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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.
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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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ASTER Level 2 Surface Kinetic Temperature (AST_08) over Kīlauea Crater, Hawaii, acquired on 2025-08-09 at 07:30:32 UTC. The image shows a semi-transparent thermal overlay on an Esri satellite basemap. A concentrated hotspot of temperatures exceeding 100°C is visible near the center of the crater floor, displayed in deep red, surrounded by a gradient of orange and yellow tones indicating elevated but cooler surface temperatures. The surrounding terrain shows ambient temperatures near 0°C. The spatial ex

Exploring AST 08 Surface Kinetic Temperature

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
False‑color composite (ASTER bands 4, 6, and 8) of Railroad Valley, Nevada, showing a bright, irregular salt‑flat basin surrounded by dark, rugged mountain terrain.

Exploring ASTER L1T Radiance

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
A map of the GLanCE30 Land Cover for the Waubay National Wildlife Refuge in northeast South Dakota on 2002-07-01. The map shows water in blue and herbaceous in tan color which cover the majority of this region. The are smaller patches shown in red which are developed area.

Get Started with GLanCE30

This Jupyter Notebook shows users how to find and access Global Land Cover Mapping and Estimation Yearly 30 meter (GLanCE30) data.
External Resource
Jupyter Notebook
July 23, 2025
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