Temporally rich hyperspectral time-series can provide unique time critical information on within-field variations in vegetation health and distribution needed by farmers to effectively optimize crop production. In this study, a dense timeseries of images were acquired from the Earth Observing-1 (EO-1) Hyperion sensor over an intensive farming area in the center of Saudi Arabia. After correction for atmospheric effects, optimal links between carefully selected explanatory hyperspectral vegetation indices and target vegetation characteristics were established using a machine learning approach. A dataset of in-situ measured leaf chlorophyll (Chll) and leaf area index (LAI), collected during five intensive field campaigns over a variety of crop types, were used to train the rule-based predictive models. The ability of the narrow-band hyperspectral reflectance information to robustly assess and discriminate dynamics in foliar biochemistry and biomass through empirical relationships were investigated. This also involved evaluations of the generalization and reproducibility of the predictions beyond the conditions of the training dataset. The very high temporal resolution of the satellite retrievals constituted a specifically intriguing feature that facilitated detection of total canopy Chl and LAI dynamics down to sub-weekly intervals. The study advocates the benefits associated with the availability of optimum spectral and temporal resolution spaceborne observations for agricultural management purposes.
Scientists in the Biospheric Sciences Laboratory at NASA’s Goddard Space Flight Center have undertaken a unique instrument fusion effort for an airborne package that integrates commercial off the shelf LiDAR, Hyperspectral, and Thermal components. G-LiHT is a compact, lightweight and portable system that can be used on a wide range of airborne platforms to support a number of NASA Earth Science research projects and space-based missions. G-LiHT permits simultaneous and complementary measurements of surface reflectance, vegetation structure, and temperature, which provide an analytical framework for the development of new algorithms for mapping plant species composition, plant functional types, biodiversity, biomass, carbon stocks, and plant growth. G-LiHT and its supporting database are designed to give scientists open access to the data that are needed to understand the relationship between ecosystem form and function and to stimulate the advancement of synergistic algorithms. This system will enhance our ability to design new missions and produce data products related to biodiversity and climate change. G-LiHT has been operational since 2011 and has been used to collect data for a number of NASA and USFS sponsored studies, including NASA’s Carbon Monitoring System (CMS) and the American ICESat/GLAS Assessment of Carbon (AMIGA-Carb). These acquisitions target a broad diversity of forest communities and ecoregions across the United States and Mexico. Here, we will discuss the components of G-LiHT, their calibration and performance characteristics, operational implementation, and data processing workflows. We will also provide examples of higher level data products that are currently available.
Accurate assessment of vegetation canopy optical properties plays a critical role in monitoring natural and managed
ecosystems under environmental changes. In this context, radiative transfer (RT) models simulating vegetation canopy
reflectance have been demonstrated to be a powerful tool for understanding and estimating spectral bio-indicators. In this
study, two narrow band spectroradiometers were utilized to acquire observations over corn canopies for two summers.
These in situ spectral data were then used to validate a two-layer Markov chain-based canopy reflectance model for
simulating the Photochemical Reflectance Index (PRI), which has been widely used in recent vegetation photosynthetic
light use efficiency (LUE) studies. The in situ PRI derived from narrow band hyperspectral reflectance exhibited clear
responses to: 1) viewing geometry which affects the light environment; and 2) seasonal variation corresponding to the
growth stage. The RT model (ACRM) successfully simulated the responses to the viewing geometry. The best
simulations were obtained when the model was set to run in the two layer mode using the sunlit leaves as the upper layer
and shaded leaves as the lower layer. Simulated PRI values yielded much better correlations to in situ observations when
the cornfield was dominated by green foliage during the early growth, vegetative and reproductive stages (r = 0.78 to
0.86) than in the later senescent stage (r = 0.65). Further sensitivity analyses were conducted to show the important
influences of leaf area index (LAI) and the sunlit/shaded ratio on PRI observations.
Climate change is heavily impacted by changing vegetation cover and productivity with large scale monitoring of vegetation only possible with remote sensing techniques. The goal of this effort was to evaluate existing reflectance (R) spectroscopic methods for determining vegetation parameters related to photosynthetic function and carbon (C) dynamics in plants. Since nitrogen (N) is a key constituent of photosynthetic pigments and C fixing enzymes, biological C sequestration is regulated in part by N availability. Spectral R information was obtained from field corn grown at four N application rates (0, 70, 140, 280 kg N/ha). A hierarchy of spectral observations were obtained: leaf and canopy with a spectral radiometer; aircraft with the AISA sensor; and satellite with EO-1 Hyperion. A number of spectral R indices were calculated from these hyperspectral observations and compared to geo-located biophysical measures of plant growth and physiological condition. Top performing indices included the R derivative index D730/D705 and the normalized difference of R750 vs. R705 (ND705), both of which differentiated three of the four N fertilization rates at multiple observation levels and yielded high correlations to these carbon parameters: light use efficiency (LUE); C:N ratio; and crop grain yield. These results advocate the use of hyperspectral sensors for remotely monitoring carbon cycle dynamics in managed terrestrial ecosystems.
