Improved crop residue cover estimates obtained by coupling spectral indices for residue and moisture

摘要: Abstract Remote sensing assessment of crop residue cover (fR) and tillage intensity can improve predictions the environmental impact agricultural practices promote sustainable management. Spectral indices for estimating fR are sensitive to soil water contents, therefore uncertainty estimates increases when moisture conditions vary. Our goals were evaluate robustness spectral based on shortwave infrared region (SWIR) mitigate caused by variable estimates. Ten fields with center pivot irrigation systems (eight partially irrigated two uniformly dry fields) identified in Worldview-3 satellite imagery acquired a study site Maryland (USA). The mid-irrigation at time acquisition, allowing comparison under wet conditions. Fields subdivided into approximately equal-size wedges within portions each field, SWIR bands extracted pixel. Two (Normalized Difference Tillage Index (NDTI); Shortwave Infrared Normalized Residue (SINDRI) index (WI) calculated. Reflectance band was moisture-adjusted WI difference between wedges, updated NDTI SINDRI Finally, probability density distributions estimated from calculated field. more robust than fR. Moisture corrections reduced root mean square error 22.7% 4.7%, 6.0% 2.2%. variance distribution indices, before after correction, greatly fields, but only slightly uniform distribution. estimation should be if appropriate available, reliably combining content