Sentinel-3 SLSTR L1B
SENTINEL-3 is a European wide-swath, medium-resolution, multi-spectral imaging mission designed to monitor ocean surface topography as well as land and sea surface temperature. The satellite hosts four instruments: the Sea and Land Surface Temperature Radiometer (SLSTR), the Ocean and Land Colour Instrument (OLCI), a Sar Radar Altimeter (SRAL) and a Microwave Radiometer (MWR). Sentinel-3A was launched on 16 February 2016 and its twin Sentinel-3B on 25 April 2018.
The SLSTR instrument was designed to provide data continuity with the Advanced Along Track Scanning Radiometer (AATSR) instrument flown on Envisat. The main objective of the instrument is to provide global sea surface temperature measurements with zero bias and uncertainties of ± 0.3 K, as well as land surface temperature readings and fire monitoring.
SLSTR has an along-track dual view scanning technique, enabling acquisitions at nadir and along-track in the backward direction, which include measurements of two blackbody calibration targets and a Visible Calibration Unit for high accuracy. The radiometer has 9 channels ranging from the visible and near-infrared (VNIR) to the thermal infrared (TIR). Two additional bands (active fire bands) in the TIR are optimised for fire monitoring with an increased dynamic range to prevent saturation. In single-view mode, SLSTR has a spatial resolution of 1 km, with less than half a day revisit time (with Sentinel-3 A and B) and a swath of 1400 km. In dual-view mode, a 500m resolution is reached, but only covering a swath of 744 Kilometers and with a daily revisit time.
Level 1B provides calibrated and ortho-geolocated Top Of Atmosphere (TOA) radiances for the 6 VNIR/SWIR bands (S1 to S6) and TOA brightness temperatures for the thermal IR and fire channels (S7 to S9 and F1, F2).
|Spatial resolution||500 m or 1 km per pixel|
|Sensor||Sea and Land Surface Temperature Radiometer (SLSTR), 11 bands: 3 VNIR bands, 3 SWIR bands, 5 thermal IR bands.|
|Units||Radiance: mW.m-2.sr-1.nm-1 (Note that Sentinel Hub returns reflectance) / Brightness temperature: K.|
|Revisit time||< 0.9 days at the equator with 2 satellites|
|Spatial coverage||Land and coastal areas where the solar zenith angle < 80º|
|Data availability||Since May 2016|
|Measurement||Top of the atmosphere (TOA) radiance and brightness temperature|
|Common usage/purpose||Climate change monitoring, vegetation monitoring, active fire detection, land and sea surface temperature monitoring.|
For processing Sentinel-3 SLSTR we use tie point grids from the SLSTR L1B products for geolocation. These are lower resolution than the full pixel grid so pixel positioning is less precise than exact. Unfortunately the exact grid is broken and cannot be used. Note, however, that with the lower resolution of SLSTR this method still offers reasonably precise geolocation accuracy.
EU law grants free access to Copernicus Sentinel Data and Service Information for the purpose of the following use in so far as it is lawful: a) reproduction; b) distribution; c) communication to the public; d) adaptation, modification and combination with other data and information; e) any combination of points a to d.
Tracing based on Sentinel imagery is allowed for commercial purposes as well.
Acknowledgment or credit: Contains modified Copernicus Sentinel data [Year] processed by Sentinel Hub.
To access data you need to send a POST request to our
process API. The requested data will be returned as the response to your request. Each POST request can be tailored to get you exactly the data you require. To do this requires setting various parameters which depend on the datasource you are querying. This chapter will help you understand the parameters for S3SLSTR data. To see examples of such requests go here, and for an overview of all API parameters see the API Reference.
|creodias.sentinel-hub.com/api/||Global since May 2016|
|code-de.sentinel-hub.com/api/||Germany since May 2016|
S3SLSTR) as the value of the
input.data.type parameter in your API requests. This is mandatory and will ensure you get Sentinel-3 SLSTR L1B data.
