Modeling gross primary production of temperate deciduous broadleaf forest using satellite images and climate data

Net ecosystem exchange (NEE) of CO₂ between the atmosphere and forest ecosystems is determined by gross primary production (GPP) of vegetation and ecosystem respiration. CO₂ flux measurements at individual CO₂ eddy flux sites provide valuable information on the seasonal dynamics of GPP. In this paper, we developed and validated the satellite-based Vegetation Photosynthesis Model (VPM), using site-specific CO₂ flux and climate data from a temperate deciduous broadleaf forest at Harvard Forest, Massachusetts, USA. The VPM model is built upon the conceptual partitioning of photosynthetically active vegetation and non-photosynthetic vegetation (NPV) within the leaf and canopy. It estimates GPP, using satellite-derived Enhanced Vegetation Index (EVI), Land Surface Water Index (LSWI), air temperature and photosynthetically active radiation (PAR). Multi-year (1998-2001) data analyses have shown that EVI had a stronger linear relationship with GPP than did the Normalized Difference Vegetation Index (NDVI). Two simulations of the VPM model were conducted, using vegetation indices from the VEGETATION (VGT) sensor onboard the SPOT-4 satellite and the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard the Terra satellite. The predicted GPP values agreed reasonably well with observed GPP of the deciduous broadleaf forest at Harvard Forest, Massachusetts. This study highlighted the biophysical performance of improved vegetation indices in relation to GPP and demonstrated the potential of the VPM model for scaling-up of GPP of deciduous broadleaf forests.     

Simple reflectance indices track heat and water stress-induced changes in steady-state chlorophyll fluorescence at the canopy scale

Non-invasive remote sensing techniques for monitoring plant stress and photosynthetic status have received much attention. The majority of published vegetation indices are not sensitive to rapid changes in plant photosynthetic status brought on by common environmental stressors such as diurnal fluxes in irradiance and heat. This is due to the fact that most vegetation indices have no direct link to photosynthetic functioning beyond their sensitivity to canopy structure and pigment concentration changes. In contrast, this study makes progress on a more direct link between passive reflectance measurements and plant physiological status through an understanding of photochemical quenching (qP) and non-photochemical quenching processes. This is accomplished through the characterization of steady-state fluorescence (Fs) and its influence on apparent reflectance in the red-edge spectral region. A series of experiments were conducted under controlled environmental conditions, linking passive reflectance measurements of a grapevine canopy (Vitis vinifera L. cv. Cabernet Sauvignon) to leaf level estimates of CO₂ assimilation (A), stomatal conductance (g), qP, and Fs. Plant stress was induced by imposing a diurnal heat stress and recovery event and by withholding water from the plant canopy over the course of the experiment. We outlined evidence for a link between Fs and photosynthetic status, identified the Fs signal in passive remote sensing reflectance data, and related reflectance-derived estimates of Fs to plant photosynthetic status. These results provide evidence that simple reflectance indices calculated in the red-edge spectral region can track temperature and water-induced changes in Fs and, consequently, provide a rapid assessment of plant stress that is directly linked to plant physiological processes.     

The role of directional LAI in determining the fAPAR–NDVI relationship when using active optical sensors in tall fescue (Festuca arundinacea) pasture

Remote sensing based spectral indices, such as the normalized difference vegetation index (NDVI), are often used to estimate the fraction of absorbed photosynthetically active radiation (fAPAR) in plant canopies. Owing to similar changes in both the NDVI and fAPAR as functions of varying solar illumination angle when using entirely passive sensors, the fAPAR–NDVI relationships are often stable, appearing insensitive to solar illumination angle. Active optical sensors (AOS) on the other hand, which have their own illuminating light source and are increasingly being used to measure NDVI (NDVI_AOS), do not respond to solar illumination geometry. Yet, the passive sensor-derived fAPAR component of the fAPAR–NDVI_AOS relationship remains affected by solar illumination angle. In this paper, a simple two-stream canopy model has been used to predict the fAPAR–NDVI_AOS relationships of a pasture canopy (tall fescue; Festuca arundinacea) for a nadir-viewing active optical NDVI sensor under conditions of varying solar elevation angle. Both the model derived and subsequent experimental measurements of the fAPAR–NDVI_AOS relationship in this pasture confirmed a strong dependence of the linear fAPAR–NDVI_AOS relationships on solar illumination angle. The modelled fAPAR–NDVI_AOS relationship only agreed with the field measurements when the ‘solar angle–dependent directional leaf area index’ (LAI_θs) of the canopy, as presented to the incoming solar photons, was used as opposed to the traditionally used ‘nadir version’ of the leaf area index (LAI). Users of AOS to measure indices such as NDVI must account for the solar illumination angle dependent LAI_θs when considering any fAPAR–NDVI_AOS relationship.     

