Investigating the changes in groundwater aquifers in planning the sustainable management of water resources in each region is of particular importance. Therefore, reducing the level of groundwater aquifer changes requires proper management and planning to exploit water resources. In this study, the level of groundwater aquifer changes in Urmia Lake basin was examined for the period from 2002 to 2017 using GRACE satellite data (JPL, GFZ, CSR triple bands, CRI Filtered model, time and space filter, and Lew-Thiknth uncertainty dry product) in the Google Earth Engine. The results of the triple bands showed that the JPL band estimated the average level of groundwater aquifer changes on May 1, 2004 as 14.947 cm, while the GFZ band on estimated this as -30.558 cm on September 1, 2015 and the CSR band estimated this amount as -28.206 cm. Therefore, CRI Filtered model can very accurately identify the boundary between land and water zones. The results showed that this model estimated the maximum thickness of liquid water in the groundwater aquifer at March 31, 2002 as about 11.599 cm and its uncertainty at about 9.767 cm. It can be said that the least amount of thickness of liquid water is estimated on 13 August 2015 as 12.309 cm with an uncertainty level of 10.759 cm. According to the results, the level of groundwater change in aquifers in terms of liquid water thickness parameter (Lew-Thiknth) in the northern parts of the Urmia Lake basin and in terms of uncertainty in the northeastern part of the Urmia Lake basin is experiencing a strong decline in the aquifer water levels.

One of the main challenges in the energy transmission arena (especially the natural gas transmission) in Iran is the optimal demarcation of operational boundaries in order to cover the whole land. In other words, over time and due to the changes in the consumption level and the facilities installed in the related areas, the boundaries defined as the operational areas have lost their optimal response potential, and there have appeared challenges such as more difficult access, increased volume and importance of transmission, etc. Therefore, it is necessary to define and demarcate new boundaries based on these changes. As a result, this article addressed the optimal model for the demarcation of natural gas transmission operational areas using spatial allocation method. Spatial allocation method is an instrument for maximum optimization and high access in various algorithms. The spatial allocation methods that are usually used for positioning stations and work facilities are a great instrument for planning the public services. In this study, in line with using comparative studies and external experiences, instruments such as interview (for the determination of indices), statistical tests in GIS, weighing methods, etc., were used. According to the obtained results, the number of yards and areas should be fixed, but the boundaries of the operational natural gas transmission areas and yards should be mobilized maximally to match the defined scenario so that maximum optimization is achieved.

The intelligent managers of this era of constant changes and instability try to know opportunities, challenges, and variables effective on the system under their management so as to increase the possibility of their success. The managers of Yazd province – as one of the developed provinces of Iran – always try to step in the direction of sustainable growth and development by means of strategic planning, knowledge about the capacities of this province, and the management of the possible future challenges. The study at hand was carried out to attain this objective and to get a clearer image of the future of this province in order to identify the variables that are affective on the future of Yazd province. Moreover, conducting structural analysis through MICMAC method, it was tried to investigate the mutual effects of these variables on each other and identify the key drivers of what might form the future of this province. The important variables effective on the system were identified using library research, virtual space monitoring, surveying citizens, and future-related workshops. Variables were prioritized using importance and lack of certainty criteria. Then, the most important ones were fed into the direct effects matrix, and after completion with Delphi method, they were fed into MICMAC software. The outcome of the software was compared with the results of Dimtel method, and finally, the variables of the performance of organizations, balanced development, performance of land use plan, various types of tourism, and attention to water and environment were identified as the most effective variables in the formation of the future of the province.

Today, ecotourism is deemed a key industry and is granted a special position in the economic development of different countries. This industry has always faced risks in making decisions about selecting places with high ecotourism potential. Therefore, the purpose of this study was the assessment of ecotourism development capability in rural areas, with an emphasis on the environmental risk-taking in decision-making. In this study, 12 spatial criteria were used. Ordered weighted average (OWL), analytic network process (ANP), TOPSIS, and sensitivity analysis were used to assess the concept of decision-making risk, calculate the weight and importance of the criteria, rate the appropriate villages, and assess the modeling precision, respectively. The results showed that among the used criteria, the distance from the built lands and the distance from faults have the highest and lowest weight, respectively. With the increase and decrease in the risk-taking degree, the high potential class space increases and decreases, respectively, such that in the risk-taking degree of 0 or less, less than one percent and in the risk-taking degree of 1, thirty-five percent of all lands of the area fall in the “very high potential” class. The examination of the appropriate villages in the 0.5 risk-taking degree for ecotourism development showed that among all Mazandaran province villages, only 55 villages are in the “very high potential” class. Among these, Aali Kola with the relative distance of 0.8505 is the most capable village for ecotourism development. Finally, the results of sensitivity analysis revealed the adequate stability of the model results in various scenarios, i.e., the high reliability of the model results.

