FOSS4G Europe 2024 workshops

In an era where access to Earth system data is expanding at an unprecedented rate, effectively managing this highly-dimensional and voluminous influx poses significant challenges. The rise of Earth System Data Cubes (ESDCs) represents a revolutionary stride in efficiently handling, analysing, and visualising these complex datasets. ESDCs, with their multidimensional array structure, offer an organised, intuitive framework for robust data analysis. They encapsulate Earth system data in an analysis-ready form, defined by spatial, temporal, and variable dimensions. The integration of novel cloud technologies and cloud-ready formats, including SpatioTemporal Asset Catalogs (STAC) and Cloud Optimised GeoTIFFs (COG), has further streamlined the construction of ESDCs.

Our workshop is a comprehensive, interactive session designed to equip participants with the skills to construct and manage ESDCs using open-source Python tools.

The workshop is divided into five engaging segments:

1. Introduction to Earth System Data Cubes (15 min): This segment presents the concept of ESDCs, contrasting them with other data systems (such as image collections and information-preserving data cubes), and exposes their unique properties and construction rules.
2. ESDC Playground (15 min): Participants will engage with a global-scale ESDC (see Mahecha et al., 2020) using Python libraries such as xarray, zarr, dask, and matplotlib, demonstrating data access, exploration, analysis, and visualisation.
3. Constructing ESDCs from Scratch (30 min): Leveraging cloud technologies and open-source software, this segment guides through the creation of ESDCs from STAC catalogues and Google Earth Engine, incorporating diverse data sources like Earth Observation resources (e.g. Sentinel and Landsat missions), climate data (e.g. ERA5) and other products (e.g. Land cover and elevation products).
4. Interactive Visualisation of ESDCs (30 min): Focuses on the dynamic visual representation of ESDCs using Lexcube (see Lexcube.org) within Jupyter Notebooks, enhancing understanding through interactive widgets and coding.
5. Collaborative Outro (30 min): The workshop culminates in a brainstorming session aimed at unifying ESDC concepts, discussing standards, open-source tools, and potential applications. This collective discussion will be gathered into a white paper, aspiring for publication.

This workshop invites participants from all skill levels, from beginners to experts, with a foundational requirement of basic Python proficiency. Participants are expected to have a pre-installed Python environment to fully engage in the workshop's hands-on segments. Join us in this journey to harness the power of open-source software for exploring and understanding our planet in unprecedented detail.

In the rapidly evolving field of remote sensing, spectral indices are pivotal for monitoring and deciphering Earth system dynamics, including vegetation dynamics, water bodies ecosystems, and fire regimes. As the range of available spectral indices expands, the need for comprehensive catalogues and computational tools becomes crucial. Enter the Awesome Spectral Indices (ASI) - a novel, machine-readable, and open-source catalogue of spectral indices for Remote Sensing applications . ASI also promotes accessibility and application by integrating with three official Application Programming Interfaces (APIs) tailored for Python, Julia, and Google Earth Engine's JavaScript API. This integration facilitates the computation of a vast number of indices, adaptable to varied user experiences, data availability, and processing needs.

Our interactive workshop is structured into five engaging segments, each designed to showcase the potential of ASI in various environments:

1. Introduction to Awesome Spectral Indices (15 mins): This segment unveils the ASI catalogue, highlighting its standardisation, the comprehensive range of spectral indices, and their properties. Participants will also get a demonstration of “Espectro”, a Streamlit web app, for querying spectral indices.
2. ASI Python Mastery (30 min): Dive into “spyndex”, ASI’s Python API. This hands-on session guides attendees through exploring and computing spectral indices for several Python objects such as pandas Data Frames, numpy arrays, and xarray data arrays. Participants will leverage real-world data from STAC, such as Sentinel-2 and Landsat-9, applying parallel computing techniques with dask. This session is versatile, accommodating both Google Colab and personal Python environments.
3. ASI in Google Earth Engine (20 min): Google Earth Engine (GEE) stands as a colossus in remote sensing analysis. Here, we introduce “spectral”, a JavaScript module for GEE, offering access to ASI spectral indices. Practical exercises will involve computing indices for images and image collections using GEE’s extensive data catalogue. (GEE account required).
4. Harnessing ASI in Julia (30 min): Julia's focus in high-performance scientific computing makes it ideal for Earth system applications. “SpectralIndices.jl” brings ASI's power to Julia, enabling the computation of indices with remarkable efficiency . Participants will access indices and make computations for Arrays, Data Frames and YAXArrays. Participants should have a Julia environment pre-installed for this session, ideally with the necessary dependencies already downloaded.
5. Collaborative Outro (25 min): The workshop concludes with an interactive discussion, brainstorming enhancements for ASI (from standard improvements to computational methodologies), real-world applications and integration with other software or initiatives. This collective discussion will be gathered into a white paper, aspiring for publication.

This workshop invites participants from all skill levels, from beginners to experts, offering a unique opportunity to explore the world of spectral indices and their application in remote sensing. Join us in harnessing the power of open-source software to explore and understand our planet like never before.