Y. Nouvellon

A refined empirical line approach for reflectance factor retrieval from Landsat-5 TM and Landsat-7 ETM+

The recent launch of Landsat-7 ETM+ extends the uninterrupted stream of TM and ETM+ images to a potential span of 32 years. This exceptional image set will allow long-term studies of natural resources, but will require an operational method for converting image digital number (dn) to the temporally comparable surface reflectance factor (rsl). A refinement to the empirical line (EL) approach for reflectance factor retrieval (RFR) from the Landsat-5 and -7 TM and ETM+ has been proposed. The refined empirical line (REL) approach requires only one within-scene calibration target, minimal field measurements of that target, and a reasonable estimate of dn for rsl=0 using a radiative transfer model or values provided by this analysis. This study showed that the REL approach worked well for a 10-year Landsat5 TM and Landsat-7 ETM+ image set in Arizona and rsl was retrieved with an estimated accuracy of 0.01. A quantitative approach was proposed to determine the suitability of a within-scene target for the REL approach, and based on historical measurements, a variety of targets met the size and brightness requirements for the REL approach. This operational approach for RFR should encourage long-term investigations of natural resources to answer critical questions regarding resource management and effects of climate changes. D Published by Elsevier Science Inc.

Coupling a grassland ecosystem model with Landsat imagery for a 10-year simulation of carbon and water budgets

In this study, high-spatial, low-temporal scale visible remote sensing data were used to calibrate an ecosystem model (EM) for semiarid perennial grasslands. The model was driven by daily meteorological data and simulated plant growth and water budget on the same time step. The model was coupled with a canopy reflectance model to yield the time course of shortwave radiometric profiles. Landsat Thematic Mapper (TM) and Enhanced TM Plus (ETM+) images from 10 consecutive years were used to refine the model on a spatially distributed basis. A calibration procedure, which minimized the difference between the normalized difference vegetation index (NDVI) simulated from the coupled model and measured by the TM and ETM+ sensors, yielded the spatial distribution of an unknown parameter and initial condition. Accuracy of model products, such as daily aboveground biomass, leaf area index (LAI) and soil water content, was assessed by comparing them with field measurements. The promising results suggest that this approach could provide spatially distributed information about both vegetation and soil conditions for day-to-day grassland management.

PAR extinction in shortgrass ecosystems: effects of clumping, sky conditions and soil albedo

The amount of photosynthetically active radiation (PAR) absorbed by a canopy (APAR) is an important driving variable for vegetation processes such as photosynthesis. PAR extinction in clumped canopies of shortgrass ecosystems is the focus of this paper. Directional gap fractions estimated at peak biomass on several Mexican shortgrass ecosystems with a hemispherical radiation sensor (Li-Cor, LAI-2000) were higher than those predicted by a Poisson model assuming a random leaf dispersion (RLD). LAI-2000-estimated gap fractions, together with independent estimations of plant area index (PAI), and leaf and stem angle distribution (LSAD) were used for estimating the angular course of a leaf dispersion parameter ./. Radiation extinction coefficients simulated for all solar zenith angles using Markov chain processes and estimated ./ were subsequently incorporated in a simple radiative transfer model for estimating the efficiencies of instantaneous and daily integrated PAR interception and absorption, and for studying the effects of clumping, sky conditions and soil albedo on PAR absorption. For clear sky condition, instantaneous PAR absorption showed marked directional effects, therefore indicating that using a constant extinction coefficient in canopy photosynthesis models working at hourly time step would be inaccurate. The effects of clumping, sky conditions and soil albedo were all found to be significant for low PAI, and decreased with higher PAI. As shortgrass ecosystems are characterized by low PAI, neglecting these effects would give inaccurate estimations of PAR absorption. Daily PAR absorption was found to be significantly higher than PAR interception for low PAI, especially when soil albedo was high, and lower than PAR interception for high PAI. These results indicate that in canopy photosynthesis models where APAR is estimated from simple exponential-like relationships calibrated using PAR interception measurements, the PAR available for photosynthesis might be significantly underestimated in the first stages of the growth, and may be overestimated in the later stages of the growing season.

