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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #275311
Title: Assessment of spectral indicies for crop residue cover estimation

Author
item SERBIN, G - Collaborator
item Hunt Jr, Earle
item Daughtry, Craig
item McCarty, Gregory

Submitted to: Geoscience and Remote Sensing Letters
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/14/2013
Publication Date: 3/6/2013
Citation: Serbin, G., Hunt, E.R., Daughtry, C.S., Brown, D.J., McCarty, G.W. 2013. Assessment of spectral indicies for crop residue cover estimation. Geoscience and Remote Sensing Letters. 4(6):552-560.

Interpretive Summary: The cover of crop residue (also called senesced foliage, non-photosynthetic vegetation or plant litter) on the soil surface is important for assessing agricultural tillage practices, rangeland health, and brush fire hazards. Cellulose and lignin are plant structural materials which absorb shortwave infrared radiation from about 2100 nm to 2350 nm wavelength. Using reflected radiation at these wavelengths, two spectral indices were developed to enhance the capability of remote sensing to detect crop residue from aircraft or satellite sensors. The Cellulose Absorption Index (CAI) and the Shortwave Infrared Normalized Difference Residue Index (SINDRI) utilize three and two spectral bands, respectively, so SINDRI is somewhat less expensive to implement in future satellite sensors. However, a number of soil minerals absorb radiation at the same wavelengths as SINDRI, so the amount of residue cover will be overestimated in areas where these soil minerals occur. This study shows that the index with 3 bands, CAI, distinguishes among soils, crop residues, and live vegetation, so CAI is a better index, even with higher implementation costs.

Technical Abstract: The quantification of surficial crop residue cover is important for assessing agricultural tillage practices, rangeland health, and brush fire hazards. The Cellulose Absorption Index (CAI) and the Shortwave Infrared Normalized Difference Residue Index (SINDRI) are two spectral indices that have shown promise for remote estimation of crop residue cover. CAI and SINDRI utilize three and two spectral bands, respectively, rendering the latter less expensive to implement in future satellite sensors. This study shows that while CAI always contrasts well among soils, crop residues, and live vegetation, this is not always the case for SINDRI. A small number of surficial soil samples had positive SINDRI values that have reduced contrasts among crop residues. Some of these soils were biased by SINDRI-positive component minerals. As such, SINDRI is less applicable for remote crop residue cover estimation, even with reduced implementation costs.