This repository presents a method for optimizing the allocation of air quality monitoring stations using Sentinel-5P images.
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Updated
Jun 24, 2021 - Jupyter Notebook
This repository presents a method for optimizing the allocation of air quality monitoring stations using Sentinel-5P images.
Monitoring nitrogen dioxide levels in North Rhine-Westphalia using data from ESA's Sentinel-5P mission
Contains python notebooks used for clipping of satellite data using Geojson AOI, calculating LST from Landsat 8 Images and Correlation analysis between CO and LST
Impacts of COVID-19 lockdown on Air quality.
A quick list of access points for global air quality data.
Workflow to identify and visualize collocated EnMAP and temporally closest Sentinel-5P TROPOMI acquisitions
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.
Python scripts used to download and process the Sentinel 5P data
Automatic pipeline to download, process, and visualize Sentinel-5P data for pollution monitoring
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.
Sentinel-5P Single-Image Super-Resolution Toolbox
Example of preliminary analysis and data exploration of Sentinel-5P satellite data
Sentinel-5P: Processing and handling NO2 measured values in R
Code repository for "Toward Global Estimation of Ground-Level NO2 Pollution With Deep Learning and Remote Sensing", IEEE TGSRS, 2022
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.
Download and process satellite imagery in JavaScript or TypeScript using Sentinel Hub services.
Sentinel5P_Python
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