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Now showing items 1 - 13 of 13

  • Wetland Restoration Prioritization Using Artificial Neural Networks

    Maleki, Saeideh   Soffianian, Ali Reza   Koupaei, Saeid Soltani   Baghdadi, Nicolas   EL-Hajj, Mohamad   Sheikholeslam, Farid   Pourmanafi, Saeid  

    Wetland destruction is currently one of the greatest environmental problems in the world. Despite the functions of wetlands, these valuable ecosystems have steadily decreased because of human activities and climate change. To protect these valuable ecosystems, wetland restoration and rehabilitation are important operations that have been conducted worldwide. Since a wetland is a complex ecosystem with a variety of phenomena, increasing the number of variables considered during a restoration project will further boost the success rate of a restoration project. However, the inclusion of more variables will increase the complexity of the analysis. Thus, a method that can analyze complex models using many input variables is valuable. In most scientific studies, artificial intelligence algorithms have been widely applied to complex projects. However, the main question is whether these algorithms can learn the ecological patterns of a restoration project. For this reason, a multilayer perceptron (MLP) neural network was applied in this paper to investigate the ability to use these algorithms for wetland restoration. An artificial neural network (ANN) with one hidden layer and 15 neurons was used to determine the best areas for wetland restoration. The neural network was trained using the Levenberg-Marquardt algorithm; then, the trained ANN was used to determine the best areas for wetland restoration. The root mean square error (RMSE) of the model that was trained to prioritize wetland restoration was 0.04 ha. Because of water limitations in the study area, it is not possible to restore entire wetlands. Therefore, areas for restoration are prioritized based on ecological objectives. The results of the ANN demonstrate its ability to learn the ecological patterns and illustrates the performance of using this method for wetland restoration. Neural networks can calculate the final weights mathematically, and these algorithms are able to analyze complex models using many input variables; thus, ANNs are practical for wetland restoration.
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  • Environmental vulnerability assessment of Choghakhor International Wetland during 1985 to 2018

    Hedayati, Aliakbar   Pourmanafi, Saeid   Kashkooli, Omid Beyraghdar   Ghorbani, Rasul  

    As of natural constraints, and the specific climate of Iran, as well as the increasing importance of international water resources in the socio-economic development of societies, studies on surface water resources, especially wetlands, merit special attention. Accordingly, the TM, ETM+ and OLI satellite images of 1985, 2000 and 2018 were used in the present study to detect changes in the Choghakhor international wetland. Classifying the images with a supervised method, and using maximum likelihood algorithms, the distinct land use/land cover classes of waterbody, aquatic plants, pasture and forest, agricultural lands, bare land and human built lands were ranked. Selected landscape metrics information on the spatial pattern of the Choghakhor wetland was quantitatively determined, using Fragstats software, and the spatial composition and vulnerability of the wetland were evaluated. The vulnerability assessment of wetland contamination was investigated using the WRASTIC index based on the catchment area scale. Time processing of the data obtained from the maps indicated a 26.63% decrease in the pasture and forest area, and a 12.1% increase in the area of human built lands and agriculture lands during the period from 1985 to 2018. Further, in spite of the waterbody area expanding during 1985 to 2000, it subsequently shrunk in size from 2000 to 2018, with the area of aquatic plants lands increasing during the same period. Analysis of landscape metrics generally indicated the natural wetland cover has been changing during this period along with increasing anthropogenic impacts. Degradation, rotation and replacement of natural land cover such as pastures and forests with human built areas can be considered undesirable development effects on the Choghakhor wetland. The results of the WRASTIC index calculation indicated a major impact of Choghakhor wetland components from water pollution. The results of the present study place an emphasis on more sustainable land use and prevention of land destruction in the Choghakhor wetland basin.
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  • Comparing different classification algorithms for monitoring mangrove cover changes in southern Iran

    Toosi, Neda Bihamta   Soffianian, Ali Reza   Fakheran, Sima   Pourmanafi, Saeid   Ginzler, Christian   Waser, Lars T.  

