Python scripts to download and preprocess air pollution concentration level data aquired from the Sentinel-5P mission
Download and process satellite imagery in JavaScript or TypeScript using Sentinel Hub services.
Sentinel5P_Python
Estimation of Air Pollution with Remote Sensing Data: Revealing Greenhouse Gas Emissions from Space, presented at Tackling Climate Change with Machine Learning workshop at ICML 2021.
Code repository for "Toward Global Estimation of Ground-Level NO2 Pollution With Deep Learning and Remote Sensing", IEEE TGSRS, 2022
Exploring the effect of COVID-19 in air pollution by using satellite data, with the sentinelsat and cartopy libraries.
Python scripts and Jupyter Notebooks to download and preprocess Sentinel-5P NO2 data.
Automatic pipeline to download, process, and visualize Sentinel-5P data for pollution monitoring
Example of preliminary analysis and data exploration of Sentinel-5P satellite data
Sentinel-5P: Processing and handling NO2 measured values in R
Sentinel-5P Single-Image Super-Resolution Toolbox
Another Sentinel-5 Precursor data query and downloader tool with automation for daily downloads and a ReactJS app that can visualise the data on a map.
Monitoring nitrogen dioxide levels in North Rhine-Westphalia using data from ESA's Sentinel-5P mission
Impacts of COVID-19 lockdown on Air quality.
Workflow to identify and visualize collocated EnMAP and temporally closest Sentinel-5P TROPOMI acquisitions
This repository presents a method for optimizing the allocation of air quality monitoring stations using Sentinel-5P images.
Air Pollution Analysis of NO₂ Levels in India (2020-2024)
Python scripts used to download and process the Sentinel 5P data
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