Patterns of change in vegetation growth and condition are one of the primary indicators of the present and future
ecological status of the globe. Nitrogen (N) is involved in photochemical processes and is one of the primary resources
regulating plant growth. As a result, biological carbon (C) sequestration is driven by N availability. Large scale
monitoring of photosynthetic processes are currently possible only with remote sensing systems that rely heavily on
passive reflectance (R) information. Unlike R, fluorescence (F) emitted from chlorophyll is directly related to
photochemical reactions and has been extensively used for the elucidation of the photosynthetic pathways. Recent
advances in passive fluorescence instrumentation have made the remote acquisition of solar-induced fluorescence
possible. The goal of this effort is to evaluate existing reflectance and emerging fluorescence methodologies for
determining vegetation parameters related to photosynthetic function and carbon sequestration dynamics in plants. Field
corn N treatment levels of 280, 140, 70, and 0 kg N / ha were sampled from an intensive test site for a multi-disciplinary
project, Optimizing Production Inputs for Economic and Environmental Enhancement (OPE). Aircraft, near-ground,
and leaf-level measurements were used to compare and contrast treatment effects within this experiment site assessed
with both reflectance and fluorescence approaches. A number of spectral indices including the R derivative index
D730/D705, the normalized difference of R750 vs. R705, and simple ratio R800/R750 differentiated three of the four N
fertilization rates and yielded high correlations to three important carbon parameters: C:N, light use efficiency, and grain
yield. These results advocate the application of hyperspectral sensors for remotely monitoring carbon cycle dynamics in
We present preliminary design studies and modeling results for a new system for the assessment of vegetation
photosynthetic function, especially carbon uptake.
Plant health and carbon uptake efficiency are of key consideration in assessing global productivity, biomass, changes in
land cover and carbon dioxide flux. Chlorophyll fluorescence (ChlF) measurements are critical for understanding
photosynthetic functioning, plant environmental stress responses and direct assessments of plant health. Plant ChlF
occurs predominately in two broad emission bands in the red and infrared regions of the spectrum. Unfortunately, the
fluorescence signal from vegetation is much weaker than, and obscured by, the reflected signal. This limitation can be
overcome by acquiring ChlF measurements in atmospheric absorption lines.
The Interferometric Sensor for Plant Fluorescence (ISPF) will measure plant ChlF using the Fraunhofer Line
Discrimination approach. Fabry-Perot (FP) etalons will be used to restrict the measurement to radiation in the Solar
Fraunhofer lines (SFL). An advantage of the proposed sensor design is that it will collect measurements using two sets
of SFL at the same time. This technique increases the optical throughput producing a larger signal to noise ratio (SNR).
The instrument is designed to have two channels for two different spectral regions. Each channel will have two sub-channels,
one defined by a prefilter (Reference, Ref) and the other having a tunable FP etalon. The first subchannel (the
Ref) will cover a relatively broad spectral range to include at least two Fraunhofer lines but for which the fluorescence
signal will represent only a small fraction of total reflected light. The second subchannel will use a FP interferometer to
restrict the detected light to include only the selected SFL where the ChlF in-filling is significant. A small change in the
fluorescence will then produce an insignificant change in the Ref subchannel but a relatively large change in signal from
the FP subchannel. Changes in albedo or clouds will affect both subchannels proportionally so that the ratio of FP/Ref
will be sensitive only to ChlF and almost insensitive to other parameters.
The ISPF sensor will measure the fluorescence energy emitted by vegetation under natural sunlight. Advantages of the
sensor over other designs are that it is passive (i.e., does not require an external illumination source), has simple structure
and can be manufactured in a rugged, monolithic form that has no moving parts.
This manuscript details the development and validation of a unique forward thinking instrument and methodology for
monitoring terrestrial carbon dynamics through synthesis of existing hyperspectal sensing and Light Detection and
Ranging (LIDAR) technologies. This technology demonstration is directly applicable to linking target mission concepts
identified as scientific priorities in the National Research Council (NRC, 2007) Earth Science Decadal Survey; namely,
DESDynI and HyspIRI. The primary components of the Hyperspec-LIDAR system are the ruggedized imaging
spectrometer and a small footprint LIDAR system. The system is mounted on a heavy duty motorized pan-tilt unit
programmed to support both push-broom style hyperspectral imaging and 3-D canopy LIDAR structural profiling. The
integrated Hyperspec-LIDAR sensor system yields a hypserspectral data cube with up to 800 bands covering the spectral
range of 400 to 1000 nm and a 3-D scanning LIDAR system accurately measuring the vertical distribution of intercepted
surfaces within a range of 150 m with an accuracy of 15 mm. Preliminary field tests of the Hyperspec-LIDAR sensor
system were conducted at a mature deciduous mixed forest tower site located at the Smithsonian Environmental
Research Center in Edgewater, MD. The goal of this research is to produce integrated science and data products from
ground observations that will support satellite-based hybrid spectral/structural profile linked through appropriate models
to monitor Net Ecosystem Exchange and related parameters such as ecosystem Light Use Efficiency.