    Mangrove forests in Iran are highly productive and complex ecosystems since they represent the interface between land and sea. They are a unique environment for supporting biodiversity, and they provide direct and indirect benefits to humans. Investigating changes in mangrove forests is essential for ecologists and forest managers to improve the assessment and conservation of natural ecosystems. The goals of the present study include: (I) to evaluate and compare four supervised classification algorithms based on Landsat time series imagery to detect mangrove cover in southern Iran, (II) to detect changes in mangrove cover between 1985, 1998, and 2017; and (III) to compare the four different predictions resulting from the applied classification algorithms. An accuracy assessment was conducted using k-fold cross-validation and independent validation, and differences between the classification techniques were analyzed. Although all four algorithms produced high overall accuracy (ranging from 81% to 93%) and Kappa values (from 0.81 to 0.92), visual comparisons of the predictions revealed that Random Forest (RF) performed best. The results of the change analysis showed that mangrove cover areas decreased by approximately 4% from 1985 to 1998 and then increased by approximately 8.9% from 1998 to 2017. A change detection map shows a decrease in mangrove cover in near coastal regions, such as the Tabl and Gavarzin areas, and an increase in mangrove cover at a distance from the Qeshm coastline that involves open spaces between the trees. Rising water levels and human development are important factors in the decline of mangroves. The findings of this research are useful for the management, restoration and conservation planning of mangrove forest in southern Iran. (C) 2019 The Authors. Published by Elsevier B.V.
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  • Exploring structural and functional corridors for wild sheep (Ovis orientalis) in a semi-arid area

    Dehaghi, Iman Momeni   Soffianian, Alireza   Hemami, Mahmoud-Reza   Pourmanafi, Saeid   Salmanmahiny, Abdolrassoul   Wu, Gi-Mick  

    Although corridors have been the subject of extensive research in the recent years, the probable correlation between structural and functional corridors have not been addressed to date. To fill this scientific gap, we compared structural and functional corridors of wild sheep (Ovis orientalis) as a threatened species in a semi-arid area of central Iran. We first used Maximum-Entropy to develop wild sheep habitat suitability map. We then used Morphological-Spatial-Pattern-Analysis (MSPA) and circuit theory to map structural and functional corridors of wild sheep respectively. Bootstrapping techniques then were used to compare structural and functional corridors. We found that structural corridor is a concept which is dependent on the scale of observation. By changing edge-width from 600 to 1200 m, the total area of structural corridors increased by 63%. We also only found very small differences in the functional connectivity role of different MSPA categories (including structural corridors). All MSPA categories together accounted for only 20% of the functional connectivity. Although, in some cases functional corridors had a better performance in showing migration path of wild sheep between reserves, other cases showed that for effective conservation, both structural and functional corridors should be identified and considered in the planning step.
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  • Integrated Coastal-Terrestrial Conservation Planning for landscape-scale reserve design in Southeastern Iran

    Shafiezadeh, Mohammad   Moradi, Hossein   Fakheran, Sima   Pourmanafi, Saeid   Senn, Josef  

    Natural habitats of Southeastern Iran are threatened by both natural and anthropogenic pressures such as longterm drought, dust storms, and land use change. Surveys on habitat suitability of vulnerable species and integration of protected areas have raised alarm over potential species extinction and geographical isolation of populations. Reducing the threats of human activities on sensitive terrestrial and coastal ecosystems requires integrated planning and management of terrestrial and coastal protected areas, however many of these areas have been selected and managed independently. Selecting coastal protected areas network require a systematic conservation planning approach, to reduce the development impacts on sensitive habitats. Therefore, this study aimed to identify an optimized integrative network of terrestrial and coastal protected areas in southeast Iran. An attempt was made to maximize biodiversity conservation, reduce the isolation of populations, and increase the resilience of the region's natural habitats to new development plans by including coastal habitats meeting the requirements of key species. Firstly, suitable habitats for seven key species were simulated by Species Distribution Models (SDMs) performed via Generalized Linear Model (GLM), Generalized Boosted Model (GBM), Random Forest (RF), and Maximum Entropy (MaxEnt) models fitted with 20 ecological and anthropogenic variables. A habitat suitability map was produced by integrating the SDM-derived habitat suitability maps with the suitable extents identified for egg-laying green sea turtle and potential habitat for aquatic and semi-aquatic birds. An attempt was then made for selecting new terrestrial and coastal protected areas using the simulated annealing algorithm under six scenarios. All SDMs exhibited promising performances in predicting the distribution of suitable habitats with AUC values of above 0.8 and the discrimination power of GBM and RF was higher than that of the other SDMs. In total, more than 34 percent of the study area, along the coastline, was categorized as sensitive or extremely sensitive habitat. An east-west habitat corridor presently unprotected playing an important role in connecting habitats needs to be safeguarded to maintain regional biodiversity. Moreover, our study revealed that the majority of suitable habitats with high potential for sensitive species are not currently protected by the existing protected area network.
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  • Integrated Coastal-Terrestrial Conservation Planning for landscape-scale reserve design in Southeastern Iran

    Shafiezadeh, Mohammad   Moradi, Hossein   Fakheran, Sima   Pourmanafi, Saeid   Senn, Josef  