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

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 (A_dp). 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.     

Responses of the reflectance indices PRI and NDVI to experimental warming and drought in European shrublands along a north-south climatic gradient

The aim of this study was to evaluate the use of ground-based canopy reflectance measurements to detect changes in physiology and structure of vegetation in response to experimental warming and drought treatment at six European shrublands located along a North-South climatic gradient. We measured canopy reflectance, effective green leaf area index (green LAIe) and chlorophyll fluorescence of dominant species. The treatment effects on green LAIe varied among sites. We calculated three reflectance indices: photochemical reflectance index PRI [531 nm; 570 nm], normalized difference vegetation index NDVI₆₈₀ [780 nm; 680 nm] using red spectral region, and NDVI₅₇₀ [780 nm; 570 nm] using the same green spectral region as PRI. All three reflectance indices were significantly related to green LAIe and were able to detect changes in shrubland vegetation among treatments. In general warming treatment increased PRI and drought treatment reduced NDVI values. The significant treatment effect on photochemical efficiency of plants detected with PRI could not be detected by fluorescence measurements. However, we found canopy level measured PRI to be very sensitive to soil reflectance properties especially in vegetation areas with low green LAIe. As both soil reflectance and LAI varied between northern and southern sites it is problematic to draw universal conclusions of climate-derived changes in all vegetation types based merely on PRI measurements. We propose that canopy level PRI measurements can be more useful in areas of dense vegetation and dark soils.     

Modeling gross primary production of alpine ecosystems in the Tibetan Plateau using MODIS images and climate data

The eddy covariance technique provides measurements of net ecosystem exchange (NEE) of CO₂ between the atmosphere and terrestrial ecosystems, which is widely used to estimate ecosystem respiration and gross primary production (GPP) at a number of CO₂ eddy flux tower sites. In this paper, canopy-level maximum light use efficiency, a key parameter in the satellite-based Vegetation Photosynthesis Model (VPM), was estimated by using the observed CO₂ flux data and photosynthetically active radiation (PAR) data from eddy flux tower sites in an alpine swamp ecosystem, an alpine shrub ecosystem and an alpine meadow ecosystem in Qinghai-Tibetan Plateau, China. The VPM model uses two improved vegetation indices (Enhanced Vegetation Index (EVI), Land Surface Water Index (LSWI)) derived from the Moderate Resolution Imaging Spectral radiometer (MODIS) data and climate data at the flux tower sites, and estimated the seasonal dynamics of GPP of the three alpine grassland ecosystems in Qinghai-Tibetan Plateau. The seasonal dynamics of GPP predicted by the VPM model agreed well with estimated GPP from eddy flux towers. These results demonstrated the potential of the satellite-driven VPM model for scaling-up GPP of alpine grassland ecosystems, a key component for the study of the carbon cycle at regional and global scales.     

Impact of nutrients on peatland GPP estimations using MODIS time series data

Time series of satellite sensor-derived data can be used in the light use efficiency (LUE) model for gross primary productivity (GPP). The LUE model and a closely related linear regression model were studied at an ombrotrophic peatland in southern Sweden. Eddy covariance and chamber GPP, incoming and reflected photosynthetic photon flux density (PPFD), field-measured spectral reflectance, and data from the Moderate Resolution Imaging Spectroradiometer (MODIS) were used in this study. The chamber and spectral reflectance measurements were made on four experimental treatments: unfertilized control (Ctrl), nitrogen fertilized (N), phosphorus fertilized (P), and nitrogen plus phosphorus fertilized (NP). For Ctrl, a strong linear relationship was found between GPP and the photosynthetically active radiation absorbed by vegetation (APAR) (R² = 0.90). The slope coefficient (ε_s, where s stands for “slope”) for the linear relationship between seasonal time series of GPP and the product of the normalized difference vegetation index (NDVI) and PPFD was used as a proxy for the light use efficiency factor (ε). There were differences in ε_s depending on the treatments with a significant effect for N compared to Ctrl (ANOVA: p = 0.042, Tukey's: p ≤ 0.05). Also, ε_s was linearly related to the cover degree of vascular plants (R² = 0.66). As a sensitivity test, the regression coefficients (ε_s and intercept) for each treatment were used to model time series of 16-day GPP from the product of MODIS NDVI and PPFD. Seasonal averages of GPP were calculated for 2005, 2006, and 2007, which resulted in up to 19% higher average GPP for the fertilization treatments compared to Ctrl. The main conclusion is that the LUE model and the regression model can be applied in peatlands but also that temporal and spatial changes in ε or the regression coefficients should be considered.     

