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Radiant Earth
United States
Приєднався 24 січ 2017
Radiant Earth works to increase the shared understanding of our world through community-led initiatives that make data easier to access and use.
What do we do with all this data?
Presentation by Jed Sundwall from Radiant Earth for the 2024 ESIP Summer Meeting.
Переглядів: 81
Відео
#RadiantFaces: Michelle Roby, Geospatial Software Engineer
Переглядів 2032 роки тому
In this #RadiantFaces episode, we are highlighting Radiant's Geospatial Software Engineer, Michelle Roby. We talked about her work and what brings her joy.
#RadiantFaces: Kevin Booth, Engineering Lead and Geospatial Software Engineer
Переглядів 1462 роки тому
In this #RadiantFaces episode, we sat down with Kevin Booth, Engineering Lead and Geospatial Software Engineer at Radiant Earth to talk about Radiant MLHub and what inspires him.
#RadiantFaces: Louisa Nakanuku-Diggs, Marketing and Communications Manager
Переглядів 1232 роки тому
In this #RadiantFaces episode, we sat down with Louisa, Radiant Earth Foundation's marketing and communications manager. She shares her thoughts on changes in the Earth observation industry and talks about how she stays creative.
#RadiantFaces: Daniel Nwaeze
Переглядів 1772 роки тому
In this #RadiantFaces episode, we sat down with Daniel Nwaeze, Data Scientist at Radiant Earth Foundation to talk U-Net Agri, our fully reproducible instance segmentation model to detect #ag field boundaries, what's cool about working at Radiant & some great advice on success.
Role of Earth Observation Data in Achieving the SDGs
Переглядів 853 роки тому
In this interview, Dr. Hamed Alemohammad, Radiant Earth Foundation's Executive Director and Chief Data Scientist, and Ivan Mukiibi, Technical Advisor at GIZ Fair Forward program talk about the impact of the Machine Learning for Earth Observation Training of Trainers virtual bootcamp. 40 professionals from Uganda, Rwanda, Ghana, and South Africa participated in the Bootcamp. It was organized in ...
Webinar: Machine Learning and the Satellite Revolution for Climate Resilience
Переглядів 5983 роки тому
How can we leverage machine learning and the satellite revolution for climate resilience? As climate change accelerates, so does the need to build adaptive disaster response information systems. A new approach requires solutions that center on providing data that is not only accurate but has practical applications for decision-makers on the ground. In this discussion, experts from Cloud to Stre...
Creating STACs with PySTAC
Переглядів 2,4 тис.4 роки тому
In this beginner session, Rob Emanuele from Azavea walks you through creating a STAC of open data using PySTAC in a Jupyter notebook.
Introduction to TileDB
Переглядів 1,7 тис.4 роки тому
In this talk, Norman Barker gives an introduction to TileDB and its use as a cloud-native universal data engine for geospatial data from point clouds to hyperspectral.
Packing Your Geospatial Data Science Toolkit
Переглядів 3194 роки тому
In this talk, Ash Hoover from Planet gives an introduction to open source tools for geospatial data analysis and visualization.
STAC & COG Intro + Q&A
Переглядів 6084 роки тому
In this presentation, Chris Holmes digs deeper into how COG & STAC work. He goes into each of the 'sub-specs': Item, Catalog, Collection, and STAC API. This talk provides a deeper dive into how COG's are set up. There is an open forum at the end where attendees ask any question about STAC or COG.
Getting Started with Geospatial Raster Data, Digital Earth Africa
Переглядів 5774 роки тому
In this talk, Alex Leith with Geoscience Australia introduces Digital Earth Africa, including its software and data ecosystems. He also dives into a brief training course on doing data science in their Jupyter environment. You'll learn how to view their Cloud Optimised GeoTIFFs on a web map, how to analyze Earth observation data in Jupyter, using the Open Data Cube, and about how you can use ou...
