Since the beginning of time, Earth has been in a constant state of experimenting with Nature’s harmony in different internal and external processes, but since human beings arrived on the scene, several new phenomena have produced effects that the planet has not been able to cope with [1
]. To overcome this problem, there are various ways to achieve equilibrium, like population training in concepts such as energy conservation, recycling and reuse, tolerance and sharing. Despite all this, attaining optimum methods of reaching Earth’s perfect state of equilibrium, numerous research works were undertaken to look for suitable methodologies for sustainable town planning. Among others, Zapf’s Law was one of the possible solutions since it was observed in natural processes and in social institutions [1
]. Besides this, more research works tried to find out the rank and size scaling relationship by means of the so-called entropy maximising methods. Despite this, and except in a few works [2
], they often failed in their attempts. Finally, in the most recent works, as a method of measuring the system’s disorderliness, the entropy concept was employed in environmental systems [3
]. Thus, the entropy of an urban ecosystem can be defined as a parameter indicative of the disorder [8
]. In particular, Shannon’s entropy shows that the concentration of a spatial variable in a city quantifies its urban sprawl. For example, entropy can be divided into entropy flow and entropy production [8
], and increases with sprawl [9
]. Consequently, four types of entropy can be obtained with positive and negative values being the final values of the total entropy of the system. Once the total entropy is obtained, its difference between two periods of time will show the tendency of the urban sprawl [10
]. From these theoretical concepts, different case studies were conducted in cities all over the world. For example, a research work developed in 2007 [10
] in Canada implemented a land use classification for the City of Calgary, and simulated the future land use pattern based on the interactions between these land uses and the transportation network. Its results showed an adequate methodology in land use classification from Landsat images and the eCognition software, and concluded that entropy will grow in Calgary during the period 1985–2001 as a clear consequence of population growth. Other works analysed urban sprawl by means of Shannon’s entropy in the city of Baguio (northern Philippines) in 2010 [11
], and showed the adequacy of remote sensing, Geographical Information Systems and photogrammetric techniques to show built-up concentration. In 2011, in the City of Vadodara (India), the integration of remote sensing and Geographical Information System was analysed to detect urban sprawl [12
]. Once again, its results showed an entropy growth from 1.50 to 2.16 between years 1978 and 2001. A later study in Jorhat district of Assam (India) [13
] showed an entropy growth between 2.32 in 1996 and 2.49 in 2010, which are near the highest entropy value of 2.63 which was identified with a clearly dispersed development. In 2012, the City of Beijing (China) [8
] had analysed the developmental degree of the urban ecosystem from 2000 to 2007. Their results showed that the flow changes are the main factors that affect the system entropy changes, and showed quantitative indicators of the system state as adjustable indicators, controllable indicators and indicators that are not easily regulated. The first one can be adjusted by policies like economic growth indicators; the second one can be controlled by administrative and engineering technical means, like population density; and finally, the third indicators are those which cannot be adjusted by technical or economical procedures, like total annual electricity consumption. Its results showed that once the regulation program was improved, a negative entropy flow can be obtained. The more recent research works were developed in Iranian cities. For example, in the Iranian City of Shiraz in 2011 [9
], its growth patterns between 1976 and 2005 were analysed using the Geographical Information System. Its results showed that the built-up area increased by 145%, while the population grew by only 55% due to the significantly unplanned development, and the proliferation of low population density construction. More recently, in another Iranian city (Urmia) in 2012 [14
], urban growth was analysed using methods like Holdern and Shannon’s entropy. Its results showed that the value of entropy was 1.3738 in 1989, while the maximum value was 1.3862, showing the urban sprawl and physical developments. Finally, the entropy value was 1.3231 in 2007, indicating that over 20 years, physical growth has been both in the sprawl as well as in compact form. Therefore, it was concluded that changing a central city into a multicentric one based on centralisation and multiplication of activities in subcentres is the solution for coping with urban sprawl.
In Iran, which is a developing country, many big, medium, and even small cities, for various reasons, are encountering rapid spatial growth or urban sprawl. Tehran, the capital of Iran, is recognised as one of these expanding cities due to it being the main destination of migrants, because of its several modernistic urban attractions, in addition to a rapid population growth, and is experiencing rapid physical and spatial expansion. This phenomenon has many adverse effects on different aspects of the city, such as: the loss of environs, agricultural lands and orchards [15
], increasing air pollution [20
], increasing socioeconomic inequality [21
], and so on.
At the same time, one of the most important environmental issues that is happening in Tehran, like in other metropolitan centres in the world, is climate change, and subsequent bioclimatic boundary changes in microclimatology on an urban scale. To prevent dangerous health consequences of these microclimatic conditions over the population, and at the same time to improve urban sprawl, new weather indexes must be employed.
However, the purpose of this research is to analyse and evaluate the microclimate in Tehran according to the urban sprawl of the city in different study periods, and to define new indexes to be employed in decisions for improving urban sprawl.