Activities and demographic characteristic of a plain urban area, located in close proximity to a particular type of eco-sensitive area, influence the habitation growth in that eco-sensitive area. This influencing plain urban area located adjacent to the eco- sensitive area is termed as ‘‘area of influence’’ (AOI) of that eco-sensitive area. Green hills, forests, and wetlands are the most commonly found eco-sensitive areas in and around a city. Though the proposed modelling concept can be applied to any type of eco-sensitive area, the potential driving factors considered for a particular type of eco- sensitive area may not be relevant to another type of eco-sensitive area. If the social and geographical condition of a city is almost uniform, allotment of AOI for an eco- sensitive area can be done by Euclidian allocation, where every cell in the image of the study area is assigned to an eco-sensitive area which is closest to that cell. Otherwise, it should be allotted giving due emphasis on geographical and social uniformity extent.
Potential factors considered in the proposed ASEA model are given below:
(a) Free space availability in AOI (Af): Due to the availability of more resources and facilities, people prefer to settle in a plain urban area, which is ideal for residential purpose. Gradually, as the plain plots of land become scarce in the main city area, the city starts to expand both in the outward direction and to the eco-sensitive areas located in the city (Rahman et al. 2008; Sultana et al. 2009; Ajibola et al. 2012). From this view, low availability of free space in AOI is considered as an indicator of increasing urban settlement in the corresponding eco-sensitive area. Af can be considered as a demographic factor since it depends on urban population growth. However, this free space excludes areas (A0) with no likelihood of having urban settlement, e.g. river, lake, wildlife sanctuary, zoo, park, playground (Clarke and Gaydos 1998). Hence, Af is expressed as,
(3.1) where,
Ai = AOI of the eco-sensitive area.
A0 = Areas with no likelihood of having urban settlement.
An = Net AOI where urban settlement is possible Aus = Urban settlement area in Ai.
(b) Commercial unit density in AOI (Cu): Commercial growth which can be measured in terms of clear count of shops or local markets is one of the major signs of urbanization. People are attracted towards an area having better facilities added by commercial development in that area (Preston 1979). Consequently, the growth of Cu
(numbers of commercial units or shops per unit area) forces to increase urban settlement in the corresponding eco-sensitive area. Here, Cu can be considered as socio- economic as well as a demographic factor since its growth is governed by both size of population (local needs or demands) and the socio-economic status of the society.
(c) Land value in AOI (Lv): Land value is an important factor influencing urban sprawl (Amoateng et al. 2013; Oueslati et al. 2014). In general, land value is a function of various factors like geographical location of the area, accessibility to various facilities like shopping, school, parks and playgrounds and increasing demand of plot with population growth. Hence, Lv is affected by the geographical, socioeconomic and
demographic characteristic of the area. In developing countries, plain urban areas are having high land values which are not affordable by low-moderate income group of people (Sarma et al. 2015). Due to the lack of strict regulation of the protection acts, these people encroach on the eco-sensitive areas causing unauthorized settlement in those prohibited lands.
(d) Geographical condition of the eco-sensitive area (Gi): The geographical condition or the site quality determines the developmental potential in an area (Lee 1979). As for example, average slope and average elevation in case of a hill and water depth in case of a wetland may affect the extent of urban settlement in that hill or wetland. Here, the subscript ‘‘i’’ in Gi indicates the type of the geographical parameter.
Every type can be considered as an individual factor in the model.
(e) Favouring index (F): Apart from the above-mentioned factors, some additional factors like educational facilities, tourism activities, economic activities and location of the eco-sensitive area also favour urban growth in an eco-sensitive area. A favouring index F has been introduced to indicate combined effect of all such factors. The capability of these components to pull urban population is incorporated in computing
‘‘F’’ in terms of some weights. Available literature or data on the contribution of these components to increasing urban settlement in the study area can help to determine the weights. Otherwise, these can also be determined by expert weighting approach (Goetz et al. 2011), i.e. applying weight based on the opinion of experienced urban planners and other stakeholders having in-depth knowledge on urban growth of the study area.
Finally, ‘‘F’’ for every eco-sensitive area is calculated as the average of the weights given to all of these components, i.e.
(3.2)
where,
are the components of 'F'.
Weight applied to the ith component of 'F'.
Details of the components of F are given below:
i. Educational facilities in AOI: In developing countries, rural-urban migration for education is playing a key role in increasing urban population (Ichimura 2003;
Acharjee et al. 2013). For easy access, people prefer to settle in a place located in the proximity of an educational institute. Moreover, with the establishment of a new university or college in an area, construction of hostels, staff quarters, etc., contributes to increment of urban settlement in that area. From this viewpoint, the educational facility in an AOI, which improves the socio-economic condition of a place by improving the personal proficiencies, livelihood, social awareness, people’s involvement in socio-economic activities, is considered as a favouring factor for urban settlement. Weight is assigned based on how many numbers of higher educational institutes are present in an AOI.
ii. Tourist places in AOI: Tourist places can be considered as a socio-economic factor influencing urban settlement in an area, as it can improve the socio-economic condition of an area by producing opportunities for businesses and employment and also by influencing the lifestyle and culture (Liu et al. 2015). Additionally, due to the presence of such a tourist place, the special development plan is taken for that area to provide more facilities to tourists, which, in turn, attracts more people to settle in that place (Dumitru 2012). Weight for tourist place is given based on its degree of importance and also on the basis of numbers of tourist places within an AOI.
iii. Economically active places in AOI: Urbanization and economic development are the two sides of the same coin. Economic development acts as the pull factor in rural-urban migration (Henderson 2003; Jedwab et al. 2015). Here, economically active places indicate city-level places for small-scale industry, major industry, construction, trade and commerce, transportation, communication, etc. These are the sources of job/ income opportunities for all economic groups of people, and hence, urban settlement increases in the nearby area. Weight for this factor is assigned depending on how many prominent economically active areas are lying in the AOI of an eco-sensitive area.
iv. Location of the eco-sensitive area with respect to the city centre: Eco-sensitive areas, which are located in core city area, become the very early victims of urban settlement (Tan et al. 2013; Mensah 2014). Therefore, the location of the eco- sensitive area with respect to core city area has been considered as urban settlement
favouring factor and some weight is assigned to an eco-sensitive area based on the percentage of AOI lying within the heart of the city.
Considering all the above-mentioned factors, the proposed ASEA model can be expressed as:
(3.3) Here, Eus is the amount of urban settlement in the eco-sensitive area (in % of area). The model structure is presented in Fig. 3.1. For modelling urban development in an eco- sensitive area of a particular city, one essential task is to check whether and how the urban settlement in an eco-sensitive area is influenced by every individual factor (independent variable). The efficiency of the ASEA model also depends on the availability of data. More the dataset, better will be the model. Therefore, availability of historical data series is desired. In the absence of a historical record, which is very common in developing countries, data set of similar type of eco-sensitive areas can also be used for developing the model.
Fig. 3.1: ASEA model structure
Free space availability in
‘AOI' (Af)
Commercial unit density in ‘AOI' (Cu)
Land value in ‘AOI' (Lv) Geographical condition of eco-sensitive area (Gi) Favouring index (F)
Educational facilities in AOI.
Tourist places in AOI.
Economically active places in AOI.
Location of the eco- sensitive area with respect to the city centre.
Eus= f (Af, Cu, Lv, Gi, F)