Estimation of Crop Residue Cover Utilization Multiple Ground Truth Survey Techniques and Multi-Satelite Regression Models, 2024

This study found that photo analysis surveys are the most reliable method for estimating crop residue cover in regression models using satellite data, surpassing common windshield-based survey techniques, which are only effective for differentiating broad tillage categories like no-till versus conventional tillage. While photo analysis surveys offer greater accuracy, they are more costly and time-consuming to perform, but technological advances and data binning approaches could enhance their efficiency in the future. Remote sensing tools such as Google Earth Engine enable large-scale assessment of residue cover when paired with accurate ground truth data. The authors recommend citizen science, streamlined photo methods, and machine learning as innovative solutions to lower survey costs and broaden spatial coverage.