G. Guyot

Potentials and limits of vegetation indices for LAI and APAR assessment

Abstract Most vegetation indices (VI) combine information contained in two spectral bands: red and near-infrared. These indices are established in order to minimize the effect of external factors on spectral data and to derive canopy characteristics such as leaf area index (LAI) and fraction of absorbed photosynthetic active radiation (P). The potentials and limits of different vegetation indices are discussed in this paper using the normalized difference (NDVI), perpendicular vegetation index (PVI), soil adjusted vegetation index (SAVI), and transformed soil adjusted vegetation index (TSAVI). The discussion is based on a sensitivity analysis in which the effect of canopy geometry (LAI and leaf inclination) and soil background are analyzed. The calculation is performed on data derived from the SAIL reflectance model. General semiempirical models, describing the relations between VI and LAI or P, are elaborated and used to derive the relative equivalent noise (REN) for the determination of LAI and P. The performances of VIs are discussed on the basis of the REN concept.

A ratio vegetation index adjusted for soil brightness

Abstract Improved parameters for a soil-adjusted vegetation index (SAVI) are derived using SAIL model output for simulated wheat canopy reflectance. The SAVI is much less sensitive than the ratio vegetation index to changes in background caused by soil colour or surface soil moisture content. The parameters are developed to minimize variability due to soil brightness over the practical range of solar elevations, lear angle distributions (LAD) and leaf area indices (LAI). The parameters are added to the near-infrared (NIR) and red reflectances before calculating the NIR/red ratio. Three new versions of the SAVI are developed based on the theoretical consideration of the effects of wet and dry soils. All three are superior to the NIR/red ratio, the perpendicular vegetation index and a soil-adjusted vegetation index. Our simplest version requires the addition of a parameter to the red reflectance. The second and third versions require an iterative procedure to find the best parameters that are then added to ...

Estimating surface soil moisture and leaf area index of a wheat canopy using a dual-frequency (C and X bands) scatterometer

Abstract Since microwave remote sensing techniques are insensitive to cloud cover, they can overcome this strong limitation of optical remote sensing. As in the optical domain, their use for monitoring vegetation canopies requires the development of suitable inversion algorithms. These would allow the estimation of variables such as LAI from radar data. This article investigates the possible use of a semiempirical water-cloud model in an inversion scheme. Using radar data obtained with a ground-based dual-frequency (C and X bands, 5.7 and 3.3 cm wavelength, respectively) scatterometer on experimental winter wheat fields, it is first verified that a semiempirical water-cloud model can adequately simulate the backscattering coefficients obtained over the growing season, as a function of LAI and surface soil moisture. Then it is shown that the model can be numerically inverted. This yields simultaneous estimation of LAI and surface soil moisture, the standard deviations of the residuals being respectively 0.64 m2 m−2 and 0.065 cm3 cm−3. Finally, the influence of radar measurement errors on the inversion scheme is quantified by means of a simulation study. This shows that a 1 dB accuracy of the radar is required for a 1 m2 m−2 precision of the estimated LAI.

Modeled analysis of the biophysical nature of spectral shifts and comparison with information content of broad bands

Abstract Spectral shifts characterized by the wavelength λi of the inflexion point in the red-edge region (670–780 nm) are analyzed using model simulations. Leaf optical properties are computed with the PROSPECT model, canopy reflectance with the SAIL model, and atmospheric effects with the 5S model. The information provided by the high spectral resolution index (λi) appears to be equivalent to that obtained from the red and near-infrared broad band reflectances at leaf level. This is not true at canopy level: λi is very sensitive to leaf area index and chlorophyll concentration and, when observed from space sensors, it minimizes the effects of atmosphere and soil background optical properties. Moreover, λi could be a pertinent indicator of canopy photosynthetic capacity. But its small dynamic range requires further studies in which sensor noise has to be considered, depending on the method of λi computation.

Factors affecting the spectral response of forest canopies: A review

Abstract Interpreting remote sensing data on forest canopies demands an adequate knowledge of factors affecting their optical properties. After a short analysis of the optical properties of a forest canopy, a review of the factors acting on the forest reflectance is presented. These factors can be external or internal. The five external factors considered are: size of the viewed area, orientation and inclination of the view axis, sun elevation, nebulosity and wind speed. Three internal factors can also affect forest reflectance: row orientation (for young artificial forests), optical properties of the background (soil and understory), and canopy geometry. The effects of these different factors are analysed and discussed.

