Journal of Spatial Analysis

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Coastal areas are constantly changing physically and ecologically, depending on natural and human factors. The natural causes of coastline changes are assessed in three ways: short-term changes including the effects of up and down currents, long-term changes including climate change, periodic storms and waves, and accidental changes including sudden natural events. Today, coastal tourism is considered as one of the important factors in the development of coastal areas. In this regard, the Caspian Sea, with many tourist attractions such as lush forests, accessible foothills and mountains, historical monuments and appropriate welfare facilities, benefits from the sea and beaches. The coastal area of Babolsar City, due to its many facilities and capabilities to attract tourists, much of which is due to natural and environmental attractions, every year, hosts a large number of tourists who come to this area to take advantage of its facilities and attractions, including the beautiful beach and very beautiful forests. This coastal area because its dynamic nature, is exposed to permanent erosion and variability due to processes such as river, wind, tectonic, wave and tide and marine transgression-regression in the area causes the destruction of coastal facilities and recreational places. Therefore, any planning to change the land use and construction in this coastal area should be considered in terms of the sea water fluctuation impacts on the shoreline position. Coastal environmental degradation as a result of Caspian Sea water level fluctuation are very probable and human behaviors in non-optimal choice of the land use locate intensify these losses. Coastal tourism, as one of the coastal land uses is heavily influenced by fluctuations in sea level in both marine transgression-regression statuses.
 

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Air pollution can have serious negative effects on human health, including cardiovascular and respiratory diseases. Monitoring and controlling air pollutants is very important to protect public health and the environment. Like many developing countries, Iran is facing air pollution, especially in its big cities and industrial cities. One of the powerful tools in air pollution monitoring is remote sensing methods. The aim of this study is to use relatively high-resolution satellite data to monitor air quality and air pollution using Sentinel-5 (Sentinel-5P) sensor images. In this study, a comprehensive monitoring based on the values of some of the most important air pollutants (including AI, O3, NO2, SO2, CH4 and CO) has been done using Sentinel-5 satellite images for Iran in 2019-2023. The results of this research showed that the emission of carbon monoxide and sulfur dioxide gases had a decreasing trend (in the months of June as an example of the examined month), but nitrogen dioxide gas, methane gas, ozone gas and aerosols had an increasing trend during the month. from June 2021 to 2023. In general, air pollution is more serious in the northern parts of the country, especially in big cities and several large urban gatherings. In this study, it was investigated how the levels of six air pollutants in Iran vary and differ from June 2019 to 2023. Another important result of this research is that the total amount of air pollution in 2020-2023 has faced an increasing trend compared to 2019. Also, the monitoring by Sentinel-5 satellite images shows that in recent years, Tehran has had the most polluted air in terms of carbon monoxide, nitrogen dioxide, sulfur dioxide and suspended particles (dust). Also, changes in the concentration of pollutants do not follow a specific pattern. It was also found that the GEE system is able to process a large amount of data in a very short time with high accuracy.
 

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The purpose of this study is to investigate one of the supporting services of the ecosystem, called habitat quality, and to assess the spatial vulnerability of natural landscapes in the city of Khorramabad using the InVEST habitat quality module. To achieve this objective, it is essential to identify the sources of threats, the relative weight of each threat, the maximum distance of its effect in space, the types of habitats, and the sensitivity of each to the source of the threat. In addition, one of the most important inputs of InVEST is the land use/land cover (LULC) of the study area. The Local Climate Zone classification method has been used for the creation of this map. Finally, the model generates spatial distribution maps of habitat quality and degradation across the landscape by combining LULC and different threat sources. The findings indicated that the city, airport, and highway factors are the most destructive threat factors to all habitats with an average score of 0.51, 0.345, and 0.33, respectively. Compared to other LULC, water, dense trees, and scattered trees suffered the most destruction, with sensitivity ratings of 0.47, 0.39, and 0.36, respectively. The results also revealed that habitat quality in Khorramabad is at a medium to low level, and the habitat quality is in very good condition in only 3% of the landscape area.
 