Utility of spectral vegetation index for estimation of gross CO2 flux under varied sky conditions

To estimate the gross CO₂ flux (F_CO2) of deciduous coniferous forest from canopy spectral reflectance, we introduced spectral vegetation indices (VIs) into a light use efficiency (LUE) model of mature Japanese larch (Larix kaempferi) forest. We measured the eddy covariance CO₂ flux and spectral reflectance of larch canopy at half-hourly intervals during one growing season, and investigated the relationships between the parameters of the LUE model (FAPAR, ?) and 3 types of VIs (NDVI, PRI, EVI) in both clear sky and cloudy conditions.FAPAR (fraction of absorbed photosynthetically active radiation) had a positive linear relationship with both NDVI (normalized difference vegetation index) and EVI (enhanced vegetation index), and the sky condition had little effect on the relationships. The relative RMSE (root mean square error) of the APAR (absorbed photosynthetically active radiation) based on the incoming PAR and estimated FAPAR from a linear function of NDVI was less than 10.5%, irrespective of sky condition.Half-hourly values of ? (conversion efficiency of absorbed energy) showed both seasonal variation related to leaf phenology and short-term variation related to light intensity due to varied sun position and sky condition. Both EVI and PRI (photochemical reflectance index) were significantly correlated with ?. EVI showed a positive linear relationship with ? as a result of their similar seasonal variation. However, since EVI did not detect short-term variation of ?, their relationship differed among sky conditions. On the other hand, although PRI could trace the short-term variation of ? in green needles, the relationship became non-linear due to drastic reduction of PRI in the senescent needles.EVI/(PRI/PRI_min), a combined index based on a 6-day moving minimum value of PRI (PRI_min), showed a linear relationship with half-hourly values of ? throughout the seasons irrespective of sky condition. This index allow us to estimate ? in all sky conditions with a smaller error (rRMSE = 35.2%) than using EVI or PRI alone (38.7%-48.7%). Consequently, this combined index-derived ? and NDVI-based FAPAR gave a low estimation error of F_CO2 (rRMSE = 36.4%, RMSE = 8.3 μmol m^− 2 s^− 1). Although there are still various issues to resolve, including adaptive limit and combination of vegetation index type, we conclude that the combination of PRI and EVI increased the accuracy of estimation of CO₂ uptake in deciduous forest even though sky conditions varied.     

Correlation between soil apparent electroconductivity and plant hyperspectral reflectance in a managed wetland

The apparent electrical conductivity (σ_a) of soil is influenced by a complex combination of soil physical and chemical properties. For this reason, σ_a is proposed as an indicator of plant stress and potential community structure changes in an alkaline wetland setting. However, assessing soil σ_a is relatively laborious and difficult to accomplish over large wetland areas. This work examines the feasibility of using the hyperspectral reflectance of the vegetation canopy to characterize the σ_a of the underlying substrate in a study conducted in a Central California managed wetland. σ_a determined by electromagnetic (EM) inductance was tested for correlation with in-situ hyperspectral reflectance measurements, focusing on a key waterfowl forage species, swamp timothy (Crypsis schoenoides). Three typical hyperspectral indices, individual narrow-band reflectance, first-derivative reflectance and a narrow-band normalized difference spectral index (NDSI), were developed and related to soil σ_a using univariate regression models. The coefficient of determination (R ²) was used to determine optimal models for predicting σ_a, with the highest value of R ² at 2206 nm for the individual narrow bands (R ²?=?0.56), 462 nm for the first-derivative reflectance (R ²?=?0.59), and 1549 and 2205 nm for the narrow-band NDSI (R ²?=?0.57). The root mean squared error (RMSE) and relative root mean squared error (RRMSE) were computed using leave-one-out cross-validation (LOOCV) for accuracy assessment. The results demonstrate that the three indices tested are valid for estimating σ_a, with the first-derivative reflectance performing better (RMSE?=?30.3 mS m^?1, RRMSE?=?16.1%) than the individual narrow-band reflectance (RMSE?=?32.3 mS m^?1, RRMSE?=?17.1%) and the narrow-band NDSI (RMSE?=?31.5 mS m^?1, RRMSE?=?16.7%). The results presented in this paper demonstrate the feasibility of linking plant–soil σ_a interactions using hyperspectral indices based on in-situ spectral measurements.     

