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Title: Assessing the extent of conservation tillage using remotely sensed data

Author
item Daughtry, Craig
item Doraiswamy, Paul
item Hunt Jr, Earle
item SERBIN, GUY - Foreign Agricultural Service (FAS, USDA)

Submitted to: Agronomy Abstracts
Publication Type: Proceedings
Publication Acceptance Date: 10/28/2010
Publication Date: 10/31/2010
Citation: Daughtry, C.S., Doraiswamy, P.C., Hunt, E.R., Serbin, G. 2010. Assessing the extent of conservation tillage using remotely sensed data. Proceedings. ASA-CSSA-SSSA International Meetings, October 31 - November 4, 2010, Long Beach, CA. CDROM.

Interpretive Summary:

Technical Abstract: Management of crop residues in agricultural fields is an important consideration for reducing soil erosion and increasing soil organic carbon. Current methods of quantifying crop residue cover are inadequate for characterizing the spatial variability of residue cover within fields or across large regions. Our objectives were to evaluate spectral indices for measuring crop residue cover and to categorize soil tillage intensity in agricultural fields. Ground-, aircraft- and satellite-based multispectral and hyperspectral data were acquired over corn (Zea mays L.) and soybean (Glycine max Merr.) fields in Iowa, Indiana, and Maryland, shortly after most fields in the area were planted. Crop residue cover was measured in using line-point transects. Crop residue cover was weakly related to the spectral residue indices that used the relatively broad Landsat TM bands. However, spectral residue indices that measured the relatively narrow spectral absorption features associated with cellulose and lignin near 2100 or 2350 nm were robust and were often linearly related to crop residue cover. Tillage intensity classes, based on residue cover after planting, were combined with information on the previous season’s crop classification (Cropland Data Layer from USDA-NASS) to produce an inventory of soil tillage intensity for each scene. Regional surveys of soil management practices that affect soil conservation and soil C dynamics are possible using advanced multispectral or hyperspectral imaging systems.