Elizabeth M. Middleton

EO-1 Hyperion Reflectance Time Series at Calibration and Validation Sites: Stability and Sensitivity to Seasonal Dynamics

This study evaluated Earth Observing 1 (EO-1) Hyperion reflectance time series at established calibration sites to assess the instrument stability and suitability for monitoring vegetation functional parameters. Our analysis using three pseudo-invariant calibration sites in North America indicated that the reflectance time series are devoid of apparent spectral trends and their stability consistently is within 2.5-5 percent throughout most of the spectral range spanning the 12+ year data record. Using three vegetated sites instrumented with eddy covariance towers, the Hyperion reflectance time series were evaluated for their ability to determine important variables of ecosystem function. A number of narrowband and derivative vegetation indices (VI) closely described the seasonal profiles in vegetation function and ecosystem carbon exchange (e.g., net and gross ecosystem productivity) in three very different ecosystems, including a hardwood forest and tallgrass prairie in North America, and a Miombo woodland in Africa. Our results demonstrate the potential for scaling the carbon flux tower measurements to local and regional landscape levels. The VIs with stronger relationships to the CO2 parameters were derived using continuous reflectance spectra and included wavelengths associated with chlorophyll content and/or chlorophyll fluorescence. Since these indices cannot be calculated from broadband multispectral instrument data, the opportunity to exploit these spectrometer-based VIs in the future will depend on the launch of satellites such as EnMAP and HyspIRI. This study highlights the practical utility of space-borne spectrometers for characterization of the spectral stability and uniformity of the calibration sites in support of sensor cross-comparisons, and demonstrates the potential of narrowband VIs to track and spatially extend ecosystem functional status as well as carbon processes measured at flux towers.

Optical reflectance and fluorescence for detecting nitrogen needs in Zea mays L

Nitrogen (N) status in field grown corn (Zea mays L.) was assessed using spectral techniques. Passive airborne hyperspectral reflectance remote sensing, passive leaf level reflectance, and both passive and active leaf level fluorescence sensing methods were tested. Reflectance of leaves could track total Cha levels in the red dip of the spectrum and auxiliary plant pigments of Chb and carotenoids in the yellow/orange/red edge reflectance. Based on leaf level reflectance behavior, a modified chlorophyll absorption reflectance index (MCARI) method was tested with narrow bands from the Airborne Imaging Spectroradiometer for Applications. MCARI indices could detect variations in N levels across field plots. At the leaf level, ratios of fluorescence emissions in the blue, green, red and far-red wavelengths sensed responses that were associated with the plant pigments, and were indicative of energy transfer in the photosynthetic process. Fluorescence emissions of leaves could distinguish N stressed corn from those with optimally applied N. Reflectance and fluorescence methods are sensitive in detecting corn N needs and may be especially powerful in monitoring crop conditions if both types of information can be combined.

Chlorophyll Fluorescence Emissions of Vegetation Canopies From High Resolution Field Reflectance Spectra

A two-year experiment was performed on corn (Zea mays L.) crops under nitrogen (N) fertilization regimes to examine the use of hyperspectral canopy reflectance information for estimating chlorophyll fluorescence (ChlF) and vegetation production. Fluorescence of foliage in the laboratory has proven more rigorous than reflectance for correlation to plant physiology. Especially useful are emissions produced from two stable red and far-red chlorophyll ChlF peaks centered at 685V10 nm and 735V5 nm. Methods have been developed elsewhere to extract steady state solar induced fluorescence (SF) from apparent reflectance of vegetation canopies/landscapes using the Fraunhofer Line Depth (FLD) principal. Our study utilized these methods in conjunction with field-acquired high spectral resolution canopy reflectance spectra obtained in 2004 and 2005 over corn crops, as part of an ongoing multi-year experiment at the USDA/Agriculture Research Service in Beltsville, MD. A spectroradiometer (ASD-FR Fieldspec Pro, Analytical Spectral Devices, Inc., Boulder, CO) was used to measure canopy radiances 1 m above plant canopies with a 22deg field of view and a 0deg nadir view zenith angle. Canopy and plant measurements were made at the R3 grain fill reproductive stage on 3-4 replicate N application plots provided seasonal inputs of 280, 140, 70, and 28 kg N/ha. Leaf level measurements were also made which included ChlF, photosynthesis, and leaf constituents (photosynthetic pigment, carbon (C), and N contents). Crop yields were determined at harvest. SIF intensities for ChlF were derived directly from canopy reflectance spectra in specific narrowband regions associated with atmospheric oxygen absorption features centered at 688 and 760 nm. The red/far-red S F ratio derived from these field reflectance spectra successfully discriminated foliar pigment levels (e.g., total chlorophyll, Chl) associated with N application rates in both corn crops. This canopy-level spectral ratio was also positively correlated to the foliar C/N ratio (r = 0.89, n = go), as was a leaf-level steady state fluorescence ratio (Fs/Chl, r = 0.92). The latter ratio was inversely correlated with crop grain yield (Kg 1 ha) (r = 0.9). This study has relevance to future passive satellite remote sensing approaches to monitoring C dynamics from space.

Fluorescence responses from nitrogen plant stress in 4 Fraunhofer band regions

The potential of solar Fraunhofer line features centered at 532, 607, 677 and 745nm for tracking changes in plant canopy chlorophyll content and photosynthetic capacity was studied. Excitation wavelengths similar to full sun light were considered. Canopy changes were tested experimentally by monitoring treatments of plant stress due to nitrogen application rate in corn. Corn leaves were obtained from field plots that were given different nitrogen application rates at 20, 50, 100, and 150% of optimal N in 2001. The data infers that leaves in plant canopies that have the greatest photosynthetic performance potential can be identified. Information collected in Fraunhofer regions compared favorably with data taken by laser induced fluorescence excitation and detection methods in peak emission areas. The technique may be useful in projecting what can be expected if a space-born interferometer type sensor can be developed for capturing plant canopy fluorescence.

Solar Induced Fluorescence and Reflectance Sensing Techniques for Monitoring Nitrogen Utilization in Corn

Remote sensing systems using either passive reflectance (R) or actively induced fluorescence (F) have long been explored as a means to monitor species composition and vegetative productivity. Passive F techniques using the Fraunhofer line depth (FLD) principle to isolate solar induced F (SIF) from the high resolution R continuum have also been suggested for the large-scale remote assessment of vegetation. The FLD principle was applied to both canopy R spectra and AISA multi-spectral imagery to discriminate the relatively weak in situ vegetation F in-fill of the telluric O2 bands located at 688 nm and 760 nm. The magnitudes of SIF retrieved from R ranged from 7 to 36 mW/m2/nm/sr and the ratio of the two spectral bands successfully discriminated the four N treatment levels. In addition, a number of R indices including but not limited to the physiological reflectance index (PRI), R550/R515 and R750/R800 were calculated from the AISA aircraft imagery and the high-resolution canopy R spectra. These indexes were then evaluated against georeferenced ground measurements of leaf area index (LAI), pigment contents, grain yields, and light use efficiency (LUE). A number of significant relationships were evident in both R and SIF indices to the biophysical changes in corn induced by N application rates. From this investigation we conclude that valuable SIF information can be extracted from high-resolution canopy R data and indices calculated from both data types can supply useful information for modeling N use for carbon sequestration by vegetation.