Pablo J. Zarco-Tejada

Integrated narrow-band vegetation indices for prediction of crop chlorophyll content for application to precision agriculture

Recent studies have demonstrated the usefulness of optical indices from hyperspectral remote sensing in the assessment of vegetation biophysical variables both in forestry and agriculture. Those indices are, however, the combined response to variations of several vegetation and environmental properties, such as Leaf Area Index (LAI), leaf chlorophyll content, canopy shadows, and background soil reflectance. Of particular significance to precision agriculture is chlorophyll content, an indicator of photosynthesis activity, which is related to the nitrogen concentration in green vegetation and serves as a measure of the crop response to nitrogen application. This paper presents a combined modeling and indices-based approach to predicting the crop chlorophyll content from remote sensing data while minimizing LAI (vegetation parameter) influence and underlying soil (background) effects. This combined method has been developed first using simulated data and followed by evaluation in terms of quantitative predictive capability using real hyperspectral airborne data. Simulations consisted of leaf and canopy reflectance modeling with PROSPECT and SAILH radiative transfer models. In this modeling study, we developed an index that integrates advantages of indices minimizing soil background effects and indices that are sensitive to chlorophyll concentration. Simulated data have shown that the proposed index Transformed Chlorophyll Absorption in Reflectance Index/Optimized Soil-Adjusted Vegetation Index (TCARI/OSAVI) is both very sensitive to chlorophyll content variations and very resistant to the variations of LAI and solar zenith angle. It was therefore possible to generate a predictive equation to estimate leaf chlorophyll content from the combined optical index derived from above-canopy reflectance. This relationship was evaluated by application to hyperspectral CASI imagery collected over corn crops in three experimental farms from Ontario and Quebec, Canada. The results presented here are from the L’Acadie, Quebec, Agriculture and AgriFood Canada research site. Images of predicted leaf chlorophyll content were generated. Evaluation showed chlorophyll variability over crop plots with various levels of nitrogen, and revealed an excellent agreement with ground truth, with a correlation of r 2 =.81 between estimated

Scaling-up and model inversion methods with narrowband optical indices for chlorophyll content estimation in closed forest canopies with hyperspectral data

Radiative transfer theory and modeling assumptions were applied at laboratory and field scales in order to study the link between leaf reflectance and transmittance and canopy hyper-spectral data for chlorophyll content estimation. This study was focused on 12 sites of Acer saccharum M. (sugar maple) in the Algoma Region, Canada, where field measurements, laboratory-simulation experiments, and hyper-spectral compact airborne spectrographic imager (CASI) imagery of 72 channels in the visible and near-infrared region and up to 1-m spatial resolution data were acquired in the 1997, 1998, and 1999 campaigns. A different set of 14 sites of the same species were used in 2000 for validation of methodologies. Infinite reflectance and canopy reflectance models were used to link leaf to canopy levels through radiative transfer simulation. The closed and dense (LAI>4) forest canopies of Acer saccharum M. used for this study, and the high spatial resolution reflectance data targeting crowns, allowed the use of optically thick simulation formulae and turbid-medium SAILH and MCRM canopy reflectance models for chlorophyll content estimation by scaling-up and by numerical model inversion approaches through coupling to the PROSPECT leaf radiative transfer model. Study of the merit function in the numerical inversion showed that red edge optical indices used in the minimizing function such as R/sub 750//R/sub 710/ perform better than when all single spectral reflectance channels from hyper-spectral airborne CASI data are used, and in addition, the effect of shadows and LAI variation are minimized.

