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Full-Text Articles in Social and Behavioral Sciences
An Assessment Of Methods And Remote-Sensing Derived Covariates For Regional Predictions Of 1 Km Daily Maximum Air Temperature, Beniot Parmentier, Brian Mcgill, Adam Wilson, James Regetz, Walter Jetz, Robert Guralnick, Mao-Ning Tuanmu, Natalie Robinson, Mark Schildhauer
An Assessment Of Methods And Remote-Sensing Derived Covariates For Regional Predictions Of 1 Km Daily Maximum Air Temperature, Beniot Parmentier, Brian Mcgill, Adam Wilson, James Regetz, Walter Jetz, Robert Guralnick, Mao-Ning Tuanmu, Natalie Robinson, Mark Schildhauer
Publications
The monitoring and prediction of biodiversity and environmental changes is constrained by the availability of accurate and spatially contiguous climatic variables at fine temporal and spatial grains. In this study, we evaluate best practices for generating gridded, one-kilometer resolution, daily maximum air temperature surfaces in a regional context, the state of Oregon, USA. Covariates used in the interpolation include remote sensing derived elevation, aspect, canopy height, percent forest cover and MODIS Land Surface Temperature (LST). Because of missing values, we aggregated daily LST values as long term (2000–2010) monthly climatologies to leverage its spatial detail in the interpolation. We predicted …