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), with color enhancement algorithm (histogram stretching) has been applied to enhance the visual quality of the image.

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:

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 in 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	5,70
satl-qa:geoaccuracy_rmse	Root mean square error geoaccuracy	3,77
satl-qa:alignment_ce95_red	Band alignment percentile 95 red band	0,52
satl-qa:alignment_ce95_blue	Band alignment percentile 95 blue band	0,71
satl-qa:snr_red	Signal to noise rastio for red band	25.56
satl-qa:snr_blue	Signal to noise rastio for blue band	30.87
satl-qa:snr_green	Signal to noise rastio for green band	32.56
satl-qa:snr_nir	Signal to noise rastio for nir band	35.72
satl-qa:dr_red	Dynamic range rastio for red band	60.56
satl-qa:dr_blue	Dynamic range to noise rastio for blue band	35.36
satl-qa:dr_green	Dynamic range to noise rastio for green band	40.56
satl-qa:dr_nir	Dynamic range to noise rastio for nir band	65.56
satl-qa:cc_red	Colorcast red band	1.3
satl-qa:cc_blue	Colorcast blue band	1.2
satl-qa:cc_green	Colorcast green band	1.4
satl-qa:cc_nir	Colorcast nir band	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

[1.0.1] 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

Varies with altitude of the satellites and off nadir angle. ↩↩
Varies with terrain and only applicable for terrains with rich features. ↩

Last update: 2024-10-15