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  • Evaluating optimal sites for combined-cycle power plants using GIS:comparison of two aggregation methods in Iran

    Karimi, Hazhir   Soffianian, Alireza   Seifi, Sadri   Pourmanafi, Saeid   Ramin, Hadi  

    This study aims to use an integration of GIS and multi-criteria evaluation for combined-cycle power plant site selection and compares two aggregation methods for Iran. The information layers of the criteria are prepared in the GIS environment and then the layers standardised using fuzzy functions in IDRISI. All layers are combined using two conventional methods of fuzzy logic and weighted linear combination; from this information, the suitability maps were created. Results show that only 2.0% of the region under study is scored high-suitable using the fuzzy logic, while 21% of the area is considered as highly suitable when the weighted linear combination is used. Despite this significant difference, both approaches recommend the ideal place in the north and northwest of the study area. In conclusion, integrating GIS and multi-criteria evaluation is a comprehensive approach that improves and strengthens the suitability of site selection studies.
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  • Road-induced fragmentation and the environmental value of roadless areas in a partly protected landscape in Central Iran

    Mehdipour, Niloofar   Fakheran, Sima   Soffianian, Alireza   Pourmanafi, Saeid  

    This study assessed the effect of road development on vegetation fragmentation in and around a protected area network in western Isfahan Province, Central Iran. As the first study in Iran, an attempt was also made using the weighted linear combination-informed ecological value index of roadless area (EVIRA), to evaluate the environmental value of roadless areas based on a set of ecological and anthropogenic factors. Toward these aims, a Landsat 8-OLI image was processed to delineate land use/cover of the region. Road-induced fragmentation was then estimated by comparing the results of a small set of landscape metrics (DIVISION, SPLIT, MESH, LPI, and NP) measured from the original and road-included LULC map. The results showed road-induced increasing DIVISION (by 4.8-85.9%) and SPLIT (by 0.01-23.1%) and decreasing MESH (by 2.7-14%), LPI (by 1.3-32.4%), and NP (by 6-97.8%) values within all protected areas and across the entire study area, indicating a significant rise in landscape fragmentation and habitat loss. Roadless patch area and Thiessen connectivity stood out as the most salient criteria in determining environmentally valuable roadless areas. The results of EVIRA showed that the study region comprises some valuable but unprotected roadless areas which should be protected against road development or any kind of destructive human activities by laying out conservation plans or their inclusion to the current protected area network.
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  • The study of thermal pattern changes using Landsat-derived land surface temperature in the central part of Isfahan province

    Madanian, Maliheh   Soffianian, Ali Reza   Koupai, Saeid Soltani   Pourmanafi, Saeid   Momeni, Mehdi  

    Urban development and consequently, the growth of construction can result in changing the climatic parameters, such as land surface temperature (LST). This study was conducted in the central part of Isfahan province to investigate changes in thermal patterns during 1985-2015 time period. To generate land-use/land-cover maps and LST, Landsat-TM, ETM+ and OLI/TIRS data were utilized. The results demonstrated that impervious surfaces had been increased by 2.8 times from 1985 to 2015. The results also indicated a negative correlation between LST and the Normalized Difference Vegetation Index (NDVI) in hot months. This research also focused on exploring the occurrence of surface urban heat island (SUHI) in hot and cold months in the city of Isfahan. Buffer zones in various widths were created to measure SUHI. In August 1985, in buffers of 1 km-3 km and in July 1992, in all buffers, SUHI was observed. In contrast, in July 2001, in buffers of 3 km-10 km and in July 2015, in all buffers, LST of Isfahan rural area was higher than that of city, showing surface urban cool island (SUCI). The results also demonstrated that the urban area was cooler than the surrounding rural area in the cold months.
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  • Analyzing the effects of urban expansion on land surface temperature patterns by landscape metrics: a case study of Isfahan city, Iran.

    Madanian, Maliheh   Soffianian, Ali Reza   Koupai, Saeid Soltani   Pourmanafi, Saeid   Momeni, Mehdi  

