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

提供AERONET AOD SSA FMF等数据，以及PARASOL HDF和哨兵五号SENTINEL-5数据下载连接的批量获取。

This Python script automates the retrieval and visualization of tropospheric NO2 data from Sentinel-5P satellite's TROPOMI instrument, enabling efficient monitoring of atmospheric pollution patterns through automated data processing and visualization.

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.

Impacts of COVID-19 lockdown on Air quality.

Monitoring nitrogen dioxide levels in North Rhine-Westphalia using data from ESA's Sentinel-5P mission

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)