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

Statistical and radiative-transfer physically based studies have previously demonstrated the relationship between leaf water content and leaf-level reflectance in the near-infrared spectral region. The successful scaling up of such methods to the canopy level requires modeling the effect of canopy structure and viewing geometry on reflectance bands and optical indices used for estimation of water content, such as normalized difference water index (NDWI), simple ratio water index (SRWI) and plant water index (PWI). This study conducts a radiative transfer simulation, linking leaf and canopy models, to study the effects of leaf structure, dry matter content, leaf area index (LAI), and the viewing geometry, on the estimation of leaf equivalent water thickness from canopy-level reflectance. The applicability of radiative transfer model inversion methods to MODIS is studied, investigating its spectral capability for water content estimation. A modeling study is conducted, simulating leaf and canopy MODIS-equivalent synthetic spectra with random input variables to test different inversion assumptions. A field sampling campaign to assess the investigated simulation methods was undertaken for analysis of leaf water content from leaf samples in 10 study sites of chaparral vegetation in California, USA, between March and September 2000. MODIS reflectance data were processed from the same period for equivalent water thickness estimation by model inversion linking the PROSPECT leaf model and SAILH canopy reflectance model. MODIS reflectance data, viewing geometry values, and LAI were used as inputs in the model inversion for estimation of leaf equivalent water thickness, dry matter, and leaf structure. Results showed good correlation between the time series of MODIS-estimated equivalent water thickness and ground measured leaf fuel moisture (LFM) content (r²=0.7), demonstrating that these inversion methods could potentially be used for global monitoring of leaf water content in vegetation.     

Spectroscopic classification of tropical forest species using radiative transfer modeling

Leaf spectroscopy may be useful for tropical species discrimination, but few studies have provided an understanding of the spectral separability of species or how leaf spectroscopy scales to the canopy level relevant to mapping. Here we report on a study to classify humid tropical forest canopy species using field-measured leaf optical properties with leaf and canopy radiative transfer models. The experimental dataset included 188 canopy species collected in humid tropical forests of Hawaii. The leaf optical model PROSPECT-5 was used to simulate the leaf spectra of each species, which was used to train a classifier based on Linear Discriminant Analysis, and a canopy radiative transfer model 4SAIL2 to scale leaf measurements to the canopy level. The relationship linking classification accuracy at the leaf level to biodiversity showed an asymptotic trend reaching a maximum error of 47% when applied to the entire 188 species experimental dataset, and 56% when a simulated dataset showing amplified within-species spectral variability was used, suggesting uniqueness of the spectral signature for a significant proportion of species under study. The maximum error in canopy-level species classification was higher than leaf-level classification: 55% when canopy structure was held constant, and 64% with varying and unknown canopy structure. However, when classifying fewer species at a time, errors dropped considerably; for example, 20 species can be classified to 82-88% accuracy. These results highlight the potential of imaging spectroscopy to provide species discrimination in high-diversity, humid tropical forests.     

The effect of clumping on canopy scattering and its directional properties: a model simulation using spectral invariants

The spectral invariants theory predicts that the bidirectional reflectance factor (BRF) of a vegetation canopy can be expressed in terms of the canopy interceptance (i₀), the recollision probability (p), and the directional escape probability (ρ). These spectral invariant parameters together form a novel canopy structural parameter – the directional area scattering factor (DASF). The DASF can be retrieved from remotely sensed hyperspectral imagery and has been found to be useful, e.g. for the separation of tree species. The spectral invariants theory, however, does not provide an interpretation of which specific canopy structural properties are captured by the DASF. In this study, we examined the possible link between the DASF and the canopy clumping index (β). A simple model was designed to simulate the effect of β on canopy first order scattering, which was assumed to govern the directional behaviour of the DASF. The model is based on a modified spectral invariants approach, where the assumption of constant p is relaxed so that the first order recollision probability (p₁) and single scattering are calculated separately, and canopy BRF is expressed as the sum of the first and multiple order components. Simulations were performed on model canopies, where radiation penetration is described using a traditional statistical approach but allowing non-random foliage distributions caused by clumping. The results indicated a strong dependency between the modelled DASF and the canopy clumping index.     

