Observations of environmental variables from satellites and aircraft, or collected in the field represent snapshots of a continuously varying Earth system at specific places and times. Satellites offer a global view, but miss important details on local environmental conditions and context for interpreting local variability.  The emergence of advanced remote sensors on airplanes and drones offer new opportunities to bridge local and regional data with this global view. Field observations from citizen scientists, field surveys, social sensing, camera traps, and others offer very specific information locally, but are often time consuming and limited in space or time. We use novel analytics for curating cross-scale datasets that  integrate these observations to help us better resolve and understand underlying ecological processes.


See our page on Earth Data Across Scales for more. 

Featured Work



    ImgSPEC is a prototype on-demand processing system on the cloud that enables use of many different kinds of datasets but...

Project Team

Project Lead

Cibele Amaral

Cibele is a Remote Sensing Scientist who currently works with cutting-edge remote sensing data processing and analytics, artificial intelligence models, open-source languages and tools, and cyberinfrastructure for scalable computing. She enjoys developing research workflows for multi-source data harmonization, cross-scale analysis, feature extraction, and data analytics and visualization.

Ty Tuff

Earth Lab

Adam Mahood

USDA-ARS, Fort Collins

Johannes Uhl

Institute of Behavioral Science, CIRES