FAQ

The User Guides relevant to the Explorer can be found here.

The User Guides relevant to the Explorer can be found here.

The User Guides relevant to the Explorer can be found here.

The Multi-Mission Algorithm and Analysis Platform (MAAP) is an ESA-NASA collaborative project focused on improving the understanding of aboveground terrestrial carbon dynamics.

The MAAP will provide computing capabilities co-located with data as well as a set of tools and algorithms developed to support this specific field of research.

It’s a collaboration framework to share data, science algorithms and compute resources in order to foster and accelerate scientific research conducted by NASA and ESA scientists.

This guide aims to help users get started with using the platform for searching, visualizing, accessing, processing, querying, and sharing biomass relevant data to the MAAP. These data, collected from satellites, aircraft, and ground stations, are organized into collections and granules. Collections are a grouping of files that share the same product specification. Granules are the individual files which are independently described, inventoried, and retrieved within a collection. Granules inherit additional attributes from their containing collection. Explanations of the various functions available in MAAP to use in the ADE will also be explored.

• Enable researchers to easily discover, process, visualize, and analyze large volumes of data from both agencies
• Provide tools and infrastructures to bring data into the same coordinate reference frame to enable comparison, analyze, data evaluation, and data generation
• Provide a version-controlled science algorithm development environment that support tools, co-located data, and processing resources
• Address intellectual property and sharing issues related to collaborative algorithm development and sharing of data and algorithms

The available JupyterLab environments for users belonging to BIOMASS Collaborative Environment are:
• Minimal
• Datascience
• MAAP
• Rtools add-on

The “Minimal” environment is designed to work only with Python. It is recommended for those who do not need other languages, providing a faster configuration and avoiding possible package conflicts.
The “Datascience” environment provides Python, R and Julia, covering a vast range of code operativity.
The “MAAP environment” and “Rtools add-on environment” are designed to handle and process BIOMASS data, with apposite libraries already installed.
The “Rtools add-on” environment has both Python and R kernels installed, while only Python is available within the “MAAP environment”. Once an environment is selected; the workspace will be prepared. Depending on the chosen environment, it can take few seconds to a couple of minutes.

Registered users can download available products; be notified, through a dedicated interface, for products that are not yet available;
access the specific Collaborative Environment workspace through the PAL.