(Disclaimer: This project is currently under development.)
Python for RAW Sentinel-2 data (PyRawS) is a powerful open-source Python package that provides a comprehensive set of tools for working with Sentinel-2 Raw data🔬.
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It provides utilities for coarse spatial bands coregistration, geo-referencing, data visualization📊, and image processing🖼️.
The software is demonstrated on the first Sentinel-2 🛰️ Raw database for warm temperature hotspots 🔥 detection/classification, making it an ideal tool for a wide range of applications in remote sensing and earth observation🌍.
The package is written in Python and is open source💻, making it easy to use and modify for your specific needs.
The systme is based on pytorch, which be installed with CUDA support, to enable GPU acceleation.
The use of PyRawS and ideas behind raw data is described in our paper G. Meoni, R. D. Prete, F. Serva, A. De Beusscher, O. Colin and N. Longépé, "Unlocking the Use of Raw Multispectral Earth Observation Imagery for Onboard Artificial Intelligence," in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 17, pp. 12521-12537, 2024, doi: 10.1109/JSTARS.2024.3418891.
Important
NB: What we call raw data in this project are Sentinel-2 data generated by the decompression and metadata addition of Sentinel-2 L0 data. Because of that, with the exception of the effects due to onboard equalization and lossy compression, they are the most similar version of the rawest form of data acquired by the satellite's sensors. Both the compression and equalization are applied onboard the satellite to reduce the amount of data transmitted to the ground station. For easy naming convention, this repo refer to the term "Raw" as the products decompressed with ancillary information appended. For further information browse our paper at https://arxiv.org/abs/2305.11891 ↩
Note
A demo showcasing PyRawS capabilities is available on the YouTube channel of Robin Cole
The PyRawS repository includes the following directories:
| Directory Name | Description |
|---|---|
| quickstart | Contains Jupyter notebooks for quick start: |
| 1. API demonstration: Notebook demonstrating PyRawS API. | |
| 2. DB_creation: Notebook for automatic creation of a database for a target dataset. | |
| 3. geographical_distribution: Notebook to display the geographical distribution of dataset events on a map. | |
| pyraws | Contains PyRawS package with the following subdirectories: |
| 1. database: Various PyRawS and other databases. | |
| 2. raw: Includes Raw_event and Raw_granule classes for modeling Sentinel-2 Raw events and granules. | |
| 3. l1: Contains L1_event and L1_tiles classes for modeling Sentinel-2 L1C events and tiles. | |
| 4. utils: Utilities for the PYRAW package. | |
| resources | Contains various resources, such as images for the README. |
| scripts_and_studies | Contains scripts and code for different studies related to the THRAWS dataset: |
| 1. coregistration_study: Utils for coregistration study and coarse coregistration technique. | |
| 2. dataset_preparation: Scripts and files for designing THRAWS files, including data download and event selection. | |
| 3. hta_detection_algorithms: Custom and simplified implementation of various high-thermal-anomalies-detection algorithms, including those used for designing the THRAWS dataset. | |
| 4. runscripts: Runscripts and utils for cropping Sentinel-2 L1C tiles, generating images, and exporting tif. | |
| 5. granules_filtering: Script for running and mapping cropped Sentinel-2 L1C tiles to corresponding Raw granules. | |
| 6. download_thraws: Utility for downloading the THRAWS dataset from Zenodo. |
Install pyraws referring to the guide in here.
Downloading Sentinel-2 Raw data requires to specify a polygon surrounding the area of interest and a date. Given the pushbroom nature of the Sentinel-2 sensor, bands of data at Raw level do not look at the same area (i.e., they are not registered). Therefore,to be sure to collect all the band around an event (i.e., volcanic eruptions, wildfires) rectangular polygons centered on the events of area 28x10 B02) interesects the polygon area.
The image above shows the footprint of the all the Sentinel-2 Raw granules that are downloaded for the eruption named "Etna_00" in our database by using the white rectangular polygon. We define the collection of Raw granules that are downloaded for each of the rows of our database "Sentinel-2 Raw event".
However, as you can see in the image above, most of the Sentinel-2 Raw granules in Etna_00 Sentinel-2 Raw event do not contain the volcanic eruption (big red spot) of interest (red rectangulars). Indeed, only the yellow and the pink rectangulars intersects or include part of the volcanic eruption.
In addition, the fact that one Raw granule intersects or include one event, this does not mean that the latter interesects or is included in all the bands of that Raw granule. In particular,
since we use the bands [B8A, B11, B12] to detect wildfires and volcanic eruptions, we consider Raw useful granules those granules whose band B8A interesects the event. This is true for the yellow rectangular but not for the pink one (you need to trust us here, since the bands are not displaced in the image above). We take the band B8A only because after the coregistration, the other bands will be moved to match the area of B8A.