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 fluorescence (ChlF) peaks centered at 685 nm and 735 nm. Methods have been developed elsewhere to extract steady state solar induced fluorescence (SIF) 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 and small tree plots of three deciduous species (red maple, tulip poplar, sweet gum). Leaf level measurements were also made of foliage which included ChlF, photosynthesis, and leaf constituents (photosynthetic pigment, carbon (C), and nitrogen (N) contents). As part of ongoing experiments, measurements were made on N application plots within corn (280, 140, 70, and 0 kg N/ha) and tree (0, 37.5, 75, 112.5, 150 kg N /ha) sites at the USDA/Agriculture Research Service in Beltsville, MD. SIF intensities for ChlF were derived directly from canopy reflectance spectra in specific narrow- band regions associated with atmospheric oxygen absorption features centered at 688 and 760 nm. The red/far-red SIF ratio (SIFratio) derived from these field reflectance spectra successfully discriminated foliar pigment ratios altered by N application rates in both corn crops. This ratio was also positively correlated to the C/N ratio at leaf and canopy levels, for the available corn data (e.g., 2004). No consistent N treatment or species differences in SIF were detected in the tree foliage, but additional 2005 data are forthcoming. This study has relevance to future passive satellite remote sensing approaches to monitoring C dynamics from space.
Understanding the dynamics of the global carbon cycle requires an accurate determination of the spatial and temporal distribution of photosynthetic CO2 uptake by terrestrial vegetation. Stress factors may cause sub-optimal photosynthetic function resulting in down-regulation (i.e., reduced rate of photosynthesis). Photosynthetic down-regulation is related to changes in the apparent spectral reflectance of leaves. Present approaches to determine ecosystem carbon exchange rely on meteorological data as inputs to models that predict the relative photosynthetic function in response to environmental conditions inducing stress (e.g., drought, high/low temperatures). This study examines the determination of ecosystem photosynthetic light use efficiency (LUE) from satellite observations, through measurement of vegetation spectral reflectance changes associated with physiologic stress responses. This approach is possible using the Moderate-Resolution Spectroradiometer (MODIS) on Terra to provide frequent, narrow-band measurements of high radiometric accuracy. Data from reflective MODIS ocean bands were used over land to calculate the Photochemical Reflectance Index (PRI), an index that is sensitive to reflectance changes near 531nm associated with vegetation stress responses exhibited by photosynthetic pigments. MODIS PRI values were compared with LUE calculated from values of CO2 flux measured at the overpass time at a flux tower located in a Douglas fir forest on Vancouver Island in Canada. Preliminary results show a relationship between MODIS PRI and LUE when using MODIS observations in the backscattering direction. These results compare well to previous work at a boreal aspen forest suggesting this approach may be generally useful.
The important role of nitrogen (N) in limiting or enhancing vegetation productivity is relatively well understood, although the interaction of N with other environmental variables in natural and agricultural ecosystems needs more study. In 2001, a suite of optical, fluorescence, and biophysical measurements were collected on leaves of corn (Zea Mays L.) from field plots provided four N fertilizer application rates: 20%, 50%, 100% and 150% of optimal N levels. Two complementary sets of high-resolution (< 2 nm) optical spectra were acquired for both adaxial and abaxial leaf surfaces. The first was comprised of leaf optical properties (350-2500 nm) for reflectance, transmittance, and absorptance. The second was comprised of reflectance spectra (500-1000 nm) acquired with and without a long pass 665 nm filter to determine the fluorescence contribution to "apparent reflectance" in the 670-750 nm spectrum that includes the 685 and 740 nm chlorophyll fluorescence (ChlF) peaks. Two types of fluorescence measurements were also made on adaxial and abaxial surfaces: 1) fluorescence images in four 10 nm bands (blue, green, red, far-red) resulting from broadband irradiance excitation; and 2) emission spectra at 5 nm resolution produced by three excitation wavelengths (280, 380, and 532 nm). The strongest relationships between optical properties and foliar chemistry were obtained for a "red-edge" optical parameter versus C/N and chlorophyll b. Select optical indices and ChlF parameters were correlated. A significant contribution of steady-state ChlF to apparent reflectance was observed, averaging 10-25% at 685 nm and 2-6% at 740 nm over the range of N treatments. From all measurements assessing fluorescence, higher ChlF was measured from the abaxial leaf surfaces.