Grassland modeling and monitoring with SPOT-4 VEGETATION instrument during the 1997-1999 SALSA experiment.

A coupled vegetation growth and soil‐vegetation‐atmosphere transfer (SVAT) model is used in conjunction with data collected in the course of the SALSA program during the 1997‐1999 growing seasons in Mexico. The objective is to provide insights on the interactions between grassland dynamics and water and energy budgets. These three years exhibit drastically different precipitation regimes and thus different vegetation growth. The result of the coupled model showed that for the 3 years, the observed seasonal variation of plant biomass, leaf area index (LAI) are well reproduced by the model. It is also shown that the model simulations of soil moisture, radiative surface temperature and surface fluxes compared fairly well with the observations. Reflectance data in the red, near infrared, and short wave infrared (SWIR, 1600 nm) bands measured by the VEGETATION sensor onboard SPOT-4 were corrected from atmospheric and directional effects and compared to the observed biomass and LAI during the 1998‐1999 seasons. The results of this ‘ground to satellite’ approach established that the biomass and LAI are linearly related to the satellite reflectances (RED and SWIR), and to vegetation indices (NDVI and SWVI, which is a SWIR-based NDVI). The SWIR and SWVI sensitivity to the amount of plant tissues were similar to the classical RED and NDVI sensitivity, for LAI ranging from 0 and 0.8 m 2 m 2 and biomass ranging from 0 to 120 g DM m 2 . Finally, LAI values simulated by the vegetation model were fed into a canopy radiative transfer scheme (a ‘model to satellite’ approach). Using two leaf optical properties datasets, the computed RED, NIR and SWIR reflectances and vegetation indices (NDVI and SWVI) compared reasonably well with the VEGETATION observations in 1998 and 1999, except for the NIR band and during the senescence period, when the leaf optical properties present a larger uncertainty. We conclude that a physically-sound linkage between the vegetation model and the satellite can be used for red to short wave infrared domain over these grasslands. These different results represent an important step toward using new generation satellite data to control and validate model’s simulations at regional scale.

Estimation of surface sensible heat flux using dual angle observations of radiative surface temperature

Abstract In this study, dual angle observations of radiative surface temperature have been used in conjunction with a two-layer model to derive sensible heat flux over a sparsely vegetated surface. Data collected during the semi-arid-land-surface-atmosphere program (SALSA) over a semi-arid grassland in Mexico were used to assess the performance of the approach. The results showed that this approach led to reasonable estimates of the observed fluxes. The mean average percentage difference (MAPD) between observed and simulated fluxes was about 23%, which is not statistically different from the expected 20% scatter, when different flux measuring devices are compared over the same site. However, the sensitivity analysis indicated that the approach was rather sensitive to uncertainties in both measured radiative temperatures and aerodynamic characteristics of the vegetation. Finally, the issue of using dual angle observations of surface temperature for characterizing the difference between aerodynamic and nadir viewing radiative temperature has been examined. The results showed that this difference is linearly correlated with the difference between nadir and oblique radiative temperatures. Based on this finding, we expressed sensible heat flux in terms of the (nadir) radiative-air temperature gradient and a corrective term involving the nadir–oblique temperature differences. This formulation has been successfully tested. The resulting MAPD was about 33%.

Modelling of daily fluxes of water and carbon from shortgrass steppes.

A process-based model for semi-arid grassland ecosystems was developed. It is driven by standard daily meteorological data and simulates with a daily time step the seasonal course of root, aboveground green, and dead biomass. Water infiltration and redistribution in the soil, transpiration and evaporation are simulated in a coupled water budget submodel. The main plant processes are photosynthesis, allocation of assimilates between aboveground and belowground compartments, shoots and roots respiration and senescence, and litter fall. Structural parameters of the canopy such as fractional cover and LAI are also simulated. This model was validated in southwest Arizona on a semi-arid grassland site. n nIn spite of simplifications inherent to the process-based modelling approach, this model is useful for elucidating interactions between the shortgrass ecosystem and environmental variables, for interpreting H2O exchange measurements, and for predicting the temporal variation of above- and belowground biomass and the ecosystem carbon budget.

