Climate posts
Explore the latest in our mission to build a better world using data science and AI.
Content list
Meet the winners of the Forecast and Final Prize Stages of the Water Supply Forecast Rodeo
Learn about the winners and winning solutions from the final stages of the Water Supply Forecast Rodeo.
Meet the winners of the Water Supply Forecast Rodeo Hindcast Stage
Learn about the winning models for forecasting seasonal water supply from the first stage of the Water Supply Forecast Rodeo.
Meet the winners of the Kelp Wanted challenge
Dive into the solutions from the super segmenters who best detected kelp in Landsat imagery!
Open data using AI for climate action
How can we use data and AI to help combat the effects of climate change? This second post pulls together real-world datasets from DrivenData challenges for those looking to get hands-on experience.
5 ways organizations are using AI for climate action
How can we use data and AI to help combat the effects of climate change? This post walks through real-world examples from DrivenData challenges working with public, private, and social sector organizations.
Meet the winners of the Tick Tick Bloom: Harmful Algal Bloom Detection Challenge
Meet the participants who cracked the code to detect harmful algal blooms! Monitoring cyanobacteria in lakes and reservoirs keeps both the human and marine life that rely on these water bodies safe and healthy.
Meet the BioMassters
Meet the minds behind the top models for predicting aboveground biomass using remote sensing data!
How to Predict Harmful Algal Blooms Using LightGBM and Satellite Imagery
We'll show how to use satellite imagery and LightGBM to create a tree-based model predicting harmful algal blooms. This post will help you get started on our new Tick Tick Bloom Challenge!
The BioMassters Challenge - Benchmark
In this guest post by MathWorks, we'll show you how to start working with satellite data to help conservationists predict above ground biomass.
Meet the winners of the Snowcast Showdown competition
Meet the winners who most accurately estimated snow water equivalent across the Western U.S. in real-time.
Meet the winners of the NASA Airathon: Predict Air Quality Challenge
Meet the competitors who topped the leaderboards in the NASA Airathon challenge. Their predictions of surface-level air pollution could give millions of people the information required to protect their health.
Meet the winners of the Cloud Cover Detection Challenge
Better identifying and removing clouds from satellite imagery enables a wide variety of environmental applications in disaster recovery, conservation, and more. Get to know the winning participants who advanced state-of-the-art methods in cloud detection!
How to Estimate Surface-level NO2 using OMI Column NO2 Data
We'll show you how to preprocess HDF5 files and work with an OMI NO2 data product to estimate air quality around the world!
How to Predict PM2.5 using MAIAC Aerosol Optical Depth Data
We'll show you how to preprocess HDF4 files and work with a MAIAC AOD data product to estimate air quality around the world!
How to Use Deep Learning, PyTorch Lightning, and the Planetary Computer to Predict Cloud Cover in Satellite Imagery
We'll demonstrate how to get started predicting cloud cover in satellite imagery for our new competition!
How to Map Floodwater from Radar Imagery using Semantic Segmentation - Benchmark
We'll show you how to tune a U-Net model to measure flood extent using Sentinel-1 synthetic-aperture radar imagery.
Visualizing a Future for Fog Nets
Meet the folks who used their data visualization and modeling skills to help Dar Si Hamd!
Cloudy with a chance of models
We're excited to launch a new competition with our partner Dar Si Hmad and sponsor Tableau Foundation.
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