Water content estimation in vegetation with MODIS reflectance data and model inversion methods

Statistical and radiative-transfer physically based studies have previously demonstrated the relationship between leaf water content and leaf-level reflectance in the near-infrared spectral region. The successful scaling up of such methods to the canopy level requires modeling the effect of canopy structure and viewing geometry on reflectance bands and optical indices used for estimation of water content, such as normalized difference water index (NDWI), simple ratio water index (SRWI) and plant water index (PWI). This study conducts a radiative transfer simulation, linking leaf and canopy models, to study the effects of leaf structure, dry matter content, leaf area index (LAI), and the viewing geometry, on the estimation of leaf equivalent water thickness from canopy-level reflectance. The applicability of radiative transfer model inversion methods to MODIS is studied, investigating its spectral capability for water content estimation. A modeling study is conducted, simulating leaf and canopy MODIS-equivalent synthetic spectra with random input variables to test different inversion assumptions. A field sampling campaign to assess the investigated simulation methods was undertaken for analysis of leaf water content from leaf samples in 10 study sites of chaparral vegetation in California, USA, between March and September 2000. MODIS reflectance data were processed from the same period for equivalent water thickness estimation by model inversion linking the PROSPECT leaf model and SAILH canopy reflectance model. MODIS reflectance data, viewing geometry values, and LAI were used as inputs in the model inversion for estimation of leaf equivalent water thickness, dry matter, and leaf structure. Results showed good correlation between the time series of MODIS-estimated equivalent water thickness and ground measured leaf fuel moisture (LFM) content (r 2 =0.7), demonstrating that these

Steady-state chlorophyll a fluorescence detection from canopy derivative reflectance and double-peak red-edge effects

Abstract A series of experiments carried out in a controlled environment facility to induce steady-state chlorophyll a fluorescence variation demonstrate that natural fluorescence emission is observable on the derivative reflectance spectra as a double-peak feature in the 690–710 nm spectral region. This work describes that the unexplained double-peak feature previously seen on canopy derivative reflectance is due entirely to chlorophyll fluorescence (CF) effects, demonstrating the importance of derivative methods for fluorescence detection in vegetation. Measurements were made in a controlled environmental chamber where temperature and humidity were varied through the time course of the experiments in both short- and long-term trials using Acer negundo ssp. californium canopies. Continuous canopy reflectance measurements were made with a spectrometer on healthy and stressed vegetation, along with leaf-level steady-state fluorescence measurements with the PAM-2000 Fluorometer during both temperature–stress induction and recovery stages. In 9-h trials, temperatures were ramped from 10 to 35 °C and relative humidity adjusted from 92% to 42% during stress induction, returning gradually to initial conditions during the recovery stage. Canopy reflectance difference calculations and derivative analysis of reflectance spectra demonstrate that a double-peak feature created between 688, 697 and 710 nm on the derivative reflectance is a function of natural steady-state fluorescence emission, which gradually diminished with induction of maximum stress. Derivative reflectance indices based on this double-peak feature are demonstrated to track natural steady-state fluorescence emission as quantified by two indices, the double-peak index (DPi) and the area of the double peak (Adp). Results obtained employing these double-peak indices from canopy derivative reflectance suggest a potential for natural steady-state fluorescence detection with hyperspectral data. Short- and long-term stress effects on the observed double-peak derivative indices due to pigment degradation and canopy structure changes were studied, showing that both indices are capable of tracking steady-state fluorescence changes from canopy remote sensing reflectance.

Chlorophyll Fluorescence Effects on Vegetation Apparent Reflectance: I. Leaf-Level Measurements and Model Simulation

Results from a series of laboratory measurements of spectral reflectance and transmittance of individual leaves and from a modeling study are presented which demonstrate that effects of natural chlorophyll fluorescence (CF) are observable in the red edge spectral region. Measurements have been made with a Li-Cor Model 1800 integrating sphere apparatus coupled to an Ocean Optics Model ST1000 fiber spectrometer in which the same leaves are illuminated alternately with and without fluorescence-exciting radiation in order to separate the fluorescence emission component from the reflectance spectrum. The resulting difference spectrum is shown experimentally to be consistent with a fluorescence signature imposed on the inherent leaf reflectance signature. A study of the diurnal change in leaf reflectance spectra, combined with fluorescence measurements with the PAM-2000 Fluorometer, show that the difference spectra are consistent with observed diurnal changes in steady-state fluorescence. In addition, the time decay in the difference signature from repetitive leaf spectral reflectance measurements is seen to be consistent with the time decay of the leaf fluorescence signal (Kautsky effect) of dark-adapted leaves. The expected effects of chlorophyll fluorescence emission on the apparent spectral reflectance from a single leaf are also simulated theoretically using the doubling radiative transfer method. These modeling results demonstrate that the laboratory observations of a difference spectrum with broad peak at about 750 nm and a much smaller peak near 690 nm are in agreement with theory. Model simulation shows that chlorophyll pigment and fluorescence each affect indices that are being used in optical remote sensing to characterize pigment levels and stress in vegetation canopies. Implications for high spectral resolution remote sensing of forest canopies are presented in a companion paper.