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Natural biological crises are a constant threat to human societies; Therefore, it is considered important to be prepared to control and prevent such disasters. In dealing with such urban crises, addressing the category of non-pharmacological interventions against infectious diseases can be a way forward. Therefore, the aim of the current research is to find the main effective indicators in the epidemic and to explain the environmental components resulting from the interaction and correlation of the relevant measurable indicators at the locality level based on previous environmental studies.
 In this research, in order to obtain a community of opinion about effective indicators in epidemiological crises, a systematic search was first conducted using the keyword of pandemic resilience. For this purpose, several widely used databases such as Web of Science, Scopus and Elsevier were searched between 2013 and 2023. After checking the quality of the conducted researches, 42 indicators were selected. Further, in order to find out the underlying variables and identify the basic factors or criteria in order to explain the correlation pattern between the observed variables, the exploratory factor analysis method was used and SPSS version 26 software was used to analyze the data. Data from 118 Tabriz neighborhoods were used for exploratory factor analysis. After collecting the data, the process of change, standardization has been done to prepare the data and convert the raw data into percentage, growth rate, average and ratio. Then, the status of urban resilience components against epidemic diseases was calculated and normalized separately based on factor load for each neighborhood. Finally, the results were illustrated using Arc GIS software.
 The findings of the research indicate that 42 indicators affecting the spread of epidemic diseases at the level of localities can be re-categorized into 8 components of accumulation, diversity and design, social factors, density, economic factors, health infrastructure, environmental pollution and green spaces. Also, based on the findings, it can be said that the condition of most of the components in the neighborhoods of Tabriz city is at an average level.
 Based on the results, the effects of environmental factors on the transmission of Covid-19 are differentiated spatially. These components represent more than 82% of the changes in effective environmental factors.
 

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he spread of Covid-19 in the rural areas of the country has caused more dangers due to the common rural cultures, and the ignorance and lack of efficient management of this crisis in the villages has caused irreparable consequences for these areas. In such cases, the existence of social capital can be very vital in creating national consensus and successful policies to pass this critical stage. Leading research is applied in terms of purpose and based on descriptive-analytical nature. To determine the sample size of villagers, using Cochran's formula, from the total of 6903 households in sample villages, 362 households were calculated as sample households to complete the questionnaire. In order to investigate the effects of social capital on economic and social indicators that are effective in reducing the vulnerability of the outbreak of Covid-19 in the border villages of Sistan, a wide range of indicators was determined, and from the one-sample T-test and the analysis of variance of the regression model to measure the The evaluation of the effects of social capital on socio-economic indicators effective in reducing the vulnerability of the outbreak of Covid-19 in the border villages of Sistan was used. The results of the research showed that the higher the level of people's participation and their trust towards each other, the higher the level of responsibility and knowledge of people, it has a positive role and effect on social and economic indicators in order to reduce the vulnerability of the spread of the covid disease. has had 19
 

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Drought is one of the most important challenges faced by pastoralists around the world. This phenomenon can have significant negative effects on livestock health, production, and livelihoods. However, pastoralists can adapt to drought and reduce its negative effects by adopting various strategies. Semi-nomadic people in Darbandi, Kalat-Naderi County, have been facing drought since 2007 due to their livestock farming. Since livestock farming has profound impacts on the lifestyle and livelihoods of these communities, the present study examines their experience in facing drought and identifies their management strategies in these conditions. The research method is qualitative and the research tool is in-depth interviews with 20 semi-nomadic people in Darbandi, Kalat-Naderi. Sampling was purposeful and carried out until theoretical saturation was reached to ensure that a wide range of perspectives and experiences were collected. The data from the interviews were analyzed using a qualitative grounded theory approach to extract key patterns and concepts. According to the findings, the semi-nomadic Darbandi people of Kalat County have adopted various strategies in the face of drought, which are classified into four categories: rangeland and grazing management strategies, livestock nutrition management, water consumption management, and livelihood diversification. These results can be used as a basis for formulating better policies in the field of crisis management and rural development. Also, these results can be used for more effective planning to reduce the vulnerability of nomads to drought.

