Newsletter March 2025

Beginnings

Concordia was partially funded by the U.S. government’s Intelligence Advanced Research Projects Activity (IARPA) through the Space-based Machine Automated Recognition Technique (SMART) program. This initiative supported research on integrating multi-satellite data to detect real-time environmental changes using AI.

Building on the foundation of HLS, Concordia advances satellite data processing with cutting-edge algorithms and high-resolution inputs. Harmonizing data from multiple sensors delivers global coverage with high revisit rates. These harmonized data products enable various applications, from vegetation monitoring and land use mapping to change detection. Concordia creates an advanced 'virtual constellation' of georeferenced satellite image time stacks. The result is cloud-free, temporally consistent data—ideal for generating superior time series inputs benefitting from:

• Enhanced Data Quality: Concordia’s improved cloud masking, geo-registration, and advanced denoising algorithms deliver data with superior clarity and usability. 

• Integration of High-Resolution Data: Concordia’s inclusion of high-resolution commercial satellite data further improves revisit time while also providing detailed insights crucial for applications requiring fine spatial resolution.

• Cloud-Free Time Series:  Concordia generates cloud-free time series data while preserving data integrity, enabling continuous monitoring, more frequent and accurate observations, and streamlined distribution.

Concordia offers multiple data products. Data can be provided at 10-m, 30-m, or mixed ground sample distance (GSD) with several temporal smoothing options.

• Mixed GSD harmonized to Sentinel-2A (all available bands)

• 10-m GSD harmonized to Sentinel-2A (visible and near infrared (NIR) bands)

  • • No temporal smoothing

    • Temporally smoothed to reduce noise and remove missed clouds

• 30m GSD harmonized to Landsat 8 (coastal, visible, NIR and shortwave infrared (SWIR) bands)

  • • No temporal smoothing

    • Temporally smoothed to reduce noise and remove missed clouds

In addition to individual image files, Concordia can also produce time series movies. Available band combinations for movies include:

• Agriculture: Improved data quality and resolution support precision agriculture, irrigation optimization, and crop health monitoring for better yield management.

• Environmental Monitoring: Enhanced time series data aids in monitoring deforestation, land degradation, and other ecological changes, supporting conservation and sustainable management efforts.

• Disaster Management: Cloud-free, high-resolution data enhances disaster assessment and supports long-term response strategies.

• Base Layer for Other Satellite Imagery: Concordia provides a trusted base map for other satellite imagery, providing an accurate reference.

• AI Applications:  Optimized for AI applications, Concordia provides consistent, cloud-free data that enhances machine learning models for land cover classification and environmental monitoring. Its advanced analytics capabilities enable AI-driven insights from complex datasets.

Bolton, B.K., J.M. Gray, E.K. Melaas, M. Moon, L. Eklundh, and M.A. Friedl. 2020. “Continental-Scale Land Surface Phenology from Harmonized Landsat 8 and Sentinel-2 Imagery.” Remote Sensing of Environment 240 (April):111685. 

“HLS: Harmonized Landsat-Sentinel 2.” n.d. NASA EarthData. Accessed November 12, 2024.