Journal of Spatial Analysis

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Urban planners consider historical fabric as the beating heart of cities. However, cities and specifically their historical fabrics are constantly under influence of natural and human-induced hazards.  This study aimed to assess the vulnerability of Ferdowsi neighborhood as an example of Tehran’s historical fabric. The data was obtained from geographical information system (GIS) files and a survey, as well as historical contexts and documents were analyzed as part of this study. Ten municipal experts were also asked to provide a score of 1 to 5 for each of the 29 indicators compared to standard levels. The mean value of these scores was then used to evaluate the role of each parameter in the vulnerability of this neighborhood.  Study findings indicate a high potential for the occurrence of natural and human-induced hazards in the study area. The abundance of unstable multistory buildings and derelict electricity and water networks, storage of flammables in warehouses, and lack of sewage network for half of the buildings were the most significant factors contributing to the vulnerability of this ancient fabric. Problems such as insecurity, drug abuse in public spaces, overcrowding and daytime congestion have also led to rapid relocation of neighborhood residents, who subsequently were replaced by commercial activities and warehouses. In conclusion, numerous problems are contributing to the vulnerability of historical fabric of this neighborhood and such problems are highly likely to be applied to other urban historical fabrics in Tehran. 
 

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Identification of dust centers and, of course, the behavior of this phenomenon in different regions creates one of the problems of the last few decades, which is investigated as a hazard. To this end, statistics from 15 meteorological stations in the northeastern region of Iran, including North Khorasan, Razavi Khorasan, and South Khorasan provinces, were used over a 17-year period (2016-2000). To clarify the mechanisms governing dusty days, the meridional and zonal wind components and geopotential height were obtained by referring to the National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR). HYSPLIT model and MODIS AOD values were used to track and identify dust centers. The results showed that during the warm season, due to the establishment of a strong quasi-stationary blocking system in the lower levels of the atmosphere, negative vorticity increased in the maximum air descent area, ultimately leading to the dominance of a northern flow for the region. Anomalies in geopotential height and vorticity were identified, and three dominant abnormal patterns were found in the occurrence of maximum dust storms in the region. An increase in geopotential height of more than 5 to 10 geopotential meters and an increase in negative vorticity are considered major conditions. By examining the tracking model and using satellite data, five main centers that affect over 90% of the region's dust storms were identified, among which Turkmenistan has a significant role with two separate centers and one common center with Uzbekistan in the occurrence of summer dust storms in northeastern Iran.
 

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Abstract
In geosciences, morphotectonic indicators are used to investigate the effectiveness of land surfaces from neotectonic activities. In this article, the results of morphotectonic indices by tectonic zones of Iran, according to the energy released from the earthquake of 1900-2009 and the position of the basins relative to the types of faults (young seismic faults), Quaternary and pre-Quaternary) were analyzed. For this purpose, 110 years old Iran seismic data was extracted from the geodatabase, and during the programming process in MATLAB, it was converted from point-vector to surface-raster. In addition the results of the evaluation of morphotectonic indices of 142 basins of different zones were used; 8 inactive basins, 40 semi- active basins, and 94 active basins. Inactive basins are located in Alborz, Zagros, and Central Iran. . The results indicate that the amount of energy released can't examine a significant role in evaluating the morphotectonic indices of the basins. Basin’s location in the area of Quaternary faults and young seismic is of great value in the tectonically active basin. The lie of semi-active basins adjacent to active basins, or the lie of inactive basins adjacent to semi-active and active basins; and it should be borne in mind that the thresholds used to estimate the tectonic activity status of basins cannot be used as a definite and mathematical criterion in estimating the tectonic status of basins.

 

