Technical Tutorials
This section of the documentation includes hands-on tutorials with example algorithms and data-sets. It is focused on learning how to use the MAAP platform, and not science-oriented.
Note: Tutorials are written in Python except for those under Working with R. For current documents written in R, please see Working with R.
- Data Processing System (DPS) Tutorial A to Z
- Importing and Installing Packages
- Before Starting
- An Overview of How DPS Works
- Overview of this Tutorial
- Run and Monitor an example Algorithm
- Context within a Typical Workflow
- Clone the Demo Algorithm
- Edit and Test your Code
- Prepare the Algorithm for DPS
- Register the Algorithm with DPS using the Register Algorithm UI
- Running and Monitoring the Algorithm with the Jobs UI
- Running and Monitoring using the HySDS Jobs UI (Figaro)
- Registering and Running the Algorithm using maap.py
- Getting the Outputs of the Job
- Frequently Asked Questions (FAQ)
- Search
- MAAP’s Dual Catalog
- Using the NASA Earthdata Search Client Graphical User Interface
- Searching for Collections in NASA’s Operational CMR using maap-py
- Searching for Granules in NASA’s Operational CMR using maap-py
- Searching the STAC Catalog
- BETA - Collection Discovery: searching for collections across multiple APIs using the Federated Collection Discovery API
- Finding and Accessing Data in R (OpenScapes)
- Visualize
- Access
- Accessing Data from the MAAP
- Accessing Data Provided by NASA’s Distributed Active Archive Centers (DAACs)
- Accessing Cloud Optimized Data
- MAAP AWS Access With Python
- Accessing EDAV Data via Web Coverage Service
- GEDI S3 Bucket Access at LPDAAC (BETA)
- Direct DAAC S3 Bucket Access (BETA)
- Finding and Accessing Data in R (OpenScapes)
- Query
- User Data
- Working with R