Urban Growth of Toronto

Abstract

Urbanization has become something popular worldwide. It is in most cases in the form of environmental zones, rangelands, and agricultural regions. There is a significant increment of urban areas in many developed countries, which occur as economic centers and result in demographic shifts (Bourne, 1975). It’s precisely Southern Ontario’s case, where significant economic growth in the metropolitan area has led to rapid urban expansion. The migration growth to Canada and the rapid demographic changes felt across Canada result from the increment. The population growth pattern is expected to increase to 72% by 2050 in urban regions. This is according to United Nations (Vaz & Arsanjani, 2015). A total of six million people are in Toronto and 5,583,064 people in the census metropolitan area (CMA), in 2011, per the Canadian census.

The urban core of Toronto is well-represented by the CMA, together with its neighboring areas that have grown progressively during previous decades. Very soon, the Toronto CMA will become a megacity since it’s just a matter of time for a population of more than 10 million inhabitants. It was assumed that an increase in urban density had afflicted some Greenbelt parts after the city density of Toronto was calculated. It was co-related with Ontario’s Greenbelt boundaries (Simmons & Bourne, 1989). Land use change and urban planning in line with the expansion of the transportation system in the Toronto core have also contributed to more downtown pressure. Monitoring and planning of Greater Toronto can only be efficient by having past information and current land use. The policy dimensions found in the urban growth models suggested a new regional sustainability paradigm. Here, the local, national and regional interventions must collaborate. This study enhances understanding of Toronto’s region’s use of land using a multi-criteria evaluation system (Taylor & Van 2014).

Research Questions

• Are the urban classes in the CMA increasingly afflicting land use?
• Which are the key characteristics of the use of land and urbanization in the Toronto region?
• Which patterns of land use can Markov Transition Chains and cellular Automata predict in the future, and is there any help in establishing a notion of priorities on urbanization processes for Toronto CMA by the current documentation? (Simmons, 1974).

Literature Review

2.1 Area of Study

CMA core of Toronto is at 43 degrees 38’33″N, 79 degrees 23′ 14″ W. Toronto is its central metropolitan region, surrounded by three regions; York, Peel, and Durham. Hamilton has also been considered for our study’s purpose since it has previously been part of the region. After adding Hamilton, this region has been ranked among the top fifty largest cities globally. The CMA has a total of 6,054,191people, with 850 inhabitants/ squared km population density, and extends 7124 cubed km. There is significant variation in population density in Ontario since, despite Toronto’s population density is very high, the rest of the province shows only a population density of 14.1 per square km. Toronto Transit Commission and GO Transit are the two major public transportation systems that mark the existing infrastructure (Taylor, 2007).

Immigration patterns and anthropogenic activity locations have been shaped by Toronto’s economic importance, leading to rapid urban change in the environment. The rapid urbanization faced by Toronto’s CMA has also resulted from the economy’s fluctuations and demography. The urban core is, therefore, a highly diversified region with great potential for future economic growth. The felt economic climate in northern parts of America since 2009 has marked Toronto’s successful recovery. This rapid recovery has enhanced stakeholders’ and investors to have a growing interest in recent years as a result of investing in the region. Toronto’s metropolitan area is the fourth largest economic center in North America. It has also been recently ranked among the top 10 according to the Global Financial Centers Index (GFCI).

2.2. Data

The urban growth model was generated after combining different spatial data sets. Landsat Imagery provided a cheap option for assessing land use for temporal and spatial monitoring. The fact that the Landsat imagery is multi-temporal; makes the imagery adequate for determining the region. This is proven by its mid-spatial resolution characteristics and data availability at the Global Land Cover Facility repository (Desfor et al., 2006). A combination of the use of land that was in existence and some raw data was done for ground truth and enabled the creation of accuracy in classifying land use over a more significant metropolitan as in Toronto’s CMA case. Satellite imagery of higher resolution was used for the design of training sites, adequate classification of urban extents, and assessment of accuracy for completion of integration review later. The following time-stamps were considered for this research: 1992, 2010,1995, 2011, 2010, and 2001. The combined Landsat mosaics enabled the classification of different decades’ land use (1980, 1990. 2000, and 2010). Resampling the resulting land use to 30 m allowed consistency in assessing Toronto’s CMA land use. The data sets entail population density variation between 2006 and 2011. The available data sets were projected into the Universal Transverse Mercator coordinate system for the North American Datum 1983, zone 17 N, so spatial consistency for different data sources could be allowed.

