Balancing nitrogen use is critical for maximizing crop yield while minimizing environmental and economic costs. A new approach integrates drone-based multispectral imaging with machine learning to ...
Researchers at UCLA's Institute of the Environment and Sustainability have developed the most high-resolution statewide maps of California's kelp forests to date, giving researchers, conservationists ...
Researchers from UC Berkeley, Yale, Stanford’s Global Policy Laboratory, and NBER developed a deep learning method to predict ...
Drone pilots earn USDC on Base blockchain to map Earth for AI world models. Spexi's LayerDrone network delivers imagery 900x ...
The organization folds the Taylor Geospatial Institute and Taylor Geospatial Engine together to spur new geospatial artificial intelligence tools.
Abstract: Geospatial use cases involve data with a geospatial and a temporal dimension. Machine learning is applied to such use cases for tasks such as prediction and classification. However, machine ...
TorchGeo is a Python package for integrating geospatial data into the PyTorch deep learning ecosystem, making it easy for machine learning and remote sensing experts to use geospatial data in their ...
A map has revealed America’s “epilepsy belt,” highlighting how some states in particular see higher rates of the neurological condition among older adults. The first-of-its kind nationwide study ...
Artificial intelligence is redefining how humanity monitors and manages the planet’s land systems. A new editorial study titled “GeoAI for Land Use Observations, Analysis, and Forecasting”, published ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results