Canopy spectral invariants for remote sensing and model applications

The concept of canopy spectral invariants expresses the observation that simple algebraic combinations of leaf and canopy spectral transmittance and reflectance become wavelength independent and determine a small set of canopy structure specific variables. This set includes the canopy interceptance, the recollision and the escape probabilities. These variables specify an accurate relationship between the spectral response of a vegetation canopy to the incident solar radiation at the leaf and the canopy scale and allow for a simple and accurate parameterization for the partitioning of the incoming radiation into canopy transmission, reflection and absorption at any wavelength in the solar spectrum. This paper presents a solid theoretical basis for spectral invariant relationships reported in literature with an emphasis on their accuracies in describing the shortwave radiative properties of the three-dimensional vegetation canopies. The analysis of data on leaf and canopy spectral transmittance and reflectance collected during the international field campaign in Flakaliden, Sweden, June 25-July 4, 2002 supports the proposed theory. The results presented here are essential to both modeling and remote sensing communities because they allow the separation of the structural and radiometric components of the measured/modeled signal. The canopy spectral invariants offer a simple and accurate parameterization for the shortwave radiation block in many global models of climate, hydrology, biogeochemistry, and ecology. In remote sensing applications, the information content of hyperspectral data can be fully exploited if the wavelength-independent variables can be retrieved, for they can be more directly related to structural characteristics of the three-dimensional vegetation canopy.     

Detection of leaf and canopy EWT by calculating REWT from reflectance spectra

The spectral characteristics of and the interaction between leaves and light were analysed based on the optical absorption coefficients of foliar water and biochemical components. The equations for calculating the radiative-equivalent water thickness (REWT) of leaves and canopy were presented based on the difference in reflectance at 945 and 975 nm. Because of the direct reflection on leaf surface and the leaf internal scattering, the REWT derived from the Beer–Lambert principle was different from the leaf or canopy equivalent water thickness (EWT). Two independent datasets at canopy or leaf scales were designed to calibrate and validate the relationships between EWT and REWT. The results show that (1) the leaf or canopy REWT can be calculated from the reflectance difference between 945 and 975 nm; (2) the leaf REWT was 3.3 times larger than the EWT with a significant determination coefficient (R ²) of 0.80 for our dataset and 0.86 for the Leaf Optical Properties Experiment (LOPEX'93) dataset; (3) the canopy REWT was 1.4 times larger than the EWT with a significant R ² of 0.56 for the winter wheat canopy spectral dataset in 2002, and 0.61 for the 2004 dataset. Therefore, the leaf or canopy EWT can be detected by calculating REWT from the difference in reflectance at 945 and 975 nm. Furthermore, because the relationship between REWT and EWT reflected the interaction of light with leaves or canopy, the multiple scattering optical pathlength in the near-infrared (NIR) bands can also be calculated by the ratio of REWT to EWT.     

Evaluation of an improved version of SAIL model for simulating bidirectional reflectance of sugar beet canopies

The processing of remote-sensing data requires simple but accurate models of directional reflectance of the vegetation canopy. In this study, a reflectance model for a homogeneous canopy is evaluated over an extensive set of radiometric measurements performed on sugar beet canopies. The model corresponds to the Scattering by Arbitrary Inclined Leaves (SAIL) model (Verhoef, 1984) in which the term for first order scattering is corrected for hot-spot and leaf specular reflectance. Leaf optical properties are calculated using the PROSPECT model (Jacquemond and Baret, 1990). Experimental data correspond to a two-year experiment and express a large variability of leaf area index, chlorophyll concentration and soil background optical properties. In the first data set, reflectance was measured about midday under vertical viewing in five optical Thematic Mapper bands. In the second data set, both vertical and oblique measurements (zenith angle 45°, four azimuth angles) were performed from sunrise to sunset in the three SPOT bands. Except for leaf cuticle reflectance, structure and optical variables were measured in the field or adjusted to field measurement, independently of reflectance calculations. Although the structure of sugar beet canopies departs strongly from a turbid medium, a good agreement with measurements was obtained in the case of vertical, north and south view directions. However, the model underestimated the measurements close to the hot-spot direction. In the near infrared, there was also some underestimation of canopy reflectance in the opposite direction to the hot-spot. Possible reasons for these differences are discussed.     

