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Optical Products Calibration

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Description

The calibration of Optical EO data is done in the ESA Charter Mapper via a dedicated processing service, named Optical Products Calibration (OPT-Calib), which derives in systematic calibrated images from ingested optical EO data products acquired from multiple EO-missions. Output optical calibrated single-band assets of TOA/BOA reflectance can be used as input for further thematic processing (e.g. co-location, change detection).

Workflow

The OPT-Calib service implements the workflow depicted below.

graph TB i[(COS-2)] style i fill:#ffde86,stroke:#333,color:#282828,stroke-width:2px i --> a1(EO data product) subgraph Inputs style Inputs fill:#e8e8e8,stroke:#333,color:#282828 a1[/Optical Dataset/] style a1 fill:#acc8ff,stroke:#333,color:#282828,stroke-width:2px end subgraph OPT-Calib a1 --> dntor[DN to radiance] style a1 fill:#cfdfff,stroke:#333,color:#282828 dntor --> rtor[Radiance to reflectance] rtor --> p1(TOA/BOA Reflectance) style p1 fill:#cfdfff,stroke:#333,color:#282828 p1 --> opt_index[Spectral Index generation] opt_index --> p2(NDVI, NDWI) style p2 fill:#cfdfff,stroke:#333,color:#282828 opt_index --> p3(NDBI) style p3 fill:#cfdfff,stroke:#333,color:#282828 p1 --> bav[Burned Area Visualization<br>algorithm] p2 --> bav[Burned Area Visualization<br>algorithm] bav --> p4(BAV) style p4 fill:#cfdfff,stroke:#333,color:#282828 p1 --> cloud[Cloud Masking] cloud --> p5(Cloud mask <br> and probability) style p5 fill:#cfdfff,stroke:#333,color:#282828 p1 --> over[Creation of Overviews] p4 --> over[Creation of Overviews] p5 --> over[Creation of Overviews] over --> p6(overviews) style p6 fill:#cfdfff,stroke:#333,color:#282828 p1 --> cog[Convert to COG] p2 --> cog[Convert to COG] p3 --> cog[Convert to COG] p4 --> cog[Convert to COG] p5 --> cog[Convert to COG] p6 --> cog[Convert to COG] cog --> stac[Create STAC item] end subgraph Outputs style Outputs fill:#e8e8e8,stroke:#333,color:#282828 stac --> o1[/Reflectance asset for each CBN: pan, red, green, etc./] style o1 fill:#acc8ff,stroke:#87afff,color:#282828,stroke-width:2px stac --> o2[/Spectral indexes: NDVI, NDWI, NDBI/] style o2 fill:#acc8ff,stroke:#87afff,color:#282828,stroke-width:2px stac --> o3[/BAV/] style o3 fill:#acc8ff,stroke:#87afff,color:#282828,stroke-width:2px stac --> o4[/CLM, CLP/] style o4 fill:#acc8ff,stroke:#87afff,color:#282828,stroke-width:2px stac --> o5[/overview-pan, overview-trc, overview-civ, etc./] style o5 fill:#acc8ff,stroke:#87afff,color:#282828,stroke-width:2px end

The processor employs the Optical Calibration application of Orfeo Toolbox1 or plain matrix calculations to apply the conversion of DN to radiance and reflectance. The cloud masking step supports only Sentinel-2 data and is built with the Sentinel-2 Cloudless processor.

A detailed description of each step of the OPT-Calib chain is provided below.

Digital Numbers to Radiance

Top Of Atmosphere (TOA) Radiance in Wμm-1 m-2 sr-1 is derived from DN values using the following formula:

\[ L_\lambda = gain \times DN + offset \]

where: \(L_\lambda\) is TOA Radiance in Wμm-1 m-2 sr-1.

Radiance to Reflectance

TOA reflectance \(\rho_\lambda\) in spectral band \(\lambda\) is then derived from:

\[ \rho_\lambda = \frac {L \times d^2_{E,S} \times \pi} {ESUN \times cos(θ_{S})} \]

where: \(L_\lambda\) is the radiance in spectral band \(\lambda\), \(d^2_{E,S}\) is the is the earth-Sun distance in AU at given time, \(ESUN\) is the band averaged Exo Atmospheric Solar Irradiance at 1AU in mW m^-2 nm^-1, and \(θ_{S}\) is the solar zenith angle, and \(L\) is TOA Radiance in Wμm-1 m-2 sr-1.

ESUN is derived from reference Solar Spectral Irradiance and depends on radiometric resolution and Filter Spectral Response Profiles for each band of the optical EO data.

This information is usually provided in the mission handbooks or manuals. For those missions where the ESUN values were not provided, these are derived from Thuillier 2002, over nominal band spectral ranges. ESUN values can be refined once Filter Spectral Response Profiles for VHRI 100 imager sensors are known. Table 1 reports an example of ESUN for multiple assets made using Thuillier2 2002 model for Vision-13.

