parameters. These steps were selected 5 years apart from 1989 to 2019. The study time point was considered to be the end of spring and the beginning of summer. The reason for this was the end of the rainy season in the area. Then the images of various Landsat satellite sensors were taken at specified time steps, and these images were pre-processed, processed, and classified into 11 classes. These 11 classes included; bare land, salty land, sandy land, tree, rock, urban areas, agricultural lands, and 3 different types of range. The results were also presented quantitatively and qualitatively. Based on the available real data, which was obtained visually and by sampling from different classes, the two maximum likelihood and minimum distance classification methods in Qom province were properly evaluated, which of the two, the maximum likelihood method yielded relatively better results considering the whole province with all classes and was used in the final classification. Finally, class changes between time steps were calculated and presented as a change matrix.

The results show that between 2014 and 2019, urban, water, agriculture, and ranges (types 1 and 3) have grown significantly. Also, between the two steps of 2009 to 2014, on average, about 30% of the total rangelands, ie three different types of classified rangelands, have become barren lands. Also, in this step, the main change observed was the largest change of sandy lands to bare lands, the reasons for which need further investigation. An examination of the changes between 2004 and 2009 shows that the negative growth in urban areas is mainly due to the poor quality of Landsat 7 satellite imagery and the similarity of the spectral behavior of salt lands and urban areas. The other negatively growing classes, including lakes, have become saltier lands and rocky areas have become barren, as well as salt lands have become barren and sandy. Examining the changes between 1999 and 2004, it is concluded that the negative changes in the tree class are due to the spectral behavior of vegetation, and this class has become mainly agricultural and rangeland classes. In the lake class, a 4 % change to the salt and rocky class has been detected. Major changes in the bare land class of about 12% have been detected in the rock and sand class. Also, more than 50% of the total area of range classes has been converted to bare land class, which is significant. The study of changes from 1994 to 1999 shows that only 3 classes had positive growth and the rest of the classes have negative growth, most of which was related to the urban class and the main changes were focused on bare lands. Vegetation classes all had negative growth and also due to the spectral similarity of these classes with each other, there was no proper separation between them. 12% of the bare land class has also been turned into a sandy land class. The classification of images and the display of changes from 1989 to 1994 show that sandy soils, range type 1, trees, salt lands, and lakes have grown negatively. In total, about 34% of different types of ranges have become bare lands, which seems reasonable due to the negative change in water areas (lake) and in a way indicates a faster drought. The extent to which other classes change to the bare land class, which includes relatively large numbers, also confirms this in some way.

Considering the geographical location of Qom province and a large area of this province, especially in the eastern half of it, which includes desert lands, including barren, saline, and sandy land classes, the selection of the classes mentioned in this research makes sense. Considering the major coverage of the province, one of the problems in the present study was that almost the majority of the pixels covering the province had a lot of similar spectral behavior and this issue made the classification process difficult.  In general, the classification results related to the images taken in 2019, which is related to the recent time, show positive growth in urban, agricultural, range, and water areas according to the rainfall in early spring 2019 it was logical. Another important point related to this year is the extensive change and conversion of the class of rocky lands into different types of ranges. According to the original image taken from 2019 and the classified images, the error related to the degrees of gray is evident in those images. The software considers the similarity of the degrees of gray and the same spectrum of urban and salt classes as part of a class. These errors are also evident in bare and sandy classes.

In recent year’s groundwater pomping in the Mashhad plain and decreasing of rainfall in the Mashhad, plain is cause subsidence and creat damage to province infrastructure. This problem is causing more application for deep well water in agriculture, industries, and drinking water. Follow by this demand the number of illegal wells dicking by customers is increasing, therefore the water level of groundwater in Mashhad plain decreasing and the subsidence rate is growing. Mashhad plain is one of the significant plains in the Khorasan Razavi province which is the main water source to support the cropland and industries. High pressure in Groundwater pumping and rainfall is decreasing it causes aquifer recharge reduction.  Groundwater depletion induced a variety of inadequate in the Mashhad plain such as reducing well discharge, Qanat destructive, Water quality decreasing and land subsidence, etc. In this research, the rate of land subsidence by satellite radar data of ALOS-1 and Sentinel-1 and its relationship with groundwater depletion are investigated. For this purpose the time-series InSAR with multiple SAR data in L and C- bands are used for land subsidence analysis for ten years from 2007 to 2018.

The main goal of this research is to find the land subsidence rate in relationship with groundwater depletion of the Mashhad plain for a period of 2007-2018 using the InSAR technique. For achieving the research goal the three pairs of SAR images of ALOS data and three pairs of Sentinel-1 data are used. For analyzing the water delation with land subsidence the ten years piezometric well data for a period of 2006-2017 are modeled to create the groundwater table contour line. This map is used for finding the relationship with land subsidence. The final result of the subsidence map was assessed with field observation and previous work.

