# Difference between revisions of "IKONOS"

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=== Calculate Planetary Reflectance === | === Calculate Planetary Reflectance === | ||

Converting a Blue Band (Digital Numbers) in to Spectral at-sensor Radiance: | |||

{{cmd|r.mapcalc}} <source lang="bash" enclose=none>"Blue_Radiance = ( (10000 * IKONOS_Blue_Band_DN) / (728 * 71.3) )"</source> | |||

Converting the in-Blue spectral band at-sensor Radiance in to Planerary Reflectance: | |||

{{cmd|r.mapcalc}} <source lang="bash" enclose=none>"Blue_Reflectance = ( ${PI} * Blue_Radiance * ${ESD}^2 ) / ( ${!BAND_Esun} * cos(${SZA}) )"</source> | |||

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## Revision as of 19:43, 26 July 2013

**[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 **Failed to parse (syntax error): {\displaystyle W * sr^−1 * m^−2 * nm^−1}**
, 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 (MathML with SVG or PNG fallback (recommended for modern browsers and accessibility tools): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \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 (syntax error): {\displaystyle 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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### Calculate Planetary Reflectance

Converting a Blue Band (Digital Numbers) in to Spectral at-sensor Radiance:

`r.mapcalc ``"Blue_Radiance = ( (10000 * IKONOS_Blue_Band_DN) / (728 * 71.3) )"`

Converting the in-Blue spectral band at-sensor Radiance in to Planerary Reflectance:

`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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