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Hassan Afrakhteh,
Volume 1, Issue 2 (7-2014)
Abstract

Settlement's Systems are evolving as any other systemic phenomenon. Multitudinous and different factors are involved in settlements evolution and shaping. One of the effective factors on settlement system evolution is society public power intervention and planning based on approaches which had been approved as predominant paradigm on its time.    

Creation and reinforcement of growth poles was considered as national economic growth instrument in developing country, till 1970. It was supposed that growth pole effect will cause surrounding area's prosperity. The theory of Perroux growth pole was one of these theories in regional planning.

During recent years, some rural settlements of country have experienced physical-spatial changes and have transformed to Towns. These processes have been rising based on theoretical approaches related to spatial development or according to political consideration and election requirements. This trend imposed inconsistency landscape to settlements, and has been the source of crises and economic, social, management and environmental disasters.

     The main question in this research is "what has been the environmental subsequent of Maklevan evolution based on rural planning and also political consideration, and alteration it into town from 2013? Study area of research is Maklevan in Fuman county, Guilan province, Iran. Required data are collected from documents, Satellite images, and field study and questionnaire fulfillment. Collected data has analyzed based on variable frequencies distribution and locational-spatial approaches. Documents show that Maklevan development trend was done without passing any gradual organic process and only inspired from growth pole theory. Assignment the role of service center (services including health, education, agricultural, post, bank, administrative, business services, and Saturdays week local market), creation of main big avenue and concentration of investment (although limited) with the purpose of hinterland development and population centralization, are some of these evidences. That outcome of current development trend in Maklevan is creation a situation which has reinforces incidence and prevalence of environmental hazards including:

  • Destruction and loss of agricultural soil, the soil of Maklevan was very rich for rice cultivation, because it is provided from alluvial of Masuleh Rudkhan River. Deficiency of arable soil is considerable, therefore arable soil elimination could result to food insecurity, unemployment, extension of unofficial jobs in the region and urban fringes. Research depicted that the area of paddy lands were reduced from 1.27 square kilometers to 0.8 square kilometers during 5 years (2010-2015), which means that 46 percent of rich paddy lands has been reduced. Agricultural lands and forest has been destructed by establishment of unnecessary roads and villas. Due to above mentioned changes the area of Maklenan (constructed area) was increased from 6.12 square kilometers to 12.11square kilometers during last five years (2010-2015).
  • Destruction of forest and flood extension risk, regarding to climate situation of area, topography and kind of soil, the probability of flood risk and landfall has been increased. The evidence of land destruction, housing and bridge by the flood obviously can be seen in the point of bridge between Maklevan and Kondesar.
  • As the experience of Masuleh shows, concentration of population in a location such as Maklevan will intensify the pollution of water resources especially Masuleh Rudhan River, because of the drainage of all wastewater are into this River.
  • Undermining the foundations of traditional production and its subsidiary production, elimination of handicraft production and vernacular architecture resulted into the attenuation of area tourism foundation. Extension of Tourism activities was one of the main goals of Maklevan development.
  • Due to Physical disturbance, functionally Maklevan has become a space that is urban space nor rural. Livelihood system shows the coexistence of agricultural, animal husbandry, service and business activities. Modern buildings are seen besides the cottages.

     As a conclusion it can be said that growth pole theory is not suitable approach for settlements development in the country, or at least in the studied area. Since land use control and management should be in accordance with existing local reality. Land use planning process should be responsible of three fundamental questions: where are we? Where are we going? How can we arrive there? Rational decision making, different situation flexible approaches, emphasis on conservation of sustainability, harmony with nature, can prevent from adverse consequences of interference in nature. Therefore, abrupt town creation without gradual processes and using indigenous knowledge and people participation doesn't lead to creation of sustainable cities, but its outcome will irreparable harm to people and natural resources.


Hassan Afrakhteh,
Volume 2, Issue 4 (1-2016)
Abstract

The City-region of Tehran is encountered with various environmental problems, including traffic, air pollution, lack of drinking water and green space, physical texture conflict, flood and earthquake. Capital accumulation has considerable role in shaping spaces which can create and intensify environmental disaster in special socio-economic situation. The second cycle is the conversion of capital to fixed and long-term assets with the aim of further benefits, which in fact produces two types of artificially environment during this process namely the built environment for production, and the built environment for consumption.

The third cycle is aiming to connect science to production and increase production capacity by investment in science and technology. When production of surplus value reduced in the first cycle, surplus value of second cycle increases through speculation and real estate transaction (real estate capital). Therefore, the owners of the lands and buildings are encouraged in production, trade and supply of these type assets.

