Human Well-being, Ecosystem Services And Watershed Management In The Credit River Valley: Web-distributed Mechanisms And Indicators For Communication And Awareness

This paper seeks to assess 12 human health and well-being indicators through qualitative analysis. These 12 indicators are: air quality, traffic patterns/modes of transportation, land cover change, urban heat islands, % imperviousness, % canopy cover, water quality index, % people using natural space, proximity to green space, connectivity of green space, access to green spaces, and wildlife (habitat). To evaluate the utility of each indicator, 18 professionals from various organizations were interviewed. The interviewees were asked to score how relevant each indicator was to achieving their mandate, and the specific benefits of measuring each indicator for the well being of the general population and for vulnerable groups such as infants and seniors, as well as any weaknesses of the indicator, and who might be able to use the data in the future. This was a mixed-methods approach, and was based on the principles of grounded theory. Semi-structured interviews were conducted, and followed by a qualitative content analysis using NVivo software to group and code references to human health and well-being within all 12 indicators. Some quantitative analysis was also added to provide direction and reasoning to relevancy of the 12 indicators in terms of human health and well-being. The analysis included two data sets of 18, and 19 interviews, for a total pool of 37 interviews. Most of the indicators were ranked quite high, indicating relevance to human health and well-being over a number of various organizations. Most interviewees agreed that air quality and green spares have been found to have many benefits to human health and well-being. It was noted that indicators were hard to define and had a lot of overlap. Similar trends were found in the new data when compared to the previous researcher's data set, and that the larger pool can perhaps add validity to the conclusions drawn from the data.