Directional effect on radiative surface temperature measurements over a semiarid grassland site

In this study, an experimental design was conceived, as part of the Semi-Arid-Land-Surface-Atmosphere (SALSA) program, to document the effect of view angle variation on surface radiative temperature measurements. The results indicated differences between nadir and off-nadir radiative temperature of up to 5 K. The data also illustrated that, under clear sky and constant vegetation conditions, this difference is well correlated with surface soil moisture. However, the correlation decreased when the same comparison was made under changing vegetation conditions. To investigate the possibility of deriving component surface temperatures (soil and vegetation) using dual-angle observations of directional radiative temperature, two radiative transfer models (RTM) with different degrees of complexity were used. The results showed that despite their differences, the two models performed similarly in predicting the directional radiative temperature at a third angle. In contrast to other investigations, our study indicated that the impact of ignoring the cavity effect term is not very significant. However, omitting the contribution of the incoming long-wave radiation on measured directional radiance seemed to have a much larger impact. Finally, sensitivity analysis showed that an accuracy of better than 10% on the plant area index (PAI) was required for achieving a precision of 1 K for inverted vegetation temperature. An error of 1 K in measured directional radiative temperature can lead to an error of about 1 K in the soil and vegetation temperatures derived by inverting the RTM.

Combining remote sensing and plant growth modeling to describe the carbon and water budget of semi-arid grasslands

The authors investigate the opportunity of coupling a vegetation growth model developed for semi-arid perennial grasslands, with a soil/vegetation reflectance model in order to use remote sensing data to improve the model simulations. The vegetation functioning model developed for this purpose has been validated in Southeastern Arizona and Northeastern Sonora on several semiarid grassland sites. The assimilation of radiometric data into the shortgrass prairie ecosystem model is based on an iterative numerical procedure that recalibrates the combined model until model simulations match radiometric observations. For this purpose, a prior sensitivity analysis was carried out for the vegetation growth model in order to determine the most important input parameters or initial conditions on which to base the recalibration procedure. The results obtained and the potential of such an approach are discussed.

Assimilating LANDSAT data in an ecosystem model for multi-year simulation of grassland carbon, water and energy budget

In this study, a spatially explicit hydro-ecological model (SEHEM) has been developed and validated over a semi-arid grassland sub-watershed in Arizona. The model combines a plant growth sub-model to simulate the seasonal dynamics of root and aboveground biomass, and a hydrological sub-model to simulate soil moisture and temperature dynamics, energy and water budgets for the soil and the vegetation. In addition, the model has been coupled to radiative transfer models (RTMs) in the visible, near infrared and thermal infrared (TIR) bands so that canopy reflectance and directional radiative surface temperature are simulated. Landsat Thematic Mapper (TM) images obtained during a six year period were used to adjust some spatially variable model parameters by minimizing the difference between model simulations and remotely sensed data. Comparisons between observations and model estimates of above ground biomass, net radiation, sensible and latent heat flux, component temperatures are presented.

Examination of the factors controlling directional effects on radiative surface temperature over vegetated surfaces

In this study, the effect of view angle variation on surface radiative temperature measurements has been examined from both experimental and modeling perspectives. A coupled SVAT-vegetation functioning model associated with a radiative transfer model in thermal infrared has been used to document the factors controlling the departure of nadir from off-nadir radiative surface temperature under different soil moisture conditions and vegetation status and dynamics. In the same vein, an experimental setup has been conceived to document the same effect over sparsely vegetated surfaces. This include 3 infrared radiometers observing the same spot at 0, 45 and 55 degrees, respectively. The experimental results indicated differences between nadir and off-nadir radiative temperature of up to 5 K. The data also illustrated that, under clear sky and constant vegetation conditions, this difference is well correlated with surface soil moisture. However, the correlation decreased when the same comparison was made under changing vegetation conditions.