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LP DAAC Learning Resources

Explore webinars, trainings, tutorials, and other learning resources from NASA’s Land Processes Distributed Active Archive Center (LP DAAC). Learn how to discover, access, process, and apply Earth science data from platforms and instruments such as MODIS, ASTER, VIIRS, GEDI, ECOSTRESS, EMIT, and HLS.

LP DAAC maintains a collection of dataset and topic-specific GitHub repositories that include step-by-step tutorials, scripts, guides, and example workflows for getting started with LP DAAC data. Users can browse available resources in the LP DAAC Data Resources GitHub repository, which serves as a central hub and provides links to additional LP DAAC–maintained GitHub repositories for specific datasets and topics. 

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This tutorial will demonstrate how to preprocess the EMIT and PACE reflectance data so that they can be used together to investigate science questions. Using the emit_tools and pace_tools modules, the data are orthorectified, geolocated, merged where needed, and resampled onto a common grid, enabling direct comparison of observations from the two sensors.
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Jupyter Notebook
July 14, 2026
This tutorial demonstrates how to find colocated EMIT and PACE Ocean Color Instrument (OCI) granules using the earthaccess Python library.
External Resource
Jupyter Notebook
July 14, 2026
This Jupyter Notebook shows users how to find, access, process and display ASTER Level-2 Surface Kinetic Temperature (AST_08) data.
External Resource
Jupyter Notebook
May 14, 2026
This Jupyter Notebook shows users how to find and access ASTER Level-1 Precision Terrain Corrected Registered at Sensor Radiance (AST_L1T) data.
External Resource
Jupyter Notebook
May 8, 2026
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