Simulation of citrus orchard reflectance by means of a geometrical canopy model

Computer simulation of the reflectance for citrus crops, by using a geometrical canopy model, has been carried out to analyse and interpret the reflectance values from Landsat-5 Thematic Mapper (TM) images in two different periods: summer and winter. As well as the tree cover of the crop, the plantation framework and orientation of the citrus parcels have also been analysed. These architectural parameters determine, together with the sun zenith angle, the proportion of shadows in the scene. In summer, the main influence of shadows occurs in the near-infrared band (TM4). Shadow is such an important effect in this spectral region that it may cause an overlap between spectral responses of canopies with different tree cover. In winter, the high proportion of shadows produces a saturation effect on the reflectance values when the tree cover of the parcels is increased. A threshold value of tree cover (~40 per cent) has been observed experimentally and explained theoretically. Above this threshold, all the citrus parcels present approximately similar reflectance values.     

Leaf water stress detection utilizing thematic mapper bands 3, 4 and 5 in soybean plants

Abstract

Foliar water stress in a mature soybean canopy, manifested as wilt rather than as a reflectance shift, was studied using reflectance measurements for Thematic Mapper bands 3 (0.63-0.69 μm), 4 (0.76-0.90 μm) and 5 (1.55-1.75μm). Diffuse and total reflectances were determined using polarization measurements and compared statistically at a variety of look angles at 15min intervals from about 09.00 until 14.00 hours EST. Plots of the data from unstressed canopy show that the behaviour of both the diffuse and total reflectances mimics that of the solar radiance curve with time of day, whereas the stressed canopy reflectance data revealed a nearly linear behaviour with a small negative slope. For both the diffuse and total reflectances measured in the nadir position, TM4 was found to be the most responsive spectral band for foliar water stress detection when the water deficit was sufficient to cause wilting, implying that substantial changes in canopy leaf geometry can best be monitored by TM4. TM3 was not found as responsive to the level of foliar water stress which occurred during this investigation. TM5 showed a response intermediate between TM4 and TM3. The results of polarization calculations for TM4 indicated that during the process of wilting, the level of canopy polarization gradually decreased.     

Anisotropic Reflection by Melting Glacier Ice: Measurements and Parametrizations in Landsat TM Bands 2 and 4

This article deals with the anisotropic reflection of radiation by melting glacier ice. Ground-based measurements of the directional distribution of the reflected radiation over the hemisphere (so-called BRDFs=bidirectional reflectance distribution functions) were made on the Morteratschgletscher (Switzerland) in Landsat TM bands 2 (520–600 nm) and 4 (760–900 nm). These BRDFs cover a wide range of solar zenith angles (26–75°) and surface characteristics (quantified by a variation in the spectrally integrated albedo between 0.14 and 0.50). All BRDFs exhibit a similar pattern with a minimum in the nadir direction and a maximum in the forward limb, but the amount of anisotropy increases with increasing wavelength, with increasing solar zenith angle and with decreasing albedo. The data were used to derive parametrizations (one for each TM band) which relate the bidirectional reflectance (the reflectance in a specific direction) to the albedo for a given solar-view geometry. Specific parametrizations (one for each TM band) for “near-nadir reflection” are also presented. All these parametrizations can be used to convert satellite-derived bidirectional reflectances into surface albedos and thus to correct for anisotropic reflectance. The residual uncertainty in the albedo due to inaccuracy of the correction is estimated to be 0.02 in both TM bands.     

Inferring hemispherical reflectance of the earth's surface for global energy budgets from remotely sensed nadir or directional radiance values

The importance of the hemispherical reflectance (albedo) of terrestrial surfaces to biospheric and atmospheric processes is briefly reviewed. It is proposed that satellite-borne instruments represent the only practical means of obtaining global estimates of surface albedo data at reasonable time resolution, the problem being how to relate the nadir or directional reflectance observations obtained from such sensors to the integrated hemispherical reflectance. This paper discusses results measured at ground level in which NOAA satellite 7/8 AVHRR data, Bands 1 (0.58–0.68 μm) and 2 (0.73–1.1 μm), were used to investigate 1) the relationships between directional reflectances (spanning the entire reflecting hemisphere) and hemispherical reflectance (albedo) and 2) the effect of solar zenith angle and cover type on these relationships. Eleven natural vegetation surfaces ranging from bare soils to dense vegetation canopies were considered in the study. The results show that errors in inferring hemispherical reflectance from nadir reflectance can be as high as 45% for all cover types and solar zenith angles. By choosing a time of observation such that the solar zenith angle is between 30 and 40° the same error is reduced to less than 20% in both bands. For both bands a view angle of 60° off-nadir and ±90° from the solar azimuth reduces this error to less than 11% for all sun angles and cover types. A technique using two specific view angles reduces this error to less than 6% for both bands and for all sun angles and cover types. These techniques may yield considerable dividends in terms of more reliable estimation of hemispherical reflectance of natural surfaces.     