Chlorophyll fluorescence effects on vegetation apparent reflectance : II. Laboratory and Airborne canopy-level measurements with hyperspectral data

Abstract Relationships found between Compact Airborne Spectrographic Imager (CASI) hyperspectral canopy reflectance measurements at laboratory and field levels with PAM-2000 chlorophyll fluorescence data are presented. This is a continuation of the paper where relationships at the leaf level between leaf reflectance and chlorophyll fluorescence were found and demonstrated to be consistent with theory using the Fluorescence-Reflectance-Transmittance (FRT) model. Experiments using the hyperspectral CASI sensor in the laboratory to observe a canopy of maple seedlings are performed as an intermediate step to demonstrate the link between the results at leaf-level and the CASI field canopy levels. Scene observations of the seedlings utilizing a long-pass blocking filter showed that apparent canopy reflectance in the laboratory is affected by changes in fluorescence emissions. A laboratory experiment on seedlings subjected to diurnally induced change shows the strong link between CASI canopy reflectance optical indices in the 680–690-nm region and Fv/Fm dark-adapted chlorophyll fluorescence. Stressed and healthy maple seedlings are used to demonstrate the use of optical indices calculated from the 680–690-nm spectral region to track changes in steady-state fluorescence: the curvature index R683 2 /(R675·R691) and the R685/R655 ratio calculated from the canopy reflectance are related to leaf-measured Ft, Fm′ and ΔF/Fm′ steady-state features, and are in agreement with theoretical simulations using the leaf Fluorescence-Reflectance-Transmittance model. To test these findings in a field setting, airborne field hyperspectral CASI data of 2-m spatial resolution, 7.5-nm spectral resolution, and 72 channels was used, collected in deployments over 12 sites of Acer saccharum M. in the Algoma Region, Ontario (Canada) in 1997 and 1998. A field sampling campaign was carried out for biochemical contents of leaf chlorophyll and carotenoids, chlorophyll fluorescence, and leaf reflectance and transmittance. Leaf-level relationships obtained between optical indices and physiological indicators were scaled up to canopy level through canopy reflectance models using input model parameters related to the canopy structure and viewing geometry at the time of data acquisition. Results show that scaled-up optical indices in the 680–690-nm region are related to Fv/Fm chlorophyll fluorescence measured in the 20×20-m study sites. Consistency between leaf, laboratory, and field canopy hyperspectral data is shown in this and the previous paper, demonstrating the effect of fluorescence on observations of apparent vegetation reflectance.

Modeling canopy water content for carbon estimates from MODIS data at land EOS validation sites

This paper reports on progress made to improve our understanding of the biophysical and ecological processes governing the linked exchanges of water, energy, carbon and trace gases between the terrestrial biosphere and the atmosphere by improving satellite data products for models. The project aims to tests new biophysical data products from MODIS and ASTER EOS sensors and incorporates them into the SiB2 and CASA models. Traditional carbon estimates of such models use NDVI satellite data as inputs, although it is known that NDVI saturates at high LAI values. Radiative transfer models PROSPECT, SAILH and SPRINT were used to study a water-based optical index from MODIS as a measure of canopy water content that potentially improves estimates of LAI, specifically for ecosystems having high LAI (>4). This study shows the validity of the new data product and the. potential extent of model improvements for biospheric and atmospheric processes. Validation of the models and the data products is conducted at EOS core land validation sites part of AmeriFlux.