A fluorescence imaging system and chlorophyll fluorescence emissions were used to evaluate whether EDU, N-[2-(2-oxo-1- imidazolidinyl) ethyl]-N'-phenylurea, provided protection against ultraviolet-B (UV-B) irradiation (290 - 320 nm) in cucumber (Cucumis sativus L.) leaves. Plants were grown in growth chambers illuminated for 14 h per day with 400 W high pressure sodium and metal halide lamps. Photosynthetically active radiation (PAR) for 1 hr at the beginning and end of each cycle was provided at 270 micrometers ol m-2 s-1 PAR; during the other 12 hr of the photoperiod, the plants received 840 micrometers ol m-2 s-1 PAR. Beginning on the twelfth day, the plants were exposed to UV-B radiation (0.2 & 18.0 kJ m-2d-1) for 2 days at 8 h per day centered in the photoperiod. Rapidly acquired (less than 1 s), high spatial resolution (less than 1 mm2) images were obtained for whole adaxial leaf surfaces using a fluorescence imaging system. The steady-state fluorescence images were acquired in four spectral regions: blue (F450 nm), green (F550 nm), red (F680 nm), and far-red (F740 nm). Fluorescence emission spectra for leaf pigments extracted in dimethyl sulfoxide (DMSO) were obtained by excitation at 280 and 380 nm (280EX 300 - 530 nm; 380EX 400 - 800 nm). Both UV-B and EDU induced stress responses in cucumber leaves that altered the fluorescence emissions obtained from extracts. In the fluorescence images only UV-B induced stress responses were observed but this damage was detected before it was visually apparent. There was no evidence that EDU afforded protection against UV-B irradiation. Use of fluorescence imaging may provide an early stress detection capability for helping to assess damage to the photosynthetic apparatus of plants.
As a part of an ongoing laser induced fluorescence (LIF) project, out laboratories have developed a fluorescence imaging system (FIS) to acquire fluorescence images at wavelengths centered at 450 nm, 550 nm, 680 nm, and 740 nm. The system consists of ultraviolet (UV) fluorescent lamps as an exciting source, automated filter wheel, and charge coupled device (CCD) camera. The automated filter wheel and CD camera are controlled by a microcomputer via a computer interface,a nd digital images are captured. The FIS is capable of capturing steady state fluorescence and chlorophyll fluorescence induction images. Experimental studies were conducted to demonstrate the utility of the FIS. One such study included experiments to observe the effects of ethylenediurea (EDU) in soybean leaves with FIS. Five different concentrations of EDU were sued to establish a doe-response relationship. Although visual effects of EDU treatment were not apparent, the intensities of the fluorescence images of the plant leaves varied depending on the EDU concentration, the location on the leaf surface and the emission wavelength. EDU appeared mainly to affect the photosynthetic apparatus causing non-uniform increases in red and far-red fluorescence. Ratio images of red-green and blue/far-red were found to be sensitive indicators in detecting EDU effects. A ratio of fluorescence induction to steady state fluorescence had a curvilinear relationship with EDU-dosage. Such kinetic measurements can be used to assess photosynthetic activity in response to a range of chemical and environmental stresses. This study demonstrates that FIS is an excellent tool to detect stress symptoms before the onset of visible injury. It will enhance our understanding of the interactions among photosynthetic activity, vegetative stresses and fluorescence responses. Characterization of steady state fluorescence patterns in leaves is of significant value in our LIF research studies, and images taken with FIS greatly complement non-imaging fluorescence measurements by finding the spatial distribution of fluorescence in leaves.
Spectral reflectances were acquired above three different coniferous forest stands. Continuous visible/near-infrared (0.400 - 1.100 micrometers ) spectra were collected at multiple (8 - 12) view angles in the solar principal plane by a spectroradiometer (SE590, Spectron Engineering, Denver, CO) placed on ground-based platforms that extended above the forest tops. Data were collected over a full sun angle range in August 1991 above a 14 m high mixed spruce-hemlock stand at a research site managed by the University of Maine in Howland. Data were also collected at multiple sun angles in June/July 1992 at the Petawawa National Forest Institute in Petawawa, Ontario, Canada above two stands: a 14 m high jack pine stand and a 18 m high red pine stand. Reflectances were calculated from calibrated radiances, and corrected for panel anisotropy per sun angle. As a function of view angle per sun angle, forwardscatter and backscatter spectra from all sites were used to compute vegetation indices and Photosynthetically Active Radiation (PAR, 0.400 - 0.700 micrometers ) reflectance. These unique data sets reveal that these forest stands were highly anisotropic, both in terms of sun angle, view angle, and spectral wavebands. Additionally, the vegetation indices exhibited sun and view angle changes, with maximum values at moderately oblique forwardscatter view angles (approximately 30 - 40 degree(s)).