Satellite-based modeling of gross primary production in an evergreen needleleaf forest

The eddy covariance technique provides valuable information on net ecosystem exchange (NEE) of CO₂, between the atmosphere and terrestrial ecosystems, ecosystem respiration, and gross primary production (GPP) at a variety of CO₂ eddy flux tower sites. In this paper, we develop a new, satellite-based Vegetation Photosynthesis Model (VPM) to estimate the seasonal dynamics and interannual variation of GPP of evergreen needleleaf forests. The VPM model uses two improved vegetation indices (Enhanced Vegetation Index (EVI), Land Surface Water Index (LSWI)). We used multi-year (1998-2001) images from the VEGETATION sensor onboard the SPOT-4 satellite and CO₂ flux data from a CO₂ eddy flux tower site in Howland, Maine, USA. The seasonal dynamics of GPP predicted by the VPM model agreed well with observed GPP in 1998-2001 at the Howland Forest. These results demonstrate the potential of the satellite-driven VPM model for scaling-up GPP of forests at the CO₂ flux tower sites, a key component for the study of the carbon cycle at regional and global scales.     

Remote sensing of tundra gross ecosystem productivity and light use efficiency under varying temperature and moisture conditions

Satellite observations have shown greening trends in tundra in response to climate change, suggesting increases in productivity. To better understand the ability of remote sensing to detect climate impacts on tundra vegetation productivity, we applied a photosynthetic light use efficiency model to simulated climate change treatments of tundra vegetation. We examined changes in the Normalized Difference Vegetation Index (NDVI) and photosynthetic light use efficiency (ε) in experimental warming and moisture treatments designed to simulate climate change in northern Alaska. Plots were warmed either passively, using Open Top Chambers, or actively using electric heaters in the soil. In one set of plots water table depth was actively altered, while other plots were established in locations that were naturally wet or dry. Over two growing seasons, plot-level carbon flux and spectral reflectance measurements were collected, and the results were used to derive a light use efficiency model that could explore the effects of moisture and temperature treatments using remote sensing.Warming increased values of canopy greenness (NDVI) relative to control plots, this effect being more pronounced in wet plots than in dry plots. Light use efficiency (LUE), the relationship between absorbed photosynthetically active radiation (PAR) and gross ecosystem production (GEP), was consistent across warming treatments, growing season, subsequent years, and sites. However, LUE was affected by vegetation type, which varied with moisture; plots in naturally dry locations showed reduced light use efficiency relative to moist plots. Additionally moss exhibited reduced LUE relative to vascular plants. Understory moss production, not accounted for by the usual definition of the fraction of absorbed PAR (f_APAR), was found to be a significant part of total GEP, particularly in areas with low vascular plant cover. These results support the use of light use efficiency models driven by spectral reflectance for estimating GEP in tundra vegetation, provided effects of vegetation functional type (e.g. mosses versus vascular plants) and microtopography are considered.     

New spectral vegetation indices based on the near-infrared shoulder wavelengths for remote detection of grassland phytomass

This article examines the possibility of exploiting ground reflectance in the near-infrared (NIR) for monitoring grassland phytomass on a temporal basis. Three new spectral vegetation indices (infrared slope index, ISI; normalized infrared difference index, NIDI; and normalized difference structural index, NDSI), which are based on the reflectance values in the H25 (863–881 nm) and the H18 (745–751 nm) Chris Proba (mode 5) bands, are proposed. Ground measurements of hyperspectral reflectance and phytomass were made at six grassland sites in the Italian and Austrian mountains using a hand-held spectroradiometer. At full canopy cover, strong saturation was observed for many traditional vegetation indices (normalized difference vegetation index (NDVI), modified simple ratio (MSR), enhanced vegetation index (EVI), enhanced vegetation index 2 (EVI 2), renormalized difference vegetation index (RDVI), wide dynamic range vegetation index (WDRVI)). Conversely, ISI and NDSI were linearly related to grassland phytomass with negligible inter-annual variability. The relationships between both ISI and NDSI and phytomass were however site specific. The WinSail model indicated that this was mostly due to grassland species composition and background reflectance. Further studies are needed to confirm the usefulness of these indices (e.g. using multispectral specific sensors) for monitoring vegetation structural biophysical variables in other ecosystem types and to test these relationships with aircraft and satellite sensors data. For grassland ecosystems, we conclude that ISI and NDSI hold great promise for non-destructively monitoring the temporal variability of grassland phytomass.     

