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‎README.md

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@@ -16,7 +16,7 @@ The package is written in Python and is open source💻, making it easy to use a
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The systme is based on [pytorch]("https://pytorch.org/"), which be installed with `CUDA` support, to enable GPU acceleation.
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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 <a href="#fnref:1" class="reversefootnote">&#8617;</a></li>
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> 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 <a href="#fnref:1" class="reversefootnote">&#8617;</a></li>
2020
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*(Disclaimer: This project is currently under development.)*
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Every [raw data](#sentinel-2-decompressed-raw-data) and [L1C](#sentinel-2-l1c-data) data shall be contained in a specific subdirectory --placed in `raw`or `l1c`-- whose name shall match one of the **ID_event** entries of the **.csv** file, located in `database` directory.
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## PyRawS databases
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## PyRawS Database Structure
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To create the "THRAWS" database, the user should refer to the notebook called "database_creation.ipynb". This notebook contains the necessary code and instructions for creating the database. Simply follow the steps outlined in the notebook to successfully create the "THRAWS" database.
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> [!IMPORTANT]
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> In case you want to create your own database of event for your target aplication, the user should refer to the notebook called "database_creation.ipynb". This notebook contains the necessary code and instructions for creating the database. Simply follow the steps outlined in the notebook to successfully create something similar to the "THRAWS" database.
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> [!WARNING]
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> Additionally, make sure that all required dependencies and packages are installed before running the code in the notebook. Please note that it is important to carefully follow the instructions in the notebook to ensure that a database is created correctly and without errors.
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This respository contains an example of database (`THRAWS`) that is used by PyRawS to read and process [Sentinel-2 Raw data](#sentinel-2-raw-data) and [Sentinel-2 L1 data](#sentinel-2-l1-data) correctly. The minimal fields of the database include:
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| ID_event | Start | End | Sat | Coords (Lat, Lon) | class | Raw_useful_granules | Raw_complementary_granules | Polygon_square | Raw_files | l1c_files | bbox_list | bbox_list_merged | Polygon |
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|-----------------------|-------------|-------------------|-----|----------------------|----------|---------------------|----------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------|--------------------------------------------|-------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
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| Barren_Island_00 | 28/09/2018 | 28/09/2018 23:59 | S2A | (12.28474241, 93.86212046) | eruption | [2] | [4] | POLYGON ((93.82076157486179 12.244061101857305, 93.8207488665122 12.325417348895849, 93.9034920534878 12.325417348895849, 93.90347934513821 12.244061101857305, 93.82076157486179 12.244061101857305)) | ['S2A_OPER_MSI_L0__GR_EPAE_20180929T132957_S20180928T042450_D10_N02.06', 'S2A_OPER_MSI_L0__GR_EPAE_20180929T132957_S20180928T042453_D09_N02.06', 'S2A_OPER_MSI_L0__GR_EPAE_20180929T132957_S20180928T042453_D10_N02.06', 'S2A_OPER_MSI_L0__GR_EPAE_20180929T132957_S20180928T042457_D09_N02.06', 'S2A_OPER_MSI_L0__GR_EPAE_20180929T132957_S20180928T042457_D10_N02.06'] | ['S2A_MSIL1C_20180928T040541_N0206_R047_T46PEU_20180929T135308'] | {2: [[[403, 290], [427, 284], [435, 316], [410, 322]]]} | {2: [[[403, 290], [427, 284], [435, 316], [410, 322], [403, 290]]]} | POLYGON((93.81618097217948 12.158183811523221, 93.81613704194822 12.411292126632908, 93.90810387805179 12.41129212663291, 93.90805994782052 12.158183811523221, 93.81618097217948 12.158183811523221)) |
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| Barren_Island_01 | 28/10/2018 | 28/10/2018 23:59 | S2A | (12.28474241, 93.86212046) | eruption | [2] | [4] | POLYGON ((93.82076157486179 12.244061101857305, 93.8207488665122 12.325417348895849, 93.9034920534878 12.325417348895849, 93.90347934513821 12.244061101857305, 93.82076157486179 12.244061101857305)) | ['S2A_OPER_MSI_L0__GR_EPAE_20181028T064658_S20181028T042451_D10_N02.06', 'S2A_OPER_MSI_L0__GR_EPAE_20181028T064658_S20181028T042455_D09_N02.06', 'S2A_OPER_MSI_L0__GR_EPAE_20181028T064658_S20181028T042455_D10_N02.06', 'S2A_OPER_MSI_L0__GR_EPAE_20181028T064658_S20181028T042458_D09_N02.06', 'S2A_OPER_MSI_L0__GR_EPAE_20181028T064658_S20181028T042458_D10_N02.06'] | ['S2A_MSIL1C_20181028T040851_N0206_R047_T46PEU_20181028T070450'] | {2: [[[391, 59], [412, 54], [418,
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Please note that it is important to carefully follow the instructions in the notebook to ensure that the database is created correctly and without errors. Additionally, make sure that all required dependencies and packages are installed before running the code in the notebook.
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![Alt Text](resources/images/database_structure.png) <!-- Leave two free lines below -->
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This respository contains an example of database (`THRAWS`) that is used by PyRawS to read and process [Sentinel-2 Raw data](#sentinel-2-raw-data) and [Sentinel-2 L1 data](#sentinel-2-l1-data) correctly. The minimal fields of the database include:
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* **ID_event**: ID of the event (e.g., volcanic-eruption, wildfire, not-event). All the other fields of the row are referred to that `Sentinel-2` acquisition.
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* **class**: class of the event (e.g., eruption, fire, not-event). Leave it **empty**

‎resources/images/etna_00_granules.png

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