Lightning Talks, Round 2 - Cloud Native Geospatial Outreach Day
Переглядів 1,1 тис.4 роки тому
(00:00) James Banting (SparkGeo and STAC); (5:00) Norman Barker (Introduction to TileDB); (12:30) Kurt Schwehr (The Google Earth Engine Data Catalog); (19:12) Matthias Mohr (STAC Index); (25:57) Javier de la Torre (How cloud-based data warehouses will change the industry at $5 per TeraByte); (33:50) Phil Varner (How Astraea Uses COGs and STAC API to Support Geospatial Data Science); (38:51) Fre...
Lightning Talks, Round 1 - Cloud Native Geospatial Outreach Day
Переглядів 5914 роки тому
(00:00) Jeff Albrecht (STAC & COG at Arturo); (07:53) Zac Flamig (Amazon Web Services Open Data Program); (12:27) Caitlin Mahanna (Overview of STAC at Maxar); (17:27) Drew Daniel (NASA's Common Metadata Repository (CMR) STAC Interface); (24:31) Anderson Banihirwe (Zarr: chunked, compressed, multidimensional arrays); (30:22) Simone Mantovani (Enabling STAC and pixel-based access services to Sent...
Introduction to STAC API
Переглядів 2 тис.4 роки тому
Phil Varner from Astraea presents on the principles and patterns for querying imagery from a STAC API-compliant web service.
COG's and STAC with Titiler & Arturo-STAC-API
Переглядів 2,7 тис.4 роки тому
COG's and STAC with Titiler & Arturo-STAC-API
Intro to Multi-Scale Ultra High Resolution (MUR) Sea Surface Temperature (SST) Zarr on AWS PDS
Переглядів 3494 роки тому
Intro to Multi-Scale Ultra High Resolution (MUR) Sea Surface Temperature (SST) Zarr on AWS PDS
Intake-STAC: Interactive catalog analysis with Python
Переглядів 9884 роки тому
Intake-STAC: Interactive catalog analysis with Python
Machine Learning and Satellite Imagery overview
Переглядів 8 тис.4 роки тому
Machine Learning and Satellite Imagery overview
Browsing and Downloading Assets from STAC APIs with the QGIS STAC Plugin
Переглядів 1 тис.4 роки тому
Browsing and Downloading Assets from STAC APIs with the QGIS STAC Plugin
Sentinel Hub: Cloud Native at Large Scale
Переглядів 1634 роки тому
Sentinel Hub: Cloud Native at Large Scale
AI for Earth and the Planetary Computer Overview
Переглядів 4214 роки тому
AI for Earth and the Planetary Computer Overview
Data Labeling with Groundwork (training for the contest)
Переглядів 2704 роки тому
Data Labeling with Groundwork (training for the contest)
Introduction to SpatioTemporal Asset Catalogs (STAC)
Переглядів 4,7 тис.4 роки тому
Introduction to SpatioTemporal Asset Catalogs (STAC)
Cloud Native Geospatial - Welcome, Opening Remarks & Data Labeling Contest Intro
Переглядів 4754 роки тому
Cloud Native Geospatial - Welcome, Opening Remarks & Data Labeling Contest Intro
NASA ML4EO - ML for Land Cover Change Mapping & Surface Water Detection [lightning presentations 4]
Переглядів 3594 роки тому
NASA ML4EO - ML for Land Cover Change Mapping & Surface Water Detection [lightning presentations 4]
NASA ML4EO - Open EO Data, ML for Land Change Analysis & Crop Analytics [Lightning Presentations 3]
Переглядів 3264 роки тому
NASA ML4EO - Open EO Data, ML for Land Change Analysis & Crop Analytics [Lightning Presentations 3]
NASA ML4EO - ML Labels & Validation, ML for Ocean Currents & Agriculture [lightning presentations 2]
Переглядів 2944 роки тому
NASA ML4EO - ML Labels & Validation, ML for Ocean Currents & Agriculture [lightning presentations 2]
i have question that C:\Users\sub\AppData\Local\Temp\ipykernel_17264\3111211276.py:7: DeprecationWarning: datetime.datetime.utcnow() is deprecated and scheduled for removal in a future version. Use timezone-aware objects to represent datetimes in UTC: datetime.datetime.now(datetime.UTC). datetime=datetime.utcnow(), I get this error where I enter the time in the item. I want to know what time I need to put in the datetime and how I can fix the error
help me TT🥲
datetime=datetime.now(timezone.utc) fix it!!!!!
