Skip to content

Ortho (L1D/L1D_SR)

drawing

Product description

The L1D and L1D_SR imagery products are 4-band (RGB and Near infrared) product designed for accuracy and best of class image quality. It is delivered to customers after going through radiometric and geometric correction process.

Note: starting from 1 October 2024 the L1D_SR_TOA, L1D_SR_VISUAL product replace the naming L1 and L3 namings used in the delivery package. For the old delivery package (product version < v0.3.0) structure please refer to page Ortho (legacy).

Technical Specifications

Parameter

Mark IV

Mark V
Sepctral bands

Blue : 450 - 510 nm
Green: 510 - 580 nm
Red : 590 - 690 nm
NIR : 750 - 900 nm

Blue : 450 - 517 nm
Green: 517 - 583 nm
Red : 597 - 690 nm
NIR : 759 - 890 nm

GSD

1m (L1D) / 0.7m for (L1D_SR)

0.7m (L1) / 0.5m (L1_SR)

Scene Swath

4.8 - 5.5 Km 1

6.8Km - 8.5Km 1

Image bit depth

8-bit for VISUAL, 16 bit for TOA

⁠
Max Off-Nadir angle

± 25 deg

⁠
Algorithms applied

Radiometric correction, Band Aligment, Fine geolocation, Projection to UTM and orthorection

⁠
Geolocation Accuracy

10m CE90 Varies with the availabilty of GCPs and cloud coverage2

⁠
Band aligment

<= 2pxTBD

⁠
Image format

GeoTiff, LZW loseless compression

⁠
Ancilliary files

Cloud mask (GeoTiff), preview (PNG), thumbnail (PNG) and imagery footprint in vector format.

 ⁠
Metadata

STAC metadata, ISO metadata, TOA factors and solar and viewing angles

⁠

Product presentation

The ortho products are currently offered in two major processing levels:

  • L1D TOA Reflectance (L1D)
  • L1D TOA Reflectance SuperResolution (L1D_SR)

L1D_TOA, is a 4 bands (blue, green, read and Near Infrared) imagery product with Top of the Atmosphere reflectance records measurements in physical units, and enables analysts to perform basic classifications and analytics. The imagery is radiometrically and geometrically corrected. Pixel values are scaled to TOA Reflectance (0 to 1) multiplied by a factor 10000 (1e4) to avoid float numbers. L1D TOA has a resolution of 1m after resampling, which harmonises native pixel size that varies between 0.7m and 1.3m.

L1D_SR_TOA goes through one step further in processing which applies proprietary super resolution algorithm to improve the Ground Sample Distance (GSD) from 1m to 70 cm for Mark IV satellites and from 70cm to 50cm for Mark V satellites.

Both L1D and L1D_SR products are currently delivered along with a corresponding VISUAL Products called L1D_VISUAL and L1D_SR_VISUAL. This is a 3 bands imagery (red, green and blue) derived from the TOA product, processed with a color enhancement algorithm as descibed at section.

The figure below illustrates the high level image processing workflow, which begins upon receiving raw data and is completed after the transfer of processed data to the image catalog and product delivery package:

drawing

For geometric and radiometric processing details please refer to Image processing section.

Product framing

drawing

Ortho products are currently packaged as entire scenes. Each scene is a full swath (approximately 5Km) image with a varying length depending on the capture or requiered area by the user. In case the of very big scenes, the scene is divided into 10km chunks and identified with a chunk number indicated at the end of the file name starting from 0. Also the provided VRT merges all these chunks for easier manipulation.

drawing

For example, a long scene is shown on the right that has been automatically "chunked" into 3 ~10Km chunks. Colors and transparency had been modified to show the concept.

Projection

Each ortho scene is projected to the corresponding projection according to their closest matching UTM Zone. The projection is indicated in the proj:epsg property of each product metadata. If a scene is captured across different zones, the entire scene and corresponding chunk are projected to the zone with more data.

