- GC22A-06: Predicting Drought Outcomes for Riparian Woodlands Using Dense Seasonal Time Series of Fractional Cover and Land Surface Temperature
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NOLA CC
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Conor McMahon, University of California Santa Barbara (First Author, Presenting Author)
Dar Roberts, University of California, Santa Barbara
Anna Trugman, University of California Santa Barbara
John Stella, SUNY College of Environmental Science and Forestry
Michael Singer, Cardiff University
Kelly Caylor, University of California Santa Barbara
Woodland ecosystems along rivers are critically important for human society and conservation values. However, they are threatened by a host of factors, including drought, with impacts that are uncertain and may become more severe in the future. New and upcoming satellite missions have the potential to improve our ability to track and predict drought-related damage to these ecosystems. However, there has not yet been enough work to develop software supporting this.We developed new methods to track drought-related changes in plant health. Importantly, we focus on detecting both death of trees and early warning stress indicators that precede subsequent death. Our statistical model is broadly extensible and allows tracking drought-related tree death over a very large area and a 40-year time span. This development was enabled by recently launched NASA sensors, and will become even more relevant and extensible in the near future after new missions launch.
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