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Aging is one of the most prominent indicators of demographic decline that most modern societies experience. At this stage of demographic decline, alongside a decrease and stabilization of mortality rates, birth rates also sharply decline. The development of technology and the mechanization of tasks, the improvement of quality of life and health-related indicators, individual-centered lifestyles, and increased economic inflation are significant factors in this issue. Iran is also among the countries on the verge of entering the stage of demographic decline. However, the intensity of this trend varies in different regions of the country. This article examines and analyzes the state of aging in the neighborhoods of the metropolis of Tehran. This research falls into the category of applied research in terms of purpose and is descriptive-analytical in terms of method. The research is based on the census data from 2016 and utilizes spatial statistical analyses. The positive values of Moran's autocorrelation analysis for each of the indices: aging (0.664), old-age dependency ratio (0.644), youth ratio (0.653), aging ratio (0.664), and aging index (0.665) in the neighborhoods of Tehran indicate a clustered pattern. This means that the issue of aging is more acute in some neighborhoods and areas of Tehran. Accordingly, the density of the elderly population is higher in most neighborhoods of the central and northern parts of the city. The final result shows that the distribution of the elderly space follows the logic of the social macro-ecology of Tehran and is relatively consistent with its natural-social topography. Furthermore, the spatial analysis of aging in the neighborhoods of this city shows that although all neighborhoods generally grapple with the issue of aging, planning and management should be based on the patterns and nature of the spatial distribution of this issue.
 

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Deforestation is one of the primary challenges and environmental threats facing forest ecosystems, including the Hyrcanian forests, and occurs under the influence of various natural and anthropogenic drivers. This study aimed to model the probability of deforestation occurrence within the Loveh forest management district located in northern Iran. The dataset comprised 104 documented deforestation points and 14 explanatory variables, derived through spatial analysis using GIS and environmental, topographic, and anthropogenic data. To assess the relationships among variables and predict the likelihood of deforestation, two statistical models were employed: logistic regression and the Generalized Additive Model (GAM). The results revealed that the GAM outperformed the logistic regression model, achieving a higher Kappa coefficient (0.84) and Area Under the Curve (AUC) value (0.956), and providing a more realistic spatial distribution of deforestation risk. The most influential variables included distance from roads, slope, wind effect, and elevation. Based on the GAM output, approximately 20% of the study area was categorized as high and very high risk. These findings underscore the pivotal role of access infrastructure, human pressure, and climatic factors in accelerating deforestation processes. The results of this study can serve as a scientific basis for prioritizing conservation interventions, reassessing road development policies, and enhancing spatial planning for sustainable forest management in northern Iran.
 

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Reducing the emissions caused by deforestation and forest degradation REDD is a strategy to moderate climate change, which is used to reduce the intensity of deforestation and greenhouse gas emissions in developing countries. In the last few decades, drastic changes in land use have caused a significant decrease in Hyrkan forests located in Mazandaran province. For this purpose, the aim of this study is to investigate the changes in land use and its prediction for the year 2050 using the Markov chain and the REDD project to reduce carbon dioxide emissions for the cities of Nowshahr and Chalus. Using the images of TM and ETM⁺ sensors of Landsat satellite, a land use map has been prepared in three time periods related to the years 1989, 2000 and 2021. Maximum likelihood method was used to classify images from supervised classification. From the error matrix, the Kappa coefficient in this evaluation was equal to 0.83 for 1989, 0.81 for 2000, and 0.92 for 2021. The results show that the forest cover decreases in 2050. In contrast, the area of ​​range land, city, barren land, agriculture and wetland will increase. Based on the goals of the REDD project, the amount of carbon dioxide emissions was calculated until 2050. If the REDD project is not implemented, a large area of ​​forest cover will be destroyed and a lot of carbon dioxide is released. The amount of carbon dioxide in the project area in 2021 is 49,681 tons and will reach 806,732 tons by 2051, and with the implementation of the REDD project in the region, this amount of gas can be increased to the equivalent of 402,321 tons. 404411 tons of carbon dioxide was prevented from entering the upper atmosphere of the earth. Examining changes using satellite images can help managers and planners to make more informed decisions.
 