Estimation of chlorophyll fluorescence under natural illumination from hyperspectral data

This paper reports a series of laboratory and field measurements of spectral reflectance under artificial and natural light conditions which demonstrate that effects of natural chlorophyll fluorescence are observable in the reflectance red edge spectral region. These are results from the progress made to link physiologically-based indicators to optical indices from hyperspectral remote sensing in the Bioindicators of Forest Sustainability Project. This study is carried out on twelve sites of Acer saccharum M. in the Algoma Region, Ontario (Canada), where field measurements, laboratory-simulation experiments, and hyperspectral CASI imagery have been carried out in 1997, 1998, 1999 and 2000 campaigns. Leaf samples from the study sites have been used for reflectance and transmittance measurements with the Li-Cor Model 1800 integrating sphere apparatus coupled to an Ocean Optics Model ST1000 fibre spectrometer in which the same leaves are illuminated alternatively with and without fluorescence-exciting radiation. A study of the diurnal change in leaf reflectance spectra, combined with fluorescence measurements with the PAM-2000 Fluorometer show that the difference spectra are consistent with observed diurnal changes in steady-state fluorescence. Small canopies of Acer saccharum M. have been used for laboratory measurements with the CASI hyperspectral sensor, and under natural light conditions with a fibre spectrometer in diurnal trials, in which the variation of measured reflectance is shown experimentally to be consistent with a fluorescence signature imposed on the inherent leaf reflectance signature. Such reflectance changes due to CF are measurable under natural illumination conditions, although airborne experiments with the CASI hyperspectral sensor produced promising but less convincing results in two diurnal experiments carried out in 1999 and 2000, where small variations of reflectance due to the effect of CF were observed.

Progress on the development of an integrated canopy fluorescence model

Typical environment plant stress factors are excess of light, deficiencies of water and nutrients, temperature extremes, diseases, pests and pollutants. An early indicator for vegetation status and vitality by means of remote sensing would therefore serve a range of applications such as renewable resource management and precision farming. Vegetation fluorescence is a direct indicator for plant physiology, and could therefore be used as an early indicator for vegetation health status and vitality. Vegetation chlorophyll fluorescence is a function of photochemical processes and efficiency, which are directly linked to primary productivity and CO/sub 2/ flux from the atmosphere, and could therefore also provide a means to assess the terrestrial carbon cycle. A study was launched in October 2002 by the European Space Agency to advance the underlying science of a possible future vegetation fluorescence space mission by addressing the need for an integrated canopy fluorescence model. The objective of this study is to review and advance existing fluorescence models at the leaf level and to integrate these into canopy models in order to simulate the combined spectral reflected radiance and passive fluorescence emission signals. This model is to be validated with new and existing field campaign measurements. This paper reports on the status of this project, the input radiometric and photosynthetic variables have been selected to define the vegetation fluorescence signal consisting of far-red and red-chlorophyll fluorescence as spectral emission features, normalized to the canopy illumination levels, when linked to the leaf-level fluorescence reflectance-transmittance model defined in this study. Measurement protocols to validate fluorescence-leaf models will be defined.

Canopy optical indices from infinite reflectance and canopy reflectance models for forest condition monitoring: application to hyperspectral CASI data

This paper reports on progress made to link physiologically-based indicators to optical indices from hyperspectral remote sensing. This study is carried out on twelve sites of Acer saccharum M. in the Algoma Region, Ontario (Canada), where field measurements and hyperspectral CASI imagery have been collected in 1997 and 1998 deployments. Individual tree samples were collected at each site for biochemical analysis and measurement of leaf chlorophyll, chlorophyll fluorescence and carotenoid concentrations, as well as leaf reflectance and transmittance. Physiological indices and derivative analysis indices extracted from leaf spectral reflectance have been tested at canopy level using CASI data of 72 channels and 2 m spatial resolution at 3 simulation scales which progressively more closely represent the observed above-canopy reflectance spectra from the sites: single leaf reflectance data, infinite reflectance calculated from optically-thick leaf simulation formulae, and canopy reflectance models using nominal site canopy architecture data. This study shows that selected algorithms connecting leaf reflectance and transmittance data to corresponding bioindicators at the leaf level can be expressed at canopy level through canopy models yielding predictions of bioindicators in airborne imaging spectrometer with coefficients of determination as high as 0.91.