New blog post: Accessing Planetary Computer STAC files in DuckDB - see https://blog.rtwilson.com/accessing-planetary-computer-stac-files-in-duckdb/
This is a report of my experimentation on how to access STAC GeoParquet files provided by Planetary Computer in DuckDB - I struggle a bit with authentication and libraries, but get it working after a while.
Given the lack of outrage (outside my WhatsApp peers) on the demise of #PlanetaryComputer , I guess not many #earthobservation peeps used it. Such a shame.... Cool open technology!
So #Microsoft is retiring the #PlanetaryComputer Hub, which allowed you to do quite advanced analyses using standard #Python packages. I guess we can run it elsewhere, and this was always on the cards, that's why using a standard #pangeo setup was good, but as with all things cloud, it's infuriating!!!
@hughagraham @esa Depending on what type of SAR data you'll use, you can often (application dependent) get away with using already RTC'ed ARD data (e.g., from #PlanetaryComputer), and by using fairly simple speckle reduction filters (mostly, they are ways of cleverly blurring images). For polarimetric or interferometic data, things are more complex. Let us know how you're getting on!
Have you wanted to use segment-geospatial (https://samgeo.gishub.org/) on Microsoft Planetary Computer and struggled? My blog post shows the simple solution: https://blog.rtwilson.com/how-to-get-segment-geospatial-working-on-microsoft-planetary-computer/
#python #ml #segmentation #PlanetaryComputer #geospatial #gis
Who is using Microsoft's Planetary Computer? This is a good little summary for those who are wondering what it is about https://gogeomatics.ca/the-microsoft-planetary-computer-and-cloud-based-gis/ #datascience #PlanetaryComputer
USGS 3DEP LiDAR Collection @ Microsoft
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https://planetarycomputer.microsoft.com/dataset/group/3dep-LiDAR <-- Microsoft data / use case portal
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“To respond to growing needs for high-quality elevation data, the goal of 3DEP is to complete acquisition of nationwide lidar (IfSAR in AK) to provide the first-ever national baseline of consistent high-resolution topographic elevation data – both bare earth and 3D point clouds. This dataset provides the raw 3D point clouds in the Cloud Optimized Point Cloud format, and various derived products as Cloud Optimized GeoTIFFs…”
#GIS #spatial #mapping #gischat #3dep #elevation #opendata #planetarycomputer #LiDAR #ifsar #USA #nationwide #acquistion #topography #topographic #dem #bareearth #pointclouds #cloudoptimization #geotiffs #download #library #usgs #microsoft
@microsoft @usgs
If you haven't read our recent blog focused on the components of Microsoft's #PlanetaryComputer and how it connects with #STAC, what are you waiting for?
https://www.element84.com/blog/how-microsofts-planetary-computer-uses-stac
🚨New blog alert! 🚨
In our latest from E84's Pete Gadomski, we're covering:
- The components of the #PlanetaryComputer
- Demonstrating how it's based on both #cloud-optimized formats & the #STAC spec
- & Discussing how this work benefits the larger community
Learn more: https://www.element84.com/blog/how-microsofts-planetary-computer-uses-stac
@conorosully @lavergnetho Also, consider getting a Microsoft Planetary Computer account. Although Google's equivalent has been around longer, #PlanetaryComputer allows you to do these things easily with standard Python tools and libraries (eg #xarray )
#Leafmap v0.16.0 has been released. It supports searching and visualizing open #geospatial datasets interactively from public #STAC API endpoint (e.g., #AWS, #PlanetaryComputer). Search results can be returned as a GeoDataFrame, list, dict.
Notebook: https://leafmap.org/notebooks/64_stac_search
GitHub: https://github.com/giswqs/leafmap
Searching and visualizing #PlanetaryComputer #geospatial datasets interactively with #leafmap. Image footprints with attribute data can be added to the map automatically and accessed through a GeoPandas GeoDataFrame
https://github.com/giswqs/leafmap/pull/347
#dataviz #geopython #opensource #stac
Earlier this week, we did the same workflow with 3 #GIS tools: Google #EarthEngine, Microsoft #PlanetaryComputer and @qgis. You can see the video here https://www.youtube.com/watch?v=Jv3P7WRoQhc cc @giswqs, @datamongerbonny and @MaxLenormand
Tune in for the YouTube live stream at 3:30 PM EST on Monday, Jan 23. We will showcase how to estimate flood extent using #PlanetaryComputer, #EarthEngine, & #QGIS.
Twitter post: https://twitter.com/MaxLenormand/status/1616134693069389832
YouTube: https://youtube.com/@MindsBehindMaps
The list of open #geospatial datasets now includes NASA's Common Metadata Repository (CMR) with 350 datasets, in addition to other open datasets on major cloud computing platforms (#AWS, #EarthEngine, #PlanetaryComputer) and STAC Index. The list is updated daily.
GitHub: https://github.com/giswqs/geospatial-data-catalogs
NASA-CMR: https://cmr.earthdata.nasa.gov/search
A comprehensive list of open #geospatial datasets on major cloud computing platforms (#AWS, #EarthEngine, #PlanetaryComputer) and STAC Index. The lists are provided in TSV and JSON formats, making it easier to find and use them programmatically. The list is updated daily.
Kicking the tires on Microsoft's #PlanetaryComputer. This is a cool demo working with their global building footprints dataset.
https://planetarycomputer.microsoft.com/dataset/ms-buildings#Example-Notebook
For all #xarray and #PlanetaryComputer folk, here's some nice #Sentinel 1 accessing and visualisation using #Python:
👉 https://discourse.pangeo.io/t/wednesday-november-2nd-2022-jupyter-book-tutorials-demonstrating-xarray-based-workflows-for-cloud-hosted-remote-sensing-data/2834
#RemoteSensing #EarthObservation
@jgomezdans @Exopixelist Might be due to the fact that #PlanetaryComputer is newer than #EarthEngine. I don't know how many users there are of #PlanetaryComputer but I'd guess they are fewer in number than EE users. I'd encourage you to take the initiative to gather a community by organizing a meetup or activities. :)