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Waste management is one of the main challenges faced by modern cities. Given the population growth and the increasing generation of waste, there is a growing need for innovative and intelligent methods in this field. Smart growth indicators can serve as tools to improve urban waste management. A waste management system comprises a set of activities aimed at organizing community waste through engineering and sanitary approaches. One of the most significant problems of coastal areas is the lack of proper waste management. Smart growth in waste management focuses on integrating technology and sustainable practices to optimize waste collection, reduce environmental impacts, and promote recycling. This study presents key indicators and trends related to smart waste management. The research employs a mixed-methods approach, combining quantitative and qualitative data via a descriptive survey. The study collected opinions from 20 experts in waste management and urban growth issues, as well as from randomly selected residents of Mahmoudabad city. Data analysis was conducted using grounded theory for qualitative data and structural equation modeling for quantitative data. The results indicate that the smart growth indicator of modern leadership, with a mean score of 4.6, and adequate infrastructure, with a mean score of 4.04, hold the highest average values among the smart growth indicators affecting waste management in the coastal city of Mahmoudabad.
 

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Objective: During a landscape, it is not facile to discriminate land parts that have dissimilar amounts and types of vegetation. Plant Ecological Units (PEUs) are known as management units and are a reflection of the management actions and natural disturbances in the region. This research aims to fuse different resolutions of satellite images to increase the PEUs classification accuracy.
Methods: For this purpose, the Marjan-Borujen watershed in Chaharmahal va Bakhtiari province was selected. After field monitoring and surveys, four dominant PEUs groups were identified in the study area. In this study, bands from the Landsat_8 satellite images with 30 m  spatial resolution (bands 7_2) and a 15 m panchromatic band (band 8) were used, as well as the Sentinel_2 satellite images including panchromatic bands (8, 4, 2, 3) with 10 m spatial resolution. First step, using the Landsat panchromatic band, the 30-m bands were upgraded to 15 m through the pen-sharpening process; so the 15 m  data set was prepared from the Landsat_8 satellite. Then, to increase the spatial resolution of the 15-meter data set to 10 m, the Sentinel_2 panchromatic bands were used. In this way, the Sentinel_2 panchromatic bands were geometrically matched with the Landsat_8 15 m data set, and the Co-Registration process was performed with the minimum RMSE(0.05). Finally,  two data sets (2 to 8 bands) of the Landsat_8 satellite images with 15 m and 10 m spatial resolution, the PEUs classification maps were prepared using the RF classification algorithm, and the maps' accuracy was displayed as an error matrix.
Results: The results show that increasing the spatial resolution significantly enhances the accuracy of PEUs classification maps. The 15 m set shows an overall classification map accuracy of 66%, while increasing the spatial resolution to 10 m enhances the overall accuracy to 82%. As well as, the error matrix results show that the classification map procured from the 10 m set, all four PEUs groups have improved the producer accuracy, user accuracy, and kappa agreement index. So, in this map, PEU 2 and PEU 3 have the highest kappa agreement coefficient (83 percent).
Conclusions: This study shows that using the Gram-Schmidt fusion algorithm and consequently increasing the spatial resolution of Landsat 8 images from 30 m to 10 m reduces mixed pixels and increases pure pixels, which in turn improves the quality of PEU classification maps.
 

