View of the #MarshallFire smoke from Golden. It’s late December and wildfire season in Colorado. Climate change is not a distant threat. It’s here. #DontLookUp
In what ways can #MachineLearning accelerate and further our understanding of #WindEnergy? Recent research by myself and others @NREL highlights fruitful opportunities in this space.
A group of NREL scientists deliberated on the intersection of #WindEnergy and #ArtificialIntelligence in the last Wind Energy Science Leadership webinar. Watch the video on our NREL Learning channel: https://t.co/i5qkmYSjek
A group of NREL scientists deliberated on the intersection of #WindEnergy and #ArtificialIntelligence in the last Wind Energy Science Leadership webinar. Watch the video on our NREL Learning channel: https://t.co/i5qkmYSjek
what started out as tinkering with generative models for political landscapes ended up as this:
https://t.co/sQwM7N422c
so honored to work with the unparalleled @wallacetim who really drove the creative vision here and pushed me to keep going.
You know that time in the committee meeting when we ask the PhD candidate to step out of the room? What if we did the same thing with the mentor and asked if the student had anything they’d like to share? Could the committee help them more?
I think the satellite imagery industry isn't living up to its potential. I wrote about why it's broken and what can be done to fix it: https://t.co/SwsUuUB1mg
Here’s a thread of 10 strongly held opinions I have formed about the “geospatial industry”:
1. The most successful and ambitious mapping project of all time, Google Maps, is an advertising platform. There is no “geospatial industry,” only industries with spatial problems.
A new large-scale conservation dataset pairing species observations with remote sensing and climate variables has been released: https://t.co/NRzmgtT01x, along with an associated machine learning competition: https://t.co/tLfN1BO7V8
As the economic slow-down due to the coronavirus pandemic shutters industry, air pollution and carbon emissions are dropping. A lot of people have asked what this means for carbon emissions and climate change. Here is a short explainer. (thread)
Loving this new interactive mapping in #Jupyter notebooks using geemap (https://t.co/V5uhpKMq9H) for #EarthEngine. Credit to @giswqs for extending this powerful tool with a fantastic open source contributions.
Effective data visualizations and accompanying explanations like the one provided here can go a long way towards contextualizing patterns and key insights that might otherwise be obscured for the average reader #numeracy
Google Dataset Search is now officially out of beta.
"Dataset Search has indexed almost 25 million of these datasets, giving you a single place to search for datasets & find links to where the data is."
Nice work, Natasha Noy and everyone else involved!
https://t.co/7eMIfTOd36