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Flash floods are one of the most dangerous natural events and often cause loss of life and damage to infrastructure and the environment. This research investigated the occurrence of the most intense continuous monthly floods (October-March) from 1989 to 2021. Precipitation data from 115 synoptic stations were selected. Then, the total rainfall of 1 to 9 days was sorted according to intensity. Using Minitab statistical software and the Andersen-Darling index, heavy rains were extracted based on the 95th percentile. Then, based on the criteria of the highest and lowest number of rainy days, the highest and lowest accumulated rainfall, the wettest and driest months were determined. Considering the three criteria of intensity, continuity, and rainfall coverage, the strongest storms in the wettest months were selected. The data used for synoptic analysis include the average sea level pressure data, the height and vertical component of the wind at 500 hPa, the wind and humidity field specific to the pressure levels 925, 850, and 700 hPa, and the horizontal moisture flux values specific to the pressure level 925, 850 and 700 hPa. The probability of the occurrence of atmospheric rivers was identified by the moisture flux extracted from the specific, meridional, and meridional wind components. The results showed that the storms of October 27-31, 2015, November 5-7, 1994, December 12-16, 1991, January 11-15, 2004, February 3-9, 1993, and March 13-15, 1996 were the strongest in the wettest months. During the storms of October, November, February, and March, moisture has been transported from the southwest of the Red Sea by atmospheric rivers to the western, southwestern, southern, and southeastern regions of Iran.
 

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Developing roads and constructing new highway are urban policices contributing to solve transportation problems in cities. These projects often being passed through urban fabrics, so it is nessessery to buy and demolish buildings from their owners including individuals or governmental and public institutions to imply the projects. However, acquiring land is not an easy task and completing these projects may hit with long-term delays. This paper aimed to analyze the impacts of delaying in constructing Shoosh Highway in Tehran. The investigated impacts originate from land acquisition problems. The research data was obtained from many sources including documents and research reports, a survey, and interviews with Tehran Municipality managers. The One Sample T-Test in SPSS software was performed to analyze the data obtained form the survey. Findings indicate that the residents are often dissatisfied with the project because since the beginning of the project, social security decreased a lot and people are less likely to respect citizens' rights than before, recreational sites are often demolished, the value of residential buildings slowed down significantly, living costs incresed, and businesses were stagnant. In conclusion, if urban highways are not contributing to proper planning and site selection, they will disrupt the physical, social, and economic structures of urban neighborhoods and cause to many environmental problemes including air pollution. To avoid these adverse outcomes, it should be thought in advance about sufficient financial resources and possible practical methods to acquire land for projects. These consequences are reduced by studying and managing the risk of projects.
 

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Abstract
Dust storm is a complex process that it was affected by relation between earth-atmophere system and point of veiw climatologist and meteorologist that they assessing atmospheric and climatic change, in general of world veiw, monitoring from dust cover is a need structures.
The western region of Iran is the study area. The data used in this study are divided into two categories: ground-based observations in 27 synoptic stations extracted from the Iran’s Meteorological Organization during period (1998-2010) and satellite MODIS images during the first to fourth days of July 2008. Finally, the aim has analyzed using Arc GIS and ENVI softwares and NDDI index.
According to results, interpolated map for the number of dusty days during the study period over the western half of Iran showed that extent of case study have not a equal system aspect quantity of occuring from dust phenomenon and how is it trend. The number of dust days increase from north toward south and sites located in northen proprotion of studied area have experienced a lower dust events. While, maximum hotspots are occuring over southwestern sites such as: Ahvaz, Ilam, Boushehr and Shiraz. Therefore, principle offspring of dust input has been out of country boundaries and arrived far way area. On based resultes obtined on satellite images using NDDI index also idicate that maximun of intense cover dust is observed over Fars, Ilam, Boushehr and Ahvaz provinces on the first, second, thrid and forth of July. But, the lowest rate of index situated in extent far such as: Eastern Azarbayjan, Western Azarbayjan provinces. Thus, parts located on the north of the study area experienced less dusty days and the maximum dust core was located in the southwestern (mostly ahvaz). The long-term result was consistent with the use of NDDI index and the daily average of NDDI index in the whole study area indicated the hotspot areas (Ilam, Ahvaz, Omidieh, Bushehr and Shiraz) during the first to fourth days July 2008. However, in the region has reduced the level of dust cover when a wet and cloudy synoptic system pass over the central and northwestern parts of the study area.