Finally, for some Raw useful granules part of the eruptions or the wildfire could extend until the top or the bottom edge of the polygon. In this case, some of the bands could be missing for a portion of the area of interest. To be sure that this is not happening, in addition to the Raw useful granules, it is important to consider Raw complementary granules, which fills the missing part of the interest bands of the Raw useful granules.
For each Sentinel-2 Raw event, the THRAWS dataset clearly states those Raw granules that are Raw useful granules or Raw complementary granules. However, the entire Raw granules collection is provided for each Raw event to permit users that wants to use other bands to detect warm temeprature anomalies to do it.
The PyRawS project is open to contributions. To discuss new ideas and applications, please, reach us via email (please, refer to Contacts). To report a bug or request a new feature, please, open an issue to report a bug or to request a new feature.
If you want to contribute, please proceed as follow:
- Fork the Project
- Create your Feature Branch (
git checkout -b feature/NewFeature) - Commit your Changes (
git commit -m 'Create NewFeature') - Push to the Branch (
git push origin feature/NewFeature) - Open a Pull Request
Distributed under the Apache License.
Created by the European Space Agency
- Gabriele Meoni - gabriele.meoni@esa.int
- Roberto Del Prete - roberto.delprete at ext.esa.int and unina.it
- Nicolas Longepe - nicolas.longepe at esa.int
- Federico Serva - federico.serva at ext.esa.int
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Lightweight spatial coregistration method optimized for onboard-satellite applications. It simply shifts the various bands of a fixed factor that depends only on the bands, the satellite and detector number.
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Sentinel-2 data at
level-0(L0) are data that are transmitted to Ground from Sentinel-2 satellites. TheL0format is compressed to diminish downlink bandwidth requirements. For more information, refer to the Sentinel-2 Products Specification Document -
In the frame of this project, the Sentinel-2 Raw represents a particular product in the Sentinel-2 processing chain that matches a decompressed version of Sentinel-2 L0 data with additional metadata that are produced on ground. Once decompressed,
Sentinel-2 Raw dataare the data available on Ground that better emulate the one produced by Sentinel-2 detectors with the exception of the effects due to compression and onboard equalization, which are not compensated at this stage. Therefore,Sentinel-2 raw dataare those exploited in this project. For more information, refer to the Sentinel-2 Products Specification Document.
N.B: the nomenclatureraw dataand its location in the Sentinel-2 processing chain is specific for this project only. -
A
granuleis the image acquired by a Sentinel-2 detector during a single acquisition lasting 3.6 s. Granules are defined at L0 level. However, since the processing perfomed on the ground between L0 and raw data does not alter the image content (with the exception of the decompression process) but just provide additional metadata, granules are defined also at Sentinel-2 Raw level. Given the pushbroom nature of the Sentinel-2 sensor, bands do not look at the same area at Raw level. For more information, refer to the Sentinel-2 Products Specification Document -
Sentinel-2 Raw data are produced by decompressing Sentinel-2 L0 data. To download L0 data, it is necessary to specify one polygon that surrounds a particular area-of-interest. This leads to download all those Sentinel-2 Raw granules whose reference band intersects the specified polygon. Such collection is a
Raw-event. EachRaw-eventmatches one of theID_evententry of the database.
For eachRaw-event, we do not provide all the collection of Sentinel-2 Raw granules, but only the set of Raw data useful granules and Raw data complementary granules. For an intuitive example, please, check Raw events and granules. -
The
Level 1-C(L1C) is one format forSentinel-2data. To convert Sentinel-2 Raw data toL1Cdata, numerous processing steps are applied to correct defects, including bands coregistration, ortho-rectification, decompression, noise-suppression and other. For more information, refer to the Sentinel-2 Products Specification Document. -
Same concept for Sentinel-2 Raw events but applied on Sentinel-2 L1C data.
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The
Sentinel-2 L1C tileis the minimumL1Cproduct that can be downloaded. -
Given a certain set of bands of interest
[Bx,By,...,Bz],Raw complementarey granulesare the granules adjacents at Raw-useful-granules that that can be used to fill missing pixels of[By,...,Bz]bands due to their coregistration with respecto the bandBx. For an intuitive example, please, check Raw events and granules. -
Given a certain set of bands of interest
[Bx,By,...,Bz], whereBxis the first band in the set, anRaw useful granuleis one of the collection of Sentinel-2 Raw granules that compose a Sentinel-2 Raw event whose bandBxinclude (or intersects) a certain area of interest (e.g., an eruption or an area covered by a fire). For an intuitive example, please, check Raw data events and granules.