 InSAR result of ALOS-1 data in this research is shown the subsidence maximum rate of 5.2 cm in the period of 2007.10.16 to 2008.10.16 for 92 days, subsidence maximum rate of 3.8 cm in the period of 2008.01.16 to 2008.03.02 for 46 days, and subsidence maximum rate of 4.7 cm in the period of 2008.03.02 to 2008.06.02 for 92 days. In addition, the Sentinel-1 data processing for InSAR analysis has shown the subsidence maximum rate of 16.1 cm between 2015.05.28 to 2016.05.22 for a year, subsidence maximum rate of 17.4 cm from 2016.05.22 to 2017.05.29 for 372 days, and subsidence maximum rate of 20.3 cm from 2017.05.29 to 2018.05.24 in a year. The spatial distribution of the subsidence area is mostly in the central and southeast of Mashhad plain. The subsidence area is extended in the area with a 39 km length and 8 km wide. The Mashhad plain does not have a permanent river therefore most of the water demand in agriculture, industries, and drink water is supplying by groundwater pumping. The correlation between the subsidence map and groundwater level contour map obviously has shown that groundwater depletion affects land subsidence. Field observation was also confirmed the subsidence by wall and building crack, wellhead uplifting in the test site.

The result showed that the area with the maximum rate of subsidence is the counterpart to cropland and garden which have more influence on groundwater pumping. In addition, the piezometric well date is shown the groundwater table continuously decreasing. According to the result of this research, the main reason for subsidence is a force to groundwater pumping. The field observation approved that the subsidence is happening in the Mashhad plain by some cracks in the wall, bridge, road, well destructive.

Mapping soil salinity changes on a large scale is very costly and time consuming. One of the most cost-effective ways to map soil salinity is to use satellite imagery. Investigation of spectral characteristics of soils with saline surfaces and determining the extent of areas affected by this phenomenon, by using new images with relatively high spatial and spectral resolution can be used in preparing soil salinity maps. In recent years, many indicators have been developed to detect and extract the characteristics of saline surfaces from satellite images, most of which have been studied based on the spectral reflection of these surfaces in different bands of satellite images or intermediate ratios. The purpose of this study is to estimate the salinity changes from 2001 to 2016 in Miandoab region located in West Azerbaijan province. For this purpose, 42 samples with appropriate distribution were taken from the area. The samples were then transferred to the laboratory to measure soil salinity parameters. To evaluate soil salinity, in addition to sampling of topsoil, the NDSI, IBI, NDVI, SI7 and NIR, RED, SWIR2 bands of Landsat 7 for 2001 and Landsat 8 for 2016 were used. The regression equation for determining soil salinity for 2001 showed that soil salinity has a positive and significant correlation with NDSI index at the level of 5%, While for 2016, the highest significant correlation at the 5% level was with the RED and NIR bands of the Landsat 8 image. In 2001, the highest and lowest lands in the region were non-saline lands (39%) and very saline lands (12%), respectively; While in 2016, the highest and lowest lands in the region are relatively saline lands (35%) and non-saline lands (18%). The results of the present study showed that the salinity of the region can be easily calculated using Remote sensing indices. Due to its proximity to Lake Urmia, the study area faces soil salinity problems, so the identification and classification of saline areas is necessary for land management.

Land use patterns, agricultural activities, and decreased vegetation have accelerated land degradation processes. Therefore, implementing land and vegetation-based management measures and utilizing land resources according to suitability/capability is essential to achieve integrated watershed resources management in critical watersheds. Hence, the present study was planned to evaluate the changes of erosion and sediment yield to evaluate management scenarios based on land capability in the high priority sub-watersheds of Glazchai watershed Oshnavieh, West Azerbaijan province, Iran. Therefore, the land capability of priority sub-watersheds was first extracted according to the FAO method. The soil erosion, sediment yield variability, and the maximum discharge were estimated using the IntErO model. The results showed that six percent of the study area in studied sub-watersheds did not follow the land capability rules. The forest land use had a 2.21% net increase. Also, the good rangeland area had a net change of 1.2% compared to the current conditions. In this regard, the allocation of land capability in these areas will reduce the erosion amount, sediment yield, and the maximum discharge of the watershed by 7.1 and 1.33%, respectively. At the watershed scale, the amount of specific sediment yield is also reduced by 12.6 m3y-1km-2. The present study results can provide a suitable management approach for planners and policymakers to make a sound decision regarding the land use-oriented measures in high-priority areas at the watershed scale.