Inevitably, inconsideration of the population evacuation of villages can have irreparable consequences for the human settlements. Analysis and identification of the qualities of this issue can greatly help planners and decisionmakers in the spatial planning domain to prevent full evacuation of population from rural settlements. The study at hand was an applied research project done using descriptive-analytical approach. The statistical population comprised of villages with less than 100 residents in Khorasan Razavi province from 1986 to 2016. Moran’s local spatial analysis was used to investigate the spatial dimensions, and arithmetic mean and skewed distribution were used to examine the direction and range of distribution. The results showed that in the 1986, 1996, 2006, and 2016 censuses, 92.2, 90.1, 94.8, and 79.9 percent of the villages evacuated in the previous decade have had lower than 100 residents. The results of Moran’s spatial autocorrelation analysis demonstrated that the distribution pattern of villages on the threshold of evacuation during these three decades is cluster-like. Moreover, the results of arithmetic mean and skewed distribution indicated that 68 percent of the villages that are on the threshold of population evacuation are within the oval domain, and except for the 1986-1996 period – when the distribution direction of villages on the threshold of evacuation has been northwest-southeast, the direct has been northeast-southwest from 1996 to 2016.

Water provision service is one of the most valuable ecosystem services that is important as a key service for the healthfulness and management of water resources. In this study, using the Water Yield model of InVEST software, the water supply and demand in Ilam watershed was modeled. The data related to average annual precipitation, annual evaporation and transpiration, root limiting depth, water available for plants,  land use map, water consumption and estimation of water provision quantity, basin boundary, and subbasins of the watershed were the inputs of this model. The results of model application showed that in Ilam watershed, 45 million cubic meters of water provided annually, with the highest and lowest water provision volumes being in Arghavan (7 million cubic meters) and Chalimar (802 thousand cubic meters) subbasins, respectively. According to results, there are great differences in the water supply and demand in the subbasins of this watershed. Therefore, planner and policymakers should pay attention to this important issue in the layout of land uses and foresee sustainable use of rich forests in the high yield subbasins such as Arghavan subbasin. The results provided in this study, along with showing the importance of modeling surface water demand and its used in macro-policies of water allocation, can function as a guideline and help the managers and planners of Ilam city to adopt reasonable decisions in managing ecosystem and correctly using land in this area.

Due to the vast changes it brings about in the land use and land cover, the rapid expansion of cities has had many negative effects on the environmental quality at global level. Examples include air quality, increased temperature, changes in perspective, and the alteration of agricultural lands into barren lands that leads to the loss of biodiversity. Since land use changes happen at extensively, remote sensing technology is a necessary, efficient, and valuable means to monitor changes. In this study, the effect of land use changes on the temporal-spatial patterns of land surface temperature in the urban lands of Ilam city in a 30-year period (1990-2020) was examined using Landsat satellite images and simulation of changes using fuzzy ARTMAP neural network model. Landsat satellite sensors (TM, OLI, ETM) were used to investigate the longitudinal and spatial changes (LST) in Ilam city.  To provide the land use map, the pixel-based classification for all periods (1990-1995-2000-2005-2010-2015-2020) was applied using ENVI and Ecognitio software packs and then estimations were made using NDVI and LST models. The results showed that Ilam city ecosystem has moderate levels of NDVI. The average temperature of residential land use level in June is 35.8 degrees centigrade, and the temperatures of three land uses of horticulture, agriculture, and other uses (uncovered lands) were 32.22, 37.25, and 38.46, respectively, with the main lands with the minimum temperature being green highlands. In city, existence of high rise buildings and building shading, use of materials with less heat absorption such as Isogam, urban green space and furniture, and air pollution lead to lesser absorption of energy. On the other hand, the spatial distribution of NDVI was aligned with LSP values. The results regarding land use areas using fuzzy-neural network show that residential land uses has risen from 19.18 percent in 1990 to 39.35 percent in 2020, which shows the city expansion and development. On the other hand, the horticultural land use has declined from 8.64 in 1990 to 3.49 in 2020, which can be attributed to the development of urban space.

