[Latest News][7]

2017
khampha
maytinh
sach
tintuc
v.map
vientham

Ad Section

Using the USGS Landsat 8 Product

Background
Standard Landsat 8 data products provided by the USGS EROS Center consist of quantized and calibrated scaled Digital Numbers (DN) representing multispectral image data acquired by both the Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS).
The products are delivered in 16-bit unsigned integer format and can be rescaled to the Top Of Atmosphere (TOA) reflectance and/or radiance using radiometric rescaling coefficients provided in the product metadata file (MTL file), as briefly described below.  The MTL file also contains the thermal constants needed to convert TIRS data to the at-satellite brightness temperature.
Since the launch of Landsat 8 in 2013, thermal energy from outside the normal field of view (stray light) has affected the data collected in TIRS Bands 10 and 11. This can vary throughout each scene and depends upon radiance outside the instrument field of view, which users cannot correct in the Landsat Level 1 data product. Band 11 is significantly more contaminated by stray light than Band 10. It is recommended that users refrain from using Band 11 data in quantitative analysis including use of Band 11 in split-window surface temperature retrieval algorithms. Details about Landsat 8 TIRS stray light can be found in Appendix A of the Landsat 8 Data User Handbook.

Conversion to TOA Radiance
OLI and TIRS band data can be converted to TOA spectral radiance using the radiance rescaling factors provided in the metadata file:
Lλ = MLQcal + AL 
where:              
Lλ          = TOA spectral radiance (Watts/( m2 * srad * μm))
ML         = Band-specific multiplicative rescaling factor from the metadata (RADIANCE_MULT_BAND_x, where x is the band number)
AL          = Band-specific additive rescaling factor from the metadata (RADIANCE_ADD_BAND_x, where x is the band number)
Qcal        = Quantized and calibrated standard product pixel values (DN)         

Conversion to TOA Reflectance
OLI band data can also be converted to TOA planetary reflectance using reflectance rescaling coefficients provided in the product metadata file (MTL file).  The following equation is used to convert DN values to TOA reflectance for OLI data as follows:
ρλ' = MρQcal + Aρ 
where:              
ρλ'          = TOA planetary reflectance, without correction for solar angle.  Note that ρλ' does not contain a correction for the sun angle.
Mρ         = Band-specific multiplicative rescaling factor from the metadata (REFLECTANCE_MULT_BAND_x, where x is the band number)
Aρ          = Band-specific additive rescaling factor from the metadata (REFLECTANCE_ADD_BAND_x, where x is the band number)
Qcal        = Quantized and calibrated standard product pixel values (DN)

TOA reflectance with a correction for the sun angle is then:
ρλ ρλ'=ρλ'
cos(θSZ)sin(θSE)
where:              
ρλ          = TOA planetary reflectance
θSE         = Local sun elevation angle. The scene center sun elevation angle in degrees is provided in the metadata (SUN_ELEVATION).
θSZ         = Local solar zenith angle;  θSZ = 90° - θSE
For more accurate reflectance calculations, per pixel solar angles could be used instead of the scene center solar angle, but per pixel solar zenith angles are not currently provided with the Landsat 8 products.

Conversion to At-Satellite Brightness Temperature
TIRS band data can be converted from spectral radiance to brightness temperature using the thermal constants provided in the metadata file:
T =  K2
ln( K1 +1)
Lλ
where:              
T           = At-satellite brightness temperature (K)
Lλ          = TOA spectral radiance (Watts/( m2 * srad * μm))
K1          = Band-specific thermal conversion constant from the metadata (K1_CONSTANT_BAND_x, where x is the thermal band number)
K2          = Band-specific thermal conversion constant from the metadata (K2_CONSTANT_BAND_x, where x is the thermal band number)
Nguồn: USGS 
0
tuan rimf
tuan rimf

Has laoreet percipitur ad. Vide interesset in mei, no his legimus verterem. Et nostrum imperdiet nostrum imperdiet appellantur appellantur usu, mnesarchum referrentur. Has laoreet percipitur ad. Vide interesset in mei, no his legimus verterem. Et nostrum imperdiet nostrum imperdiet.