This chapter will explain the
input.data.dataFilter object of the
Sets the order of overlapping tiles from which the output result is mosaicked. The tiling is based on ESA's Product Dissemination Units for easier distribution.
|mostRecent||the pixel will be selected from the most recently acquired tile||If there are multiple products with the same timestamp then NTC will be used over NRT.|
|leastRecent||the pixel will be selected from the oldest acquired tile||If there are multiple products with the same timestamp then NTC will be used over NRT.|
|leastCC||pixel is selected from tile with the least cloud coverage metadata||Note that "per tile" information is used here.|
Filters the acquisition orbit direction.
|ASCENDING||the pixel will be selected from the ascending node.||Default value.|
|DESCENDING||the pixel will be selected from the descending node.|
Filters the acquisition by view.
|NADIR||the image acquired by the nadir viewing scanner will be selected.||Default value.|
|OBLIQUE||the image acquired by the oblique (rear) viewing scanner will be selected.|
This chapter will explain the
input.data.processing object of the
|upsampling||Defines the interpolation used for processing when the pixel resolution is greater than the source resolution (e.g. 100m/px with a 500m/px source).||NEAREST - nearest neighbour interpolation |
BILINEAR - bilinear interpolation
BICUBIC - bicubic interpolation
|downsampling||Defines the interpolation used for processing when the pixel resolution is lower than the source resolution (e.g. 800m/px with a 500m/px source).||NEAREST - nearest neighbour interpolation |
BILINEAR - bilinear interpolation
BICUBIC - bicubic interpolation
This chapter will explain the bands and data which can be set in the evalscript input object:
Any string listed in the column Name can be an element of the
input.bands array in your evalscript.
|Name||Description||Wavelength centre (nm)||Resolution (m/px)|
|S1||Cloud screening, vegetation monitoring, aerosol||554.27||500|
|S2||NDVI, vegetation monitoring, aerosol||659.47||500|
|S3||NDVI, cloud flagging, pixel co-registration||868||500|
|S4||Cirrus detection over land||1374.80||500|
|S5||Cloud clearing, ice, snow, vegetation monitoring||1613.40||500|
|S6||Vegetation state and cloud clearing||2255.70||500|
|S7||SST, LST, Active fire||3742||1000|
|S8||SST, LST, Active fire||10854||1000|
|dataMask||The mask of data/no data pixels (more).||N/A*||N/A**|
*dataMask has no wavelength information, as it carries only boolean information on whether a pixel has data or not. See the chapter on Units for more.
**dataMask has no source resolution as it is calculated for each output pixel.
For more about Sentinel-3 SLSTR bands, visit this ESA website.
The data values for each band in your custom script are presented in the units as specified here. In case more than one unit is available for a given band, you may optionally set the value of
input.units in your evalscript
setup function to one of the values in the
Sentinel Hub Units column. Doing so will present data in that unit. The Sentinel Hub
units parameter combines the physical quantity and corresponding units of measurement values. As such, some names more closely resemble physical quantities, others resemble units of measurement.
Source Format specifies how and with what precision the digital numbers (
DN) from which the unit is derived are encoded. Bands requested in
DN units contain exactly the pixel values of the source data. Note that resampling may produce interpolated values.
DN is also used whenever a band is derived computationally (like dataMask); such bands can be identified by having
DN units and
N/A source format.
DN values are typically not offered if they do not simply represent any physical quantity, in particular, when
DN values require source-specific (i.e. non-global) conversion to physical quantities.
Values in non-
DN units are computed from the source (
DN) values with at least float32 precision. Note that the conversion might be nonlinear, therefore the full value range and quantization step size of such a band can be hard to predict. Band values in evalscripts always behave as floating point numbers, regardless of the actual precision.
Typical Range indicates what values are common for a given band and unit, however outliers can be expected.
|Band||Physical Quantity (units)||Sentinel Hub Units||Source Format||Typical Range||Notes|
S1 - S6
|Reflectance (unitless)||REFLECTANCE||UINT16||0 - 0.4||Higher values in infrared bands. Reflectance values can easily be above 1.|
|Thermal infrared bands |
S7 - F2
|Brightness temperature (kelvin)||BRIGHTNESS_TEMPERATURE||UINT16||250 - 320||Roughly -20 to +50 C. Can reach outside this range in extreme environments.|
|dataMask||N/A||DN||N/A||0 - no data|
1 - data
All mosaicking types are supported.
scenes object stores metadata. An example of metadata available in
scenes object for Sentinel-3 SLSTR when mosaicking is
Properties of a
scenes object can differ depending on the selected mosaicking and in which evalscript function the object is accessed. Working with metadata in evalscript user guide explains all details and provides examples.
To access Sentinel 3 SLSTR product metadata you need to send search request to our Catalog API. The requested metadata will be returned as JSON formatted response to your request.
|creodias.sentinel-hub.com/api/v1/catalog/collections/sentinel-3-slstr/||Global since May 2016|
|code-de.sentinel-hub.com/api/v1/catalog/collections/sentinel-3-slstr/||Germany since May 2016|
eo:cloud_covercloud cover percentage
eo:gsdground sample distance (resolution)