# Mixed-Species Cover Crop Biomass Estimation Using Planet Imagery
## 5 Conclusions  
An exploratory analysis was conducted to estimate mixed-species cover crop biomass using higher-resolution satellite imagery from the PlanetScope lab and canopy-level hyperspectral reflectance data captured using the FieldSpec4 instrument. Four field study sites with different cover crop species and their mix were analyzed in this paper. Cover crop biomass increased linearly with a higher seeding rate (R\({}^{2}\) = 0.79) and pure live seeds (R\({}^{2}\) = 0.42), where a higher seeding rate primarily indicated a mixture of cover crops from the grass and legume family. The results showed that mixed cover crops increased biomass production by 24% compared to single species rye. Evaluation of biomass yield and Planet imagery-based VIs showed that VIs increased over time, but their correlation with biomass yield decreased after March. This result indicates that March (\(r\) = 0-0.74) is the best time to predict cover crop biomass compared to November (\(r\) = 0.01-0.41) and April (\(r\) = 0.03-0.57). Cover crop biomass estimation using the random forest model using the VIs and bands derived from Planet imagery collected during the month of March was below expectation, resulting in an R\({}^{2}\) value of 0.25. However, the biomass predictability improved (R\({}^{2}\) = 0.61) with the addition of cover crop species to the model predictors. This result suggests that cover crop biomass estimation is affected by mixed species, and estimation can be improved if species and their mix are classified and used in the model-building process. Contrary to this result, further examination of the same hypothesis with hyperspectral data showed that biomass estimation is not affected by mixed-species due to more biomass variability captured by the increased number of bands used in the model. However, more study with multiple-timepoint biomass, hyperspectral, and imagery collection is needed to choose appropriate bands and predict the biomass of mixed cover crop species.  
Conceptualization, T.P.K.; methodology, T.P.K.; software, T.P.K.; validation, A.B.B., P.M., H.L.T., R.S.F. and K.N.R.; formal analysis, T.P.K.; investigation, T.P.K., A.B.B., P.M. and H.L.T.; resources, P.M., H.L.T., R.S.F. and K.N.R.; data curation, T.P.K., P.M. and H.L.T.; writing--original draft preparation, T.P.K.; writing--review and editing, T.P.K., A.B.B., P.M., H.L.T., R.S.F. and K.N.R.; visualization, T.P.K.; supervision, H.L.T., R.S.F. and K.N.R.; project administration, K.N.R. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** Data presented are available on request.  
**Acknowledgments:** The authors would like to thank [PERSON], [PERSON] and [PERSON] for their help in establishing the field study and data collection. Trade names or commercial products mentioned in this article are solely for the purpose of providing specific information and do not infer either recommendation or endorsement by the U.S. Department of Agriculture. The findingsand conclusions in this publication are those of the authors and should not be construed to represent any official USDA or U.S. Government determination or policy. USDA is an equal opportunity provider and employer.  
The authors declare no conflict of interest.