Submitted to: International Geoscience and Remote Sensing Symposium Proceedings
Publication Type: Abstract Only
Publication Acceptance Date: March 26, 2010
Publication Date: July 25, 2010
Citation: Serbin, G., Hunt, E.R., Daughtry, C.S., Brown, D.J., McCarty, G.W., Doraiswamy, P.C. 2010. Assessment of spectral indices for crop residue cover estimation [abstract]. International Geoscience and Remote Sensing Symposium Proceedings. 2010 CDROM. Technical Abstract: Agricultural soils are an important terrestrial carbon (C) stock, accounting for a significant portion of global C estimates. Soil tillage method is important in agricultural C sequestration models. Traditional intensive tillage systems greatly disturb the soil and have been shown to deplete the soil of soil organic carbon (SOC). Modern reduced- and conservation tillage systems minimally disturb the soil and leave increased quantities of crop residues (non-photosynthetic vegetation, NPV) on the soil surface after harvest and planting. These surficial crop residues act as a barrier to wind and water erosion, and act as a mulch, reducing surface evaporation. The biological breakdown of residues returns nutrients and sequesters atmospheric C to SOC. Furthermore, as reduced- and conservation tillage methods require fewer farm equipment passes in the field, fuel is saved and greenhouse gas emissions are reduced. Farmers implementing these modern tillage methods can receive governmental conservation benefits and sell C credits. As such, modern tillage methods can be more profitable for farmers to implement, even with reduced yields. However, recent fluctuations in the price of crude oil has made biofuels an attractive alternative to fossil fuels, increasing demands both for corn grain and crop residues as ethanol feedstock. In rangeland, NPV is an important parameter for soil health and forage quality, and in dry grassland, NPV serves as fuel for brush fires. A efficient method of verification of tillage via crop residue cover (fR) in needed over large swaths. Since traditional ground-based methods are not efficient nor scale-up well to the field level, remote sensing is an excellent alternative. Of the numerous remote sensing methods have been devised, two indices, the hyperspectral-based three-band Cellulose Absorption Index (CAI)and the ASTER-based two-band Shortwave Infrared Normalized Difference Residue Index (SINDRI), have shown the most promise in spatial portability and minimal calibration. While CAI is preferable, it is more costly to implement of future satellite-based advanced multispectral systems than the two SINDRI bands, which have already been flown on the Terra ASTER sensor. Thus, an analysis needs to be done to see how effective SINDRI will be for global estimation of crop residue cover in comparison with CAI.