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.
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Updated
Dec 3, 2021 - 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
Arduino project on a ESP32 for NO2 measurement sending the data with LoRaWan to TheThingsNetwork.
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.
Australia SA3-level analysis of relationship between child mortality/morbidity and climate conditions/air pollution
Python scripts and Jupyter Notebooks to download and preprocess Sentinel-5P NO2 data.
Website (startpage and map)
Geostatistical modeling of urban air pollutants (NO₂ and PM₁₀) across Los Angeles County using the Hidden Dynamic Geostatistical Model (HDGM) framework implemented in MATLAB with the D-STEM package. Includes full data processing, model fitting, cross-validation, and spatial prediction workflow.
ME975 - Satellite Data Assimilation and Analysis - Assignment 2021/22
This is a COVID-19 Air Pollution tracking program that looks at the correlation between COVID-19 Lockdowns and the overall pollution impact in certain European cities. The program utilses graphs and other visual stats to allow visual representations of significant or minimal difference in pollution levels with as a result to the on going pandemic.
air quality model benchmarking
MICS4514 Breakout board sensor for CO2 and NO2 only 3.3v
Satellite observations showed a negligible reduction in NO2 pollution due to COVID-19 lockdown over Poland
This repository implements Inverse Distance Weighting (IDW) interpolation in R to create prediction surfaces for NO₂, PM₂.₅, and O₃ concentrations.
Some notebooks for [S5P-LNO2](https://github.com/zxdawn/S5P-LNO2).
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