OpenNEX: Earth observation by constellations of CubeSats: New opportunities and challenges

Rasmus Houborg (August 16, 2018)

Constellations of small CubeSats are emerging as a novel observational resource with the potential to overcome the spatiotemporal constraints associated with conventional single-sensor satellite missions. With a constellation of more than 175 active CubeSats deployed in low-earth orbits, Planet has realized daily RGB and near-infrared (NIR) imaging of the entire Earth land area at very high spatial resolution (~3 m), which was unimaginable just a few years ago. The spatial and temporal enhancements enabled by CubeSat systems can provide critical insights into rapidly evolving vegetation dynamics with a factor of 10 increase in spatial resolution compared to Landsat. However, the large number of constellation satellites, and relatively cheap sensor components and design, introduce cross-sensor inconsistencies and cross-calibration challenges. While superior in terms of spatiotemporal resolution, the radiometric quality and spectral resolution is clearly not equivalent to that of rigorously calibrated space-agency satellites such as Landsat and Sentinel.


A CubeSat Enabled Spatio-Temporal Enhancement Method (CESTEM) has been developed to realize the full potential of CubeSat systems by exploring synergies with more conventional satellite systems. CESTEM serves as a multi-purpose data fusion scheme for radiometric normalization, smooth temporally-consistent phenology reconstruction, and spatiotemporal enhancement of biophysical properties. CESTEM can use high quality Landsat 8 or Sentinel-2 surface reflectance and vegetation biophysical retrievals as references to transform relatively noisy CubeSat time series observations into Landsat or Sentinel consistent estimates. CESTEM offers a unique data-driven avenue towards cross-platform interoperability enabling spatiotemporal enhancement of spectral metrics and biophysical properties retrievable from conventional large satellite systems. The application of CESTEM over a variety of agricultural landscapes and environments highlights the resolution advantage and impressive capability to provide repeatable time-critical insights into within-field vegetation dynamics, the rate of vegetation green-up, and the timing and progress of key phenological transitions, that are largely uncaptured by Landsat or Sentinel-2 imagery.