On the relationship of canopy LAI and photon recollision probability in boreal forests

The theory of spectral invariants, or ‘p-theory’, states that the canopy scattering coefficient at any wavelength can be related to the leaf scattering coefficient at the same wavelength through a spectrally invariant canopy structural parameter — the photon recollision probability p. The p-theory has recently gained interest in the vegetation reflectance modeling community as an efficient tool for characterizing scattering in clumped foliage structures. In this short communication paper, we report empirical data of the relationship of canopy leaf area index (LAI), diffuse non-interceptance and photon recollision probability for 1032 coniferous and broadleaved forest plots measured in Finland. Our results indicate that the relationship of canopy LAI and diffuse non-interceptance is near-universal in boreal stands i.e. it does not depend on stand age, tree species or growth conditions. This allows improving parameterizations used by canopy reflectance models which utilize the photon recollision probability concept. Our results also suggest that establishing species-specific p-LAI functions for northern European forests requires more research on the influence of micro- and macroscale foliage grouping on photon recollision probability.     

The photochemical reflectance index (PRI) and the remote sensing of leaf, canopy and ecosystem radiation use efficiencies: A review and meta-analysis

Traditional remote sensing techniques allow the assessment of green plant biomass, and therefore plant photosynthetic capacity. However, detecting how much of this capacity is actually realized is a more challenging goal. Is it possible to remotely assess actual carbon fluxes? Can this be done at leaf, canopy and ecosystem scales and at different temporal scales? Different approaches can be used to answer these questions. Among them, the Photochemical Reflectance Index (PRI) derived from narrow-band spectroradiometers is a spectral index increasingly being used as an indicator of photosynthetic efficiency. We examined and synthesized the scientific literature on the relationships between PRI and several ecophysiological variables across a range of plant functional types and ecosystems at the leaf, canopy and ecosystem levels and at the daily and seasonal time scales. Our analysis shows that although the strength of these relationships varied across vegetation types, levels of organization and temporal scales, in most reviewed articles PRI was a good predictor of photosynthetic efficiency or related variables with performances at least as good as the widely used NDVI as indicator of green biomass. There are possible confounding factors related to the intensity of the physiological processes linked to the PRI signals, to the structure of the canopies and to the illumination and viewing angles that warrant further studies, and it is expected that the utility of PRI will vary with the ecosystem in question due to contrasting environmental constraints, evolutionary strategies, and radiation use efficiency (RUE; the ratio between carbon uptake and light absorbed by vegetation) variability. Clearly, more research comparing ecosystem responses is warranted. Additionally, like any 2-band index that is affected by multiple factors, the interpretation of PRI can be readily confounded by multiple environmental variables, and further work is needed to understand and constrain these effects. Despite these limitations, this review shows an emerging consistency of the RUE-PRI relationship that suggests a surprising degree of functional convergence of biochemical, physiological and structural components affecting leaf, canopy and ecosystem carbon uptake efficiencies. PRI accounted for 42%, 59% and 62% of the variability of RUE at the leaf, canopy and ecosystem respective levels in unique exponential relationships for all the vegetation types studied. It seems thus that by complementing the estimations of the fraction of photosynthetically active radiation intercepted by the vegetation (FPAR), estimated with NDVI-like indices, PRI enables improved assessment of carbon fluxes in leaves, canopies and many of the ecosystems of the world from ground, airborne and satellite sensors.     

Simple parameterizations of the radiation budget of uniform broadleaved and coniferous canopies

Simulations of the different components of the spectral radiation budget of structurally simple leaf and shoot canopies with varying canopy leaf area index (LAI) were performed. The aims were (1) to test a proposed parameterization of the budget using two spectrally invariant canopy structural parameters (p and p_t) governing canopy absorption and transmittance, respectively, and (2) to incorporate the effect of within-shoot scattering in the parameterization for shoot canopies. Results showed that canopy spectral absorption and scattering were well described by a single parameter, the canopy p value or ‘recollision probability’, which was closely related to LAI. The relationship between p and LAI was however different in leaf and shoot canopy: e.g., at the same LAI the recollision probability was larger in the shoot canopy. It was shown that the p value of the shoot canopy could be decomposed into the p value of an individual shoot (p_sh) and the p value of the leaf canopy with the same effective LAI (LAI_e). The canopy p value allows calculation of canopy absorption and scattering at any given wavelength from the leaf (or needle) scattering coefficient at the same wavelength. To calculate canopy reflectance, separation of the downward and upward scattered parts is needed in addition. The proposed parameter p_t worked rather well in the leaf canopy at moderate values of LAI, but not in the coniferous shoot canopy nor at high values of LAI. However, the simulated fraction of upward scattered radiation increased in a straightforward manner with LAI, and was not particularly sensitive to the leaf (or needle) scattering coefficient. Judged by this ‘smooth’ behavior, the existence of another kind of simple parameterization for this separation remains an interesting possibility.     