    Urban expansion can cause extensive changes in land use and land cover (LULC), leading to changes in temperature conditions. Land surface temperature (LST) is one of the key parameters that should be considered in the study of urban temperature conditions. The purpose of this study was, therefore, to investigate the effects of changes in LULC due to the expansion of the city of Isfahan on LST using landscape metrics. To this aim, two Landsat 5 and Landsat 8 images, which had been acquired, respectively, on August 2, 1985, and July 4, 2015, were used. The support vector machine method was then used to classify the images. The results showed that Isfahan city had been encountered with an increase of impervious surfaces; in fact, this class covered 15% of the total area in 1985, while this value had been increased to 30% in 2015. Then LST zoning maps were created, indicating that the bare land and impervious surfaces categories were dominant in high temperature zones, while in the zones where water was present or NDVI was high, LST was low. Then, the landscape metrics in each of the LST zones were analyzed in relation to the LULC changes, showing that LULC changes due to urban expansion changed such landscape properties as the percentage of landscape, patch density, large patch index, and aggregation index. This information could be beneficial for urban planners to monitor and manage changes in the LULC patterns.=20
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  • Monitoring spatiotemporal variability of water quality parameters Using Landsat imagery in Choghakhor International Wetland during the last 32 years

    Hedayati, Aliakbar   Pourmanafi, Saeid   Kashkooli, Omid Beyraghdar   Ghorbani, Rasoul  

    Use of Landsat is of importance in monitoring and assessment of long-term changes of water quality in freshwater ecosystems, especially in small water bodies. In this study, over a 32-year period (1985-2017), the changes in water surface temperature (WST), secchi disk transparency (SDT), and chlorophyll-a (Chl-a) concentration were estimated at the Choghakhor wetland using Landsat imagery. Based on WST three detectable temperature zones can be observed within the wetland aquatic environment where the highest amount was observed in thermal strips. The results showed Chl-a concentration volatility in different periods in the wetland as well as its long-term increasing trend. The western part of the wetland, as compared to other areas, was affected by these changes, which could be due to the human activity concentrated in this area. In contrast (SDT) showed a decreasing trend during this period that was consistent with the observed changes in Chl-a concentration. This could be due to an increase in organic matter load and suspended solids in the water body of wetland during this time. Comparison of the extracted satellite data with the field data showed the least RMSE and high R-2. Also, ANOVA results showed significant spatio-temporal differences between the studied parameters in Choghakhor wetland (p < 0.05). The present study can help to detect long-term changes in Choghakhor wetland and help toward moving to optimal management and protection of this wetland.Mapping the spatio-temporal distribution for Chl-a, SDT, and WST with remotely sensed data would be helpful for management of freshwater ecosystems (here the wetland). According to the results of this study, large changes in these parameters were observed in the Choghakhor wetland during the period 1985-2017 and reflect the ecological conditions in the wetland. Considering that this first study with a new approach to the region, it can be used as a comprehensive guideline for remote monitoring as a viable tool for monitoring wetlands.
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  • A Statistical Comparison between Less and Common Applied Models to Estimate Geographical Distribution of Endangered Species (Felis margarita) in Central Iran

    Torabian, Shiva   Ranaei, Mehrdad   Pourmanafi, Saeid   Chisholm, Laurie  

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  • Modelling the impact of climate change on rangeland forage production using a generalized regression neural network:a case study in Isfahan Province,Central Iran

    Jaberalansar, Zahra   Tarkesh, Mostafa   Bassiri, Mehdi   Pourmanafi, Saeid  

    Monitoring of rangeland forage production at specified spatial and temporal scales is necessary for grazing management and also for implementation of rehabilitation projects in rangelands. This study focused on the capability of a generalized regression neural network (GRNN) model combined with GIS techniques to explore the impact of climate change on rangeland forage production. Specifically, a dataset of 115 monitored records of forage production were collected from 16 rangeland sites during the period 1998-2007 in Isfahan Province, Central Iran. Neural network models were designed using the monitored forage production values and available environmental data (including climate and topography data), and the performance of each network model was assessed using the mean estimation error (MEE), model efficiency factor (MEF), and correlation coefficient (r). The best neural network model was then selected and further applied to predict the forage production of rangelands in the future (in 2030 and 2080) under A1B climate change scenario using Hadley Centre coupled model. The present and future forage production maps were also produced. Rangeland forage production exhibited strong correlations with environmental factors, such as slope, elevation, aspect and annual temperature. The present forage production in the study area varied from 25.6 to 574.1 kg/hm(2). Under climate change scenario, the annual temperature was predicted to increase and the annual precipitation was predicted to decrease. The prediction maps of forage production in the future indicated that the area with low level of forage production (0-100 kg/hm(2)) will increase while the areas with moderate, moderately high and high levels of forage production (>=3D 100 kg/hm(2)) will decrease both in 2030 and in 2080, which may be attributable to the increasing annual temperature and decreasing annual precipitation. It was predicted that forage production of rangelands will decrease in the next couple of decades, especially in the western and southern parts of Isfahan Province. These changes are more pronounced in elevations between 2200 and 2900 m. Therefore, rangeland managers have to cope with these changes by holistic management approaches through mitigation and human adaptations.
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