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Iran is a country with low rainfall and high-intensity rainfall that is affected by various synoptic systems, the most important of these systems is Sudan low pressure, Therefore, recognizing the low pressures of the Sudan region is of particular importance, The purpose of this study is to gather a complete and comprehensive knowledge of the set of studies conducted about this low pressure, structure and formation and its effects on the surrounding climate. The present study was conducted using the library method and a search for authoritative scientific and research sources in connection with research on low pressure in Sudan and no data processing was performed in it. Thus, it has studied and analyzed the temporal and spatial changes of Sudan's low pressure over several years and its effect on the climate of the surrounding areas, especially Iran. In general, the results of this study can be divided into several categories, including studies on the recognition and study of Sudan low pressure, its structure and formation over time, pressure patterns affecting it at different atmospheric levels, and its effects on the climate of surrounding areas, especially Iran. Has been studied, The effect of this low pressure on seasonal and spring rainfall in Iran, snow and hail, floods, thunderstorms and also the effect of remote connection patterns on this low-pressure system have been studied, and finally, the analysis of these findings has been studied. It can be concluded that the Sudanese low-pressure system is a Low-pressure reverse in the region of Northeast Africa and southwest of the Middle East, which is strengthened and displaced in the upper levels of the Mediterranean and Subtropical jet stream and in the lower surface moisture injection from the Arabian Sea and Oman through high pressure. Saudi Arabia is inwardly the cause of severe instability in Iran and a major cause of heavy rainfall in various parts of the country.

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Dust storms affect different regions of the globe countries and Iran. The dust storm events were considered as one of the climatic components in arid and semi-arid regions and it is called one of the most important environmental problems of these regions. Therefore, in this research, the activity class of sand dunes were investigated based on the Lancaster index in Iranshahr city in Sistan and Baluchistan province. The aim of this study is to investigate the climatic different conditions on the mobility of sand dunes in Iranshahr city. Meteorological data for synoptic station of Iranshahr were collected from the Iranian Meteorological Organization for 15 years (2003 to 2018). After examining the wind speed velocity in Iranshahr, and extracting the seasonal and annual Wind rose diagrams, Dust Storm Index (DSI) was calculated.  Finally, the effects of possible changes in climatic elements on the mobility of sand dunes were predicted. The results showed a significant correlation between the Lancaster index and the amount of annual rainfall, wind and drought index. The results of the sensitivity analysis also showed that if the frequency of erosive winds and potential evaporation and transpiration increases to 30%, the activity of sand dunes in Iranshahr station increases by 25 and 23%, respectively, on the other hand, with a 30% increase in rainfall, the activity of sand dunes decreases by 30%.
 

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The growth of settlements and the increase of human activities in the floodplains, especially the banks of rivers and flood-prone places, have increased the amount of capital caused by this risk. Therefore, it is very important to determine the extent of the watershed in order to increase risk reduction planning, preparedness and response and reopening of this risk. The present study uses the common pattern of the machine and the classification of Sentinel 2 images to produce land cover maps, in order to construct sandy areas and determine land issues affected by the flood of March 2018 in Aqqla city. Also, in order to check and increase the accuracy of the algorithms, three software indices of vegetation cover (NDVI), water areas (MNDWI) and built-up land (NDBI) were used using images. The different sets of setting of each algorithm were evaluated by cross-validation method in order to determine their effect on the accuracy of the results and prevent the optimistic acquisition of spatial correlation from the training and test samples. The results show that the combination of different indices in order to increase the overall accuracy of the algorithms and to produce land cover maps, the forest algorithm is used with an accuracy of 83.08% due to the use of the collection method of higher accuracy and generalizability than compared to. Other algorithms of support vector machine and neural network with accuracy of 79.11% and 75.44% of attention respectively. After determining the most accurate algorithm, the map of flood zones was produced using the forest algorithm in two classes of irrigated and non-irrigated lands, and the overall accuracy of the algorithm in the most optimal models and by combining vegetation indices (MNDWI) was 93.40%. Then, with overlapping maps of land cover and flood plains, the surface of built-up land, agricultural land and green space covered by flood was 4.2008 and 41.0772 square kilometers, respectively.
 

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Human health depends on living in a healthy environment. Various factors determine environmental health, which should be explored to be able to improve them. The purpose of this research is to analyze the factors affecting the health level of urban environment in district 20 of Tehran municipality and to find out their spatial inequality. This is a descriptive-analytical research based on documentary data of 6 indicators and survey data of 26 indicators. For the analysis, various tools of the GIS, especially the spatial analysis tool of Interpolation, are used. Quantitative analyzes are carried out by calculating statistical parameters in attribute tables. Findings show that the score of 2.29 out of 5 in the evaluation range of 1 to 5, indicates a poor situation of environmental health. Higher weakness belongs to the 6 indicators of the economic dimension including saving, sufficient income for buying cultural goods or going to recreational journeys, and residential home per capita. Access to urban parks and green spaces with scores of 4.55 and 3.43 respectively, show a superiority compared to other indicators. In the outskirts, the environmental health condition is much weaker than in the interior areas. Despite the vastness of worn-out fabric and informal constructions and abandoned spaces, what is more effective are the impacts of external factors, 3 sides of the district are limited to fringe lands, where the establishment of polluting industries, the passage of sewage canals and the replacement of foreign and the population involved in informal and illegal jobs are affected the health level of the urban environment.
 

