High-resolution air quality data is helpful for monitoring urban air pollution. In this training led by NASA's Applied Remote Sensing Training program (ARSET), participants learned how to use Python scripts to map and analyze air quality data through hands-on exercises. The training covered Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth data and Ozone Monitoring Instrument (OMI) NO2 and SO2 data.
By the end of the training, attendees will be able to:
This training is primarily intended for air quality professionals and decision makers from local, state, and federal agencies, non-governmental organizations (NGOs), and the private sector. Governmental and NGOs engaged in air quality monitoring will be given preference over organizations focused primarily on research.
Wednesday, Jan. 17, 2018
Part 1 is an introduction to relevant datasets (basics, advantages, and limitations) and instruction on how to download data.
Friday, Jan. 19, 2018
Part 2 includes hands-on exercises using Python scripts to read, map, and analyze Level 2 MODIS aerosol optical depth (AOD) data.
Part 3 includes hands-on exercises using Python scripts to read, map, and analyze OMI NO2 and SO2 data.
(2018). ARSET - Data Analysis Tools for High Resolution Air Quality Satellite Datasets. NASA Applied Remote Sensing Training Program (ARSET). https://www.earthdata.nasa.gov/learn/trainings/data-analysis-tools-high-resolution-air-quality-satellite-datasets.