Skip to content

Ortho (L1D/L1D_SR)


Product description

The L1 and L1_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 corretion process

Technical Specifications


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


1m (L1) / 0.7m for (L1_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.


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

Product presentation

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

  • L1 TOA Reflectance (L1)
  • L1 TOA Reflectance SuperResolution (L1_SR)

L1, 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. L1 TOA has a resolution of 1m after resampling, which harmonises native pixel size that varies between 0.7m and 1.3m.

L1_SR_, 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 L1 and L1_SR products are currently delivered along with a corresponding VISUAL Products called L3 and L3 SR. 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


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.


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.


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:


The date is in UTC time observed at the centre of image, the product level correspond to the level of processing. For example, “L1”=Reflectance (TOA) 4 Bands, “L3”=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>_L1_SR_MS_cloud_mask.vrt
├── <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1_SR_MS_footprint.kml
├── <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1_SR_MS_metadata_iso.xml
├── <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1_SR_MS_metadata_stac.geojson
├── <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1_SR_MS_solar_and_viewing_angles.geojson
├── <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1_SR_MS_toa_factors.json
├── <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L3_SR_MS_thumbnail.png
└── rasters
    ├── <DATE>_<TIME>_SN<SATELLITE_NUMBER>_L1_SR_MS_cloud_mask_<N>.tif
File Description
*_L1_SR_MS.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.
*_L1_SR_cloud_mask.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.
*_L1_SR_MS_footprint.kml The overal raster ground footprint in KML
*_L1_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.
*_L1_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.
*_L1_SR_MS_toa_factors.geojson A Geojson file that contains the coefficients to transform the TOA product into Radiance units.
*_L1_SR_MS_solar_and_viewing_angles.geojson A Geojson file that contains extra metadata about the sun and viewing angles.
*_L3_SR_MS.vrt A GDAL Virtual raster that contains all the corresponding VISUAL L3 TIFs in the rasters folder. In case of very big images, mutliple tifs can be included in the package.
*_L3_SR_MS_preview.png The preview component of the product for the entire scene
*_L3_SR_MS_thumbnail.png A low resolution thumbnail of the scene
rasters/*L1_SR_MS.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/*L3_SR_MS.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/*L1_SR_MS_cloud_mask.tif The cloud mask raster files


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.


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:extensionOnLineResource string Internet location (address) for on-line access
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:spatialResolution_equivalentScale_denominator integer The scale of a map expressed as a fraction which relates unit distance on the map, measured in the same units, on the ground
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:

Item Type Properties
title string The title describing the dataset
description string Scene set identification (scene set id)
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
proj:centroid [number] Coordinates of the center point of the dataset in latitude/longitude
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
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

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.

Known issues

This section lists product anomalies which sometimes elude the automatic quality assurance criteria, distinguishing those correctable by repeating the image processing steps with different configurations, and those uncorrectable or needing further analysis / pipeline improvements. The most common and best known features are listed in this section.

Color artifacts due to image compositing

Some images can show sharp intensity steps between two adjacent frames when composited together. This usually corresponds to a difference of 3% or less between the mean brightness levels of the frames in the overlapping area. In flat and homogeneous targets, such as oceans and deserts, as well as in clouds, this can appear visually noticeable.

Example of tonal differences (compositing artifact) between adjacent frames, mostly noticeable in homogeneous targets, such as water.

The following image shows an example of an uncorrected compositing artifact in a RGB image.

Example of uncorrected compositing artifact in a RGB image, inferring to the image a violet shade in alternate bands along the track direction.

Payload artifacts in saturated images

In the areas of frames with very high reflectance values, such as bright clouds or snow, the raw frame value can saturate. The flat-field (gain) correction cannot work because of non-linearity in these saturated areas. As a consequence the final products most likely present payload artifacts, such as sensor defects, pixel response non-uniformity (PRNU) and undesired dust particles on the filter, and processing artifacts such as color bands. In the future, the pixels affected by saturation will be masked.

Example of a target with very high reflectance: a field entirely covered by snow. The target is overexposed and the image cannot be corrected by the flat-field frame. The result is that the payload artifacts are not corrected (notice the high frequency parallel lines and the donut-like shapes due to dust on the filter). Additionally, big tonal differences between adjacent frames create strong color artifacts which cannot be corrected.

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.

Flipped pixel values visible in saturated areas of RGB composites.

Reduced geo-accuracy

Some terrain types and environmental conditions might cause the GCP-based geometric correction to fail, producing captures of lower geo-accuracy (with overall inaccuracy larger than 10 m). Such products are marked as a low quality tier and not delivered to customers which require mappable data. However, some cases may elude the automatic quality assurance and require further processing after data delivery. Some examples are provided below.

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.


[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: 2024-07-12