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Python script downloading NO2 pollution datas from the European satellite Sentinel5 and aggregating by country, regions, states, cities. This work is carried out within the framework of the juanporrasl/AMSECovid19 project.

License: MIT License

Python 25.74% Jupyter Notebook 74.26%
esa pollution no2 satelite sentinel5 sentinel5-no2 python

sentinel5_no2's Introduction

Sentinel5_NO2 V2

Downloading, cleaning and aggregation of NO2 (Nitrogen Dioxide) datas from the European satellite Sentinel5. This work is being carried out as part of the AMSECovid19 project.

DOWNLOAD AVAILABLE HERE : https://drive.google.com/drive/folders/1fJWwxo8MXBL7DKDqvwYQVlYa2W7g0TpQ?usp=sharing

MAJOR UPDATE : Complete overhaul of the file structure. Addition of a powerful logging system and a progressbar. Optimization of the code.

Increase of ~30-50% in file size and processing time, with the benefit of less RAM required and new information essential for data processing: Wind angle, surface altitude, number of observations, snow/ice flag, soil classification, quality decreased to > 0.5, surface pressure...

Change of the data source: ONDA DIAS imposed a restrictive archiving system. We now use CREODIAS.

Project Organization

├── LICENSE
├── README.md          <- The top-level README for developers using this project.
│
├── datas_sentinel5    <- You have to look here if you are only interested in downloading the data.
│   ├─ archives_old        <- Previous version of archived files
│   ├─ archives            <- File in which the files are recorded and definitively processed
│   ├─ cleaned             <- Folder where cleaned, non-aggregated records are temporarily stored.
│   ├─ csv                 <- Data file extracted from the ONDA DIAS API to obtain the links to
│   │                         download the files.
│   └─ tracking_files.csv  <- Automatically generated file, allows you to record the days processed,
│                             with the number of files downloaded. This makes it possible to detect
│                             the presence of new files for a day that has already been downloaded.
│
├── get_sentinel5_V2.ipynb <- Notebook to get datas. Not available.
│
└── requirements.txt   <- The requirements file for reproducing the analysis environment, e.g.
                          generated with `pip freeze > requirements.txt`

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