Band λ(nm) ESUN (Thuillier 2002) mW m^-2 nm^-1
PAN 450-650 1830.15
Blue 440-510 2002.25
Green 510-590 1822.22
Red 600-670 1613.83
NIR 760-910 948.98

Table 1 - ESUN values for multispectral bands of Vision-1 (VHRI 100 imager) sensor.

Spectral index generation

In the spectral index generation step a selection of spectral indexes are derived from the multispectral calibrated single band assets. The spectral indexes already included in an optical calibrated dataset are listed in Table 2.

Asset name Index Reference
ndvi NDVI - Normalised Difference Vegetation Index Rouse et al. (1973)4
ndwi NDBI - Normalised Difference Water Index Mc Feeters (1996)5
ndbi NDBI - Normalised Difference Build-up Index Zha et al. (2003)6
bav Burned Area Visualization binary mask Monja B. Šebela7

Table 2 - List of spectral indexes potentially available in an Optical Calibrated Dataset.

Warning

Please be aware that the NDBI index is only available for those missions having SWIR assets (e.g. Sentinel-2, Landsat-8/9).

Burned Area Visualization

To support PM/VA users in estimating burnt areas the Burned Area Visualization algorithm is included in the Optical Calibration chain. This script7 is employed to derive a Burned Area Visualization (BAV) single band (bav) and overview (overview-bav) assets from EO data having at least blue, green nir, swir16, and swir22 spectral bands.

Note

Notes from the authors of the script (Monja Šebela): "The script does well at detecting burned areas and covers burned land well in most cases. The script is not perfect, as it sometimes fails to completely cover the burned area or overestimates them. It is however useful for detecting burned areas nonetheless, as it consistently detects large scale recently burned areas".

Warning

BAV single band and overview assets are offered in calibrated datasets ONLY in workspaces of volcano or wildfire activations.

Warning

Please be aware that BAV single band and overview assets are only available for the missions having SWIR assets (e.g. Sentinel-2, Landsat-8/9).

Cloud Masking

The cloud masking step of OPT-Calib employs the S2-Cloudless processor and derives the following single band assets in COG format:

  • Cloud Mask (CLM) single band asset (s2cloudless_clm): 0 (no clouds), 1 (clouds), 255 (no data),

  • Cloud Probability (CLP) single band asset (s2cloudless_clp): probabilty in the [0-1] range,

Warning

Cloud mask and probability assets are available ONLY for Sentinel-2 datasets.

Creation of overviews

In the overview image creation, the service generates multiple full-resolution overviews derived from the assets of calibrated optical EO data. Multiple pre-defined RGB band composites are available in the ESA Charter Mapper for optical EO data. All the possible RGB composite options with the associated CBN combinations are listed in Table 3. Output visual products are given as RGBA band composites.

Code Composite RGB (CBN)
TRC True Color red, green, blue
CIV Color Infrared (vegetation) nir, red, green
LAW Land/Water nir, swir16, red
VEA Vegetation Analysis swir16, nir, red
SIR Shortwave Infrared swir22, nir, red
FCU False Color Urban swir22, swir16, red
ATP Atmospheric Penetration swir22, swir16, nir
WAD Water Depth green, blue, coastal

Table 3 - RGB Composites for ESA Charter Mapper using CBNs.

Note

More information about the creation of visual products in the ESA Charter Mapper can be found here.

Outputs

The outputs of the Optical Products Calibration service are the following products given in COG format:

  1. TOA/BOA reflectance or brightness temperature single band assets for all multispectral bands,

  2. Single band assets representing NDVI, NDWI, and NDBI spectral indexes,

  3. BAV single band asset which estimates burned areas,

  4. Cloud Mask (CLM) and Cloud Probability (CLP) single band assets,

  5. Seven overview assets (a true color and multiple false color composites) derived from multispectral bands,

  6. BAV overview asset derived by combining a True Color composite with the BAV binary mask superimposed in red.

  7. A pair of overviews assets derived by combining a True Color composite with CLM and CLP.

The output of OPT-Calib is a STAC Item with the all the output Assets included.

Product specifications for the Optical Products Calibration service can be found in the following following tables.