Leaf chlorophyll content retrieval from airborne hyperspectral remote sensing imagery

Hyperspectral remote sensing has great potential for accurate retrieval of forest biochemical parameters. In this paper, a hyperspectral remote sensing algorithm is developed to retrieve total leaf chlorophyll content for both open spruce and closed forests, and tested for open forest canopies. Ten black spruce (Picea mariana (Mill.)) stands near Sudbury, Ontario, Canada, were selected as study sites, where extensive field and laboratory measurements were carried out to collect forest structural parameters, needle and forest background optical properties, and needle biophysical parameters and biochemical contents chlorophyll a and b. Airborne hyperspectral remote sensing imagery was acquired, within one week of ground measurements, by the Compact Airborne Spectrographic Imager (CASI) in a hyperspectral mode, with 72 bands and half bandwidth 4.25-4.36 nm in the visible and near-infrared region and a 2 m spatial resolution. The geometrical-optical model 4-Scale and the modified leaf optical model PROSPECT were combined to estimate leaf chlorophyll content from the CASI imagery. Forest canopy reflectance was first estimated with the measured leaf reflectance and transmittance spectra, forest background reflectance, CASI acquisition parameters, and a set of stand parameters as inputs to 4-Scale. The estimated canopy reflectance agrees well with the CASI measured reflectance in the chlorophyll absorption sensitive regions, with discrepancies of 0.06%-1.07% and 0.36%-1.63%, respectively, in the average reflectances of the red and red-edge region. A look-up-table approach was developed to provide the probabilities of viewing the sunlit foliage and background, and to determine a spectral multiple scattering factor as functions of leaf area index, view zenith angle, and solar zenith angle. With the look-up tables, the 4-Scale model was inverted to estimate leaf reflectance spectra from hyperspectral remote sensing imagery. Good agreements were obtained between the inverted and measured leaf reflectance spectra across the visible and near-infrared region, with R² = 0.89 to R² = 0.97 and discrepancies of 0.02%-3.63% and 0.24%-7.88% in the average red and red-edge reflectances, respectively. Leaf chlorophyll content was estimated from the retrieved leaf reflectance spectra using the modified PROSPECT inversion model, with R² = 0.47, RMSE = 4.34 μg/cm², and jackknifed RMSE of 5.69 μg/cm² for needle chlorophyll content ranging from 24.9 μg/cm² to 37.6 μg/cm². The estimates were also assessed at leaf and canopy scales using chlorophyll spectral indices TCARI/OSAVI and MTCI. An empirical relationship of simple ratio derived from the CASI imagery to the ground-measured leaf area index was developed (R² = 0.88) to map leaf area index. Canopy chlorophyll content per unit ground surface area was then estimated, based on the spatial distributions of leaf chlorophyll content per unit leaf area and the leaf area index.     

Towards red‐edge positions less sensitive to canopy biophysical parameters for leaf chlorophyll estimation using properties optique spectrales des feuilles (PROSPECT) and scattering by arbitrarily inclined leaves (SAILH) simulated data

