Characterizing multi-decadal vegetative greenness and land use dynamics across Canadian urban areas using satellite remote sensing

Canada’s urban areas experienced extensive growth over the past-quarter century; however, there has been no reliable, spatially explicit approach for quantifying urban vegetation and land use patterns nationally. Satellite imagery, such as Landsat, provide an opportunity to measure large areas frequently, consistently, and accurately over long temporal periods. Using Landsat imagery, this thesis characterizes multi-decadal trends of vegetative greenness and land use transitions from 1984 to 2016 on the pixel and census dissemination area levels for 18 major Canadian urban areas. First, I developed an urban greenness score using spectrally unmixed Landsat imagery to categorize multi-decadal greenness change relative to its current greenness level across Canadian geographic strata and population density groups. Second, using unmixed fractions and land cover information, I derived a dynamic land use classification scheme and applied it across Canadian peri-urban areas to quantify multi-decadal land use transitions and their correlation with current socio-economic states. Most Canadian urban areas sustained a moderate (∼ 20–40%) or low (≲ 20%) level of greenness between 1984 and 2016, with denser urban areas experiencing the greatest losses (16% of DAs). Eastern urban areas maintained the most greenness over time, while urban areas in the Prairies had the greatest increase in greenness. During the same time, 47% of Canadian peri-urban areas experienced an increase in urban use, converting about 2,000 km² of natural and agriculture uses each. The region with the most area transitioned from natural to urban use occurred in the West (39%), whereas the Prairies observed more marked rates of urbanization on natural areas (median of 3.9% per annum per sq-km) and more area with agriculture conversions (41%). Regional differences in correlations between land use trends and current levels of population density, income, new residential construction, and single-detached housing highlight the potential influence of urban policies and/or socio-economic trajectories. The methods presented take advantage of sub-pixel information from the open and longstanding Landsat archive to provide a comprehensive and accessible framework to understand current and historic urban land dynamics, which supports long-term strategic planning and can be transferred to other regions across spatial and temporal scales.Forestry, Faculty ofGraduat