Variation in spectral response of soybeans with respect to illumination,view and canopy geometry

Comparisons of the spectral response for incomplete (well-defined row structure) and complete (overlapping row structure) canopies indicated that there was a greater dependence on Sun and view geometry for the incomplete canopies. This effect was more pronounced for the highly absorptive red (0.6-0.7 μm) wavelength band than for the near-infrared (IR) (0.8-1.1 μm) based on relative reflectance factor changes.

Red and near-IR reflectance for the incomplete canopy decreased as solar zenith angle increased for a nadir view angle until the soil between the plant rows was completely shaded. Thereafter for increasing solar zenith angle the red reflectance levelled off and the near-IR reflectance increased. A ‘hot-spot’ effect was evident for the red and near-IR reflectance factors, especially when the Sun-sensor view directions were perpendicular to the rows. The ‘hot-spot’ effect was more pronounced for the red band based on relative reflectance value changes. The effect of Sun angle was more pronounced for view angles perpendicular to the row direction.

An analysis of the ratios of off-nadir- to nadir-acquired data revealed that off-nadir red band reflectance factors more closely approximated straight-down measurements for time periods away from solar noon. Near-IR and greenness responses showed a similar behaviour. Normalized difference generally approximated straight-down measurements during the middle portion of the day. An exception occurred near solar noon when sunlit bare soil was present in the scene.     

基于模型模拟的植被NDVI与观测天顶角和LAI的关系

利用PROSPECT和SAIL模型模拟了不同叶绿素含量、不同LAI和不同观测天顶角下的植被冠层反射率,分析了NDVI随LAI、观测天顶角和叶绿素含量的变化规律。结果表明:叶绿素影响冠层反射率主要在可见光波段,冠层反射率随叶绿素含量的增加而下降;冠层反射率随观测天顶角的增加而增加,而LAI较高时,其受观测天顶角的影响较小。观测天顶角相同时,随叶绿素含量的增加NDVI呈上升趋势;叶绿素含量一定时,NDVI随LAI的增加而增加。LAI为1时,在不同叶绿素含量下,随观测天顶角的增加,NDVI呈先下降后上升的趋势,拐点在观测天顶角65°或70°处,而LAI为3、5和7时,NDVI呈现下降趋势。叶绿素含量较高时,NDVI受观测天顶角的影响较小。当LAI较大和叶绿素含量较低时,NDVI随观测天顶角的增加(>70°)下降较快。     

Retrieval of forest canopy attributes based on a geometric-optical model using airborne LiDAR and optical remote-sensing data

In the retrieval of forest canopy attributes using a geometric-optical model, the spectral scene reflectance of each component should be known as prior knowledge. Generally, these reflectances were acquired by a foregone survey using an analytical spectral device. This article purposed to retrieve the forest structure parameters using light detection and ranging (LiDAR) data, and used a linear spectrum decomposition model to determine the reflectances of the spectral scene components, which are regarded as prior knowledge in the retrieval of forest canopy cover and effective plant area index (PAI_e) using a simplified Li–Strahler geometric-optical model based on a Satellites Pour l'Observation de la Terre 5 (SPOT-5) high-resolution geometry (HRG) image. The airborne LiDAR data are first used to retrieve the forest structure parameters and then the proportion of the SPOT pixel not covered by crown or shadow K_g of each pixel in the sample was calculated, which was used to extract the reflectances of the spectral scene components by a linear spectrum decomposition model. Finally, the forest canopy cover and PAI_e are retrieved by the geometric-optical model. As the acquired time of SPOT-5 image and measured data has a discrepancy of about 2 months, the retrieved result of forest canopy cover needs a further validation. The relatively high value of R ² between the retrieval result of PAI_e and the measurements indicates the efficiency of our methods.     

