#remote-sensing tag

Becoming a City Scientist: How to Draw Urban Spaces with Data

City science applies data, modeling, and AI to engineer urban systems for decarbonization, improved mobility, efficiency, resilience, and evidence-based local decision-making.

Environment

fromState of the Planet

4 days ago

What Does It Mean for Soil To Be Healthy?

Improving soil health through integrated field data and advanced modeling enhances productivity, carbon storage, water retention, biodiversity, and resilient land management.

Science

fromflowingdata.com

1 week ago

Lidar to measure climate disasters

Lidar differencing produced high-resolution maps of Southern California fire damage, showing elevation loss (red) and gains (blue) with greater detail than satellite imagery.

Environment

fromNature

2 weeks ago

Mapping urban gullies in the Democratic Republic of the Congo - Nature

Many Congolese cities host identifiable urban gullies detectable by high-resolution imagery, with analyses limited to gullies having thalwegs at least 30 m.

fromInfoQ

2 weeks ago

Google DeepMind Unveils AlphaEarth Foundations Model for Global Mapping

Google DeepMind introduced AlphaEarth Foundations, an artificial intelligence model designed to integrate massive volumes of Earth observation data into a unified digital representation of the planet. The system, described as functioning like a "virtual satellite", can process petabytes of multimodal inputs. The model addresses a long-standing challenge in Earth science: the difficulty of combining data from diverse sources and refresh rates into formats that researchers can use consistently.

Environment

#remote-sensing#remote-sensing

Becoming a City Scientist: How to Draw Urban Spaces with Data

What Does It Mean for Soil To Be Healthy?

Lidar to measure climate disasters

Mapping urban gullies in the Democratic Republic of the Congo - Nature

Google DeepMind Unveils AlphaEarth Foundations Model for Global Mapping

The Future of Remote Sensing: Few-Shot Learning and Explainable AI | HackerNoon

6 Breakthrough Few-Shot Learning Techniques for Remote Sensing | HackerNoon

Few-Shot Learning in Remote Sensing: Trends, Gaps, and Future Directions | HackerNoon

Smarter Satellite Vision with Few-Shot Learning | HackerNoon

5 Key Metrics to Evaluate Few-Shot Remote Sensing Models | HackerNoon

Few-Shot vs. One-Shot vs. Zero-Shot Learning | HackerNoon

The Future of Remote Sensing: Few-Shot Learning and Explainable AI | HackerNoon

6 Breakthrough Few-Shot Learning Techniques for Remote Sensing | HackerNoon

Few-Shot Learning in Remote Sensing: Trends, Gaps, and Future Directions | HackerNoon

Smarter Satellite Vision with Few-Shot Learning | HackerNoon

5 Key Metrics to Evaluate Few-Shot Remote Sensing Models | HackerNoon

Few-Shot vs. One-Shot vs. Zero-Shot Learning | HackerNoon

Explainable AI (XAI) for Safer, Smarter Remote Sensing | HackerNoon

Understanding the 3 Main Types of Remote Sensing Sensor Data | HackerNoon

Top Remote Sensing Datasets for Training and Evaluating AI Models | HackerNoon

Alarming Spy Device Can Read Text in an Open Book From Nearly a Mile Away

The Competitive Landscape of Field Operations: A Ground Truth War

Can NASA Help Predict Wildflower Super Blooms? | KQED

#remote-sensing
#remote-sensing