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This study investigates the spatio-temporal dynamics of evapotranspiration (ET) and its modulation by biophysical variables and land use/land cover (LULC) changes in the Karun River Basin, southwestern Iran, from 2000 to 2023. The basin, spanning 67,257 km² and characterized by diverse topography, experiences significant annual water loss (72% of 413 billion m³ national precipitation) due to ET, leading to salt and sediment accumulation. Data from MODIS products (MCD12Q1, MOD13A1, MCD43A3, MOD11A2, MOD16A3, CHIRPS) provided land cover, NDVI, albedo, LST, precipitation, and ET at 500-meter resolution, supplemented by Landsat imagery (30-meter resolution) for validation. Multiple regression and Geographically Weighted Regression (GWR) analyses revealed a 39.5% ET increase (31.48 to 43.92 mm/year), a 32.78% NDVI rise (0.18 to 0.239), and a 16.35% LST decrease (33.52°C to 28.05°C), correlated with a 6.90% agricultural decline (6,939,225 to 6,460,335 ha), a 6.94% rangeland increase (3,840,375 to 4,106,780 ha), and a 42.76% forest expansion (156,000 to 222,700 ha). GWR (AdjR² > 0.97, peak 0.9887 in 2010) identified spatial non-stationarity, with overprediction in mountainous northeast regions and underprediction in agricultural southwest plains, reflecting LULC influences. Landsat-derived false color composites and classifications (overall accuracy 85–90%, Kappa 0.85–0.90) validated a 2,477 km² forest loss to high-ET rangelands/agriculture, driving warm-season ET elevation. Results emphasize the need for integrated hydrological models incorporating irrigation data and high-resolution analyses to enhance sustainable water management in this water-stressed region.

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Objective: “This study aims to investigate the drivers of ecological rupture in the Sultanieh Grassland, one of Iran’s most valuable natural ecosystems, which has experienced severe degradation over the past two decades. The research seeks to identify and prioritize the relative contributions of climatic, hydrological, and anthropogenic factors in triggering systemic instability and to assess whether the ecosystem has crossed a critical threshold toward irreversible collapse.
Methods: An integrated analytical framework was employed, combining multi-source datasets from 2000 to 2021. Remote sensing indicators—including the Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST), and Soil Moisture (SM)—were derived from MODIS and Landsat imagery. Hydroclimatic time series (temperature, precipitation, potential evapotranspiration [PET], and groundwater levels) were analyzed alongside demographic statistics and land use/land cover (LULC) changes. A multi-criteria weighting approach, grounded in catastrophe theory, was applied to objectively quantify the relative influence of key drivers while minimizing subjective bias in decision-making.
Results: The analysis reveals a 15% decline in effective precipitation, a 1°C increase in mean annual temperature, and a groundwater table drop exceeding 30 meters over the study period. These environmental stresses were compounded by a fourfold population growth and a doubling of per capita water consumption. Consequently, vegetation cover declined persistently, with NDVI decreasing from 0.2817 in 2004 to 0.1701 in 2021, while barren lands expanded significantly. Within the catastrophe theory framework, three primary drivers—groundwater depletion, vegetation loss, and population–water pressure—were identified as collectively responsible for 50% of the system’s destabilization. The evidence confirms a transition from a stable ecological state to a dissipative, degraded phase.
Conclusions: The Sultanieh Grassland has likely crossed a critical ecological threshold due to the synergistic intensification of anthropogenic and climatic pressures within a geomorphologically and hydrologically vulnerable setting. Without immediate intervention—including sustainable groundwater management, strict control of urban expansion, and active restoration of hydrological equilibrium—the ecosystem faces irreversible transformation into an active source of dust emissions and desertification. This study underscores the urgency of science-based policy actions to prevent the total collapse of this irreplaceable natural and cultural heritage site.

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Objective: Chaharmahal and Bakhtiari Province, due to its mountainous location and exposure to Mediterranean and Sudanese synoptic systems, has experienced intense rainfall events and considerable hydrological fluctuations in recent years. These conditions have often led to flash floods and posed serious threats to regional water resources. Accordingly, this study aimed to analyze rainfall intensities, estimate their values for different return periods, and construct Intensity–Duration–Frequency (IDF) curves as well as spatial distribution maps for four synoptic stations: Kouhrang, Farsan, Shahr-e-Kord, and Borujen.
Methods: Precipitation data over a 20-year period (2000–2020) were collected, and rainfall intensities were calculated for durations ranging from 15 to 1440 minutes. Maximum rainfall intensities corresponding to return periods of 2, 5, 10, 25, 50, 100, and 200 years were then estimated using several statistical distributions, including Gumbel, Normal, Pearson type V, and Weibull. Goodness-of-fit tests were applied to identify the most suitable distribution. In addition, spatial interpolation methods within a GIS environment were employed to illustrate spatial patterns of rainfall intensity across the province.
Findings: Results indicated that the Gumbel distribution provided the best fit to the observed data. It was also revealed that rainfall intensity decreases with increasing duration, while it increases with longer return periods. Spatial analyses showed that the highest intensities occur in the northwestern mountainous areas, particularly at Kouhrang station, and gradually decrease toward the southern and eastern parts of the province.
Conclusion: The findings confirm that statistical distributions—particularly the Gumbel model—enable accurate modeling of extreme rainfall events in Chaharmahal and Bakhtiari Province. Moreover, the spatial variability of rainfall intensity highlights the necessity of incorporating such patterns into hydrological infrastructure design, flood management, and water resource planning.
Keywords: Intensity–Duration–Frequency (IDF), Convective Rainfall, IDF Curves, Spatial Distribution, Chaharmahal and Bakhtiari
 

