The Importance of Scientific Quality Data in Applications of Change Detection

There is a pressing need for a global change detection system capable of persistently monitoring the entire earth with globally consistent coverage, temporally consistent sampling, scientific-grade geometric and radiometric quality, and cost-effective management of daily data. These four conditions enable near real-time monitoring and retrospective change detection applications while minimizing false positives and the required work to develop, maintain, and run harmonizing algorithms for disparate data sources. While the virtual constellation of open and commercial data provides the ultimate wealth of unique and complementary data sources, harmonization challenges are exacerbated between different missions with different band measurements and temporal, spatial, spectral, and radiometric resolutions. The EarthDaily Constellation (EDC) has been designed from the ground up to meet the need for a persistent coverage mission with 22 spectral bands designed and prepared for environmental change and modelling applications. The EDC global land coverage mission will address challenges in food security, soil protection, water optimization, climate change response and mitigation, ESG accountability, disaster response, and many more. This talk will focus on the EDC mission parameters, design, and products that will be developed using best-in-class processing expertise and rigorous calibration approaches to produce the quality of data needed for subtle change identification.

The EDC mission collects data from visible blue to thermal infrared bands and will be made available via subscription services with several product flavours. The mission design for globally consistent coverage enables reliable expectations of when imagery attempts will be made without competition or overriding. A systematic imaging concept enables an entirely uniform temporal sampling of daily data. The highly stable geometry and radiometry produced by EarthPipeline (EarthDaily Analytics’ automated processing and calibration system) enables improved temporal analysis with reduced interventions as compared to other sources with inconsistent imaging conditions. Finally, combining all this automation within a highly available cloud-native architecture will deliver vast quantities of cost-effective EO data for users of all 
types. Advanced earth observation science users will be able to use high-quality Top of Atmosphere products, and application specialists will be able to rely on high-value Bottom of Atmosphere products produced in-house and informed by a specialized suite of spectral bands designed to create unmatched ready-for-analysis data.