Characterization of the Reflectance Anisotropy of Three Boreal Forest Canopies in Spring–Summer

As a part of the Boreal Ecosystem-Atmosphere Study (BOREAS), measurements of the spectral reflectance anisotropy of three boreal forest canopies were studied for cloudless sky conditions at the phenological growth stages which were at or near maximum leaf area index at each site. The three sites were relatively homogeneous mature stands of black spruce, jack pine, and aspen located in the southern boreal zone of central Saskatchewan. Measurements of the spectal bidirectional reflectance factors with a 15° instrument field of view in three spectral bands centered at 662 nm, 826 nm, and 1658 nm were made with the PARABOLA instrument over a range of solar zenith angles typically varying from 35° (near solar noon) to 70°. The measured reflectance factors showed large anisotropy at all three sites and for all three wavelengths, with prominant backscatter peak reflectances, and strong retro solar view angle (hot spot) maximum reflectances in the visible (662 nm) and shortwave infrared (1658 nm) for the jack pine and black spruce sites, with a less pronounced hot spot at the aspen site. Pronounced effects of canopy and understory shadowing in the visible, as a function of solar zenith angle (SZA), were observed for the black spruce and jack pine sites, with resultant large linear increases in computed normalized difference and simple ratio vegetation indices as SZA increased for near-nadir view angles. Hemispheric spectral reflectances or spectral albedos were computed from angular integration of PARABOLA measured bidirectional reflectances. Visible (662 nm) hemispheric reflectances for the jack pine and black spruce canopies showed very little variation with solar zenith angle, while near-infrared hemispheric reflectances increased strongly with increasing SZA. Estimates were made of the total shortwave albedo for the aspen and jack pine sites from irradiance and reflectance weighting of the spectral hemispheric reflectances in the three measured wavelengths. Comparison of estimated to pyranometer measured total albedo showed all estimates to be biased high, but only by about 0.007–0.018, depending on which of two sets of pyranometer measured albedos were utilized for the comparison. The measured bidirectional reflectance factor (BRF) data sets reported in this study coupled with ancillary data of biophysical parameters collected at the same sites by BOREAS researchers provide a unique data set for the development and characterization of canopy bidirectional reflectance modeling and for the interpretation of remotely sensed data for boreal forest canopies.     

Desert scrub optical density and spectral-albedo ratios of impacted-to-protected areas by model inversion

Bidirectional surface reflectances measured from NOAA AVHRR over the Negev (southern Israel) and the Sinai are analysed to assess the impact on the surface characteristics of anthropogenic pressures of overgrazing. The impacted Sinai is assumed bare, while the Negev is vegetated by desert scrub. The Negev plants are known to be much darker than the underlying soil, and thus assumed to be absorbing (black). The leaf area distribution as a function of the zenith angle is modelled initially as that of small spheres, which specifies a pronouncedly vertical architecture. We infer from the Negev-to-Sinai reflectance ratios the optical thickness b of the plants (spheres) in the range 0.12 to 0.20 for channel 1 (band centre at 0.63 w m), with only weak seasonal variability. Evaluated from average values of b, the Negev-to-Sinai ratios of the spectral albedos (hemispheric reflectances) are 0.63 and 0.55 in channel 1 and 0.67 and 0.60 in channel 2, at solar zenith angles of 30° and 60°, respectively. These ratios indicate the severe climatic impact of overgrazing in the Sinai, inasmuch as a high albedo means reduced shortwave heat absorption (which is detrimental to rainfall-inducing convection). We subsequently proceed to invert the Negev-to-Sinai reflectance ratios assuming a plant-element distribution tending even more to the vertical. The values of b are reduced when derived for a greater tendency to vertical architecture. The Negev-to-Sinai ratios of the spectral albedos are also significantly lower in these cases, which means that the assessed impact of over-grazing in the Sinai is indeed extremely severe. We conclude that plant architecture (which controls the reflection anisotropy) should be considered when evaluating the albedos of vegetated versus bare (impacted) surfaces from satellite-measured bidirectional reflectances. Uncertainty in the zenith angle distribution of the leaf area produces significant uncertainty in the albedo assessment. Multidirectional reflectance measurements made near the ground would greatly reduce uncertainties about the surface-reflection anisotropy, and thus enhance the value of satellite measurements.     

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.     

A simple geometrical model for analysing the spectral response of a citrus canopy using satellite images †

Abstract

A simple geometrical model has been proposed for a citrus canopy. We assume the citrus orchard to be a lattice structure, with the trees positioned at its points and where the composite-scene reflectance is the sum of the reflectance of its individual components as weighted by their respective surfaces within a unit area. The model has been used to analyse the citrus spectral response obtained from Landsat-5 TM images for winter and summer, where the status of the orchard is different. The correlations between spectral and geometrical data show the influence of per cent crop cover, shadows and background in the composite scene reflectance. We conclude that the summer images could be more useful than the winter ones for parcel classification according to per cent crop cover.     