In the courtiers that are legally and administratively encounter with tax receipt problems,  urban lands ownership is deposited to market system without any control, hosing transaction continues without any limitation, situation is moving forward to personal vested interests, asset value rises rather than production value, the price of land and construction increase severely. In the above mentioned condition, beneficiaries attempt convert the natural resources including park, mountain, river privacy and road privacy to marketable commodity and legally or quasi legally seize them. Therefore, unreasonable construction and population density increases and city-region will encounter with environmental disasters.  

The main objective of this research is to understand the underlying factors of capital accumulation through construction and its impacts on createion and intensification of environmental disasters in the Tehran city-region.

  Five different regions of Tehran were selected for data collection. "Q-methodology" was used for gathering and analyzing data. The society of communication or people whom the study sought to identify their mentality towards the research topic, were 25 experts selected through purposive sampling. To set the concourse of communication, a combination of primary (experts commented in an interview) and secondary (sources of credit) sources have been used and   34 statements have been developed. After sorting the data for analysis, SPSS software data matrix is ​​formed. Factor analysis, as main method of analyzing Q data matrix has been used based on Q logical methodology.

The results of Q analysis depicted four viewpoints with variance of 95.911 percent on the underlying cause of capital accumulation through construction and its contribution on increasing risk of natural hazards in Tehran city-region.

The first viewpoint has devoted 52.800 percent of total variances and can be titled as" Function of real estate transaction and Non-productive economic domination".

The second viewpoint which has received 18.914 percent of total variances is accordance with "commodification of land and housing". The third viewpoint is" management and monitoring of the city-region space" with 15.163 percent of total variances.  The fourth viewpoints under the title of" monitoring and control of natural resources" has assigned 9.034 percent of total variances.

As result of these processes, land and housing business have weakened society's productive capacity by extensive land use change in the urban peripheral area's due to its huge and quick profit. The above process accompany with selling excess density policy created a powerful political and economic stratum which harmed city sustainable development. The mountainous area of north, north east and west of Tehran, have annexed to metropolis as a result of above mentioned regulation and  may gardens have converted to construction by different gropes and institutions.

Q method analysis depicted that the Tehran City-Region has converted from use value to exchange value. It means that values of the city including work, security, education, leisure and welfare have been lost in favor of exchange value. In other words, the city has been converted to a commodity for exchange and selling in pursuit of profit, rising cost of urban land, building and housing. Consequently, the city-region construction site is extended to the river beds, steep slops and surrounding natural environment. This in turn is leading to rapid land use change and violation of environmental and spatial rules and regulations and intensification of environmental hazards.


Adel Solimani, Hassan Afrakhteh, Farhad Azizpour, Asghar Tahmasebi,
Volume 3, Issue 2 (5-2016)
Abstract

The latest report of the Intergovernmental Panel of Climate Change (IPCC) on climate and global warming Indicates that climate change and global warming in particular is one of the most important challenges of the world and drought, as a consequence of climate change around the world, has always influenced the many countries, including Iran. However, it seems that the climate changes, particularly in the West and Iran, especially among farmers and rural communities vulnerable to the effects of economic, social and environmental impacts that are more significant. In other words, Continuous droughts are faced villagers and farmers with various problems and challenges, In this regard, villagers Choose the local and specific strategies in the face of this creeping disaster that improve them adaptive capacity to drought. Nowadays, special emphasis is put on the notion of adaptive capacity instead of vulnerability. So the need to have research in rural levels obvious, especially in Iran where there has not yet been any deep and encompassing study on the concept of adaptive capacity in rural level. adaptive capacity to climate change is the ability of a system or an individual to adjust to climate change or climate variability so as to minimize the potential damages or cope with the consequences. Therefore, adaptive capacity is the ability to plan and use adaptation measures to moderate the effect of climate change. There is an increasing need to develop indicators of adaptive capacity to determine the robustness of response strategies over time and to understand better the underlying processes.

Adaptive capacities of villagers depend on certain factors or attributes such as their knowledge on and number of times they use a particular adaptation strategy. Other factors are the availability and accessibility of the adaptation strategy. Also, the number of consultations that a villagers makes on a particular adaptation strategy affect whether the villagers will be lowly or moderately or highly adaptive to drought.

Identifying the overall level of adaptive capacity to drought in rural areas, in order to Effective management is special importance, Because that by identifying and ranking of adaptive capacity in rural areas, adopt appropriate management strategies to reduce the damage caused by drought is possible.

