Difference between revisions of "IKONOS"
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* The mathematical constant {{wikipedia|Pi}} <source lang="bash" enclose=none>PI=3.14159265358</source>. | * The mathematical constant {{wikipedia|Pi}} <source lang="bash" enclose=none>PI=3.14159265358</source>. | ||
* The Earth-Sun distance in astronomical units which depends on the acquisition's day of year (DOY -- also referred to as Julian day, {{wikipedia|Ordinal_date}}) and can be retrieved from the following spreadsheet <http://landsathandbook.gsfc.nasa.gov/excel_docs/d.xls>. | * The Earth-Sun distance in astronomical units which depends on the acquisition's day of year (DOY -- also referred to as Julian day, {{wikipedia|Ordinal_date}}) and can be retrieved from the following spreadsheet <http://landsathandbook.gsfc.nasa.gov/excel_docs/d.xls>. | ||
− | * The mean solar exoatmospheric irradiance in < | + | * The mean solar exoatmospheric irradiance in <math>\frac{W}{m2*μm}</math> -- see 3rd column of (interplated) values given above. |
* The cosine of the ''Solar Zenith Angle'' (SZA) at the time of the acquisition. The SZA can be calculated from its complementary ''Solar Elevation Angle'' (SEA) given in the image acquisition's metadata. | * The cosine of the ''Solar Zenith Angle'' (SZA) at the time of the acquisition. The SZA can be calculated from its complementary ''Solar Elevation Angle'' (SEA) given in the image acquisition's metadata. | ||
Revision as of 16:33, 26 July 2013
Contents
[This page is under construction]
IKONOS is a commercial earth observation satellite. Details about the sensor are provided at Digital Globe's IKONOS Data Sheet
Availability (Sample Data)
- Search for commercial satellite image providers in the internet.
- The Global Land Cover Facility (GLCF) provides four openly available IKONOS scenes of western Sichuan.
- ISPRS provides a small IKONOS data set, fragments from a Panchromatic image as well as from a Stereo product.
Pre-Processing Overview
Typically, multispectral satellite data are converted into physical quantities such as Radiance or Reflectance before they are subjected in multispectral analysis techniques (image interpretation, band arithmetic, vegetation indices, matrix transformations, etc.). The latter can be differentiated in Top of Atmosphere Reflectance (ToAR) which does not account for atmospheric effects (absorption or scattering) and in Top of Canopy Reflectance (ToCR) which introduces a "correction" for atmospheric effects.
In order to derive Reflectance values, likewise as with remotely sensed data acquired by other sensors, IKONOS raw image digital numbers (DNs) need to be converted to at-sensor spectral Radiance values. At-sensor spectral Radiance values are an important input for the equation to derive Reflectance values. Note, Spectal Radiance is the measure of the quantity of radiation that hits the sensor and typically expressed in , that is watts per unit source area, per unit solid angle, and per unit wavelength.
Converting DNs to at-sensor Radiance can be done by using the following equation:
Converting to Top of Atmosphere Reflectance, also referred to as Planetary Reflectance, can be done by using the following equation:
Failed to parse (lexing error): \rho_p = \frac{\pi * L\lambda * d^2}{ESUN\lambda * cos(θ_S)}
where:
- - Unitless Planetary Reflectance
- - mathematical constant (3.14159265358)
- spectral Radiance at the sensor's aperture, from equation... ToADD
- - Earth-Sun distance in astronomical units, interpolated values
- - Mean solar exoatmospheric irradiance(s) (W/m2/μm), interpolated values
- Failed to parse (lexing error): cos(θ_s) - Solar zenith angle, from the image acquisition's metadata
Modules overview
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Pre-Processing
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File Formats & Metadata
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Importing data
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Derive Physical Quantities
Calculate Spectral Radiance
Converting Digital Numbers to Radiance/Reflectance requires knowledge about the sensor's specific spectral band parameters. Those are, as extracted from the document IKONOS Planetary Reflectance and Mean Solar Exoatmospheric Irradiance, by Martin Taylor (see references):
Pan_CalCoef=161 ; Pan_Width=403 ; Pan_Esun=1375.8
Blue_CalCoef=728 ; Blue_Width=71.3 ; Blue_Esun=1930.9
Green_CalCoef=720 ; Green_Width=88.6 ; Green_Esun=1854.8
Red_CalCoef=949 ; Red_Width=65.8 ; Red_Esun=1556.5
NIR_CalCoef=843 ; NIR_Width=95.4 ; NIR_Esun=1156.9
Converting a Blue Band (Digital Numbers) in to Spectral at-sensor Radiance in the correct units to be further used for the conversion in to unitless Reflectance:
r.mapcalc "Blue_Radiance = ( (10000 * IKONOS_Blue_Band_DN) / (728 * 71.3) )"
Calculate Planetary Reflectance
The equation to derive Reflectance values incorporates in addition:
- The mathematical constant Pi
PI=3.14159265358
. - The Earth-Sun distance in astronomical units which depends on the acquisition's day of year (DOY -- also referred to as Julian day, Ordinal_date) and can be retrieved from the following spreadsheet <http://landsathandbook.gsfc.nasa.gov/excel_docs/d.xls>.
- The mean solar exoatmospheric irradiance in Failed to parse (lexing error): \frac{W}{m2*μm} -- see 3rd column of (interplated) values given above.
- The cosine of the Solar Zenith Angle (SZA) at the time of the acquisition. The SZA can be calculated from its complementary Solar Elevation Angle (SEA) given in the image acquisition's metadata.
In the following example we accept as the acquisition's DOY=166
and SEA=52.78880
. Hence, we get the Earth-Sun distance ESD=1.0157675
and SZA = 37.21120 deg
.
Converting the in-Blue spectral band at-sensor Radiance in to Planerary Reflectance:
PI=3.14159265358; ESD=1.0157675; BAND_Esun=1930.9; SZA=37.21120
r.mapcalc"Blue_Reflectance = ( ${PI} * Blue_Radiance * ${ESD}^2 ) / ( ${BAND_Esun} * cos(${SZA}) )"
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Atmospheric correction
Color composites
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Pan Sharpening
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IKONOS Image classification
References / Sources
- http://www.apollomapping.com/wp-content/user_uploads/2011/09/IKONOS_Esun_Calculations.pdf
- http://web.unicen.edu.ar/crecic/docs/radrefl.pdf
- Some short presentation about the DN to Reflectance conevrsion: Calibrated Landsat Digital Number (DN) to Top of Atmosphere (TOA) Reflectance Conversion, by Richard Irish
See also
- GRASS-Wiki page about Image Processing
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