Spatial distribution of vegetation in Montreal: An uneven distribution or environmental inequity?

What is the role of trees and remnant vegetation in attracting people to urban parks?

“…People living in socio-economically advantaged neighbourhoods did not travel further for parks with higher tree cover or remnant vegetation cover than those locally available, though this effect was rather weak. This pattern could reflect the fact that more advantaged communities often have higher levels of neighbourhood vegetation cover and biodiversity (Landry and Chakraborty 2009;Strohbach et al 2009;Pham et al 2012;Clarke et al 2013;van Heezik et al 2013), and perhaps the need or desire to travel further for high quality natural areas may be lower where neighbourhood greenness is already high. Previous research in Brisbane has shown that more advantaged neighbourhoods do tend to have higher levels of tree cover .…”

Trees in Canadian Cities: Indispensable Life Form for Urban Sustainability

“…Ethnic/racial minorities and low-income residents have lower access to green space [105,106]. While city planning that incorporates tree planting and park development in lower-income areas aims to rectify this social injustice, it also increases the desirability of these areas and can contribute to their gentrification, pushing out the original residents [107].…”

The application of three methods to measure the statistical association between different social groups and the concentration of air pollutants in Montreal: A case of environmental equity

“…It should be noted, however, that Statistics Canada only provides data on the total population and the number of dwellings at the city block scale. To address this issue, we estimated the numbers of each group consistent with the approach recently put forward by Pham et al (2012) at the city block level: = where ti represents the estimated population of the group (the low-income population, for example) in the block, ta the group's population in the dissemination area, and Ti and Ta the total population in the block and in the dissemination area respectively. The summary statistics for the socioeconomic variables analyzed at the city block level are reported in Table 1.…”

“…Then, to determine whether environmental inequities exist in relation to our four targeted groups (low-income individuals, members of visible minorities, young people, and the elderly), we conducted four statistical analyses largely used in studies on environmental equity Briggs et al, 2008;Kingham et al, 2007;Pham et al, 2012). First, a T-test between each group and the rest of the population is performed, in this case to compare their respective averages in terms of pollution indicators (for example, between the population under 15 years old and the population over 15 years old).…”

“…We were thus attempting to see whether the associations between the different pollution indicators and a given population group were significant once we had controlled for the proportions of the other three population groups. A number of studies on environmental equity have however shown the spatial dependence of conventional regression models, whether in terms of dependent variables relating to air pollution (Buzzelli, 2003;Chakraborty, 2009), or in terms of those relating to the presence of urban vegetation (Pham et al, 2013;Pham et al, 2012). As we wanted to control for spatial dependence, we constructed two spatial autoregressive models, i.e., the spatial lag and spatial error models (Anselin, 2009).…”