Spatial justice of uses, or in other words, fair, wise, and balanced distribution of urban uses is one of the most important issues of urban planning. The present study is research in terms of purpose and analytical in nature. The library information of this research is collected from books and articles. For the analysis, the per capita index of service users was used, which was calculated and obtained in the GIS software. The statistical population of the research is the eight districts of Qom City. This research has tried to analyze the Spatial justice of service uses in the eight districts of Qom City with the ORESTE technique, based on indicators that are service uses per capita. For this purpose, the indicators were first weighted using Shannon's entropy method, the highest weight was assigned to tourism, and the lowest weight was assigned to the park. After weighing, the ORESTE technique was performed, and Region 7 had the highest and Region 6 had the lowest amount per capita. Then, with the dispersion coefficient, the two-by-two distribution per capita of the service uses of the regions was calculated, and the results showed that regions 2 and 8 have the highest and regions 5 and 7 have the lowest spatial distribution of service uses. Also, with the Spearman correlation coefficient, the correlation between the population of each region and the per capita service users was calculated, which showed a negative correlation, which means that as the population increases, the service users per capita decreases.

The most obvious example of human activities on the land due to the increase in population and the need for development is land use changes, which lead to changes in the provision of ecosystem services. To that end, the present study was done with the aim of quantitatively evaluating the carbon storage capacity and habitat quality and showing their spatial distribution to achieve social-ecological stability, sustainable use of land resources, and develop appropriate plans and policies in Chaharmahal and Bakhtiari province. The modeling of selected ecosystem services was calculated using InVEST software models and the capacity to provide them in land use classes using Zonal Statistics analysis in a GIS software environment. The results indicated that high-value carbon storage areas are focused in areas with forest cover, which have strong carbon storage capacity and are the largest carbon sinks in ecosystems. Likewise, the highest habitat quality was also observed in these areas, and in places where the vegetation is fragmented and the surrounding environment is occupied by human threat sources, the quality of the habitat has decreased. Spatially, carbon storage and habitat quality Indicated a low-high-medium spatial distribution pattern from north to south. The maps of ecosystem service created in this study can be useful in identifying potential areas of carbon storage supply and habitat quality, and provide a scientific basis for further discussion by policymakers about future land use planning, from the perspective of minimizing climate change and increasing biodiversity.

The purpose of this research is to select temporary accommodation centers after the earthquake crisis to meet the needs of the victims. Therefore, this research has tried to identify temporary accommodation sites in District 22 of Tehran with the help of effective criteria. The required data has been obtained from the Tehran Disaster Mitigation and Management Organization and the results of the general population and housing census of 2017. The novelty of this research is to present a new combination approach to determine the effective criteria for locating temporary shelter sites. In this regard, the combination of geographically weighted regression (Gaussian and tri-cube kernels) with a binary particle swarm optimization algorithm was used. The recommended combination method is suitable for spatial regression problems because it is compatible with two unique properties of spatial data, i.e. spatial autocorrelation and spatial non-stationarity. The best value of the fitness function (1-R2) for Gaussian and tri-cube kernels was obtained at 0.04616 and 0.0097, respectively, which indicates the high compatibility of the tri-cube kernel with effective criteria. According to the obtained maps, Chitgar Park and Azadi Sports Complex are some of the widest and most suitable areas for the construction of temporary shelter sites after the earthquake crisis in the case study. By identifying temporary shelters, relevant organizations can provide the appropriate infrastructure for these selected centers so that there is no need to spend time to provide these services in the event of an earthquake.

The growing role of science and technology in economic development makes the necessity of policymaking and planning for the science and technology system more important. In line with centralized, top-down planning approaches to science and technology policymaking, the spatial planning approach is a bottom-up effort to identify regional capacities and potentials in order to provide an endogenous and balanced model for the development of science and technology. Although the spatial planning approach in its general form has a multi-decade history in the planning literature, the optimization of this approach in the science and technology governance needs methodological innovations. The purpose of this study was to provide a science and technology spatial planning methodology using institutional mapping. To this end, we used two cross-sections. On the one hand, we took into account innovation within a regional system, and on the other hand, we adopted the institutional mapping to attain a method for its analysis and estimation. In this system, first the institutions of the science and technology institution including the science institution, the technology institution, and the market institution were identified, and then the interconnection capabilities of these three institutions and their subsidiaries were evaluated. This was done through the extraction of the similarity graph. The similarity graph, which was obtained through the quantification of binary relationships of the science and technology system sub-institutions, expressed the diversity and intensity of the connections of each institute with other institutes. The more diverse and intense the relationships among the institutions were in general, the more optimal the science and technology system would be. Ultimately, observing this graph, the policymaker can design a scenario for moving toward regional balance for each of these institutions so that in the predetermined chronological horizons, the institutional proximity is increased and the agreement and accord of the institutions are enhanced.