Several methods for extracting the chlorophyll sensitive red‐edge position (REP) from hyperspectral data are reported in literature. This study is a continuation of a recent paper published as ‘A new technique for extracting the red edge position from hyperspectral data: the linear extrapolation method’. The method was validated experimentally for estimation of foliar nitrogen concentrations of rye, maize and mixed grass/herb. The objective of this study was to test the utility of the linear extrapolation method under different conditions including variable canopy biophysical parameters, solar zenith angle, sensor noise and spectral bandwidth. REPs were extracted from synthetic canopy spectra that were simulated using properties optique spectrales des feuilles (PROSPECT) and scattering by arbitrarily inclined leaves (SAILH) radiative transfer models. REPs extracted by the linear extrapolation method involving wavebands at 680, 694, 724 and 760 nm produced the highest correlation (R ² = 0.75) with leaf chlorophyll content with minimal effects of leaf and canopy biophysical confounders (leaf area index, leaf inclination distribution and leaf dry matter content) compared to traditional techniques including the linear interpolation, inverted Gaussian modelling and polynomial fitting techniques. In addition, the new technique is insensitive to changes in solar zenith angle. However, the advantage of using the linear extrapolation method compared to the various alternative methods diminishes with increasing sensor noise and decreasing spectral resolution. In summary, the linear extrapolation technique confirms its high potential for leaf chlorophyll estimation. The efficacy of the technique under field conditions needs to be established.     

Spectral normalized indices related with forage quality in temperate grasses: scaling up from leaves to canopies

Forage quality is an important regulator of livestock performance also determining the grazing capacity in grasslands and pastures. The objective of this work was to develop spectral normalized indices to accurately predict canopy nitrogen (N), neutral detergent fibre (NDF), and acid detergent fibre (ADF) concentrations and in vitro dry matter digestibility (IVDMD) in three forage species, at two phenological stages and under two fertilization conditions. To select indices with the highest possible independence from canopy structure, we prioritized the selection of indices that were stable at both leaf and canopy scales and evaluated if the best selected indices were correlated with selected leaf and canopy structural traits and leaf water content. All possible normalized indices, based on the reflectance and the first difference reflectance, for the 400–2400 nm spectral range were related through simple regression models with N, NDF, and ADF concentrations and IVDMD. The index that combined the first difference reflectance in the 685 and 1770 nm wavelengths was found to be a potentially useful index to predict canopy N concentration under different field conditions. The best indices selected to predict canopy NDF and ADF concentration and IVDMD, based on the reflectance around 2120–2145 and 2250–2260 nm, had limited application and appeared to be suitable only to identify gross differences in fibre and IVDMD. Future studies should analyse how the best selected indices behave under field lighting conditions and for a wide range of species, phenological stages, and variations in canopy structural traits.     

Estimating dry matter content from spectral reflectance for green leaves of different species

Efficient and accurate detection of the temporal dynamics and spatial variations of leaf dry matter content would help monitor key properties and processes in vegetation and the wider ecosystem. However, leaf water content strongly absorbs at shortwave infrared wavelengths, reducing the signal from dry matter. The major objective of this study was to examine relationship between spectral reflectance of fresh leaves and the ratio of leaf dry mass to leaf area, across a wide range of species at the leaf scale. A narrow-band, normalized index combining two distinct wavebands centred at 1649 and 1722 nm achieved the highest overall performance and discriminatory power compared to either single band or first derivatives. The normalized index was evaluated using the PROSPECT (leaf optical properties spectra) simulated reflectance spectra and field measurements from the Leaf Optical Properties Experiment (LOPEX) data set. Both evaluations show that leaf dry matter contents were retrievable with R ² of 0.845 and 0.681 and regression slopes of 0.903 and 0.886. This study suggests that spectral reflectance measurements hold promise for the assessment of dry matter content for green leaves. Further investigation needs to be conducted to evaluate the effectiveness of this normalized index at canopy scales.     

A near-infrared narrow-waveband ratio to determine Leaf Area Index in orchards

An innovative index for LAI estimation over orchard canopies based on the combination of two near-infrared narrow wavebands (1050 nm and 1250 nm) is presented. The index is insensitive to physiological changes on the leaf level even under changing pheneological developmental stage. In the meantime, the index is highly sensitive for variations at the canopy level. Values of LAI estimated by means of this newly developed index, called sLAIDI (standardized LAI Determining Index), resulted in excellent agreements with in-situ measured LAI values of citrus trees, with determination coefficients (R²) of 0.83. Based on in-situ measured data and simulated data (PROSPECT and ACRM), the newly developed sLAIDI was also found to perform outstanding at high LAI values in contrary to well-known LAI related indices such as the Normalized Difference Vegetation Index (NDVI) and the Modified Chlorophyll Ratio Index 2 (MCARI2) that saturate at LAI values of 5 and 8 respectively. Moreover, the sLAIDI index was independent of changing pigment contents. Consequently, this index was regarded a valuable tool to more accurately extract biochemical parameters after normalizing the considered spectral data for LAI. By implementing sLAIDI in existing chlorophyll-related indices (e.g., GM index), the performance to estimate the leaf chlorophyll content from spectral citrus and peach canopy level data is increased (R² increases from 0.68 to 0.77). Moreover, a correction factor was proposed to enable the application of sLAIDI on fields with strong variations of water content.     

