Showing 111 results for Co
Mehranjani Mohammad Soleimani, Tahereh Nemati, Tajeddin Karami, Ahmad Zanganeh, Taher Parizadi,
Volume 12, Issue 1 (8-2025)
Abstract
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.
Saeid Shabani, Behrooz Mohseni, Aiding Kornejady, Akram Ahmadi, Hassan Faramarzi, Esmaeil Silakhori,
Volume 12, Issue 1 (8-2025)
Abstract
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.
Dr Saleh Arekhi, Mr Habib Allah Kour, Somia Emadaddian,
Volume 12, Issue 2 (9-2025)
Abstract
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.
Esmaeil Kavyanpour Sangeno, Sadroddin Motavalli, Sara Gholami, Gholamreza Janbaz Ghobadi,
Volume 12, Issue 2 (9-2025)
Abstract
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.
Dr Ataollah Ebrahimi, Dr Masoumeh Aghababaei, Dr | Ali Asghar Naghipour, Dr Esmaeil Asadi,
Volume 12, Issue 3 (12-2025)
Abstract
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.
Mohammad Hossein Nasserzadeh, Parviz Ziaian Firouzabadi, Zahra Hejazizadeh, Shirin Moradjani,
Volume 12, Issue 4 (12-2025)
Abstract
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.
Gholam , Peyam Afshar, Eisa Piri,
Volume 12, Issue 4 (12-2025)
Abstract
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.
Mrs Shokoufeh Omidi Ghaleh Mohammadi, Dr Ahmad Mazidi*, Dr Kamal Omidvar,
Volume 13, Issue 1 (7-2026)
Abstract
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
Mr Milad Heydari, Dr , Dr Ali Akbar Barati, Dr Taher Azizi Khalkheili,
Volume 13, Issue 1 (7-2026)
Abstract
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
Engineer Sama Abdollahi Milani, Engineer Sama Rahmani, Doctor Javad Imani Shamloo,
Volume 13, Issue 1 (7-2026)
Abstract
Objective: The study aims to evaluate the ecological, environmental, and economic services provided by urban vegetation within the El-Goli green network in Tabriz. Specifically, it focuses on assessing the role of green infrastructure in mitigating urban environmental challenges through carbon sequestration, air pollution reduction, and surface runoff management. The research seeks to provide insights that support informed urban planning and the sustainable expansion of green spaces.
Methods: This study is a quantitative research that employed library-based methods (literature review, definitions of urban green infrastructure, and expert opinions) and field observations, combined with statistical analysis using i-Tree software for data collection. Data analysis was conducted using a descriptive-analytical approach, and the results are presented in tables.
Evaluation Parameters: The ecosystem services assessed in this study include carbon sequestration and storage, air pollution reduction, and stormwater management.Assessment Parameters: Key ecosystem services evaluated include carbon capture and storage, air pollution reduction, and surface runoff management.
Results: The El-Goli green network in Tabriz sequesters approximately 75.84 tons of carbon annually.
The green network removes about 2,077 tons of air pollutants per year.
Among the pollutants analyzed, ozone was the most effectively removed, while carbon monoxide showed the lowest removal rate.
The findings underscore the significant role of the El-Goli green network in improving urban air quality and contributing to climate change mitigation.
Conclusions:
This study used i-Tree Canopy 7.1 to assess the ecosystem services of El-Goli Park in Tabriz from ecological and economic perspectives. The vegetation area was measured, and trees and shrubs were counted to estimate carbon storage, air pollutant removal, and surface runoff mitigation. Results showed that the park annually sequesters 75.84 tons of carbon, removes 2,077 kg of air pollutants, and mitigates 1.92 liters of surface runoff. Considering the software’s limitations, it is recommended that ecosystem productivity in the park and other urban green spaces be enhanced through the protection of valuable trees, increasing effective plant species, developing dense vegetation cover, and implementing bioretention networks.
Dr. Malihe Erfani,
Volume 13, Issue 1 (7-2026)
Abstract
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.