A new open-access paper from Resolv, Inc. argues that the long-standing promises of precision agriculture can be fulfilled by making accurate surface reflectance the standard output of satellite imagery. Published in Remote Sensing on March 30, the study benchmarks three atmospheric correction methods and outlines how a reliable standard could enable low-cost, fully automated crop intelligence.
Atmospheric correction is critical because light traveling through the atmosphere distorts the signal before it reaches a satellite sensor. Without accurate correction, small clouds and shadows can appear as crop problems, triggering costly false alarms. The paper, authored by Dr. David Groeneveld and Tim Ruggles, compares two mainstream tools—Sen2Cor and FORCE—against Resolv's CMAC method. Results show that CMAC produces precise surface reflectance estimates across a wide range of conditions, while the mainstream methods exhibit systematic bias that had previously gone undetected.
Reliable surface reflectance unlocks several applications: automated removal of clouds and shadows, an automated crop start-date index that could replace growing-degree-day scheduling, stable NDVI readings across varying atmospheric water vapor, soil capability classification from imagery, and accurate remote crop irrigation based on greenness and reference evapotranspiration. These applications could allow precision agriculture to pay for itself.
The paper also proposes a tiered approach to reduce imagery costs. Tier 1 uses free Sentinel-2 data corrected to surface reflectance, while Tier 2 fills gaps with commercial smallsat data when clouds block Sentinel-2. This smallsat data can be resampled, verified, and billed automatically, creating a turnkey pipeline without manual touchpoints. Crop insurance could serve as a natural channel for this service, streamlining loss adjustment and expanding active management while preserving grower privacy.
Resolv, Inc. develops atmospheric correction technology for satellite imagery, with initial development of CMAC funded by the National Science Foundation SBIR. The company has other peer-reviewed papers available on their website at https://resolvearth.com.
Remote sensing has often over-promised and under-delivered for agriculture, but Resolv argues that reliable surface reflectance imagery can finally close the gap.
