Future analysis of urban land use and wetland change in Saskatoon, Canada : an application in strategic environmental assessment / Anton Sizo, Bram Noble, and Scott Bell.
Material type: TextSeries: Sustainability. 7 811-830 Publication details: 2015Description: colour illustrations ; 28 cmLOC classification:- SIZ
Item type | Current library | Collection | Call number | Status | Date due | Barcode |
---|---|---|---|---|---|---|
Electronic Journal | IWWR Supported Research | Non-fiction | SIZ (Browse shelf(Opens below)) | Available | 16697 |
Includes bibliographical references (pages 827-830).
This paper presents a scenario-based approach to strategic environmental assessment
(SEA) for wetland trend analysis and land use and land cover (LUC) modeling in an urban
environment. The application is focused on the Saskatoon urban environment, a rapidly
growing urban municipality in Canada’s prairie pothole region. Alternative future LUC was
simulated using remote sensing data and city spatial planning documentation using a Markov
Chain technique. Two alternatives were developed and compared for LUC change and
threats to urban wetland sustainability: a zero alternative that simulated trends in urban
development and wetland conservation under a business as usual scenario, in the absence of
prescribed planning and zoning actions; and an alternative focused on implementation of
current urban development plans, which simulated future LUC to account for prescribed
wetland conservation strategies. Results show no improvement in future wetland conditions
under the city’s planned growth and wetland conservation scenario versus the business as
usual scenario. Results also indicate that a blanket wetland conservation strategy for the city
may not be sufficient to overcome the historic trend of urban wetland loss; and that spatially
distributed conservation rates, based on individual wetland water catchment LUC peculiarities,
may be more effective in terms of wetland conservation. The paper also demonstrates the challenges to applied SEA in a rapidly changing urban planning context, where data are often
sparse and inconsistent across the urban region, and provides potential solutions through
LUC classification and prediction tools to help overcome data limitations to support land use
planning decisions for wetland conservation.