Is it possible to visualize the COGs in a Mapbox web application?
Seems like you could just get rid of Catalogs altogether if the added fields for Collection were all optional, simplifying things quite a bit for new folks
Can I use the stack function even if it is not in COG format?
Cool stuff indeed Jeff! Cool stuff indeed 🌍🌎🌏
What is the difference between datacube and STAC ?
Very nice
Is there a notebook example for Sentinel-2 data?
Are there any startups that have built SaaS products (based on STAC) to solve this problem?
Share codings please
have you got any code you'd like to share first?
Wonderful presentation. Thanks so much.
nice👍
Is there anyway to serve my cog file from minio bucket as wmts service compatible for arcgis platform.
Than you for such and informative video.
PЯӨMӨƧM 🤔
Thanks for an interesting video.
Good job
Can the assets be anything other than TIF images? What If I want the asset to be a .csv file or .json file?
json and csv can be in asset as metadata I guess
Well done
Is there a way to automate this?
Yes, sure. For example PySTAC can do this in Python world automatically. I was doing plain stuff here so people better understand the basics.
I haven't watched all the way through, but I'm curious how you'd store point cloud data within a TileDB database. I figured it must be making use of the sparse array format, but then how would you store a point like 1.2, -4.7, 0.3? There is no index 1.2 into a sparse array. Do you have to deal with scaling factors which take all points in a point cloud to integers?
Thanks for the video! Do you have the links for the notebooks, so I can have a look? Thank you again.
Hi! How exactly to make fusion and which software to use for that? Thanks in advance
15:16 So cute and funny 😂😂
Global reset. Forget about your world domination sustainable "resource economy" plan. More and more people are waking up to your lies.
0:00 James Banting (SparkGeo and STAC) 5:00 Norman Barker (Introduction to TileDB) 12:30 Kurt Schwehr (The Google Earth Engine Data Catalog) 19:12 Matthias Mohr (STAC Index) 25:57 Javier de la Torre (How cloud-based data warehouses will change the industry at $5 per TeraByte) 33:50 Phil Varner (How Astraea Uses COGs and STAC API to Support Geospatial Data Science) 38:51 Frederico Liporace (CBERS on AWS) 46:56 Marten Hogeweg (The Needle in the STAC) 52:50 Hamed Alemohammad (Radiant MLHub - A Cloud-Native ML Commons for Geospatial Data) 57:14 Kyle Barron (Leveraging Cloud-Optimized GeoTIFFs to Enable New Methods in Web Mapping) 1:03:21 Leo Thomas (Radio-Occultation is not an occult science) 1:09:50 Daniel Dufour (Edge Compute: Cool Stuff You Can Do With COGs in the Browser) 1:14:31 Scott Henderson (Intake-STAC: Interactive catalog analysis with Python) 1:22:17 Dan "Ducky" Little (Raster Data Tiles from COG’s using Numpy and OpenLayers Planet) 1:29:03 Chris Helm (Pointclouds and STAC) 1:37:51 Aimee Barciauskas (2020 NASA SpaceApps Challenge and OceanHackweek: Cloud Optimized GeoTiffs and Zarr on AWS PDS) 1:44:27 Jérôme Gasperi (Resto - a stac search engine for geospatialized data) 1:49:45 Tom Kralidis (Pygeoapi STAC updates).
Thanks for the wonderful presentation. How do l access PlanetScope Data?
Nice!
Notebook can be found here: github.com/azavea/pystac/blob/develop/docs/tutorials/how-to-create-stac-catalogs.ipynb