Product Package content

The file name as displayed below follows this format:

<DATE>_<TIME>_SN<SATELLITE_NUMBER>_<L1D/L1D_SR>_<TASK_ID>

The date is in UTC time observed at the centre of image, the product level correspond to the level of processing. For example, “L1D_SR_MS_TOA”=Reflectance (TOA) 4 Bands, “L1D_SR_MS_VISUAL”=TOA RGB, and “SR”=SuperResolution (depending on order), the payload indicates whether the product is multispectral (MS) of hyperspectral (HS). HS product is not yet commercialised at this moment.

The folder structure is displayed below, just open the dropdowm and see the delivery folder content which including metadata and different raster formats including the light weight virtual rasters as well as image previews.

<DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1D_SR_MS_<TASK_ID>
├── <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1D_SR_MS_TOA.vrt
├── <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1D_SR_MS_CLOUD.vrt
├── <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1D_SR_MS_VISUAL.vrt
├── <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1D_SR_MS_TOA.vrt.ovr
├── <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1D_SR_MS_VISUAL.vrt.ovr
├── <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1D_SR_MS_footprint.kml
├── <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1D_SR_MS_metadata_iso.xml
├── <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1D_SR_MS_metadata_stac.geojson
├── <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1D_SR_MS_solar_and_viewing_angles.geojson
├── <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1D_SR_MS_toa_factors.json
├── <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1D_SR_MS_preview.png
├── <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1D_SR_MS_thumbnail.png
└── rasters
    ├── <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1D_SR_MS_TOA_<N>.tif
    ├── <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1D_SR_MS_CLOUD_<N>.tif
    ├── <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1D_SR_MS_VISUAL_<N>.tif
File Description
*_L1D_SR_MS_TOA.vrt A GDAL Virtual raster that contains all the corresponding TOA TIFs in the rasters folder. In case of very big images, mutliple tifs can be included in the package.
*_L1D_SR_CLOUD.vrt A GDAL Virtual raster that contains all the corresponding cloud masks TIFs in the rasters folder. In case of very big images, mutliple tifs can be included in the package.
*_L1D_SR_MS_footprint.kml The overal raster ground footprint in KML
*_L1D_SR_MS_metadata_iso.xml A Metadata file in ISO 19115-2 format containing the key information from the metadata of the product. See the metada section for more information.
*_L1D_SR_MS_metadata_stac.geojson A Metadata file in STAC format containing the aggregated information of the product. See the metada section for more information.
*_L1D_SR_MS_toa_factors.geojson A Geojson file that contains the coefficients to transform the TOA product into Radiance units.
*_L1D_SR_MS_solar_and_viewing_angles.geojson A Geojson file that contains extra metadata about the sun and viewing angles.
*_L1D_SR_MS_VISUAL.vrt A GDAL Virtual raster that contains all the corresponding VISUAL TIFs in the rasters folder. In case of very big images, mutliple tifs can be included in the package.
*_L1D_SR_MS_preview.png The preview component of the product for the entire scene
*_L1D_SR_MS_thumbnail.png A low resolution thumbnail of the scene
rasters/*L1D_SR_MS_TOA.tif The full resolution TOA raster that comprises the full scene. For very large captures, the rasters are divided into smaller chinks. The number is the chunk number
rasters/*L1D_SR_MS_VISUAL.tif The full resolution VISUAL raster that comprises the full scene. For very large captures, the rasters are divided into smaller chinks. The number is the chunk number
rasters/*L1D_SR_MS_CLOUD.tif The cloud mask raster files

TOA_factors

The *_toa_factors.geojson file contains the coefficients for converting the DNs into Radiance and Reflectance units respectively as a geojson tiled file on a grid of 4x4 km2 tiles. The image on the right depicts this file overlaid with the raster file for reference. Small variation of the radiance coefficients can be expected across the image. The *_solar_and_viewing_angles.geojson file contains the solar elevation and azimuth angles, earth/sun distance, satellite azimuth, zenith and altitude as well as ground elevation and their unit of measurmeent in a tiled fashion as shown for the *_toa_factors.geojson file.

