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Green space and its spatial formation are important elements of public welfare in urban environments and green ecosystems in big cities largely contribute to the mental and physical health of citizens. Tehran is Iran's biggest and most polluted city and air pollution in this city causes loss of human lives due to respiratory diseases. The effect of green area has been less studied in former researches in Tehran, and the reducing effects of green landscape on the mortality of respiratory diseases have not yet been evaluated. To measure the effects of green area landscape patterns (fragmentation, area-edge, shape, and aggregation) on public health, the current study evaluated the pathways and effects of green space on air pollution and the mortality of respiratory diseases using structural equation modeling approach and the partial least squares method. The results of the study indicated green space has a significant mitigating effect on air pollution and mortality of respiratory diseases and also air pollution has a meaningful increasing effect on mortality due to respiratory diseases in Tehran. The most important latent variable in green space is class area that indicates more area of green space is correlated with less mortality of respiratory diseases. The most important indicator of air pollution was the PM2.5 that needs to be considered and controlled by urban policymakers. Accordingly, maximizing the green area and its cohesion and minimizing fragmentation and green patch edge can contribute to a reduction in air pollution and consequently lower mortality of citizens.

The mechanism of noise pollution propagation is considerably affected by 1) the type and configuration of its receiving environment and 2) the distance that sound waves pass to reach that environment. This study adopts a spatio-statistical approach to quantify and model associations between noise pollution levels and landscape metrics of land categories (built-up structures and urban green covers). Accordingly, noise levels were measured employing a sound pressure meter to quantify equivalent levels (Leq in dB A), in addition to their corresponding percentiles (L10 and L90). A collection of 30 sampling points were selected to measure noise data within the fall season and between 4 p.m. and 8 p.m. hours of the day. A hierarchical distance-sampling framework based on buffer areas with different radius (300 m, 600 m and 1 km) around each sampling point was compiled to measure composition and configuration metrics of land categories within each buffer area. The results derived from Pearson correlation analysis and multiple-linear regression models indicated that there is a distance-dependent relationship between the metrics of green areas and noise levels. We didn’t find remarkable distance-dependency between built-up structures and noise levels. Based on our new spatio-statistical approach, we conclude that more connected and compacted pattern of green areas closer to pollution centers can significantly alleviate the effects of noise propagation mechanism and appropriate pattern of built-up areas follows a low density distribution with coming green areas in between. Findings of this study highlight the potential of landscape ecology approach as an effective planning paradigm for designing greener and calmer cities.

Protected areas are valuable ecosystems standpoint providing various ecological processes and functions. Unfortunately, during the recent decades, population growth and human development have been changed the land use/land cover of the most protected areas in the world. Varjin Protected Area is one of the oldest protected areas. In this study, landscape metrics were used to reveal landscape patterns in Varjin Protected Area using Landsat satellite imagery from 1986, 2000 and 2010. For this purpose, remotely sensed images have been corrected in terms of geometric and radiometric distortions and were then classified through hybrid method. The resulting land cover map was divided into four categories: residential, orchard, good rangeland quality, and poor rangeland quality. The proportion of the Class Area (CA) regarding residential class increased from 1986 to 2010 whereas the proportion of orchard class area was rather stable among the three dates. Concerning the poor rangeland quality, its total class area increased from 1986 to 2000 and then slightly declined from 2000 to 2010. Based on the Largest Patch Index (LPI), the dominant land cover class across the three dates was poor rangeland quality although the number of patches was shifted between the years 1986 and 2000. The isolation/proximity metrics represented by ENN_MN showed an increase of the residential class area, whereas the changes among other classes were limited. The main driving force of the residential area increase was the willingness of local people to sell their agricultural lands for a lot of money, so as rich Tehranian people to abandon air and noise pollution of the capital and immigrate to the protected area region, specifically to the Villa Building . This study highlighted the importance of landscape metrics in monitoring land use/land cover change over time.

Understanding and analyzing the dynamics of reservation areas, as one of the most valuable ecological resources, is of great importance for effective management of these environments. Monitoring the process of land-use/land-cover (LULC) transformations in these areas and knowing their driving forces would contribute to an informed decision making. In this study, an integrated application of satellite imagery interpretation and landscape ecology approach is implemented to quantify and analyze the landscape dynamics of Jajroud reservation area, Iran. The digital images collected by satellite at 1986, 2000, and 2010 were classified following an ensemble classification method. The resultant LULC maps included six categories of orchard, healthy rangeland, degraded rangeland, afforest, water, and urban. Landscape metrics-based analysis of temporal patterns of LULCs indicated that Jajroud reservation area has been undergoing rapid and drastic changes over the past 25 years. Based on class area metric at landscape level, changes were mostly due to the conversion of degraded rangeland and orchard to urban category. The impervious area expanded approximately fivefold from 1986 to 2010. Based on Largest Patch Index metric, the dominant land-cover class across the study time frame was degraded rangeland that decreased from 1986 to 2010. The main driving forces of urban growth in the area were willingness of local residents to sell their orchard lands and having financial interests. Because of rapid economic development and expansion of human-constructed elements, the landscape of the area experienced a fragmentation process during the last three decades. The study demonstrated that integrated application of satellite imagery and landscape metrics can be a useful and easy-to-implement tool for environmental impact assessment of an ongoing urbanization process.

Globally, land use change impacts biodiversity, water and radiation budgets, emission of green house gases, carbon cycling, and livelihoods. The study of LUCC and its dynamics is crucial for environmental management, especially with regard to sustainable agriculture and forestry. Different models, in terms of structure and application, have been used to understand LUCC dynamics. The present study aims to simulate the spatial pattern of land use change in Varjin protected area, Iran. Land cover maps for 2000 and 2010 were prepared using TM images. Images were classified using supervised classification. CA Markov model was used to predict land cover map for 2020 as a top-down approach in investigating land use change. A comparison was made between the predicted and older land use map. The findings of the study suggest that the region will experience a degradation in poor range and increase rate in urban from 2010 to 2020. Moreover, if the trend of land exploitation and current management policy of the region continue as before, the region will experience with urban development and degradation in the Varjin protected area.