Mixed-Species Cover Crop Biomass Estimation Using Planet Imagery

Area of Science:

• Agricultural Science
• Remote Sensing
• Agronomy

Background:

• Cover crops enhance soil health, nutrient cycling, and crop productivity.
• Estimating cover crop biomass is crucial for optimizing these benefits.
• Remotely sensed imagery offers a promising approach for biomass assessment.

Purpose of the Study:

• To evaluate the effectiveness of high-resolution PlanetScope imagery for estimating cover crop biomass.
• To determine the optimal timing and spectral bands for biomass estimation.
• To assess the impact of cover crop species and mixtures on biomass production and remote sensing accuracy.

Main Methods:

• Four small plot study sites used a randomized complete block design with diverse cover crops.
• PlanetScope imagery (3m resolution) was acquired from November to April over two cycles.
• Canopy-level hyperspectral data and biomass were collected before cover crop termination.

Main Results:

• Mixed cover crops produced up to 24% more biomass than single-species rye.
• Imagery from March exhibited stronger correlations with biomass (r=0-0.74) than November (r=0.01-0.41) or April (r=0.03-0.57).
• The near-infrared band in March showed the highest correlation (r=0.74); random forest model R² improved from 0.25 to 0.61 with species information.

Conclusions:

• Timing of satellite imagery acquisition is critical for accurate cover crop biomass estimation.
• Near-infrared reflectance and specific vegetation indices are valuable for biomass assessment.
• Integrating cover crop species information significantly enhances biomass prediction models.