Metadata

ISO 19115-2 Metadata

Satellogic adheres to industry standards governing metadata schemas that align with ISO standards. The adoption of ISO 19115 (ISO metadata standard) ensures that information about sensor identification, image extent, quality, spatial and temporal aspects, content, spatial references, distributions, and other properties of digital geographic data are provided in a XML format for customers seeking to integrate Satellogic map-ready orthorectified raster data directly into their workflows. The table below shows the metadata fields according to ISO 19115-2:

Identifier Type Description
gmd:fileIdentifier string Unique file identifier
gmd:language code Language used for metadata (eng)
gmd:characterSet code Character coding standard in the metadata (utf8)
gmd:contact string Contact information of the company responsible for the metadata information (Satellogic)
gmd:dateStamp date Date of dataset creation in UTC
gmd:metadataStandardName string Name of the metadata standard used (ISO)
gmd:metadataStandardVersion string ISO metadata standard version
Spatial Representation Information: Grid Spatial Representation
gmd:numberOfDimensions integer Number of independent spatial-temporal axes (2d: x, y )
gmd:axisDimensionProperties string/integer Dimension name (column) and size (integer), resolution (m)
gmd:cellGeometry code Grid data identification (area)
gmd:transformationParameterAvailability boolean Dataset coordinates and geographic or map coordinates availability
gmd:referenceSystemInfo string/date Information of CRS provider, release date, version and edition details
Metadata extension information
gmd:MD_ExtendedElementInformation string Exposure time (seconds) and responsible party information (Satellogic)
Data Identification
gmd:Citiation_title string Name of the dataset
gmd:Cititation_Date data date in UTC
gmd:abstract string Scene set identification (Scene set ID)
gmd:pointOfContact string Contact information
gmd:resourceMaintenance string Information on dataset maintenance
gmd:resourceConstraints string The limitations or constraints on the use of or access to dataset
gmd:spatialRepresentationType code Object used to represent the geographic information
gmd:language code Languages of the dataset using standard ISO three letter codes (eng)
gmd:characterSet code Character coding standard in the dataset
gmd:environmentDescription string Describes the dataset’s processing environment
gmd:extent decimal Information about geographic extent of the dataset (bounding box coordinates)
Supplemental information
Satellite Number string Satellogic satellite number
Satellite Name string Satellogic satellite name
gmd:contentInfo string Sensor type, dataset content type
gmd:dimension string Imagery bands information (name and wavelength)
gmd:illuminationElevationAngle decimal Sun elevation angle in degrees
gmd:illuminationAzimuthAngle decimal Sun azimuth angle in degrees
gmd:imageQualityCode string/date Metadata standard and version release
gmd:cloudCoverPercentage decimal Percentage of the are covered by clouds
gmd:processingLevelCode string Corresponds to data product level
gmd:compressionGenerationQuantity integer Compression information
gmd:distributionFormat string Dataset format name and version

STAC Metadata

STAC metadata have all required STAC items by their schema, in addition they contain the following properties:

Note: this section refers to the attachment *_L1D_SR_MS_metadata_stac.geojson that can be found in the delivery attachment. For information about the product in our internal stac archive see section STAC API.

Item Type Properties
Properties
datetime string The date and time of the dataset acquisition, in UTC
created date Creation date and time of the corresponding dataset package, in UTC
license string Dataset license (current: confidential, next metadata release: proprietary)
providers object Dataset providers name, description, roles and contact details (Satellogic)
platform string Unique name of the specific platform to which the instrument is attached (NewSat)
instruments string Name of instrument or sensor used (MS)
constellation string Name of the constellation to which the platform belongs (Aleph1)
gsd [number] Ground Sample Distance at the sensor, in meters (1m for L1 and 70cm for L1-SR) - for next metadata release
eo:cloud cover [number] Estimate of cloud cover, in percentage
proj:epsg string EPSG code of the dataset projection
view:sun_elevation [number] Sun elevation angle, in degrees
view:off_nadir [number] The angle from the sensor between nadir (straight down) and the scene center, in degrees
view:sun_azimuth [number] Sun azimuth elevation angle in degrees from the target
view:azimuth [number] Satellite azimuth elevation angle in degrees from the target
view:incidence_angle [number] Satellite indicence angle in degrees from the target
satl:exposure_sec [number] Sensor exposure time to light, in seconds
satl_type string Type of dataset (i.e. acquisition mode)
satl:sat_id string Unique identification of the Satellite
satl:product_level string Product processing level properties

