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Some insights of spectral optimization in ocean color inversion
| Content Provider | NASA Technical Reports Server (NTRS) |
|---|---|
| Author | Lee, Zhongping Shang, Shaoling Dong, Qiang Arnone, Robert Franz, Bryan |
| Copyright Year | 2011 |
| Description | In the past decades various algorithms have been developed for the retrieval of water constituents from the measurement of ocean color radiometry, and one of the approaches is spectral optimization. This approach defines an error target (or error function) between the input remote sensing reflectance and the output remote sensing reflectance, with the latter modeled with a few variables that represent the optically active properties (such as the absorption coefficient of phytoplankton and the backscattering coefficient of particles). The values of the variables when the error reach a minimum (optimization is achieved) are considered the properties that form the input remote sensing reflectance; or in other words, the equations are solved numerically. The applications of this approach implicitly assume that the error is a monotonic function of the various variables. Here, with data from numerical simulation and field measurements, we show the shape of the error surface, in a way to justify the possibility of finding a solution of the various variables. In addition, because the spectral properties could be modeled differently, impacts of such differences on the error surface as well as on the retrievals are also presented. |
| File Size | 24420 |
| Page Count | 1 |
| File Format | |
| Alternate Webpage(s) | http://archive.org/details/NASA_NTRS_Archive_20110022427 |
| Archival Resource Key | ark:/13960/t6256m90j |
| Language | English |
| Publisher Date | 2011-01-01 |
| Access Restriction | Open |
| Subject Keyword | Oceanography Radiometers Water Errors Water Color Oceans Inversions Spectra Remote Sensing Reflectance Ntrs Nasa Technical Reports Server (ntrs) Nasa Technical Reports Server Aerodynamics Aircraft Aerospace Engineering Aerospace Aeronautic Space Science |
| Content Type | Text |
| Resource Type | Article |