Methodology

Major parts used for the urbanization of Toronto’s CMA model are covered in this section. This methodology did a correct assessment of land-use classification for Toronto. Calculating Markov chains for 1990-2000 is done to predict an adequate allocation and outcome of land use transition. Then, there is the incorporation of more sources of data utilized in the model of urban growth in North America’s use, distance from urban extent, slope, transportation network, and excluded areas were considered. The transportation network, pitch, and past urban capacity drive urbanization. Then, through a multi-criteria Evaluation (MCE), these variables were processed, giving a response by the approach of Analytical Hierarchical Analysis (AHP). The AHP approach generated independently extracted weights and assessed all parameters. The existing documents for planning Toronto’s CMA were used to calculate the weights (Boume et al., 2003).

Findings

4.1. Urbanization in Toronto

Close inspection of the scattering of land use allows assessment of required results from the perspective of a land use plan between 2000 and 2010. Toronto’s downtown core has expanded as expected. For example, in 2000, only 21.71% of urban land use increased to 30.03% in 2010. Much attention is brought to the growth pattern since the increment of urban land results from urban sprawl (Rui & Ban, 2010). This has led to a reduction of land from 25.73% in 2000 to 17.53% in 2010. A slight increase in Barren areas has also led to the rise in Forest zones, from the abandonment of agricultural land and the creation of regions of the park and new forests within the urban cores.

4.2. Spatial-temporal change in Toronto

There has been a rapid growth in Toronto since the after-war period, more so from the rise in population dynamics and immigration in Toronto (Bourne & Gad, 1972). An increase in rapid demographic has resulted in Toronto’s growth, which has also led to the diversity of the Great Toronto Area’s landscape. As the Ministry of Infrastructure indicates, rapid growth has been noticed in Toronto’s CMA, and the transition seems consistent in the coming decades. The ministry’s vision is to ensure that the sustainability of the urbanization processes in Golden Horseshoe is catered for and maintains an ecological diversity that is unique and has a tremendous economic potential for continued growth (White, 2003). Probability interpolation of land use is allowed by the Markov Transition Chain in the Greater Toronto Area. Some findings are noted from the urban land-use distribution;

• Economic growth, mainly, increased urbanization due to the growing service sector in Toronto, especially in barren areas, and Agriculture land following.
• The tendency of Forest areas to increase in urban areas is due to the creation of parks and leisure facilities in the urban cores.
• Transformation of Agriculture land tends to either urban areas or Rangeland (Bunce, 2004).

The most dominant use of land in the landscapes of Toronto is urban land use, which is closely followed by Forests’ impacts, Agriculture and Rangeland. Urban sprawl is predicted to continue in the Toronto area in the current rural and agricultural areas of the Hinterlands region (Sorensen, 2011).

Conclusion

Urbanization in Toronto seems to be rapid, and it’s expected to elevate significantly, especially in Toronto’s northern part, to be specific in Markham, Aurora, Richmond Hill, Newmarket, and East-Gwillimbury (Harris & Luymes, 1990). Urban growth may, however, decrease in the coming decades in other parts of Toronto. Agricultural land might be lost significantly very soon from the continued urban pressure in the coming years. The fact that there is some connection between urban Toronto and some other regions in Southern Ontario implies that Toronto must be planned carefully and that this region plays a crucial role in the development sustainability of Southern Ontario. Due to the previous decades’ technical advances, Ontario province has also rapidly changed (Siegel & Woodyard, 1971).

References

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Siegel, J., & Woodyard, M. (1971). Urban growth and its relation to the urban hierarchy in central Canada.

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Simmons, J. W., & Bourne, L. S. (1989). Urban growth trends in Canada, 1981-86: A new geography of change. Centre for Urban and Community Studies, University of Toronto.

Sorensen, A. (2011). Toronto megacity: Growth, planning institutions, sustainability. In Megacities (pp. 245-271). Springer, Tokyo.

Taylor, L. E. (2007). The production of nature in planning for urban expansion: A cultural landscape study of new urban growth in Oakville, Ontario. The University of Toronto.

Taylor, Z. T., & Van Nostrand, J. (2014). Shaping the Toronto region, past, present, and future. desLibris.

Vaz, E., & Arsanjani, J. J. (2015). Predicting urban growth of the Greater Toronto area-coupling a Markov cellular automata with document meta-analysis. Journal of Environmental Informatics, 25(2), 71-80.

White, R. (2003). Urban Infrastructure and Urban Growth in the Toronto Region, 1950’s to the 1990’s (p. 11). Toronto: Neptis Foundation.