Therefore, the purpose of this study is assessing the adaptive capacity to drought of between four villages in the central part of the city Rawansar in Kermanshah province. For this purpose five most effective and important index to measure the  adaptive capacity to drought as follows:  Knowledge, Use, Availability , Accessibility and Consultation, according to the literature, were selected. Then by using one sample T-test, the effectiveness of each of the above-mentioned indicators on the villagers adaptive capacity were reviewed and approved from the point of view Village contributors of the central city Rawansar (N = 48) who were selected by census method. In the next step, to determine the index weight, using the snowball technique and purpose sampling, 10 experts in jahad  agricultural  office in Rawansar city were selected and their comments were used. The results by TOPSIS technique based on these indicators, showed that rural areas of Hasan Abad and Zalu Ab  in the Rawansar city, had the greatest adaptive capacity to drought, While  rural areas of Dawlat Abad and Badr had fewer adaptive capacity to drought. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is a multi-criteria decision analysis method, which  is based on the concept that the chosen alternative should have the shortest geometric distance from the positive ideal solution (PIS)and the longest geometric distance from the negative ideal solution (NIS).It is a method of compensatory aggregation that compares a set of alternatives by identifying weights for each criterion, normalising scores for each criterion and calculating the geometric distance between each alternative and the ideal alternative, which is the best score in each criterion.The findings of this study could have recommendations for rural planners to effective crisis management in order to reduce vulnerability and enhance resilience villagers to drought.


عزیزی Azizi, افراخته Afrakhteh, عزیزپور Azizpour,
Volume 5, Issue 4 (3-2019)
Abstract

Land cover changes as a basic factor in environmental change act and has become a global threat. In this research, changes in land cover in rural tourism areas by neural networks, Markov chains in software ArcGIS, ENVI, Terrset using the TM and OLI satellite imagery, Landsat Satellite was surveyed for a period of 30 years for three periods of 1985, 2000, and 2015. The findings of the first stage show that land cover changes at the period 1985-2015, were classified in five class residential spaces, Commercial, Green, Empty and mountainous spaces and communication networks. In this study, the area of mountainous and empty spaces (13.25%) has decreased and in contrast, has decreased the amount of green spaces (6.221%), Residential (5.258%), commercial (1.264%) and communication networks (0.529%). Changing land cover as one of the most important environmental risks has been directly influenced by the Commodification phenomenon. Also, the findings of the prediction using the Markov-CA chain showed that with the continuation of the current and excessive loading on the ground, on the horizon of 2030, green cover (Agriculture, gardens and grassland, garden and residential)  and  wild land  and mountain cover have been reduced and to cover residential and commercial villas will be added. Based on research findings concluded that land cover changes in rural tourism areas in order to achieve more profits has become incompatible applications. This change in land cover, in addition to the economic, social impacts, has led to the formation of environmental hazards in the Bharang area. Developing tourism in the study area by removing agricultural land from the production cycle has led to an increase in urban activities and the formation of new activities (service, Residential Garden, residential villa) instead of traditional activities(agriculture and livestock) that are economical. And by loading too much ecological power tolerable land, while posing environmental hazards, causing incompatible activities next to each other, they do not match. Therefore, tourism, which gradually formed over the years and now it has become a part of rural texture, Spatial Conflict and heterogeneity two strains has created for them. Spatial Conflict created, due to changes in land cover and acceptance of incompatible activities that derive from human-nature relationships. This means that the rapid and unpredictable trend of tourism development, the rural landscape has encountered a problem and with changes in land cover, has led to inconsistencies between different activities and eventually has shaped the Spatial Conflict.
 
Roshanak Afrakhteh, Abdolrasoul Salman Mahini, Mahdi Motagh, Hamidreza Kamyab,
Volume 10, Issue 3 (9-2023)
Abstract

