Utilizing high-performance computing to improve performance and investigate sensitivity of an inversion model for hyperspectral remote sensing of shallow coral ecosystems.

详细信息   

• 作者：Gerardino Neira ; Carolina.
• 学历：Master
• 年：2008
• 导师：Rivera-Gallego, Wilson,eadvisor
• 毕业院校：University of Puerto Rico
• ISBN：9780549421498
• CBH：1451319
• Country：Puerto Rico
• 语种：English
• FileSize：845984
• Pages：85

文摘

This research presents a sensitivity analysis of a semi-analytical inversion model for hyperspectral remote sensing of shallow coral ecosystems. Using this inversion model, five parameters describing water column bioptical properties, bathymetry and magnitude of bottom reflectance are retrieved. In addition to the parameters of interest, the model contains 12 nuisance parameters that are traditionally assigned a fixed set of values. A sensitivity analysis of estimates retrieved to these nuisance parameters is accomplished using SimLab software to study their impact on model output. The computationally intensive analysis was enabled implementing the inversion model within a parallel processing framework using GENCAN. The sensitivity analysis was used to identify which nuisance parameters are most influential on the parameters of interest. The nuisance parameters found to be most relevant are: S, the spectral slope of the absorption coefficient for gelbstoff, Y, the spectral power coefficient for calculating the backscattering coefficient, and Dop, a constant in the equation for the distribution function for scattered photons from the bottom.