Software Engineering
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Metadata makes the data format: metadata storage and representation across array formats
In this continuation of our recent raster data format blog series we discuss metadata: how do COG and Zarr represent metadata and how can geospatial coordinate metadata be represented across different formats? Where should metadata be stored? and more!
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Metadata makes the data format: metadata storage and representation across array formats
In this continuation of our recent raster data format blog series we discuss metadata: how do COG and Zarr represent metadata and how can geospatial coordinate metadata be represented across different formats? Where should metadata be stored? and more!
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The 2025 Geospatial Tech Radar: Agentic AI, EO Embeddings, and Cloud-Native Maturity
We analyze trends and highlights from the third iteration of our Geospatial Tech Radar including Agentic AI and MCP, EO Foundation Models and Embeddings, and the solidification of Cloud-Native Geospatial.
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STAC: A Retrospective, Part 2 (Why STAC was Successful)
In Part 1 of this series we covered the origin story of STAC, exploring the history and the initial sprints that created the spec. Now, it’s time to cover the how and the why of its success.
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Beyond the default: a modern guide to raster compression
We discuss community concerns surrounding raster compression and key metrics for evaluating compression effectiveness.
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Introducing Natural Language Geocoding v0.1.0: An LLM-Enabled Geocoding Database
The landscape of geospatial AI is rapidly evolving. Many organizations are building LLM-powered solutions that tackle complex geospatial problems and answer sophisticated questions about our planet. These agentic approaches allow LLMs to autonomously select from toolsets that include geospatial tools, Earth Observation (EO) catalogs, and EO data processing capabilities. The result? Systems that can process…
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Chunks and Chunkability: An Origin Story
If you accept that we are living through the Tyranny of the Chunk, then you might be wondering how we got to this place. Who created the first chunks and what was their motivation? As we explore the history of different data formats we’ll see recurring patterns of thinking around how much information to consolidate…
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Chunks and Chunkability: Tyranny of the Chunk
We discuss our attempt to understand chunks and chunking more deeply including where we are today and where we might go from here.
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Perceived Gaps in Earth Observation
At Element 84, our team looks forward to the Spring season and the return of a busy conference schedule every year. Our time attending, presenting, and learning at conferences helps us to feel connected and plugged into trends in the geospatial industry and beyond. It also allows us to receive feedback on our team’s latest…
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Why We’re Talking About a Centralized Vector Embeddings Catalog Now
We discuss our detailed white paper in which we make the case for how Earth Observation (EO) data providers such as NASA can dramatically improve access to their data by creating a centralized vector embeddings catalog, in addition to the more standard data catalogs that they already maintain.
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Is Zarr the new COG?
Just to be upfront and get it out there: no. Despite what you may have heard, Zarr is not (yet) a replacement for the Cloud-Optimized GeoTIFF (COG) format. Zarr is great for Level 3 and Level 4 n-dimensional data cubes. COG is great for Level 1, Level 2, and other non-data-cube rasters. Enthusiastic Zarr users…
