Lifting the clouds on land clearing and biodiversity loss

QUT researchers have developed a new machine learning mathematical system that helps to identify and detect changes in biodiversity, including land clearing, when satellite imagery is obstructed by clouds.

Landslides have long-term effects on tundra vegetation

Landslides have long-term effects on tundra vegetation, a new study shows. Conducting the study in North West Siberia, the researchers found that tundra vegetation regenerated rapidly after a major landslide event in 1989. ...

Diagnosing single trees from above

Models based on images from unmanned aerial vehicles and satellites can help farmers to monitor the health of individual trees.

Observing phytoplankton via satellite

Thanks to a new algorithm, researchers at the AWI can now use satellite data to determine in which parts of the ocean certain types of phytoplankton are dominant. In addition, they can identify toxic algal blooms and assess ...

Sharing data for improved forest protection and monitoring

Although the mapping of aboveground biomass is now possible with satellite remote sensing, these maps still have to be calibrated and validated using on-site data gathered by researchers across the world. IIASA contributed ...

Using machine learning for rewilding

There may not be an obvious connection between rewilding and machine learning, but as highlighted today at ESA's ΙΈ-week, a project in the Netherlands uses satellite data and new digital technology to understand how a nature ...

Remote sensing of toxic algal blooms

Harmful algal blooms in the Red Sea could be detected from satellite images using a method developed at KAUST. This remote sensing technique may eventually lead to a real-time monitoring system to help maintain the vital ...

page 6 from 11