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The occurrence of persistent rainfall, resulting from the integration of multi-scale cyclonic systems, is prone to producing heavy to severe precipitation. Therefore, it is highly significant due to its potential to cause disasters such as floods and landslides, as well as its importance in water resource management for agricultural purposes. In this study, persistent rainfall refers to rainfall events lasting at least three consecutive days with a total precipitation of more than 1 millimeter. The aim of this research is to identify and classify these types of rainfall for the western region of Iran over a 30-year statistical period (1993 to 2022) for the first time using the Lamb-Jenkinson method. In this method, the central coordinates of the study area are used as the reference point in the calculations. Sixteen additional points are also determined around the reference point. With the availability of instantaneous standard sea-level pressure data for these points, it becomes possible to calculate the values of geostrophic wind and vorticity. By comparing these two quantities, the types of weather patterns in the L-J method—which include four types: directional, cyclonic, hybrid, and undefined—are identified and categorized. Disregarding the undefined category, it was ultimately determined that the provinces of Kermanshah, Kurdistan, Hamedan, Lorestan, and Ilam each had 50, 50, 50, 40, and 39 occurrences of the directional state, respectively. Moreover, the frequencies of the cyclonic state for these provinces were 69, 94, 65, 66, and 38, respectively, with cyclonic rotation percentages of 100%, 98%, 97%, 95%, and 97%, respectively. As for the hybrid state, the frequencies obtained for each province were 49, 53, 43, 41, and 38, respectively.
 

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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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Objective: The main goal of this research is to identify and analyze the seasonality of the most widespread Torrential rains in Iran during the years 1940 to 2023.
Methods: To achieve this goal, precipitation data was obtained from the ECMWF database with a spatial resolution of 0.25 by 0.25 degrees of arc for the Iranian region during the study period. The next step was to calculate the threshold of torrential precipitation for each cell seasonally using the 95th percentile, and days with torrential precipitation were identified. By applying the condition of the highest spatial spread of the 95th percentile, the days with the most widespread precipitation above the threshold were identified for each season. Finally, the prevailing atmospheric conditions were examined.
Results: Analysis  shows that the highest precipitation of 146.85 mm occurs in winter and the lowest of 85 mm occurs in summer. The highest spatial coverage of total precipitation occurs in spring (41.9), winter (40.69), autumn (32.55) and summer (16.84), respectively.The analysis of sea level pressure indicates that during widespread precipitation in the summer, a low-pressure belt extended from the westernmost to the easternmost regions of the upper atmosphere map, encompassing Iran. In contrast, during other seasons, a high-pressure belt was present in the same area. At the 500 hectopascal level in summer, a closed high-pressure dynamic cell was observed over Iran, while at the 850 hectopascal level, two low-pressure centers over Saudi Arabia and Pakistan intensified instability over Iran. Consequently, it is evident that at lower levels, the conditions for atmospheric precipitation were stable, and even the omega level at 500 hectopascals over Iran on that day indicated a weak upward movement of air. However, in other seasons, a trough consistently positioned over western Iran, with active band patterns in spring and winter, facilitated the slowing and diversion of currents toward moisture sources, thereby enabling the transfer of more moisture than normal conditions to Iran. The precipitation study revealed that, except for the summer season, wind dominated over Iran. The presence of wind intensified instability at lower levels. A study of the Atmospheric River reveals that during widespread rainfall across all seasons, the Atmospheric River, which originates from the Red Sea and the Persian Gulf, has consistently been present. However, in the fall and winter seasons, a branch from the Mediterranean Sea also contributes, resulting in increased rainfall.