Solar and viewing angles

This section contains a detailed list and explaination of the fields reported the file: <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1D_SR_MS_solar_and_viewing_angles.geojson

ITEM TYPE PROPERTIES EXAMPLE
satellite object satellite viewing angles { "azimuth": 88.659999999999997, "off_nadir": 14.56, “incidence_angle”: 16, "units": "degrees"}
solar object solar angles { "azimuth": 98.519999999999996, "elevation": 54.619999999999997, “zenith”: 46, "units": "degrees"}
satellite_altitude object satellite altitude { "units": "km", "values": 407.04303963282291 }

Toa factors

This section contains a detailed list and explaination of the fields reported the file: <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1D_SR_MS_toa_factors.json

ITEM TYPE PROPERTIES Example
toa_to_radiance_units str Units used to measure radiances { "units": "W \/ (m^2 . nm . sr)" }
toa_to_radiance object Dict with conversion factor from pixel values to radiances per bands { "red": 4.1999999999999998e-05, "green": 4.6999999999999997e-05, "blue": 5.0000000000000002e-05, "nir": 2.8e-05 }
toa_to_reflectance object Dict with conversion factor from pixel values to reflectances per bands { "red": 0.0001, "green": 0.0001, "blue": 0.0001, "nir": 0.0001 }
sun_irradiance object Sun irradiances per band { "blue": 1.9652181491053091, "green": 1.8502548064710287, "nir": 1.1110366247015171, "red": 1.6358498243613719 }
toa_to_dn object Dict with conversion factor from pixel values to digital numbers { "blue": 0.12957880445214495, "green": 0.16739338801869888, "nir": 0.13506835516927529, "red": 0.21212770384515217 }
dn_to_toa object Dict with conversion factor from digital numbers to toa values { "blue": 0.00077173115173269889, "green": 0.0005973951610850327, "nir": 0.00074036586789462541, "red": 0.00047141414434484925 }
vicarious_factors object Dict with vicarious factors { "blue": { "bias_factor": 0, "scale_factor": 1.0230836891878803 }, "green": { "bias_factor": 0, "scale_factor": 1.0251017432557326 }, "nir": { "bias_factor": 0, "scale_factor": 1.3636052964183787 }, "red": { "bias_factor": 0, "scale_factor": 1.1095023024541237 } }
vicarious_correction object Dict with vicarious correction factors { "blue": { "bias_factor": 0, "scale_factor": 1.0230836891878803 }, "green": { "bias_factor": 0, "scale_factor": 1.0251017432557326 }, "nir": { "bias_factor": 0, "scale_factor": 1.3636052964183787 }, "red": { "bias_factor": 0, "scale_factor": 1.1095023024541237 } }
dn_to_radiance object Dict with conversion from digital numbers to radiance { "blue": 0.00077173115173269889, "green": 0.0005973951610850327, "nir": 0.00074036586789462541, "red": 0.00047141414434484925 }
earth_sun_distance Earth-Sun distance distance Earth-Sun { "units": "AU", "values": 1.0044458278302446 }

STAC API

The L1D/L1D_SR product can be found in our STAC archives. Internally each capture is tiled on a UTM tile grid of 4x4km. Each tile of a capture is a single Item in the corresponding L1D/L1D_SR collection. The following metadata and assets are available for each

The following table shows the description of each field and an example corresponding to the capture used in previous section.

