Assessing the Spatial Distribution of Plant Litter - Daughtry, C.; Hunt, E. R.; Walthall, C. L.; Gish, T. J.; Liang, Shunlin; Kramer, E.J. (Proceedings of the Tenth JPL Airborne Earth Science Workshop, 2001)
Quantifying crop residue cover on the soil surface is important for improving estimates of surface energy balance, net primary productivity, nutrient cycling, and carbon sequestration. Quantifying crop residue cover is also an important factor in controlling soil erosion and evaluating the effectiveness of conservation tillage practices. By reducing the movement of eroded soil into streams and rivers, the movement of nutrients and pesticides is reduced. The overall result is less soil erosion and improved water quality. Current methods for quantifying crop residue cover are tedious and somewhat subjective. The standard technique for measuring crop residue cover used by the USDA Natural Resources Conservation Service (NRCS) is visual estimation along a line-transect. Reviews of crop residue measurement techniques document recent modifications and illustrate the unresolved problems of current techniques. Rapid, accurate, and objective methods to quantify residue cover are needed. The objectives of this research were to: (1) determine the spectral reflectance of green plants, plant litters, and soils as a function of water content; (2) assess the limits of discrimination that can be expected; and (3) evaluate hyperspectral imaging data for providing information on the spatial distribution of plant litter. This research provides the scientific foundation required for sensor development and field testing.

Discriminating crop residues from soil by shortwave infrared reflectance - Daughtry, Craig S. T. (Agronomy journal, 2001)
Quantifying crop residue cover on the soil surface is important for evaluating the effectiveness of conservation tillage practices. Current methods of measuring residue cover are inadequate in characterizing the spatial variability of residue cover over large fields. The objectives of this research were to determine the spectral reflectance of crop residues and soils as a function of water content and to evaluate the limits of discrimination that can be expected. Spectral reflectances of corn (Zea mays L.), soybean [Glycine max (L.) Merr.], and wheat (Triticum aestivum L.) residues plus five diverse soils were measured over the 400- to 2400-nm wavelength region at a wide range of moisture conditions in the laboratory. Reflectance factors for scenes with varying proportions of crop residues and soils were simulated. The spectra of dry crop residues displayed a broad absorption feature near 2100 nm, associated with lignin and cellulose, that was absent in spectra of soils. The relative depth of the cellulose-lignin absorption feature, defined as the cellulose absorption index (CAI), was positive for all crop residues, except those saturated with water. In contrast, all soils had negative CAI values. Water significantly altered reflectance spectra of wet crop residues, but it did not prevent the discrimination of crop residues from the soils using the CAI. The wide range of CAI values expected for dry and moist conditions makes quantification of crop residue cover feasible. This reflectance technique appears promising for field- and regional-scale surveys of crop residue cover and conservation tillage practices.
Keywords: Glycine max , Zea mays , crop residues , quantitative analysis , reflectance , infrared radiation , spatial variation , soil water content , lignin , cellulose , absorption , water content , Minnesota , Georgia , Maryland , Texas

Plant Litter and Soil Reflectance - Nagler, P. L; Daughtry, C. S. T.; Goward, S. N. (Remote Sensing of Environment, 2000)
The presence of plant litter on the soil surface influences the flow of nutrients, carbon, water, and energy in terrestrial ecosystems. Quantifying plant litter cover is important for interpreting vegetated landscapes and for evaluating the effectiveness of conservation tillage practices. Current methods of measuring litter cover are subjective, requiring considerable visual judgment. Reliable and objective methods are needed. The spectral reflectance (0.4â2.5 μm) of wet and dry soils (six types) and plant litters (2 crops, 14 forest, and 2 grasses) of different ages were measured. Discrimination of plant litters from the soils was ambiguous in the visible and near-infrared (0.4â1.1μm) wavelength region. An absorption feature associated with cellulose and lignin was observed at 2.1 μm in the spectra of dry plant litter, which was not present in the spectra of soils. A new spectral variable, cellulose absorption index (CAI), was defined using the relative depth of the reflectance spectra at 2.1 μm. CAI of dry litter was significantly greater than CAI of soils. CAI generally decreased with age of the litter. Water absorption dominated the spectral properties of both soils and plant litter and significantly reduced the CAI of the plant litters. Nevertheless, the CAI of wet litter was significantly greater then CAI of wet soil. This study provides a new methodology to discriminate plant litter from soils by differences in spectral reflectance produced by their physical and chemical attributes. This remote sensing method should improve quantification of plant litter cover and thus improve estimates of phytomass production, surface energy balance, and the effectiveness of soil conservation practices. Plant litter reflectance is a verifiable component in vegetative landscapes and should be labeled and modeled separately from soils in landscape studies.

Hyperspectral monitoring of physiological parameters of wheat during a vegetation period using AVIS data - Oppelt, N.; Mauser, W. (International Journal of Remote Sensing, 2004)
Information on the quantity and spatial distribution of canopy physiological and biochemical components is of importance for the study of nutrient cycles, productivity, vegetation stress and, more recently, in driving ecosystem models. In this context, remote sensing can play a unique and essential role because of its ability to acquire synoptic information at different time and space scales. This paper presents parts of a two-year field and laboratory study with the new airborne hyperspectral sensor, the Airborne Visible near Infrared Imaging Spectrometer (AVIS), over a test site in the Bavarian Alpine foothills, Germany (48° 8 N, 11° 17 E). The 80-band AVIS was developed at the Department for Earth and Environmental Sciences of the Ludwig-Maximilians-University Munich and records the 550-1000 nm spectral range. Using this system, 18 hyperspectral datasets were collected between April and September of 1999 and 2000. Weekly measurements of several plant parameters (height, biomass, leaf chlorophyll content, leaf nitrogen content) were carried out during these time periods on three (1999) and six (2000) fields of winter wheat, whereby two different cultivars were investigated in 2000. After system correction and calibration, the hyperspectral data were atmospherically corrected and calibrated to reflectance. The resulting spectra were analysed for their chemical compounds. The statistical analysis was carried out using the Chlorophyll Absorption Integral (CAI) in comparison to established indices: Optimized Soil-Adjusted Vegetation Index (OSAVI) and hyperspectral Normalized Difference Vegetation Index (hNDVI). Both the chlorophyll and nitrogen content of the leaves showed good correlations with CAI on a field mean basis. These results as well as two-dimensional information on these parameters are presented to provide information about the spatial heterogeneity within a field.

The IndexDatabase - Henrich, V.; Krauss, G.; Götze, C.; Sandow, C. (2011)