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

@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

#geospatial #gischat

RT @giswqs@twitter.com

#Leafmap new feature - Searching and visualizing open #geospatial datasets (#STAC) interactively without coding. It will support #AWS Open Data, #EarthEngine, #PlanetaryComputer, NASA CMR, STAC Index.

Leafmap: https://github.com/giswqs/leafmap/pull/340
Data catalogs: https://github.com/giswqs/geospatial-data-catalogs

🐦🔗: https://twitter.com/giswqs/status/1613547421488889856

RT @giswqs
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

GitHub: https://github.com/giswqs/geospatial-data-catalogs

#opendata

RT @giswqs
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

GitHub: https://github.com/giswqs/geospatial-data-catalogs

#opendata

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

#opendata #datascience

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.

GitHub: https://github.com/giswqs/geospatial-data-catalogs

#opendata #datascience

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

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

@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. :)

@sabrinaszeto @Exopixelist Hey, thanks for the heads up. I started using #PlanetaryComputer and find there's little in ways of community, discourse sites and so on... Anybody got any pointers on this? Cheers!