Field Description Example
datetime Capture date and time of the tile. In UTC 2024-05-27T03:01:47.897033+00:00
instruments Instruments used to take the capture ms
satl:satellite_generation Satellite generation Mark4
satl:satellite_altitude Satellite altitude [km] 400
satl:exposure_sec Capture exposure time in s 0.00019
satl:outcome_id A unique identifier of the associated capture with this tile. 81b495ff-1b2a-49a0-bb08-204ac31ae732
satl:product_name The unique name of the product of which this tile corresponds to L1D/L1D_SR
satl:product_version The version of the product. Uses semantic versioning. v0.3.0
satl:software_version The version of the software. Uses semantic versioning. v0.70.3
grid:code UTM grid code and tile size SATL-4KM-34N_692_5528
satl:transaction_id Unique identifier of the processing transaction l1-sr-dqdqdq-m9ftg
satl:valid_pixel Percentage of valid pixel (i.e. pixel with data) 93,44
gsd Ground sampling distance 1m
proj:epsg EPSG code EPSG:32634
proj:shape Image dimensions in pixels 4 000 × 4 000
proj:transform Transformation matrix in the UTM reference frame [[1; 0; 692 000], [0; -1; 5 532 000], [0; 0; 1]]
satl:ground_lock True if a geoframe has been geolocated True
satl:exposure_time Exposure time of the frames of the capture 0.00133
satl:satellite_generation Generation of the satellite MarkIV
satl-qa:geoaccuracy_ce90 Percentile 90 geoaccuracy [m] 5,70
satl-qa:geoaccuracy_rmse Root mean square error geoaccuracy [m] 3,77
satl-qa:alignment_ce95_red Band alignment percentile 95 red band [pix] 0,52
satl-qa:alignment_ce95_blue Band alignment percentile 95 blue band [pix] 0,71
satl-qa:snr_red Signal to noise ratio for red band [unitless] 25.56
satl-qa:snr_blue Signal to noise ratio for blue band [unitless] 30.87
satl-qa:snr_green Signal to noise ratio for green band [unitless] 32.56
satl-qa:snr_nir Signal to noise ratio for nir band [unitless] 35.72
satl-qa:dr_red Dynamic range for red band [unitless] 60.56
satl-qa:dr_blue Dynamic range for blue band [unitless] 35.36
satl-qa:dr_green Dynamic range for green band [unitless] 40.56
satl-qa:dr_nir Dynamic range for nir band [unitless] 65.56
satl-qa:cc_red Colorcast red band [unitless] 1.3
satl-qa:cc_blue Colorcast blue band [unitless] 1.2
satl-qa:cc_green Colorcast green band [unitless] 1.4
satl-qa:cc_nir Colorcast nir band [unitless] 1.5
platform Satellite name that acquired the imagery newsat43
eo:cloud_cover The percentage of cloud cover (0-100) 0.0
view:off_nadir The off-nadir angle for the capture measured in degrees. 0.06472
view:azimuth The azimuth angle of the satellite at the target, at the moment of the capture, in degrees. 23.5
view:incidence_angle The incidence angle of the satellite at the target, at the moment of the capture, in degrees. 26.1
view:sun_azimuth The azimuth angle of the sun at the target, at the moment of the capture, in degrees. 170.25
view:sun_elevation The elevation angle of the sun at the target, at the moment of the capture, in degrees. 33

Also, each item/tile contains the following assets/components:

STAC Item asset name Component
analytic The full resolution raster corresponding to the frame
preview A small preview of the raster
thumbnail A smallthubmnail of the raster.
metadata The JSON Metadata file describe above
cloud The raster cloud mask
toa_factors A json file containing the TOA calibration factors

Imagery End User Rights Agreement and Terms of Use

All imagery products are delivered under Satellogic Imagery End User License Agreement. The terms and conditions of the agreement are available to customers and accessible online on the website under License Agreement.

Cloud masks

The end product provided by Satellogic also includes cloud masks (see section: Product Package content). The mask is a single band GeoTiff for each delivered chunk. The values of the raster represent different cloud data as follows:

0: nodata 1: valid_data 128: cloud

The current cloud detector is able to detect "thick" clouds i.e. clouds that do not allow to view the content of the image below them or only a minimal part of it. Currently haze is therefore not labelled as cloud. An example is provided in the next image.