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subtropical high pressure (STHP) and Mediterranean cyclone are among the most important synoptic systems affecting Iran's climate. In this study, the effect of the high altitude location of the sthp on the Mediterranean gyres during the droughts and wetness of Iran during 1979 to 2020 was analyzed. In this regard, two datasets were used. Station data were used to identify drought and wetness periods, and ECMWF-ERA5 grid data was used to identify the location of high pressure in the subtropical region. The results showed that STHP with 3 anticyclone cells (ridge) affects the position of atmospheric waves affecting Iran's rainfall. The STHP system, especially the Arabian Subtropical anticyclone (ASA) and North Africa, play a more important role in the location of the cyclone affecting Iran's rainfall, so that widespread droughts with the expansion of the ASA to the west and its integration with the African anticyclone, the lack of expansion of the Mediterranean trough to the sea Redness and reduction of Sudan low and Mediterranean integration systems occur. With the eastward movement of the ASA over the Arabian Sea and the northern Indian Ocean, the Mediterranean trough deepens and the amount of waves and consequently the rainfall of the country increases. Therefore, the eastward expansion of the Arabian Peninsula and the strengthening of the North African Ridge provide the conditions for the expansion of the Mediterranean Sea. Whenever the ASA is located in its easternmost position on the Oman Sea and the Arabian Sea, it will lead to the advection of moisture for Iran through the access to the large areas of southern water and eventually rainfall. The main cause of the occurrence of drought and wetness in Iran is the spatial variations of atmospheric waves due to the spatial variations in the ASA.

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The ENSO weather phenomenon, including El Niño and La Niña phases, has significant effects on precipitation, temperature, and drought patterns in different regions of the world. This study aimed to investigate the relationship between ENSO indices such as MEI, SOI, and NINO oscillations with drought indices (TCI, VCI, VHI, and SPI) in the provinces of Guilan, Golestan, and Mazandaran from 2013 to 2022. Satellite data of NDVI, LST, and precipitation were extracted from Google Earth Engine to calculate drought indices, and ENSO data were obtained from the NOAA website for correlation analysis. The results showed that the MEI index had a positive and significant correlation with SPI and showed a decrease in drought with an increase in precipitation, but had a weak relationship with other drought indices. The SOI index showed a negative and significant correlation with SPI, indicating the effect of La Niña on increasing drought, especially in Golestan province. The El Niño indices were positively correlated with SPI in the northern provinces of Iran, confirming the effect of reducing drought and increasing precipitation. During the El Niño phase, the northern regions of the studied provinces experienced an increase in temperature and the south of Mazandaran province experienced subzero temperatures, while during the La Niña phase, the temperature increased and the northern regions of the studied provinces experienced higher temperatures. Vegetation was denser in the south of Golestan province and the east of Mazandaran province during the El Niño phase, but it decreased during the La Niña phase. The SPI index showed that drought during the El Niño phase was more widespread and severe in the western half of the studied provinces and more extensive and severe during the La Niña phase. The VHI index showed better vegetation health in El Niño, especially in Gilan and Mazandaran provinces, and decreased health in La Niña phase, especially in Mazandaran and Golestan provinces.

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Climate change stands out as one of the most pressing environmental challenges of the modern era, exerting profound impacts on aquatic ecosystems—particularly wetlands. This study investigates the influence of climate change on three wetlands in Chaldoran County, West Azerbaijan Province—Pir-Ahmadkandi, Naver, and Zavieh-ye Sofla—spanning the period from 1984 to 2023. To achieve this, climate data were obtained from the TerraClimate database and CMIP6 model outputs under four emission scenarios. Landsat and Sentinel-2 satellite imagery, along with JRC/GSW data, were processed to evaluate changes in wetland surface areas. Annual wetland extents were extracted and compared against climatic parameters (temperature, precipitation, actual evapotranspiration, and snow water equivalent) using time-series analysis, Pearson correlation, and multivariate regression. Additionally, the Delta Method was employed for downscaled climate data to project possible trends over the next 20 years.
The results indicate that rising temperatures and evapotranspiration constitute the primary drivers of wetland shrinkage. Pir-Ahmadkandi and Naver have lost over 27% and around 20% of their surface area, respectively, whereas Zavieh-ye Sofla exhibits an irregular, seasonal reduction due to human interventions and agricultural runoff. Projections suggest that wetland surfaces—especially in Pir-Ahmadkandi and Naver—will continue to decline, potentially exacerbating drought conditions, diminishing biodiversity, and reducing water quality. These findings underscore the necessity of implementing sustainable water resource policies, controlling evaporation, and incorporating human impact assessments into conservation measures. Moreover, harnessing advanced hydrological modeling techniques and integrating remote sensing data with machine learning approaches may offer more effective strategies for safeguarding these vital wetland ecosystems.
 