Monitoring drought effects on vegetation water content and fluxes in chaparral with the 970 nm water band index

The goal of this study was to explore the utility of the 970 nm water band index (WBI) in estimating evapotranspiration and vegetation water status for a semiarid shrubland ecosystem. Between 2001 and 2003, spectral reflectance coupled with CO₂ and water flux data were collected at Sky Oaks Biological Field Station, a chaparral-dominated ecosystem in southern California, and one of the sites within the SpecNet network. The reflectance data were collected either by walking along a 100 m transect or by using a semi-automated tram system installed later at the site along the same 100 m transect. CO₂ and water flux data were gathered with an eddy covariance flux tower adjacent to the tram system. The 970 nm WBI and normalized difference vegetation index (NDVI) were derived from the spectral reflectance. The two indices were expressed both as points approximately a meter apart along the transect and as whole-transect averages, where all of the reflectance values along the transect were averaged together, simulating a large pixel. This study encompassed a wet year with normal precipitation (2001), a 100-year record drought (2002), and a recovery year (2003), allowing for comparison over time and between precipitation regimes. Species-specific responses to wet and dry periods were evident in the reflectance spectra, providing a basis for separating species based on their optical properties. The WBI was significantly correlated with the NDVI revealing a strong link between canopy water content and green canopy structure; however this relationship varied with species and water status, providing evidence for the independence of these two optical indices. The WBI was also strongly linked to surface-atmosphere fluxes, explaining 49% of the variance in the water vapor flux, and 24% of the carbon dioxide fluxes. These results suggest that WBI or other similar water status indices may be useful variables in modeling CO₂ and water fluxes when combined with other physiological, environmental, and atmospheric factors.     

MODIS spectral signals at a flux tower site: Relationships with high-resolution data, and CO2 flux and light use efficiency measurements

In this study, spectral indices were calculated from single date HyMap (3 m; 126 bands), Hyperion (30 m; 242 bands), ASTER (15/30 m; 9 bands), and a time series of MODIS nadir BRDF-adjusted reflectance (NBAR; 1 km, 7 bands) for a study area surrounding the Tumbarumba flux tower site in eastern Australia. The study involved: a) the calculation of a range of physiologically-based vegetation indices from ASTER, HyMap, Hyperion and MOD43B NBAR imagery over the flux tower site; b) comparison across scales between HyMap, Hyperion and MODIS for the normalized difference water index (NDWI) and the Red-Green ratio; c) analysis of relationships between tower-based flux and light use efficiency (LUE) measurements and seasonal and climatic constraints on growth; and d) examination of relationships between fluxes, LUE and time series of NDVI, NDWI and Red-Green ratio. Strong seasonal patterns of variation were observed in NDWI and Red/Green ratio from MODIS NBAR. Correlations between fine (3 and 30 m) and coarse (1 km) scale indices for a small region around the flux tower site were moderately good for Red/Green ratio, but poor for NDWI. Hymap NDWI values for the understorey canopy were much lower than values for the tree canopy. MODIS NDWI was negatively correlated with CO₂ fluxes during warm and cool seasons. The correlation indicated that surface reflectance, affected by a spectrally bright grassland understorey canopy, was decoupled from growth of trees with access to deep soil moisture. The application of physiologically-based indices at earth observation scale requires careful attention to applicability of band configurations, contribution of vegetation components to reflectance signals, mechanistic relationships between biochemical processes and spectral indexes, and incorporation of ancillary information into any analysis.     