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Objective: A major part of rural risk, such as production risks, economic risks, and severe climate changes, is related to agricultural risks, which have significant negative impacts on the agricultural sector. This study aimed to investigate the effects of risks and hazards of the rural ecosystem on the development of various types of rural tourism in the rural tourism area of ​​Mahmoudabad County, located in Mazandaran Province, in order to examine the development of various types of rural tourism as a strategy for resilience and adaptation of villagers, as well as a preventive strategy in villages against economic, environmental, and social shocks, as well as reducing vulnerability and diversifying the rural economy.
Methods: The research method is applied in terms of purpose and descriptive (non-experimental) and correlational (variance matrix analysis) in terms of data collection method with the aim of showing the relationship between variables. The study population included all 88 villages in Mahmudabad city. The data collection tool was a researcher-made questionnaire and the respondents were the villagers. The structural equation modeling (SEM) method based on Smart-PLS was used to analyze the data.
Results:
The results of the research on prioritizing dimensions and hazard and risk items for rural ecosystem assessment show that economic, environmental, and social risks were ranked in priorities one to three, respectively. Based on the path coefficient (pc), only the direct effect of environmental pressure (with a path coefficient of 0.338 and a T-value of 2.467) was significant. About 30 percent of the changes in the development of tourism types are explained by the proposed model with the direct effect of environmental hazards and the indirect effect of economic hazards and social hazards.

Conclusions: As a general conclusion, the types of rural tourism in the region should be given serious attention as opportunity driven entrepreneurship and necessity driven entrepreneurship. In this regard, recognizing ecological values ​​through education and long-term propaganda for the sustainable development of rural livelihoods with emphasis on the development of green tourism, ecotourism, and agrotourism is recommended

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Objective: Livestock grazing in the Hyrcanian forests is one of the oldest forms of traditional land use, practiced within locally defined areas known as customary systems. In contrast, formal forest utilization is conducted through management plans divided into compartments. This study aimed to examine the role of ecological factors in shaping the boundaries defined by local communities (customary systems) and by experts (compartments) in parts of the Nowshahr forests, including the Namkhaneh and Garazbon series.
Methods: The ecological factors analyzed included vegetation type, main and sub-rivers, ridge, ravine, hillsides, and aspect. Boundary maps of customary system and compartment were compared with ecological boundary maps in a Geographic Information System (GIS). Since roads play a determining role in compartment boundaries, their influence was also examined.
Results: Results showed that 90.02% of customary system boundaries aligned with ecological factors, while only 4.5 km did not. Moreover, 81.29 km and 85.2 km of compartment boundaries (equivalent to 90.22% and 94.56%) were determined by ecological factors, respectively, and by the combined effect of ecological factors and roads. In total, 8.81 km of compartment boundaries were not consistent with ecological factors, which decreased to 4.9 km when road influence was considered. Among ecological variables, vegetation type and aspect had the greatest effect on boundary formation. All major rivers contributed to defining boundaries, representing 17% of customary system boundaries and 9% of compartment boundaries. Less than one kilometer of roads did not coincide with compartment boundaries, while about 32% of compartment boundaries overlapped with roads.
Conclusions: These findings indicate that traditional knowledge used in defining customary system is rooted in a deep understanding of structural factors of ecology, whereas expert-designed compartment boundaries also incorporate management and accessibility considerations alongside ecological ones.