Landsat 8 data WV02 data
Water volume reflectance
Landsat 8 OLI data
work in progress work in progress:
- Conversion into TOA reflectance: Landsat 8 spectral images can easily be converted into Top Of Atmosphere reflectance, using the metadata provided in the _MTL.txt text file: please refer to "Using the USGS Landsat 8 Product".
- Conversion into BOA reflectance
- normally, one would have to perform a formal atmospheric correction, like using TAAFKA or the like: see for example University of California at Berkeley: this is a very complex and time consuming process, and we hear of artifacts caused by "over-correction".
- in 4SM, we use the deep water radiance Lsw and an estimate of the water volume reflectance Lw to derrive La=Lsw-Lw in units of DNs for all wavebands of Landsat 8 data.
- there is enough information in the multispectral image to do so, and the result is -to say the least- as usefull as that of a formal atmospheric correction over shallow water areas.
- with Landsat 8 data, there is even enough information to convert La and Lw in units of reflectance. This provides good control on the physical consitency of th values obtained.
- Water column correction
- normally, one would need BOA reflectances as the input to any inversion of the radiative transfer equation, whether simplified or not.
- in 4SM, water column correction is achieved using spectral BOA radiances in units of DNs: L=Ls-La-Lglint: this yields water column corrected spectral bands in units of DNs at the Base Of Atmosphere, which may then be converted into units of reflectance (scaled from 0 to 1), for the purpose of bottom typing and coastal monitoring.
more data shall be added to these plots using Landsat 8 images of
- Andros and Caicos islands, Bahamas
- Marawaah island, UAE
- La Parguera, Puerto Rico
- Perth, Marmion and SharkBay, Western Australia
- Rangiroa, Tuamotu Archipelaago
- Tarawa, Kiribati
- and more: images courtesy of USGS
I have drawn the figure below from Roelsfema et al's data.
This is in poor agreement with the work illustrated below:
How does the radiance collected by the sensor's very narrow near-nadir viewing FOV
correlate with the "Remote sensing reflectance" analyzed below? Most often I seem to observe Rwred~=0
Most often I seem to observe Rwcoastal>Lwblue Analytical modeling the water volume reflectance Rrs I suspect the water volume reflectance in the case of a Lambertian sky
is heavily dependent on
I need to oppose situations of dense atmosphere with situations of clear skies.
- the bidirectional distribution of the light field: the most famous cosine of the irradiant light field
- the sensor's viewing angle, which is commonly near-nadir