Correlated change in normalized difference vegetation index and the seasonal trajectory of photosynthetic capacity in a conifer stand

Seasonal changes in canopy photosynthetic activity play an important role in carbon assimilation. However, few simulation models for estimating carbon balances have included them due to scarcity in quality data. This paper investigates some important aspects of the relationship between the seasonal trajectory of photosynthetic capacity and the time series of a common vegetation index (normalized difference vegetation index, NDVI), which was derived from on site micrometeorological measurements or smoothed and downscaled from satellite‐borne NDVI sensors. A parameter indicating the seasonality of canopy physiological activity, P _E, was retrieved through fitting a half‐hour step process model, PROXEL_NEE, to gross primary production (GPP) estimates by inversion for carboxylation and light utilization efficiencies. The relative maximum rate of carboxylation (V _rm), a parameter that indicates the seasonality of CO₂ uptake potential under prevailing temperature, was then calculated from P _E and daily average air temperature. Statistical analysis revealed that there were obvious exponential relationships between NDVI and the seasonal courses for both canopy physiological activities P _E and V _rm. Among them, the on‐site broadband NDVI provided a robust and consistent relationship with canopy physiological activities (R ² = 0.84). The relationships between satellite‐borne NDVI time series with instantaneous canopy physiological activities at the time of satellite passing were also checked. The results indicate that daily step NDVI time series (data downscaled from composite temporal resolution NDVI) better represent the daily average activity of the canopy. These findings may enable us to retrieve the seasonal course of canopy physiological activity from widely available NDVI data series and, thus, to include it into carbon assimilation models. However, both smoothing methods for satellite‐borne NDVI time series may generate incorrect estimates and must be treated with care.     

A multi-angle spectrometer for automatic measurement of plant canopy reflectance spectra

The paper describes the design and operation of a multi-angle spectrometer (MAS) for automatic measurement of near-field spectral reflectances of plant canopies at hourly intervals. A novel feature of the instrument is a rotating periscope connected to a spectrometer via a fiber optic cable. Canopy reflectances are calculated for multiple view azimuths, at a single zenith angle from measurements of spectrometer dark current, incoming solar irradiance and reflected radiances. Spectral measurements are made between 300 and 1150 nm wavelength at a band-to-band spacing of 3 nm, and a bandwidth (full-width, half maximum) of 10 nm. Preliminary data analysis showed that the canopy reflectance model of Kuusk [Kuusk, A. (1995). A fast, invertible canopy reflectance model. Remote Sensing of Environment 51, 342-350] reproduced the observed large differences in visible and near-infrared (NIR) reflectances, but the model was unable to predict quantitatively the observed variations in the measured reflectance spectra with azimuth, particularly in the NIR. Discrepancies between model and measurements are likely due to the inhomogeneous nature of the forest canopy in contrast to the assumption of a uniformly absorbing turbid medium in the model. Measurements using the MAS can be used to investigate directional dependences of reflectance indices and for testing BRDF models used to separate geometrical and plant physiological contributions to the reflectance signals. The MAS provides continuous sampling of reflectance indices which can be compared with canopy properties such as chlorophyll content and photosynthetic capacity.     

Can a satellite-derived estimate of the fraction of PAR absorbed by chlorophyll (FAPARchl) improve predictions of light-use efficiency and ecosystem photosynthesis for a boreal aspen forest?

We used daily MODerate resolution Imaging Spectroradiometer (MODIS) imagery obtained over a five-year period to analyze the seasonal and inter-annual variability of the fraction of absorbed photosynthetically active radiation (FAPAR) and photosynthetic light use efficiency (LUE) for the Southern Old Aspen (SOA) flux tower site located near the southern limit of the boreal forest in Saskatchewan, Canada. To obtain the spectral characteristics of a standardized land area to compare with tower measurements, we scaled up the nominal 500 m MODIS products to a 2.5 km × 2.5 km area (5 × 5 MODIS 500 m grid cells). We then used the scaled-up MODIS products in a coupled canopy-leaf radiative transfer model, PROSAIL-2, to estimate the fraction of absorbed photosynthetically active radiation (APAR) by the part of the canopy dominated by chlorophyll (FAPAR_chl) versus that by the whole canopy (FAPAR_canopy). Using the additional information provided by flux tower-based measurements of gross ecosystem production (GEP) and incident PAR, we determined 90-minute averages for APAR and LUE (slope of GEP:APAR) for both the physiologically active foliage (APAR_chl, LUE_chl) and for the entire canopy (APAR_canopy, LUE_canopy).The flux tower measurements of GEP were strongly related to the MODIS-derived estimates of APAR_chl (r² = 0.78) but only weakly related to APAR_canopy (r² = 0.33). Gross LUE between 2001 and 2005 for LUE_chl was 0.0241 µmol C µmol^− 1 PPFD whereas LUE_canopy was 36% lower. Time series of the 5-year normalized difference vegetation index (NDVI) were used to estimate the average length of the core growing season as days of year 152-259. Inter-annual variability in the core growing season LUE_chl (µmol C µmol^− 1 PPFD) ranged from 0.0225 in 2003 to 0.0310 in 2004. The five-year time series of LUE_chl corresponded well with both the seasonal phase and amplitude of LUE from the tower measurements but this was not the case for LUE_canopy. We conclude that LUE_chl derived from MODIS observations could provide a more physiologically realistic parameter than the more commonly used LUE_canopy as an input to large-scale photosynthesis models.     