This paper is a discussion of urban heat islands (UHIs), which unique residential areas are characterized by dense central cores surrounded by less dense peripheral lands. UHIs experience higher temperatures due to impermeable surfaces and specific land use patterns. These temperature variations have negative environmental and social impacts, leading to increased energy consumption, air pollution, and public health concerns. It emphasizes the need for simpler approaches to comprehend UHI temperature dynamics and explains how urban development patterns contribute to land surface temperature variation. The case study of Guilan Plain illustrates the relationship between development patterns and temperature, utilizing techniques like principal component analysis and generalized additive models.
This paper focuses on mapping land use and land surface temperature in the southwestern region of the Caspian Sea, specifically in the low-lying area of Guilan province. The research utilized satellite data from Landsat sensors for three different time periods: 2002, 2012, and 2021. A spatial unit known as a "city block" was employed through object-based analysis using eCognition software. Thermal bands from Landsat, such as TM band 6, ETM+ band 6, and TIR-1 band 10, were used to retrieve land surface temperature. The radiative transfer equation was used to calculate temperature, accounting for atmospheric and emissivity effects.
The study employed the normalized difference vegetation index (NDVI) method to estimate land surface radiance. The main focus of the study was to identify predictive variables for urban land surface temperature within the context of residential city blocks. These variables were categorized as intrinsic (related to the block's structure) and neighboring (related to adjacent blocks) variables. Intrinsic variables included block area, shape index, perimeter-to-area ratio, and central core index, calculated using Fragstats software. Neighboring variables encompassed metrics like shared boundary length, mother polygon area, number of neighboring blocks, average distance to neighboring block centers, average area of neighboring blocks, average shape index of neighboring blocks, and average central core index of neighboring blocks. Principal Component Analysis (PCA) was employed to select significant variables that captured the majority of data variance. Variables with eigenvalues greater than 1 in each principal component were considered significant contributors. Varimax rotation was applied to the PCA results to ensure accurate variable selection.
The study utilized a Generalized Additive Model (GAM) approach, implemented using the mgcv package in R, to model the relationship between urban land surface temperature and predictor variables. Smoothing parameters were estimated using a restricted maximum likelihood method. Model accuracy and interpretability were assessed using the coefficient of determination (R-squared) and the F-test analysis. the study's results include the generation of land use maps for three different time periods using object-based image analysis. Urban block characteristics were aligned with spectral units through density, shape, and scale coefficients. Over the years, the average block size showed variation, increasing from 61.19 hectares to 62.21 hectares. Urban expansion was observed across the years, with the urban area expanding from 9.5% to 11.1% of the region. Surface temperatures ranged from 22.84 to 26.26°C, with urban temperatures spanning 26.14 to 53.04°C. Independent variables were calculated for intrinsic and neighboring categories, with varying characteristics like block size, shape index, and perimeter-to-area ratio. Principal Component Analysis identified influential parameters, leading to the selection of block size, and shared boundary. the polygon area, and perimeter-to-area ratio as main variables for a generalized additive regression model. This model demonstrated non-linear relationships between these predictors and urban temperature. Block size, shared boundary, and mother polygon area exhibited a positive relationship with temperature, while the perimeter-to-area ratio displayed a negative trend. The model's performance was satisfactory, indicated by an R-squared value of 0.619.
The discussion focuses on the challenges and complexities of predicting urban surface temperature through studies on land use patterns. the current study concentrates on analyzing surface temperature within urban block units and categorizing variables into intrinsic and neighboring factors to enhance the understanding of the relationship between urban surface temperature and spatial distribution. Despite calculating urban surface temperature as a seasonal average across years, notable variations in temperatures were observed across different years. These variations are attributed to environmental conditions, climatic factors, and atmospheric influences that fluctuate over time. Consequently, the study aims to mitigate the impact of dynamic parameters by basing its models on cumulative temperature changes over various years. However, despite its reliability, this approach might lead to biased results when dealing with short-term time-series imagery.
The discussion also delves into the study's approach of focusing on spatial indices of urban units as predictive neighboring parameters. This choice stems from the fact that other units, particularly agricultural ones, experience significant changes over shorter periods, which can disrupt model calibration. Principal Component Analysis highlights the importance of block size as a key predictor of urban surface temperature, emphasizing the shift from polygon area to block size as a spatial scale. The study concludes that both block size and aggregation significantly influence urban temperature patterns. The Generalized Additive Model reveals that block size and mother polygon area exhibit a positive relationship with urban surface temperature, while the perimeter-to-area ratio displays an inverse correlation. This parameter indicates that units with smaller central cores and higher perimeter-to-area ratios experience cooler temperatures due to engagement with neighboring units, especially agricultural ones. In conclusion, the findings suggest that urban blocks function as distinct entities where temperature-related factors are influenced by intrinsic attributes like shape, as well as by the positioning of a unit relative to others.
The conclusion highlights the continuous growth of studies investigating the connection between land use patterns and urban surface temperature. Block size emerges as a central factor in determining urban surface temperature, alongside block dispersion and aggregation, which play crucial roles as predictors in residential areas. Additionally, the study emphasizes the importance of spatial configuration and unit structure in shaping urban temperature patterns. The proposed methodology has the potential to enhance understanding of parameter significance in shaping urban temperature patterns across various regions of Iran.


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