Journal
INTERNATIONAL JOURNAL OF DIGITAL EARTH
Volume 8, Issue 2, Pages 118-132Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/17538947.2013.860196
Keywords
remote sensing; invasive species; ecological model; Great Basin; phenology
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Funding
- US Geological Survey Northwest Climate Science Center, US Geological Survey Land Remote Sensing project
- US Bureau of Land Management
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Cheatgrass exhibits spatial and temporal phenological variability across the Great Basin as described by ecological models formed using remote sensing and other spatial data-sets. We developed a rule-based, piecewise regression-tree model trained on 99 points that used three data-sets - latitude, elevation, and start of season time based on remote sensing input data - to estimate cheatgrass beginning of spring growth (BOSG) in the northern Great Basin. The model was then applied to map the location and timing of cheatgrass spring growth for the entire area. The model was strong (R-2 = 0.85) and predicted an average cheatgrass BOSG across the study area of 29 March-4 April. Of early cheatgrass BOSG areas, 65% occurred at elevations below 1452 m. The highest proportion of cheatgrass BOSG occurred between mid-April and late May. Predicted cheatgrass BOSG in this study matched well with previous Great Basin cheatgrass green-up studies.
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