Effect of radiometric corrections on NDVI-determined from SPOT-HRV and Landsat-TM data

Abstract The normalized difference vegetation index (NDVI), which is generally considered as an index minimizing the radiometric errors on image data has to be corrected radiometrically when a quantitative analysis is performed. In this article, the main factors affecting NDVI are analyzed: proper characteristics (MTF) and absolute calibration of the satellite sensor, Sun zenith angle, Earth-Sun distance, and atmospheric condition. The effects of these factors are theoretically and practically analyzed on two SPOT-HRV and Landsat-TM images acquired the same day over the same area in southeast France. Some simplified correction methods are proposed. The results show that: i) The conversion of digital counts into apparent reflectance is the most important step for NDVI correction. Without this correction, a relatively constant error affects NDVI depending on the sensor considered (− 0.18 for SPOT-HRV and − 0.10 for Landsat TM). ii) The MTF correction does not affect the average NDVI value; its interest is to restore the radiometric level of individual pixels that have a large contrast with their surroundings. iii) The atmospheric effects are similar in the homologous spectral bands of SPOT-HRV and Landsat TM. Their correction increases the dynamic range of NDVI variation (around 24% in the example presented) and consequently the contrast between different targets. The effect of the noncoincidence of SPOT-HRV and Landsat-TM spectral bands is also studied. This effect can be considered either as a source of error or as a supplementary source of information. An example shows that the combination of the spectral information given by the two satellites can be used to improve the discrimination of some targets such as bare soil and soil with a low vegetation density.

Monitoring wheat canopies with a high spectral resolution radiometer

Abstract The evolution of reflectance factors of 16 wheat plots (four different cultivars with four different planting dates) was monitored during the growing cycle using a high spectral resolution radiometer (1024 spectral bands between 468 and 1064 nm). The position of the inflexion point on the red edge of the reflectance curves of plants (between 670 and 760 nm) and the “red slope” (between 580 and 660 nm) give specific information on the leaf area state and percent ground coverage. Results also show that a spectral resolution of 5 nm is adequate to observe the described phenomena. Spectra have also been used to simulate and interrelate different broad spectral bands. The possibility of estimating the reflected photosynthetic active radiation, from SPOT visible channels, is discussed. We conclude that high spectral resolution gives additional information compared with classical measurement performed with broad band radiometers.

Crop biomass evaluation using radiometric measurements

Abstract Crop biomass can be evaluated from radiometric measurements either by relating biomass to instantaneous measurements or by relating an integral of biomass to a radiometric value integrated over the corresponding portion of the growth period. In this study, the success obtained by using these two methods is discussed. A simple radiative transfer model was used in conjunction with experimental results to demonstrate the universality of the relationship between the normalized difference vegetation index ( ND ) and leaf area index ( LAI ) or the photosynthetically active radiation ( PAR ) absorbed by the crop. It shows that the relationship between ND and absorbed PAR is less dependent on leaf orientation than the relationship between ND and LAI . A remaining problem is the sensitivity of those two relationships to soil optical properties. Nevertheless, temporal integration of radiometric data using the absorbed PAR concept appears to be a more promising approach than one-time measurements.

Complementarity of middle-infrared with visible and near-infrared reflectance for monitoring wheat canopies☆

Abstract Information given by middle-infrared (1.3–2.5 μm) spectral bands, in addition to visible (0.4–0.7 μm) and nearinfrared (0.7–1.3 μm) channels, was evaluated for monitoring wheat canopies. Three middle-infrared bands. TM5 (1.56–1.68 μm), TM7 (2.03–2.35 μm), and a narrower band (1.66–1.70 μm) were tested. TM5 appeared to be the best band, giving the maximum information with regard to visible and near-infrared. Results showed that the middle-infrared provides valuable complementary information on the geometrical structure of the canopy and on the optical properties of the underlying soil.

IRSUTE : A MINISATELLITE PROJECT FOR LAND SURFACE HEAT FLUX ESTIMATION FROM FIELD TO REGIONAL SCALE

Abstract Thermal infrared remote sensing has proved its usefulness in various environmental applications, including the evaluation of surface heat fluxes exchanged between the continental biosphere and the lower atmosphere. The concept of a minisatellite, IRSUTE, has been evaluated. It is designed to allow the derivation of accurate (±50 W m −2 or ±0.8 mm/d water evaporation) estimates of surface heat flux at the field scale (near 40 m). Such estimates will be useful for meteorological, hydrological, and agricultural studies. The instrument will also be useful for environmental monitoring, for example, frost mapping, forest fires, volcano activity, thermal pollution, etc. The IRSUTE concept has been further elaborated by conducting scientific studies (modeling canopy radiative temperature, method for flux estimation, ergodicity problem, emissivity of natural surfaces, correction of atmospheric effect), by analyzing methodological aspects (definition of pixel size, overpass time, time repeat cycle, analysis of angular effects) and system specification (superposition error and MTF effects assessment). These studies have resulted in the definition of a feasible instrument corresponding to the minisatellite category (95 kg), with a high spatial resolution (40 m), four bands in the thermal infrared domain (3.5–4.0 μm and three bands between 8.2 μm and 11.0 μm, with two options), a 1-day revisit, corresponding to an orbite altitude of 540 km. The narrow ground swath (40 km) precludes a global coverage; as a result IRSUTE will focus on a set of test-sites. The phase A study is now complete. The main elements of IRSUTE are defined. This article describes the IRSUTE mission characteristics and the main experimental results which led to the chosen specifications.