Attribute Value / description
Long Name TOA/BOA Reflectance from calibrated Panchromatic or Multispectral Calibrated Optical data
Short Name r-pan, r-coastal, r-blue, etc. for all optical CBN for VIS, NIR, SWIR
Description TOA/BOA Reflectance single band asset for VIS, NIR, SWIR CBNs rescaled to 10000 from calibrated optical data
Processing level As source product (L1/L2)
Data Type Unsigned 16-bit Integer
Band Single
Format COG
Projection Native
Units Dimensionless
Valid Range [0 - 10,000]
Scale Factor *0.0001
Attribute Value / description
Long Name TOA brightness Temperature from calibrated optical data
Short Name bt-lwir11, bt-lwir12
Description Brightness Temperature (K) single band asset rescaled to 100 from calibrated optical data
Processing level As source product (L1/L2)
Data Type Unsigned 16-bit Integer
Band Single band
Format COG
Projection Native
Units K
Scale Factor *0.01
Attribute Value / description
Long Name Spectral Indexes
Short Name ndvi, ndwi, and ndbi
Valid range [-1, 1]
Data type Float 32
Band Single
Format COG
Projection Native
No data value NaN
Attribute Value / description
Long Name Burned Area Visualization single band
Short Name bav
Valid range [0, 1]. Value 1 indicates burned areas
Data type Float 32
Band Single
Format COG
Projection Native
No data value NaN
Attribute Value / description
Long Name S2-Cloudless Cloud Mask single band
Short Name s2cloudless_clm
Description CLM binary mask: 1=clouds, 0=no-clouds
Data Type UnSigned 8-bit Integer
Band Single
Format COG
Projection Native as Sentinel-2 L1C or L2A product
Units N/A
Valid Range [0 - 1]
Fill Value 255
Attribute Value / description
Long Name S2-Cloudless Cloud Probability single band
Short Name s2cloudless_clp
Description Cloud probability in a [0-1] range
Data Type UnSigned 8-bit Integer
Band Single
Format COG
Projection Native as Sentinel-2 L1C or L2A product
Units N/A
Valid Range [0 - 1]
Fill Value 255
Attribute Value / description
Long Name Full resolution RGBA composite or grayscale single band image from Panchromatic or Multispectral Calibrated Optical data
Short Name overview-pan, (grayscale), overview-trc, overview-civ, overview-law, overview-vea, overview-sir, overview-fcu, overview-atp, overview-wad (false color composite)
Description Grayscale single band geo-referenced image from PAN or RGBA composites from MS Optical data (including alpha band).
Processing level As source product (L1/L2)
Data Type UnSigned 8-bit
Band 4
Format COG
Projection Native
Valid Range [0 - 255]
Fill Value 0
Attribute Value / description
Long Name BAV overview
Short Name overview-bav
Description True Color Composite with True values of BAV in red superimposed
Data Type UnSigned 8-bit Integer
Band 4
Format COG
Projection Native as Sentinel-2 L1C or L2A product
Units N/A
Valid Range [0 - 255]
Attribute Value / description
Long Name S2-Cloudless Cloud Mask overview
Short Name s2cloudless_clm_overview
Description True Color Composite with True values of CLM in white superimposed
Data Type UnSigned 8-bit Integer
Band 4
Format COG
Projection Native as Sentinel-2 L1C or L2A product
Units N/A
Valid Range [0 - 255]
Attribute Value / description
Long Name S2-Cloudless Cloud Probability overview
Short Name s2cloudless_clp_overview
Description True Color Composite with CLP in a red to white color map superimposed
Data Type UnSigned 8-bit Integer
Band 4
Format COG
Projection Native as Sentinel-2 L1C or L2A product
Units N/A
Valid Range [0 - 255]

  1. Orfeo Toolbox, Optical Calibration, Available at: https://www.orfeo-toolbox.org/CookBook/Applications/app_OpticalCalibration.html. ↩

  2. Thuillier, G., Hersé, M., Labs, D. et al. (2003), “The Solar Spectral Irradiance from 200 to 2400 nm as Measured by the SOLSPEC Spectrometer from the Atlas and Eureca Missions”. Solar Physics 214, 1–22. DOI: https://doi.org/10.1023/A:1024048429145. ↩

  3. Airbus Space and Defence, (2020) “Vision-1 Ideal High-Resolution Monitoring Solution”, Available at: https://www.intelligence-airbusds.com/automne/api/docs/v1.0/document/download/ZG9jdXRoZXF1ZS1kb2N1bWVudC02MDIyNg==/ZG9jdXRoZXF1ZS1maWxlLTYwMjI1/Vision-1_web_201906.pdf. ↩

  4. Rouse J., Haas R. H., Schell J. A., Deering D. (1973), “Monitoring vegetation systems in the great plains with ERTS”, NASA. Goddard Space Flight Center 3d ERTS-1 Symp., Vol. 1, Sect. A. Available at: ntrs.nasa.gov ↩

  5. McFeeters S. K. (1996), “The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features”, International Journal of Remote Sensing, 17:7, 1425-1432, DOI: 10.1080/01431169608948714. ↩

  6. Zha Y., Gao J., Ni S. (2003), “Use of normalized difference built-up index in automatically mapping urban areas from TM imagery”, International Journal of Remote Sensing, 24:3, 583-594, DOI: 10.1080/01431160304987. ↩

  7. Monja Šebela’s “Burned Area Visualization” script on SentinelHub, Accessible at: custom-scripts.sentinel-hub.com. ↩↩