Journal of Spatial Analysis

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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.