A TM-based hardwood-conifer mixture index for closed canopy forests in the Oregon Coast Range

The purpose of this study was to develop and evaluate a multi-spectral vegetation index for quantifying relative amounts of hardwood and conifer cover from Thematic Mapper (TM) imagery. We focused on closed canopy forests in the Oregon Coast Range, where hardwood, conifer, and mixed stand conditions are prevalent. An approach based on the Gramm-Schmidt orthogonalization process was used to derive three different hardwood-conifer mixture indices (HCMIs). Using correlation and regression analyses, the capacity of these indices to predict closed canopy hardwood percentage was compared with three other groups of spectral variables: (1) the untransformed TM reflectance bands, (2) the Tasseled Cap indices of brightness, greenness, and wetness, and (3) the first three principal components of closed canopy forest reflectance. Results show that while similar amounts of information were explained by HCMI, TM band, Tasseled Cap, and principal component models, only predictions derived from the HCMI1 and HCMI2 variables were unbiased with respect to topographic effects.     

Validation of a Markov chain canopy reflectance model

The Markov chain canopy reflectance model (MCRM) by Kuusk (1995 b) has been tested versus the ray tracing model on two different computer maquettes of field crops (Barley and Beet), and on the field data collected in the frame of the Franco-English Collaborative Reflectance Experiment in 1989 and 1990 on sugar-beet plots. Separate comparisons of single and multiple scattering components of the MCRM and the ray tracing procedure demonstrated good agreement of the models. Inversion of the MCRM on field data returned good estimates of LAI in the range LAI 0.1-4 using nadir reflectance data in three SPOT and two Landsat TM channels. The estimated chlorophyll content was well correlated to the measured one, although underestimated to some extent. The use of directional data at 45 zenith angle and four azimuth angles improved the estimates of both the LAI and the chlorophyll content. It also permitted the estimation of additional parameters of the canopy structure (leaf size, LAD, the Markov parameter).     

Vegetation canopy reflectance

Possible cause-effect relationships in producing vegetation canopy reflectance are discussed. Hemispherical reflectance and even bidirectional reflectance measurements are shown to be inadequate to predict or understand vegetation canopy reflectance in many situations. Among the additional important parameters necessary for prediction and understanding of vegetation canopy reflectance are leaf hemispherical transmittance, leaf area and orientation, characteristics of other components of the vegetation canopy (stalks, trunks, limbs), soil reflectance, solar zenith angle, look angle, and azimuth angle. The effects of these parameters on vegetation canopy bidirectional spectral reflectance are described.     

Sub‐pixel reflectance unmixing in estimating vegetation water content and dry biomass of corn and soybeans cropland using normalized difference water index (NDWI) from satellites

Estimating vegetation cover, water content, and dry biomass from space plays a significant role in a variety of scientific fields including drought monitoring, climate modelling, and agricultural prediction. However, getting accurate and consistent measurements of vegetation is complicated very often by the contamination of the remote sensing signal by the atmosphere and soil reflectance variations at the surface. This study used Landsat TM/ETM+ and MODIS data to investigate how sub‐pixel atmospheric and soil reflectance contamination can be removed from the remotely sensed vegetation growth signals. The sensitivity of spectral bands and vegetation indices to such contamination was evaluated. Combining the strengths of atmospheric models and empirical approaches, a hybrid atmospheric correction scheme was proposed. With simplicity, it can achieve reasonable accuracy in comparison with the 6S model. Insufficient vegetation coverage information and poor evaluation of fractional sub‐pixel bare soil reflectance are major difficulties in sub‐pixel soil reflectance unmixing. Vegetation coverage was estimated by the Normalized Difference Water Index (NDWI). Sub‐pixel soil reflectance was approximated from the nearest bare soil pixel. A linear reflectance mixture model was employed to unmix sub‐pixel soil reflectance from vegetation reflectance. Without sub‐pixel reflectance contamination, results demonstrate the true linkage between the growth of sub‐pixel vegetation and the corresponding change in satellite spectral signals. Results suggest that the sub‐pixel soil reflectance contamination is particularly high when vegetation coverage is low. After unmixing, the visible and shortwave infrared reflectances decrease and the near‐infrared reflectances increase. Vegetation water content and dry biomass were estimated using the unmixed vegetation indices. Superior to the NDVI and the other NDWIs, the SWIR (1650 nm) band‐based NDWI showed the best overall performance. The use of the NIR (1240 nm), which is a unique band of MODIS, was also discussed.     

