Introduction
The Sentinel-5P mission aims to perform atmospheric measurements with high spatio-temporal resolution. The Sentinel-5P Level 3 images are clipped, converted to Cloud Optimized GeoTIFF and used for air quality studies, climate monitoring or forecasting. The Sentinel-5P Level 3 images are acquired by the satellite sensor Sentinel-5P anywhere on the globe and are available starting with 2018.
Technical Information
Compatible blocks
Compatible blocks |
---|
Export Data (Raster) |
Time Series Image Statistics |
Geographic Coverage
The geographic coverage is global.
Dataset Information
Specifications | Description |
---|---|
Data Provider | AWS |
Instrument | Tropospheric Monitoring Instrument (TROPOMI) |
Image Type | Optical (wavelength bands range between ultraviolet and shortwave infrared) |
Measurements | Air quality (sulfur dioxide, carbon monoxide etc.) Ozone & UV radiation Climate monitoring Climate forecasting |
Processing Levels | L3 |
Spatial Resolutions | Min: 7 x 3.5 sq. km. |
Revisit Frequency | Daily |
Data Availability | Since July 2018 |
File Format | Cloud Optimized GeoTIFF |
Clip to Geometry | Yes |
Bit Depth | 32-bit float per pixel |
Coordinate System | WGS84 (EPSG 4326) |
Can be reused in an UP42 workflow | No |
Product Types
Layer | Description |
---|---|
L3__AER_AI | UV Aerosol Index Daily composites (averages) |
L3__CH4___ | Methane (CH4) total column Daily composites (averages) |
L3__CLOUD_ | Cloud fraction, top pressure Daily composites (averages) |
L3__CO____ | Carbon Monoxide (CO) total column Daily composites (averages) |
L3__HCHO__ | Formaldehyde (HCHO) total column Daily composites (averages) |
L3__NO2___ | Nitrogen Dioxide (NO2) Daily composites (averages) |
L3__O3____ | Ozone (O3) total column Daily composites (averages) |
L3__SO2___ | Sulphur Dioxide (SO2) total column Daily composites (averages) |
The image metadata is returned by the Sentinel-5P Pre-Operations Data Hub.
Limitations
This data block does not support test queries or quicklooks.
This data block provides one image per day for a given interval.
How it works
Supported JSON parameters | Default value | Min | Max | Examples |
---|---|---|---|---|
time | "2020-05-01T00:00:00+00:00/2021-12-31T23:59:59+00:00" | 01.07.2018 | Present | "time": "2018-11-01T00:00:00+00:00/2018-11-30T23:59:59+00:00" |
layer | "" | n.a. | n.a. | "layer": "L3__NO2___" |
qa_mask | "nomask" | n.a. | n.a. | "qa_mask": "mask75" |
geojson_url | null | n.a. | n.a. | "geojson_url": "https://gist.githubusercontent.com/up42-epicycles/first_workflow_aoi.geojson" |
fail_on_missing | false | n.a. | n.a. | "fail_on_missing": false |
bbox /contains /intersects | null | n.a. | n.a. | Please check the examples from the job parameters. |
If you provide a URL to a GeoJSON that contains multiple geometries, the output is generated per geometry and then organized in sub-folders (per geometry feature).
Examples
Example based on a workflow created with the data block Sentinel-5P Level-3 (GeoTIFF) and the processing block Time Series Image Statistics:
Capabilities
Output
raster
custom | |
---|---|
band | [
"L3__AER_AI",
"L3__CH4___",
"L3__CLOUD_",
"L3__CO____",
"L3__HCHO__",
"L3__NO2___",
"L3__O3____",
"L3__SO2___"
] |
up42_standard | |
---|---|
dtype | float |
format | GTiff |
sensor | Sentinel5P |
resolution | 3500 |
processing_level | l3 |
For more information, please refer to the marketplace.