Air pollution is one of the most important problems of industrial cities. The existence of large industrial factories, official and industrial facilities, National Iranian South Oil Company, National Iranian Drilling Company, etc., have turned Ahvaz to one of the main industrial centers and one of the most polluted cities of Iran. Coming into contact with airborne microorganisms is related to a host of negative effects on the human health. This study was carried out to find out the effect of oil industries on air pollution and its optimal locating through the environmental approach in Ahvaz metropolis. In this study, SCREEN3 software was used to find out and analyze the distribution of Sox, NOx, and CO pollutants. Based on expert opinion, the main criteria were determined as climatic, natural, environmental, and economic factors. After calculating weights through the AHP model and attaining the information layers, the GIS software capabilities to combine and overlap the maps were used. This led to a map depicting the optimal location of oil industries congruent with the environmental approach in Ahvaz metropolis. According to the obtained results, there should be no residence-based activity in at least 5000 meters distance from the oil industries, where air pollutants have a considerable density. That is to say, within this distance, the animate and inanimate creatures will be damaged the most. The most optimal areas for the establishment of oil industry facilities are located on the west, south, southwest, and parts of east and north of the area under study.

The main purpose of this study was modeling the suitability of recreational services in order to identify the high-priority areas for the development of recreational activities. To identify the spatial patterns of recreational services, the landscape attractiveness index, visit rate estimation, and access distribution were combined using a set of sub-indices. Moreover, the weight of each index was calculated using CRITIC weighting method and the importance of each index in the formation of recreational services spatial suitability was determined. The results showed that the presentation of highly recreational services is mainly done in the areas with forest ecosystems, protected areas, and aquatic ecosystems such as rivers and wetlands that have diverse landscapes. On the contrary, urban and human-built areas have the least potential for the provision of recreational services. Getis-Ord Gi* statistic was used to model the recreational suitability, identify recreational suitability clusters, and zoning. With its very low suitability, Zone 1 covers 19.9 percent of the area under study. This zone is mainly filled with agricultural lands (54.7%), grasslands (36.1%), and urban lands (6.8%). In contrast, with its very high recreational suitability, Zone 5 covers 16.5 percent of the area under study. The main uses of the lands in this zone are forest lands (55.5%) and aquatic layers including rivers and wetlands (17.2%).  Zone 3, which has an average suitability rate, covers more than half of the area under study. The approach presented in this study helps identify the development priorities in the light of the recreational potentials of the ecosystems existing in an area. Thus, it can be used to improve the spatial planning of recreation and tourism in order to preserve ecosystem services and sustainable use of them.

Hospitals are among the most important service centers, and the selection of the optimal site for them is a very important (yet complex) undertaking, as it can bring about optimal spatial distribution of hospitals and can make them optimally accessible for citizens. In the present study, in order to optimally locate hospitals in District 5 of Tehran metropolis, a combination of the geographical information system, objective weighting methods, and multi-criteria decision making method was used. The geographical information system was used to analyze and manage the optimal hospital locating criteria, the CRITIC weighting method was implemented to account for the correlation between the criteria, and Shannon's entropy method was used to model the existing uncertainty in the criteria. CODAS multi-criteria decision making method was used due to its novelty and the evaluation of alternatives based on two criteria. Based on the results obtained from CRITIC weighting method, distance from health centers, and based on the results of Shannon's entropy method, distance from industrial areas were the most important optimal hospital locating criteria. The results of ranking the candidate sites using CRITIC-CODAS and Shannon’s entropy-CODAS were almost the same, and both methods identified the sites on the western side of the District (that did not have any hospital) as the appropriate sites. The results of the study indicated the high accuracy of combined objective weighting and multi-criteria decision making methods in optimal locating of the hospitals. It might be asserted that these methods can replace thematic weighting methods such as analytical hierarchy process.