An Improved ASTER Index for Remote Sensing of Crop Residue

Abstract

Unlike traditional ground-based methodology, remote sensing allows for the rapid estimation of crop residue cover (fR). While the Cellulose Absorption Index (CAI) is ideal for fR estimation, a new index, the Shortwave Infrared Normalized Difference Residue Index (SINDRI), utilizing ASTER bands 6 and 7, is proposed for future multispectral sensors and would be less costly to implement. SINDRI performed almost as well as CAI and better than other indices at five locations in the USA on multiple dates. A minimal upgrade from one broad band to two narrow bands would provide fR data for carbon cycle modeling and tillage verification.

Keywords

• crop residue
• non-photosynthetic vegetation
• ASTER
• agricultural remote sensing