Soil and Sun angle interactions on partial canopy spectra

Abstract

The spectral behaviour of an incomplete cotton canopy was analysed in relation to solar zenith angle and soil background variations. Soil and vegetation spectral contributions towards canopy response were separated using a first-order interactive model and consequently used to compare the relative sensitivity of canopy spectra to soil background and solar angle differences. Canopy reflectance behaviour with solar angle increased, decreased or remained invariant depending on the reflectance properties of the underlying soil. Sunlit and shaded soil contributions were found to alter vegetation index behaviour significantly over different Sun angles.     

Estimation of canopy parameters for inhomogeneous vegetation canopies from reflectance data. II. Estimation of leaf area index and percentage of ground cover for row canopies

The canopy reflectance (CR) model for row-planted vegetation proposed earlier has been tested for soybean canopies in three different stages of growth and for corn canopies at early and full growth stages. The model fits the field-measured bidirectional CR data quite well. It is shown that, by inverting this model, one could estimate the leaf area index as well as the percentage of ground cover quite accurately from measured canopy reflectances.     

LANDSAT Thematic Mapper bands for characterizing fescue grass vegetation

The relationships between reflectance in the LANDSAT Thematic Mapper (TM) bands and grass canopy characteristics were studied. Data were collected from a total of 107 tall fescue (Festuca arundinacia) plots (0·2 m²) during the 1983 growing season. Canopy height, percentage cover, total wet biomass, total dry biomass, plant water and leaf area index were correlated with spectral data obtained from a Barnes Modular Multiband Radiometer. The near-infrared wavelength region corresponding to TM band 4 appeared to be the best estimator of total wet biomass (r = 0·80) and canopy height (r =0·82). Percentage canopy cover had the highest correlation coefficients with TM band 7 (r = ?0·95) and TM bands 1, 2 and 3 (r≥0·93). All canopy variables showed a curvilinear relationship with the spectral bands, except canopy cover, which showed a near linear relationship, for the biomass range in this study. Linear transformations were obtained using natural logarithms of the grass canopy variables and the spectral bands. Band ratios were more significant than individual bands when correlated with the canopy variables. The relationship between the normalized difference transformation and total wet biomass was linear for low biomass situations. The normalized difference values were constant for high biomass levels. Redundancy was found in several of the canopy variables and several of the spectral variables. Principal component transformations were effective in reducing the seven spectral bands to two principal components, while maintaining nearly all of the variance of the seven bands.     

Monitoring northern mixed prairie health using broadband satellite imagery

The mixed prairie in Canada is characterized by its low to medium green vegetation cover, high amount of non‐photosynthetic materials, and ground level biological crust. It has proven to be a challenge for the application of remotely sensed data in extracting biophysical variables for the purpose of monitoring grassland health. Therefore, this study was conducted to evaluate the efficiency of broadband‐based reflectance and vegetation indices in extracting ground canopy information. The study area was Grasslands National Park (GNP) Canada and the surrounding pastures, which represent the northern mixed prairie. Fieldwork was conducted from late June to early July 2005. Biophysical variables—canopy height, cover, biomass, and species composition—were collected for 31 sites. Two satellite images, one SPOT 4 image on 22 June 2005, and one Landsat 5 TM image on 14 July 2005, were collected for the corresponding time period. Results show that the spectral curve of the grass canopy was similar to that of the bare soil with lower reflectance at each band. Consequently, commonly used vegetation indices were not necessarily better than reflectance when it comes to single wavelength regions at extracting biophysical information. Reflectance, NDVI, ATSAVI, and two new coined cover indices were good at extracting biophysical information.     

An analysis of spectral discrimination between corn and soybeans using a row crop reflectance model

MSS and TM band reflectance calculations of soybean and corn were made using a row crop reflectance model. Crop geometries representing conditions at two different times during the growing season—mid-July and mid-August—were used in order to compare the soybean-corn discrimination potential of MSS bands and TM bands at these two times. The model results confirm experimental evidence that the TM bands can be used for soybean-corn discrimination earlier in the season than can the MSS bands. The reflectance model results suggest that the sensitivity of the TM mid-IR bands to exposed soil between rows of the early soybean canopy is responsible for the early discrimination capability.