Kyle Barron

Releasing 𝐝𝐞𝐜𝐤.𝐠𝐥-𝐫𝐚𝐬𝐭𝐞𝐫 𝐯0.3: fast, extensible, browser-based GeoTIFF visualization in deck.gl.

- 𝐍𝐞𝐰 𝐓𝐲𝐩𝐞𝐒𝐜𝐫𝐢𝐩𝐭 𝐆𝐞𝐨𝐓𝐈𝐅𝐅 𝐥𝐢𝐛𝐫𝐚𝐫𝐲: a new fast, high-level, fully-typed, easy to use GeoTIFF reader for the web. We've fully migrated off of geotiff.js.
- 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐜 𝐍𝐨𝐝𝐚𝐭𝐚 𝐦𝐚𝐬𝐤𝐢𝐧𝐠 𝐟𝐨𝐫 𝐆𝐞𝐨𝐓𝐈𝐅𝐅𝐬
- 𝐂𝐨𝐦𝐩𝐫𝐞𝐬𝐬𝐞𝐝 𝐄𝐏𝐒𝐆 𝐝𝐚𝐭𝐚𝐛𝐚𝐬𝐞 𝐟𝐨𝐫 𝐭𝐡𝐞 𝐰𝐞𝐛: the full WKT2 EPSG projection database compressed to 309kb
- 𝐍𝐞𝐰 𝐩𝐨𝐫𝐭𝐬 of rasterio/affine and Morecantile to TS
- 𝐍𝐞𝐰 𝐝𝐨𝐜𝐮𝐦𝐞𝐧𝐭𝐚𝐭𝐢𝐨𝐧 𝐰𝐞𝐛𝐬𝐢𝐭𝐞

https://developmentseed.org/deck.gl-raster/blog/v0-3-release/

Also in Lonboard, new logo! Designed by @gus@vis.social, who also designed the @developmentseed@fosstodon.org Cloud Native Zine

https://developmentseed.org/blog/2025-02-17-cloud-data-zine/
https://zines.developmentseed.org/zines/cloud-native/

Introducing 𝐀𝐬𝐲𝐧𝐜-𝐆𝐞𝐨𝐓𝐈𝐅𝐅, a new high-level library for reading GeoTIFFs and Cloud-Optimized GeoTIFFs. https://developmentseed.org/async-geotiff/latest/blog/2026/02/03/introducing-async-geotiff/

- High-level & easy-to-use
- Load from full-resolution or reduced-resolution overviews
- Fast, with a Rust core
- Uses a non-blocking thread pool for image decoding
- Integration with NumPy, PyProj, Affine, & Morecantile
- Remote data support with Obstore
- Lightweight with no GDAL dependency
- Full type hinting
- Broad decompression support

A @developmentseed@fosstodon.org project.

Native Cloud-Optimized GeoTIFF support in Lonboard!

- Stream massive COGs on demand
- Full control over image rendering: apply colormaps, change band combinations, use ML models
- Read COGs from anywhere, including local files and private data (via Obstore)

Release post: https://developmentseed.org/lonboard/latest/blog/2026/04/02/cloud-optimized-geotiffs-in-lonboard/

Land Cover example: https://developmentseed.org/lonboard/latest/examples/raster-cog-nlcd-server/
Sentinel-2 example: https://developmentseed.org/lonboard/latest/examples/raster-cog-rgb-server/

From @developmentseed@fosstodon.org

Follow Development Seed to see other cool stuff we're working on.

New from Development Seed: deck.gl-raster. 𝐅𝐮𝐥𝐥𝐲 𝐜𝐥𝐢𝐞𝐧𝐭-𝐬𝐢𝐝𝐞 𝐂𝐎𝐆 𝐫𝐞𝐧𝐝𝐞𝐫𝐢𝐧𝐠. No server required.

This is a 1.3 𝐠𝐢𝐠𝐚𝐛𝐲𝐭𝐞 COG, streamed directly into the browser. Explore it yourself: https://developmentseed.org/deck.gl-raster/examples/land-cover/

- GPU-accelerated raster reprojection supports images from nearly all projections
- GPU-accelerated image processing to apply colormaps, filter out nodata values, convert color spaces, & more
- Efficient use of COG overviews to fetch the minimum data required

https://github.com/developmentseed/deck.gl-raster

New: Zarr support in deck.gl-raster! Here's a GPU-driven animation of Zarr temperature forecasts, fully client-side, no server involved.
https://developmentseed.org/deck.gl-raster/blog/initial-geozarr/

New in deck.gl-raster: 𝐌𝐮𝐥𝐭𝐢-𝐛𝐚𝐧𝐝 𝐂𝐎𝐆 𝐬𝐮𝐩𝐩𝐨𝐫𝐭! Render Sentinel-2 or Landsat COGs directly from your browser, all 𝐰𝐢𝐭𝐡𝐨𝐮𝐭 𝐚 𝐬𝐞𝐫𝐯𝐞𝐫.

https://developmentseed.org/deck.gl-raster/blog/multi-band-cog/

When the source has bands at mixed resolutions, it will 𝐚𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐜𝐚𝐥𝐥𝐲 𝐫𝐞𝐬𝐚𝐦𝐩𝐥𝐞 across mixed band resolutions — 𝐚𝐥𝐥 𝐨𝐧 𝐭𝐡𝐞 𝐆𝐏𝐔. If necessary, lower-resolution bands will be upsampled to the highest-resolution band resolution.