CLOUD_MASKS

Example of clouds detected by Satellogic clouds dector. Only the thickest clouds are detected.

Known issues

This section lists imagery product anomalies which sometimes slip through the automatic quality assurance filters due different reasons, apprearing clearly different from images that have gone though imagery quality assurance pipeline. The most known anomlalies are explained in this section.

Flipped pixel values in RGB enhanced images

The current image enhancement algorithm causes some flipped pixel values in saturated areas. This will be corrected in future versions of the pipeline.

ORTHO_FLIPPED_ISSUE

Flipped pixel values visible in saturated areas of RGB composites.

Reduced geo-accuracy

Some terrain types and environmental conditions might cause the Ground Control Points (GCPs)-based geometric correction to fail, producing captures of lower geo-accuracy. Standard imagery products are delivered with less than 10m geoaccuracy, however, because of high terrain and the lack of GCPs, especially in areas wihtout human made structures such over water, deserts, forests etc., less than 10m geoaccuracy is not achievable, hence some delivered images might show a shift in geolocation. In some extreme cases, such as over open water, such products are marked as a low geoacurracy quality tier and not generaly delivered to customers, but are available on demand for customers who do not have strict geoaccuracy requirements. Some examples are provided below.

ORTHO_GEO_ISSUE

Rural area close to mountain shadow in hilly terrain (left), showing reduced geo-accuracy. Features were shifted 77m relative to the reference map. On the right is the reference source - obtained from ESRI imagery.

Digital Elevation Model (DEM) distortions

Orthorectified images can present distortions in the presence of outliers in the DEM used during imagery processing. Satellogic is able to detect these problems in the DEM and use alternative models. Occasionally the detector may fail to locate the outliers and produce an effect like the one shown in the image below. This anomaly can be corrected through identifying the outlier in the DEM and reprocessing of the affected scene.

ORTHO_DISTORTION

Distortion in an orthorectified image.

Changelog

[1.1.1] 2024-11-07

Updates STAC archive

Fixed

Fix L1D visual rasters no data values. Some valid pixels were set as no data.

[1.1.0] 2024-11-06

Changed

Update visual product (3 bands RGB 8 bits) color correction. Replace Histograms stretching with custom color curve to reduce colors inconsistency between scenes.

[1.0.1] 2024-10-14

Updates STAC archive

Changed

Changed analytic and cloud rasters to be COG, add band interpretation to rasters

[1.0.0] 2024-10-01

Updates Delivery package

Changed

  • Change product namings in delivery package: 

    L1 --> L1D TOA, L3 --> L1D VISUAL and
L1_SR --> L1D_SR TOA, L3_SR --> L1D_SR VISUAL

  • Change file names in delivery package 

    <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1_SR_MS_<TASK_ID>.zip  --> <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1D_SR_MS_<TASK_ID>.zip
├── <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1_SR_MS.vrt  --> <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1D_SR_MS_TOA.vrt
├── <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1_SR_MS_cloud_mask.vrt  --> <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1D_SR_MS_CLOUD.vrt
├── <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1_SR_MS_footprint.kml  --> <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1D_SR_MS_footprint.kml
├── <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1_SR_MS_metadata_iso.xml  --> <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1D_SR_MS_metadata_iso.xml
├── <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1_SR_MS_metadata_stac.geojson  --> <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1D_SR_MS_metadata_stac.geojson
├── <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1_SR_MS_solar_and_viewing_angles.geojson  --> <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1D_SR_MS_solar_and_viewing_angles.geojson
├── <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1_SR_MS_toa_factors.json  --> <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1D_SR_MS_toa_factors.json
├── <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L3_SR_MS.vrt  --> <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1D_SR_MS_VISUAL.vrt
├── <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L3_SR_MS_preview.png  --> <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1D_SR_MS_preview.png
├── <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L3_SR_MS_thumbnail.png  --> <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1D_SR_MS_thumbnail.png
└── rasters
    ├── <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1_SR_MS_<N>.tif  --> <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1D_SR_MS_TOA_<N>.tif
    ├── <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1_SR_MS_cloud_mask_<N>.tif  --> <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1D_SR_MS_CLOUD_<N>.tif
    ├── <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L3_SR_MS_<N>.tif  --> <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1D_SR_MS_VISUAL_<N>.tif

