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Welcome to the APEx demo portal!


This portal provides access to a suite of APEx services that support the discovery, processing, and analysis of Earth Observation (EO) data. Through APEx, you can seamlessly explore datasets, develop and test algorithms, and integrate results into operational workflows.

Introduction

Welcome to the Demo Portal, your gateway to a customizable project working environment, enabled by the APEx framework. This portal serves as a central hub where you can access the different APEx services and explore geospatial data, run processing workflows, develop algorithms, and collaborate with other users—all within a seamless, cloud-based environment.

The goal of this demo project is to showcase how APEx services can be instantiated and utilized within your project. Whether you are an EO researcher, data scientist, or application developer, this portal showcases the tools you need to harness EO data effectively.

Project Portal

A central hub for managing all project-related activities, including access to documentation, datasets, processing tools, and collaboration features.

  • Navigate project datasets and metadata.
  • Explore project deliverables and related publications.
  • Access project updates, discussions, and support resources.

Collaborative Environment

A cloud-based development and execution environment for working with EO data.

  • Develop, test, and execute algorithms in a Jupyter-based environment.
  • Access shared workspaces for collaborative coding and analysis.
  • Manage and visualize outputs of processing workflows.

Product Catalogue

A registry of available datasets, including a graphical user interface for exploring.

  • Browse, search, and access published EO datasets.
  • Upload and share your own data with your community.

Geospatial Explorer

A web-based tool for visualizing and analyzing EO datasets interactively.

  • Browse available EO datasets through an intuitive map-based interface.
  • Perform spatial and temporal filtering of data.
  • Overlay multiple datasets to identify trends and patterns.