Land use in Shahre Rey has experienced unprecedented growth in urban areas in recent decades. Land use changes affect social, economic, and environmental conditions. Gathering information about these changes is essential for better planning and management of urban areas in sustainable development. Consequently, the object of this paper is to better examine the Shahre Rey land use changes affected by urban development and to investigate urban landscape integrity using the 1988-2018 "Fragmentation" index. Moreover, it was intended to provide solutions for the determination of hot spots based on appropriate criteria. With the help of Landsat satellite images, four land uses – including urban landscapes, agricultural lands, green spaces, and barren lands – were extracted and the extent of land use changes was determined. In order to investigate the fragmentation of Shahre Rey landscape, the metrics of the number of patches, patch density, and the largest patch were used. Cross-Tab was also used in a part of the study. The results showed that the land use areas of ​​urban lands and urban green space had increased by 369.7 and 55.6 hectares, respectively, while agricultural lands and barren lands had decreased by 213.8 and 211.5 hectares, respectively. In urban land use, integration had increased. In the green space and agriculture land uses, fragmentation has increased due to the creation and construction of roads. Based on the criteria of  "position relative to borders and roads as well as the area and size of patches,'' solutions were made to determine the "hot spots" of vegetation and residential areas to help making plans for the improvement of their conditions. The reason is that land use change, especially the loss of vegetation, has a negative impact on the landscape.

The topic of climate change and the dangers that lie ahead is part of the debate in land management. The dynamics of global change and the sovereign approach of global governments have opened new perspectives on land management issues. One of the hidden challenges in this regard is the increasing risk of the occurrence of floods. The purpose of this study was to undertake metric or measurement model as a spatial basis unit to predict flood occurrence. In the present article, in line with using MikeUrban 2019 software, a wide range of tools and quantitative processing steps were used in accordance with the research objectives. In order to predict floods, the past incident factors were studied, namely a review of the principles and operational indicators related to each parcel using the OLI sensor images of Landsat 8 satellite in the year 2020 through the integrated interpretation method and an examination of the basic map of Ilam city in wet seasons (autumn, winter, and spring). Then, the city coverage map was prepared in two uses, i.e., False Color (Urban) and Land / Water. Next, Google Earth images were used to determine the accuracy and precision of the coverage maps. By combining four selected measures with the highest spatial correlation in 50 random points of the city, hexagonal measures with optimal areas were selected and spatial patterns were analyzed. According to the results, in the actual event (1), eight spatial measures with an area of ​​68 hectares and coverage of 1.5% of the entire city are at risk of flood. In events 0.8 and 0.9, 19 measures with an area of ​​170 hectares, 3.6% of the land use coverage of the area, are at potential risk. While there is a high correlation between flood event and type of measure, amount and direction of slope, as well as density and width of road network on one side and drainage network on the other side, in high events (1-8), 28 measures in the residential uses in the detailed design scale with an area of ​​76.5 hectares, barren and enclosed uses with an area of 70.55 hectares, roads network with an area of 29.75 hectares, and parks and green spaces with 17 hectares were identified as the uses targeted by the flood danger. Among all risky user groups, 29.5% were identified in the newly built group, 44.5% in the maintainable group, and 18% in the decayed urban environment group.

Demographic changes in recent decades have led to rapid changes in Iran's urban system and its hierarchy, with one of its consequences being the increase or decrease in the ranking of cities in this system. The present study examines the position of Tabriz metropolis in the urban system of Iran from 1335 to 1395, and by forecasting the population of this metropolis by 2031, it tries to determine the future position of this city in the urban system of Iran. This study is practical in terms of purpose and descriptive-analytical in terms of nature and research method. The data in the present study were obtained through document analysis and field study (questionnaire and interview). Interviews were used to understand the causes of emigration and a questionnaire was used to understand the causes of fertility decline in Tabriz metropolis. The sample sizes for both instruments were determined based on the saturation principle. The exponential model, Spectrum software, and rank mobility index were used to predict the demographic factors, population forecast, and the study of metropolitan rank changes in the urban system, respectively. The obtained results showed that the decrease in fertility rate and migration are the main reasons for the sharp decline in population growth in the metropolis of Tabriz, with the economic reasons being the main reason. In addition, assuming the fertility rates of 1.5, 1.8, and 2.1 in Tabriz, we will see 1.64, 1.69, and 1.74 million increases in the population of the city, respectively, as well as a decrease in the population of minors and a doubling of elderly population over 65 by the year 2031. The results of population forecast show that the position of Tabriz metropolis will be stabilized as the sixth largest city of Iran's urban system by 2031, but its distance from the seventh metropolis (Qom) will be less, which requires special attention and proper management to prevent its rank from falling again.

