Measuring Urban Nature that Supports Mental Health

Exploring how vulnerable populations are exposed to restorative nature in the City of Vancouver using a novel Local Restorative Nature Index

Taelynn Lam

April 3, 2021

There are many types of urban nature in Vancouver and each of them support us differently.

Not All Nature is the Same

Research suggested that certain characteristics of nature can provide better psychological support than others depending on one's wellbeing state.

Supportive Environmental Theory

According to Bengtsson & Grahn's Supporting Environmental Theory, refuge, wild nature, serene, and rich in species are nature characteristics that are more beneficial for people at lower mental well-being state (2014).

Refuge: Nature that provides a sense of safety, allowing one to see their surrounding without being very exposed.

Wild Nature: The amount of natural elements (e.g. vegetation, wildlife, water bodies) in the landscape.

Serene: Nature that provides calmness, peacefulness.

Rich in Species: Variety of species types.

Restorative Nature

Refers to nature environments with qualities that help reduce stress, alleviate mental fatigue and improve overall mental wellbeing.

How can we quantify restorative nature?

I developed a novel Local Restorative Nature (LRN) index to assess the quality and quantity of restorative nature in a given area and to allow for comparison across a landscape. This LRN index integrates measurements from refuge, nature, and rich in species dimensions that Bengtsson & Grahn (2014) suggested to be important for supporting mental health.

Local Restorative Nature (LRN) Index

LRN index is calculated using six indicators, with two indicators for each dimension as shown on the figure on the right.

Each indicator was equally weighted in the calculation to get a score for the amount of restorative nature in an area.

The indicators in this study were computed using data from remote sensing imagery and municipality's geographical information system (GIS).

LRN Score in Vancouver

The map on the right shows the score of local restorative nature index of Vancouver at the scale of dissemination area (DA). We can see that, overall, Shaughnessy has very high score, indicating that this neighborhood has high quantity and quality of restorative nature.

Tip: Higher score (darker green) reflects higher amount of restorative nature in the area.

How are vulnerable populations exposed to restorative nature in the City of Vancouver?

I performed a geographically weighted regression analysis using the Canadian Index of Multiple Deprivation (CIMD) from Statistics Canada as the independent variable and the Calculated LRN index as the dependent variable to examine how are vulnerable populations exposed to nature that support mental health.

Results

Vulnerable Groups Have Different Exposure to Restorative Nature

All four vulnerability dimensions (residential instability, situational vulnerability, economic dependency, and ethnocultural composition) displayed different patterns (you can explore them in the map below), with situational vulnerability and economic dependency dimensions showing a more patchiness variations in the city.

Exposures to Restorative Nature of Vulnerable Populations Varies by Neighbourhoods

Areas with similar degree of population vulnerability can experience different exposure to restorative nature depending on the neighborhood they live. Future planning and resources allocation should focus on areas with high proportion of vulnerable population and low restorative nature to reduce urban forest inequality and to promote equity in nature-based health care services in the city.

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Residential Instability

Reflects the tendency of residents to change over time.

Areas with higher residential instability have higher proportion of dwelling that are non-single family houses, persons living alone, and dwelling that are in rental.

Residential Instability

I found a clear diagonal negative-positive correlation gradient from north-west of the city between residential instability and the amount of local restorative nature.

Tip1: Click on the map to view the vulnerability score and the coefficient value at a DA.

Tip2: Red represents negative correlations between vulnerability score and the quantity of restorative nature and blue is the opposite.

Tip3: Higher vulnerability score reflects population has a higher vulnerability at the area. Coefficient value shows the correlation between LRN index and the vulnerability score.

Situational Vulnerability

Reflects the socio-demographic condition of population in an area.

Areas with higher situational vulnerability population generally have higher proportion of aboriginal people, higher population proportion lack of high school diploma and have lower income.

Situational Vulnerability

I found the relationships between the degree of situational vulnerability and the amount local restorative nature exhibit high neighborhood variations across the city.

This pattern is mostly in alignment with the degree of situational vulnerability of the population at the neighbourhood which means that the amount of restorative nature at an area can be largely explained by the degree of situational vulnerability of the area.

Economic Dependency

Reflects population's reliance on source of income other than employment income.

Areas with high economic dependency score generally have higher proportion non-labor-force residents such as elders and children.

Economic Dependency

The observed correlations between the degree of economic dependency of a population at an DA and the quantity of local restorative nature displayed a patchy pattern across the city.

Unlike the situational vulnerability dimension, the observed correlations do not appear to align with score of economic dependency.

Ethnocultural Composition

Reflects community's make-up of visible minority and recent immigrants population.

Ethnocultural Composition

The relationship between the degree of ethno-cultural composition and the quantity of restorative nature appeared to be negative for most part of the city.

This pattern is largely aligned with the distribution of ethno-cultural composition in the city, in which most areas in the city have a moderate to high proportion of visible minority.

Where are should we prioritize efforts in increasing restorative nature?

Using a bivariate map to overlay vulnerability scores and the LRN index score can help us to visualize and identify areas to prioritize efforts in increasing restorative nature for the vulnerable population. Prioritized areas are defined as areas with more vulnerable populations and little amount of restorative nature to support mental wellbeing. The map below displayed the results of overlaying the aggregated vulnerability scores and the LRN index score. The aggregated vulnerability scores were the averaged scores of the four vulnerability scores at the DA.

Where are the high priority areas?

Areas in deep pink are areas that require high priority in restorative nature as population in these areas are highly vulnerable yet have very low exposure to restorative nature.

Tip1: Click on the circle button on the left to open up the legend.

Tip2: Click on the map to view the vulnerability score and the LRN index score at a DA.

How does this map help strategic planning?

Ideally, urban planning efforts should aim for making this pink area into sky blue where populations would have low vulnerability and high amount of local restorative nature.

If a neighbourhood has a high vulnerability score, urban planning should at least aim to increase restorative nature in the area and shift the area into a deep blue in the short term.

Acknowledgement

I acknowledge that this study took place on the traditional, ancestral, and unceded territories of the xʷməθkʷəy̓əm (Musqueam), Sḵwx̱wú7mesh (Squamish), and Sel̓íl̓witulh (Tsleil-Waututh) Nations.

Special thanks to Tahia Devisscher, Matthew Mitchell, Joanne Fitzgibbons, Ingrid Jarvis, Paul Pickell, Francois du Toit, Amy Blood, and Derek Li, for generously offering their insight, guidance, and support throughout the design and development of this study.

Author: Taelynn Lam