Follow @developmentseed@fosstodon.org for more updates!

I'm happy to announce I've been promoted to an Apache Arrow Committer, meaning I'm authorized to merge code patches into Arrow repositories!

I join this list of amazing people: https://arrow.apache.org/committers/

Lonboard v0.15 now supports geocoding! Easily jump the map to locations, using any geocoder service of your choice.

https://developmentseed.org/lonboard/latest/blog/2026/03/13/releasing-lonboard-015/

New blog post! https://kylebarron.dev/blog/fast-python-bindings

This dives into performance pitfalls of Python bindings, why projects like Lonboard are so fast, and why I care about Apache Arrow so much. The post is high level and you don't need to know C/C++/Rust to understand it!

Visualize a mosaic of NAIP imagery loaded from Microsoft Planetary Computer's STAC Collection, all in your browser, *no server involved*.

Switch between true color, false color infrared, and NDVI renderings. https://developmentseed.org/deck.gl-raster/examples/naip-mosaic/

Each of these tiles loading are individual Cloud-Optimized GeoTIFFs, loaded directly from Azure. Only the COGs in viewport are loaded and rendered.

Built at @developmentseed@fosstodon.org with deck.gl-raster: https://github.com/developmentseed/deck.gl-raster

New Lonboard release makes the first step towards rich 𝐫𝐚𝐬𝐭𝐞𝐫 data visualization in Python, starting with PMTiles!

- New RasterLayer, supporting PMTiles input via async-pmtiles
- New support for categorical data filtering on the GPU

Release post: https://developmentseed.org/lonboard/latest/blog/2026/02/12/releasing-lonboard-014
Full Changelog: https://developmentseed.org/lonboard/latest/CHANGELOG/#0140-2026-02-11

Released Lonboard v0.13!

- New layer types: H3, S2, Geohash, A5 and fixed HeatmapLayer
- Render data layers beneath Maplibre text labels
- Map UI controls: scale, fullscreen, navigation
- Significant performance improvements: fixing earlier regressions

https://developmentseed.org/lonboard/latest/blog/2025/11/05/releasing-lonboard-013

We've released a new version of async-tiff. Fast, asynchronous reading of TIFFs, GeoTIFFs and Cloud-Optimized GeoTIFFs in Rust and Python. https://developmentseed.org/async-tiff/latest/

- New Array class for zero-copy data sharing between Rust and numpy
- Easily separate CPU-bound and IO-bound work, with native support for decoding image data on a Rust thread pool
- Revamped block caching for reading metadata
- Expanding tests
- Revamped Rust API for fetching TIFF metadata and image data

https://github.com/developmentseed/async-tiff/releases/tag/py-v0.4.0

Lonboard 0.10 is now out!

Animate trajectory data on an interactive map, all from Python!

Also MovingPandas integration, draw bounding boxes on the map, Pyodide support, new ColumnLayer for rendering extruded cylinders, fewer required dependencies

https://github.com/developmentseed/lonboard/releases/tag/v0.10.0

Building on Vincent Sarago's work, I updated and published 𝐚𝐬𝐲𝐧𝐜-𝐩𝐦𝐭𝐢𝐥𝐞𝐬, an asynchronous PMTiles reader for Python: https://github.com/developmentseed/async-pmtiles

This integrates with Obstore for efficiently reading remote files and Obspec for extensibility.

New deck.gl-raster example that compares two image sources with a slider.

https://developmentseed.org/deck.gl-raster/examples/vermont-cog-comparison/

New Lonboard release and new demo! Integrating Marimo and Apache DataFusion to visualize the NYC taxi dataset. https://developmentseed.org/lonboard/latest/examples/marimo/nyc_taxi_trips/

✨New Python bindings to GeoArrow and GeoParquet in Rust!

This wrapper exposes a **full rewrite** of the GeoArrow Rust library that supports the full GeoArrow 0.2 spec, including the new Geometry and GeometryCollection array types.

It also supports reading and writing GeoParquet files, including spatial filtering and reading from remote files.

https://geoarrow.org/geoarrow-rs/python/latest/

Three updates in deck.gl-raster v0.4:
1. New example for NDVI filtering on the GPU
2. When zooming in, render coarser image data while higher-res data is still loading
3. Fixed reprojection and rendering at high latitudes
https://developmentseed.org/deck.gl-raster/blog/v0-4-release/

Published a new version of async-geotiff:

- Support for reading band-interleaved GeoTIFFs and Cloud-Optimized GeoTIFFs
- Initial support for decoding LERC, LERC_DEFLATE, LERC_ZSTD images
- Fix computation of image bounds and resolution for rotated images

https://github.com/developmentseed/async-geotiff/releases/tag/v0.2.0

Published a new version of parquet-wasm: https://github.com/kylebarron/parquet-wasm/releases/tag/v0.7.0

- Update to latest version of Rust parquet crate
- Workaround to read Parquet data containing Arrow string view/binary view types
- Streaming writes
- Comparison between parquet-wasm and hyparquet, a pure-JavaScript Parquet reader

@cartocalypse@norden.social Yes, yes, strictly speaking you could call it a server, but for the purposes of this discussion it's at least a very reliable server that is very inexpensive and requires none of your own maintenance. The goal is to not need to always deploy your own additional server just to view raster imagery

@cartocalypse@norden.social Yes! It's loaded directly from S3 using geotiff.js using HTTP range requests.