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Objective: This study aims to analyze greenhouse gas variations across Iran and to identify the gases that exert the greatest influence on their overall dynamics. The findings enhance understanding of atmospheric pollution patterns and support the development of effective mitigation strategies. These results provide a scientific basis for climate-change mitigation planning in Iran. The study relies on satellite-based remote sensing datasets.
Methods: This study analyzes the temporal and spatial variations of major greenhouse gases including carbon monoxide, nitrogen dioxide, ozone, water vapor, and methane across Iran from 2019 to 2024. Sentinel-5P satellite data were extracted via the Google Earth Engine platform, and after filtering and removing low-quality observations, the data were standardized using the Z-Score method to enhance comparability and correlation analysis. Principal Component Analysis (PCA) was applied to reduce data dimensionality and identify dominant variation patterns. Temporal and spatial trends were then quantified using complementary statistical techniques.
Results:
Methane exhibited a consistent increasing trend from late 2021 through 2024 and accounted for the largest share of total variance (R² = 0.87), likely reflecting intensified anthropogenic activities and regional climatic shifts. CO, NO₂, and O₃ were mainly affected by seasonal fluctuations and nonlinear factors, and no clear long-term increasing or decreasing trends were observed. Water vapor showed a direct relationship with temperature variations, water sources, and atmospheric patterns, with its lowest concentrations recorded during the cold months and increases observed in the warm months. PCA analysis indicated that the first two principal components explained more than 70% of the total data variance, with CH₄, O₃, and NO₂ contributing the most to the overall variations.
Conclusions: The study results indicated that greenhouse gas variations in Iran are simultaneously influenced by natural factors and human activities. The combination of satellite data, statistical analysis, and PCA enabled a precise assessment of the temporal and spatial trends of greenhouse gases, providing valuable information for planning pollutant reduction and developing strategies to combat climate change.



 

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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: Over the past two decades, land subsidence has emerged as a significant geomorphological hazard and one of the most critical environmental crises in Iran, causing irreversible damage to many plains each year. Among its primary current causes is the excessive and unregulated extraction of groundwater. The Eshtehard Plain, recognized as one of the industrial and agricultural hubs of Alborz province, is no exception. Due to severe groundwater depletion, it has been officially declared a critical zone by the Ministry of Energy. The objective of this study is to model the risk of land subsidence in this plain using the Random Forest algorithm and to analyze the contributing factors influencing its occurrence
Methods: In this study, twelve independent spatial layers were utilized, including: digital elevation model (DEM), distance to rivers, distance to qanats, distance to wells, distance to faults, groundwater depth, drainage density, soil type, lithology, land use, topographic wetness index (TWI), and solar radiation. The dependent layer consisted of subsidence zones. The Random Forest model was implemented in the R software environment. Two key importance measures—Mean Decrease Accuracy and Mean Decrease Gini—were employed to rank, assess the significance of, and assign weights to the contributing factors of land subsidence. Finally, model performance was evaluated using three complementary metrics: Accuracy, Kappa, and AUCResults: The results demonstrated that the Random Forest model achieved high accuracy in classifying land subsidence risk. Model evaluation showed strong performance with an overall accuracy of 0.963, a Kappa coefficient of 0.611, and an AUC value of 0.955, indicating that the model is highly effective for spatial risk zoning of land subsidence. The most influential variables in subsidence occurrence were identified as groundwater depth, distance to wells, geology, and land use. Furthermore, more than 65% of the study area was categorized as high-risk and very high-risk, reflecting the critical condition of the Eshtehard Plain. Notably, the share of urban land use has shown a steady increase from 2011 to 2023, with a significant spike in 2023, where increased population concentration has placed additional pressure on groundwater resources, leading to an intensification of subsidence in affected areas
Conclusions: The Random Forest algorithm successfully modeled the spatial distribution of land subsidence risk with high accuracy. This method can serve as an effective tool for informed decision-making in groundwater resource management, sustainable development planning, and hazard mitigation in similar regions.