Parallel adjustments in vegetation greenness and ecosystem CO2 exchange in response to drought in a Southern California chaparral ecosystem

Some form of the light use efficiency (LUE) model is used in most models of ecosystem carbon exchange based on remote sensing. The strong relationship between the normalized difference vegetation index (NDVI) and light absorbed by green vegetation make models based on LUE attractive in the remote sensing context. However, estimation of LUE has proven problematic since it varies with vegetation type and environmental conditions. Here we propose that LUE may in fact be correlated with vegetation greenness (measured either as NDVI at constant solar elevation angle, or a red edge chlorophyll index), making separate estimates of LUE unnecessary, at least for some vegetation types. To test this, we installed an automated tram system for measurement of spectral reflectance in the footprint of an eddy covariance flux system in the Southern California chaparral. This allowed us to match the spatial and temporal scales of the reflectance and flux measurements and thus to make direct comparisons over time scales ranging from minutes to years. The 3-year period of this study included both “normal” precipitation years and an extreme drought in 2002. In this sparse chaparral vegetation, diurnal and seasonal changes in solar angle resulted in large variation in NDVI independent of the actual quantity of green vegetation. In fact, one would come to entirely different conclusions about seasonal changes in vegetation greenness depending on whether NDVI at noon or NDVI at constant solar elevation angle were used. Although chaparral vegetation is generally considered “evergreen”, we found that the majority of the shrubs were actually semi-deciduous, leading to large seasonal changes in NDVI at constant solar elevation angle. LUE was correlated with both greenness indices at the seasonal timescale across all years. In contrast, the relationship between LUE and PRI was inconsistent. PRI was well correlated with LUE during the “normal” years but this relationship changed dramatically during the extreme drought. Contrary to expectations, none of the spectral reflectance indices showed consistent relationships with CO₂ flux or LUE over the diurnal time-course, possibly because of confounding effects of sun angle and stand structure on reflectance. These results suggest that greenness indices can be used to directly estimate CO₂ exchange at weekly timescales in this chaparral ecosystem, even in the face of changes in LUE. Greenness indices are unlikely to be as good predictors of CO₂ exchange in dense evergreen vegetation as they were in the sparse, semi-deciduous chaparral. However, since relatively few ecosystems are entirely evergreen at large spatial scales or over long time spans due to disturbance, these relationships need to be examined across a wider range of vegetation types.     

Assimilating canopy reflectance data into an ecosystem model with an Ensemble Kalman Filter

An Ensemble Kalman Filter (EnKF) is used to assimilate canopy reflectance data into an ecosystem model. We demonstrate the use of an augmented state vector approach to enable a canopy reflectance model to be used as a non-linear observation operator. A key feature of data assimilation (DA) schemes, such as the EnKF, is that they incorporate information on uncertainty in both the model and the observations to provide a best estimate of the true state of a system. In addition, estimates of uncertainty in the model outputs (given the observed data) are calculated, which is crucial in assessing the utility of model predictions.Results are compared against eddy-covariance observations of CO₂ fluxes collected over three years at a pine forest site. The assimilation of 500 m spatial resolution MODIS reflectance data significantly improves estimates of Gross Primary Production (GPP) and Net Ecosystem Productivity (NEP) from the model, with clear reduction in the resulting uncertainty of estimated fluxes. However, foliar biomass tends to be over-estimated compared with measurements. Issues regarding this over-estimate, as well as the various assumptions underlying the assimilation of reflectance data are discussed.