The assessment of the ecological potential of the environment is to determine and measure the potential power and the natural use type of the land. Therefore, the environment power assessment is a tool for the management of geographical space and strategic planning for sustainable development and correct use of land sources. The aim of this study was to evaluate the ecological potential of agricultural and rangeland use in Kangavar city with an area of ​​883.9 km2 using Makhdoom ecological model. To this end, the required data and ecological resources were collected and generated. After creating and combining the maps in the ArcGIS system in a multi-hybrid way, the maps of environmental units were constructed and the ecological potential of the area was evaluated using the features of each environmental unit. To do this, the indicators and variables that could be involved in each of these models were examined. To classify the ecological potential of the area for agricultural and rangeland uses and to produce the map of different classes potential, 15 parameters were used as criteria for weighting and measuring the power. The results of Kangavar city ecological potential assessment led to the extraction of 58 environmental units in 7 classes with completely suitable, suitable, weak, and unsuitable power classes for agricultural and rangeland use. An area of about 356.79 Km2 was found to have suitable and completely suitable power for agricultural use. In addition, it was estimated that an area of about 72.23 Km2 would be appropriate for rangeland and rainfed agricultural use with suitable power. An area of about 483.26 Km2 of Kangavar city is currently allocated to agricultural use, while the optimal area for this means is 356.79 Km2. Thus, the land use of an area of about 126.47 Km2 has been converted to agricultural purposes. According to the results, the lands of the region have been exploited more than their potential for agricultural use (irrigated and rainfed) and the lands with rangeland use have been changed to agricultural use.

The goals of the present study were to analyze changes in land cover and to estimate a future scenario for 2028 using an artificial neural network in the Karaj Metropolis. To this end, the effects of land use changes in response to urban expansion on landscape patterns were investigated in three baseline, current, and future scenarios using landscape metrics and gradient analysis. The results showed that during a 22-year period, the agricultural and Garden lands have been severely damaged due to urban expansion. The results of the evaluation of changes in landscape also indicate that urban expansion in in development in the north-south transect to the margins (especially northward) and the east-west transect with a gentle slope to the west of the region. It is also anticipated that in the future scenario, if the current trend continues, the northern margin of Karaj metropolis will be changed from natural environment to a completely human-made one. Therefore, considering the results of the Pd and Ed metrics in both transects over the three examined years, it can be said that the area has expanded to the margin and there has not been much changes in the landscape of downtown. In addition, the decrease in the Pd and NP in all three scenarios indicates the consistency of urban landscape. In general, population growth and urban development have made the landscape pattern in Karaj metropolis to be a more regular and less varied one. The results indicate that spatial heterogeneity has altered the landscape patterns. Therefore, the growth of construction land in some areas should be restricted, and balanced development should be adopted to prevent the fragmentation of the landscape.

The land-use changes and urban development are among the fundamental topics of spatial planning. Monitoring changes in previous years and predicting these changes in the coming years have a significant role in planning and organizing urban spaces. The purpose of this study was to investigate land-use change and urban development in Ahvaz with a landscaping approach based on balanced urban development. .Images of TM (1989), ETM+ (2002), and OLI (2019) of the Landsat satellite are the basis for analyzing this trend. LCM model was used to identify the past changes, while CA-Markov chain model was applied to predict the future changes. These images were classified using a support vector machine algorithm of the object-oriented method, and the land-use maps were prepared using three sensors with four classes of vegetation, barren areas, constructed areas, and water zones. The accuracy of maps was improved separately using NDVI and SAVI indexes in the classification of the images. The efficiency of the indexes was measure by kappa coefficients and the overall accuracy of land-use maps, and then changes were investigated using maps related to the superior index. The results showed that maps related to the SAVI index were more accurate and accordingly, they were used in assessing land-use changes. The LCM model showed that in the periods 1989-2002 and 2002-2019, 2602.92 hectares and 31174.77 hectares were added to the built areas, respectively. In both periods, the most changes were about converting barren lands to built-up areas and the least changes were related to the transformation of the built-up areas to water areas. The results of the CA-Markov model until 2029 showed the continuity of the increasing trend of built-up areas, such that in ten years, 2238.82 hectares will be added to the built-up areas, and it is anticipated that the area will reach approximately 12345.63 hectares by 2029.