Example: 

20240924_093957_SN24_L1_SR_MS_204885.zip  --> 20240924_093957_SN24_L1D_SR_MS_<TASK_ID>.zip
├── 20240924_093957_SN24_L1_SR_MS_.vrt  --> 20240924_093957_SN24_L1D_SR_MS_TOA.vrt
├── 20240924_093957_SN24_L1_SR_MS_cloud_mask.vrt  --> 20240924_093957_SN24_L1D_SR_MS_CLOUD.vrt
├── 20240924_093957_SN24_L1_SR_MS_footprint.kml  --> 20240924_093957_SN24_L1D_SR_MS_footprint.kml
├── 20240924_093957_SN24_L1_SR_MS_metadata_iso.xml  --> 20240924_093957_SN24_L1D_SR_MS_metadata_iso.xml
├── 20240924_093957_SN24_L1_SR_MS_L1_SR_MS_metadata_stac.geojson  --> 20240924_093957_SN24_L1D_SR_MS_metadata_stac.geojson
├── 20240924_093957_SN24_L1_SR_MS_L1_SR_MS_solar_and_viewing_angles.geojson  --> 20240924_093957_SN24_L1D_SR_MS_solar_and_viewing_angles.geojson
├── 20240924_093957_SN24_L1_SR_MS_L1_SR_MS_toa_factors.json  --> 20240924_093957_SN24_L1D_SR_MS_toa_factors.json
├── 20240924_093957_SN24_L1_SR_MS_L3_SR_MS.vrt  --> 20240924_093957_SN24_L1D_SR_MS_VISUAL.vrt
├── 20240924_093957_SN24_L1_SR_MS_L3_SR_MS_preview.png  --> 20240924_093957_SN24_L1D_SR_MS_preview.png
├── 20240924_093957_SN24_L1_SR_MS_L3_SR_MS_thumbnail.png  --> 20240924_093957_SN24_L1D_SR_MS_thumbnail.png
└── rasters
    ├── 20240924_093957_SN24_L1_SR_MS_L1_SR_MS_<N>.tif  --> 20240924_093957_SN24_L1D_SR_MS_TOA_<N>.tif
    ├── 20240924_093957_SN24_L1_SR_MS_L1_SR_MS_cloud_mask_<N>.tif  --> 20240924_093957_SN24_L1D_SR_MS_CLOUD_<N>.tif
    ├── 20240924_093957_SN24_L1_SR_MS_L3_SR_MS_<N>.tif  --> 20240924_093957_SN24_L1D_SR_MS_VISUAL_<N>.tif

  • Change fields names in toa_factors attachment <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1D_SR_MS_toa_factors.json in delivery package:
L1_to_radiance --> toa_to_radiance
toa_product --> removed
L1_to_reflectance --> toa_to_reflectance
L1_to_dn --> toa_to_dn
idx_x --> removed
idx_y --> removed
  • Change fields names in satellite and solar angles attachment <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1D_SR_MS_solar_and_viewing_angles.geojson:
satellite/elevation --> satellite/incidence_angle
idx_x --> removed
idx_y --> removed
  • Removed some fields from metadata_stac attachment <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1D_SR_MS_metadata_stac.geojson:
title --> removed
description --> removed
proj:centroid --> removed

Added

  • Added extra overview files for visualization in the delivery packaging:
<DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1D_SR_MS_TOA.vrt.ovr
<DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1D_SR_MS_VISUAL.vrt.ovr
  • Added extra view fields to metadata_stac attachment <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1D_SR_MS_metadata_stac.geojson:

For view stac extension please see (https://github.com/stac-extensions/view)

view:sun_azimuth --> sun azimuth elevation angle in degrees from the target
view:azimuth --> satellite azimuth elevation angle in degrees from the target
view:incidence_angle --> satellite indicence angle in degrees from the target

