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Want to learn more about working with remote sensing data using R or Python? This webinar will provide information and live demonstrations using both of these freely available software programs to work with land remote sensing data sets such as Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Visible Infrared Imaging Radiometer Suite (VIIRS), and Moderate Resolution Imaging Spectroradiometer (MODIS), which are archived at NASA’s Land Processes Distributed Active Archive Center (LP DAAC).

During this webinar we will demonstrate how to bring remote sensing datasets into R and Python, read metadata to georeference data, and export the data in GeoTIFF format. Demonstrations for converting digital numbers to Top of Atmosphere reflectance, calculating Normalized Difference Vegetation Index (NDVI), generating three-band RGB composites, and using quality services to filter MODIS data will be performed. The webinar will also highlight useful operations such as extracting a subset of data, computing statistics, plotting, and visualizing the data in R and Python.

Audience: This webinar is geared towards users that are new to using Python and R with remote sensing data.

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LP DAAC