2012
DOI: 10.1016/j.landurbplan.2012.06.015
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Developing spatially explicit footprints of plausible land-use scenarios in the Santa Cruz Watershed, Arizona and Sonora

Abstract: h i g h l i g h t sThe SLEUTH model is applied to a binational dryland watershed to develop future scenarios. Three scenarios simulate changing spatial patterns to help guide planning for the future. Limit growth beyond cross-border commerce areas, protects forests and wildlife habitat. Trade-offs between urban area, the economy, and environmental impacts can be realized. a b s t r a c tThe SLEUTH urban growth model is applied to a binational dryland watershed to envision and evaluate plausible future scenario… Show more

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Cited by 27 publications
(13 citation statements)
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“…Two urban growth scenarios were developed for SCWEPM using the fuzzy constrained cellular automata (CA) model, SLEUTH (Slope, Land use, Exclusion, Urban extent, Transportation, and Hillshade) (Norman et al 2012). SLEUTH is a land-use/land-cover change model that processes land surface changes that are regulated by neighborhood rule conditions (Jantz et al 2010).…”
Section: Methodology: Data Setsmentioning
confidence: 99%
See 2 more Smart Citations
“…Two urban growth scenarios were developed for SCWEPM using the fuzzy constrained cellular automata (CA) model, SLEUTH (Slope, Land use, Exclusion, Urban extent, Transportation, and Hillshade) (Norman et al 2012). SLEUTH is a land-use/land-cover change model that processes land surface changes that are regulated by neighborhood rule conditions (Jantz et al 2010).…”
Section: Methodology: Data Setsmentioning
confidence: 99%
“…SLEUTH is a land-use/land-cover change model that processes land surface changes that are regulated by neighborhood rule conditions (Jantz et al 2010). SLEUTH inputs included the following: S, slope from 30 m National Elevation Dataset Digital Elevation (DEM) raster; L, a binational, historical suite of Land Use Land Cover (LULC) data derived from 1979, 1989, 1999, and 2009 satellite imagery ); E, defined exclude areas including conservation areas, protected lands, open water, and floodplains; U, urban extent layer derived from LULC; T, binational vector transportation data sets; and H, DEM-derived hillshade (see Norman et al 2012 for detailed SLEUTH methods).…”
Section: Methodology: Data Setsmentioning
confidence: 99%
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“…Focus is being put on planning that includes all oil sands operators in a regional rehabilitation plan towards adequately addressing collaborative goals for future regional land use. However, there is evidence that regional land use planning is being undertaken more from a watershed or catchment perspective, driven by the need for long-term water supply to urban areas (Norman et al 2012;Lilieholm et al 2012); or from an ecosystem goods and services perspective (Woodruff & Bendor 2016;Dale et al 2000).…”
Section: Regional Planning Focusmentioning
confidence: 99%
“…The use of scenarios in planning processes is recommended for contexts of high uncertainty and low controllability (Peterson, Cumming, & Carpenter, 2003), and to open up constrained thinking to new possibilities (Chermack, 2004). In this journal alone, there are accounts of scenarios being used to initiate discussion about future constraints and opportunities for rural development (Van Berkel, Carvalho-Ribeiro, Verburg, & Lovett, 2011), to develop visual aids that enhance learning about climate change impacts and/or development trajectories (Albert, Zimmermann, Knieling, & von Haaren, 2012;Lamarque et al, 2013;Norman, Feller, & Villarreal, 2012), and to explore policy options for alternative futures (Pearson, Park, Harman, & Heyenga, 2010;Southern, Lovett, O'Riordan, & Watkinson, 2011).…”
Section: Introductionmentioning
confidence: 99%