Updates STAC archive

Changed

  • Rename files in internal STAC archive
<DATE>_<TIME>_NS<SATELLITE_NUMBER>_l1d_sr_<PROD_VERSION>_SATL-<GRID_CODE>_cloud.tif --> <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1D_SR_MS_<GRID_CODE>_cloud.tif
<DATE>_<TIME>_NS<SATELLITE_NUMBER>_l1d_sr_<PROD_VERSION>_SATL-<GRID_CODE>_rgb_enhanced.tif --> <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1D_SR_MS_<GRID_CODE>_visual.tif
<DATE>_<TIME>_NS<SATELLITE_NUMBER>_l1d_sr_<PROD_VERSION>_SATL-<GRID_CODE>_toa.tif --> <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1D_SR_MS_<GRID_CODE>_analytic.tif
<DATE>_<TIME>_NS<SATELLITE_NUMBER>_l1d_sr_<PROD_VERSION>_SATL-<GRID_CODE>_preview.tif --> <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1D_SR_MS_<GRID_CODE>_preview.tif

  • Change band orders of the analytic product from RGBN to BGRN

  • Move some STAC archive properties from satl to asset toa_factors:

"satl:uint16_to_reflectance_red", "satl:uint16_to_reflectance_green", "satl:uint16_to_reflectance_blue",
"satl:uint16_to_reflectance_nir", "satl:uint16_to_radiance_red", "satl:uint16_to_radiance_green", "satl:uint16_to_radiance_blue","satl:uint16_to_radiance_nir"
are moved to toa_factors attachment under the fields "toa_to_radiance" and "toa_to_reflectance" per bands.

  • Move STAC archive metrics properties from satl to satl_qa and rename/remove some of them:
"satl:ba_blue_green_ce90"     --> removed
"satl:ba_blue_green_land_ce90"--> removed
"satl:ba_red_green_ce90"      --> removed
"satl:ba_red_green_land_ce90" --> removed
"satl:cc_blue"                --> "satl-qa:cc_blue"
"satl:cc_green"               --> "satl-qa:cc_green"
"satl:cc_nir"                 --> "satl-qa:cc_nir"
"satl:cc_red"                 --> "satl-qa:cc_red"
"satl:geo_red_ce90"           --> "satl-qa:geoaccuracy_ce90"
"satl:geo_red_ce99"           --> removed
"satl:geo_red_rmse"           --> "satl-qa:geoaccuracy_rmse"
"satl:geo_red_rmse_x"         --> removed
"satl:geo_red_rmse_y"         --> removed
"satl:snr_blue"               --> "satl-qa:snr_blue"
"satl:snr_green"              --> "satl-qa:snr_green"
"satl:snr_nir"                --> "satl-qa:snr_nir"
"satl:snr_red"                --> "satl-qa:snr_red"

Added

  • Added extra properties: satl:ground_lock -> True if a geoframe has been geolocated satl:exposure_time --> Exposure time of the frames of the capture satl:satellite_generation --> Generation of the satellite instruments --> instruments used to take the image (ms=multispectral)

  • Added toa_factors attachments as asset to L1D/L1D_SR stac collections in internal archive

  • Added stac properties:

"satl-qa:dr_blue"
"satl-qa:dr_green"
"satl-qa:dr_nir"
"satl-qa:dr_red"
"satl-qa:alignment_ce95_red"
"satl-qa:alignment_ce95_blue"
"satl:exposure_sec"
"satl:satellite_altitude"

[0.3.0] 2024-07-12

Changed - Change higher percentile in histogram stretching of L3 product to deal with saturation on bright objects

[0.2.0] 2024-04-29

Fixed - Fix Stray light correction for MarkV imagery

Added - Improve sharpness for MarkV imagery

Changed - Change DN conversion to 10 bits

[0.1.0] 2024-04-03

Added - Post to new archive 2.0 L1D and L1D-SR products

  1. Varies with altitude of the satellites and off nadir angle. ↩↩

  2. Varies with terrain and only applicable for terrains with rich features. ↩

Last update: 2024-11-15