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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 #286552

Title: Assessing the extent of conservation tillage in agricultural landscapes

item Daughtry, Craig
item Beeson, Peter
item S, MILAK - Science Systems, Inc
item B, AKHMEDOV - Science Systems, Inc
item Sadeghi, Ali
item Hunt Jr, Earle
item Tomer, Mark

Submitted to: Proceedings of SPIE
Publication Type: Proceedings
Publication Acceptance Date: 9/25/2012
Publication Date: 10/30/2012
Citation: Daughtry, C.S., Beeson, P.C., Milak, S., Akhmedov, B., Sadeghi, A.M., Hunt, E.R., Tomer, M.D. 2012. Assessing the extent of conservation tillage across agricultural landscapes. In: Proceedings of SPIE 8531, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIV, 853116, September 24-27, 2012, Edinburgh, United Kingdom. DOI: 10.1117/12.974611.

Interpretive Summary:

Technical Abstract: Crop residue (or plant litter) on the soil surface can decrease soil erosion and runoff and improve soil quality. Quantification of crop residue cover is required to evaluate the effectiveness of conservation tillage practices as well as the extent of biofuel harvesting. Remote sensing techniques can provide reliable assessment of crop residue cover over large fields. With Landsat Thematic Mapper bands, crop residues can be brighter or darker than soils depending on soil type, crop type, moisture content, and residue age. With hyperspectral reflectance data, relatively narrow absorption features, centered near 2100 and 2300 nm, can be detected that are associated with cellulose and lignin concentrations. These features are evident in reflectance spectra of crop residues, but not in reflectance spectra of soils. Our objectives were to: (1) estimate crop residue cover using remotely sensed data over an agricultural site in central Iowa, and (2) evaluate alternative, less labor-intensive sampling schemes for acquiring crop residue cover surface reference data. We acquired EO-1 Hyperion imaging spectrometer data over agricultural fields in central Iowa shortly after planting in May 2004 and 2005. Crop residue cover was also measured in corn and soybean fields using line-point transects. The cellulose absorption index (CAI), which measured the relative intensity of the absorption feature near 2100 nm, was calculated using three relatively narrow bands centered at 2030, 2100, and 2210 nm. Results showed that crop residue cover was linearly related to CAI. Changes in the slopes of the regression line from year to year were related to scene moisture conditions. Tillage intensity classes corresponding to conventional tillage (= 30% cover) and conservation tillage (> 30% cover) were correctly identified in 75-82% of the fields. In addition, by combining information from previous season’s crop classification with crop residue cover after planting, an inventory of soil tillage intensity by previous crop was generated for the whole Hyperion scene for each year. Inventories and maps of tillage intensity are required for field- and watershed scale models to evaluate management practices that maximize production and minimize environmental impact.