Direct retrieval of the shape of leaf spectral albedo from multiangular hyperspectral Earth observation data

Physically-based retrieval of vegetation canopy properties from remote sensing data presumes a knowledge of the spectral albedo of the basic scattering unit, i.e. leaf. In this paper, we present a novel method to directly retrieve the spectral dependence of leaf single-scattering albedo of a closed broadleaf forest canopy from multiangular hyperspectral satellite imagery. The new algorithm is based on separating the reflected signal into a linear (first-order) and non-linear (diffuse) reflectance component. A limitation of the proposed algorithm is that the leaf single-scattering albedo ω(λ) is retrieved with an accuracy of a structural parameter (called a₀) which, in turn, depends on canopy bidirectional gap probability, ratio of leaf reflectance to transmittance, and distribution of leaf normals. The structural parameter (a₀) was found to depend on tree-level structural parameters, such as tree height and volume of a single crown, but not the amount of leaf area.     

Towards estimation of canopy foliar biomass with spectral reflectance measurements

Canopy foliar biomass, defined as the product of leaf dry matter content and leaf area index, is an important measurement for global biogeochemical cycles. This study explores the potential for retrieving foliar biomass in green canopies using a spectral index, the Normalized Dry Matter Index (NDMI). This narrow-band index is based on absorption at the C-H bond stretch overtone and is correlated with leaf dry matter content in fresh green leaves. PROSPECT and SAIL model simulations suggest that the NDMI at the canopy scale is able to minimize the effects of leaf thickness and leaf water content and to maximize sensitivity to variation in canopy foliar biomass. The simulation outputs were analyzed with an ANOVA, and 87% of the variation in the NDMI is explained by leaf dry matter content. The NDMI was linearly related to foliar biomass (g cm^− 2) from model simulations (R² = 0.97). The NDMI calculated from spectral reflectances for one to four stacked leaves was also correlated with total leaf biomass (R² = 0.59). These results suggest that it may be possible to determine foliar biomass from airborne and satellite-borne imaging spectrometers, such as NASA's HyspIRI mission.     

Effects of woody elements on simulated canopy reflectance: Implications for forest chlorophyll content retrieval

An important bio-indicator of actual plant health status, the foliar content of chlorophyll a and b (Cab), can be estimated using imaging spectroscopy. For forest canopies, however, the relationship between the spectral response and leaf chemistry is confounded by factors such as background (e.g. understory), canopy structure, and the presence of non-photosynthetic vegetation (NPV, e.g. woody elements)—particularly the appreciable amounts of standing and fallen dead wood found in older forests. We present a sensitivity analysis for the estimation of chlorophyll content in woody coniferous canopies using radiative transfer modeling, and use the modeled top-of-canopy reflectance data to analyze the contribution of woody elements, leaf area index (LAI), and crown cover (CC) to the retrieval of foliar Cab content. The radiative transfer model used comprises two linked submodels: one at leaf level (PROSPECT) and one at canopy level (FLIGHT). This generated bidirectional reflectance data according to the band settings of the Compact High Resolution Imaging Spectrometer (CHRIS) from which chlorophyll indices were calculated. Most of the chlorophyll indices outperformed single wavelengths in predicting Cab content at canopy level, with best results obtained by the Maccioni index ([R₇₈₀ − R₇₁₀] / [R₇₈₀ − R₆₈₀]). We demonstrate the performance of this index with respect to structural information on three distinct coniferous forest types (young, early mature and old-growth stands). The modeling results suggest that the spectral variation due to variation in canopy chlorophyll content is best captured for stands with medium dense canopies. However, the strength of the up-scaled Cab signal weakens with increasing crown NPV scattering elements, especially when crown cover exceeds 30%. LAI exerts the least perturbations. We conclude that the spectral influence of woody elements is an important variable that should be considered in radiative transfer approaches when retrieving foliar pigment estimates in heterogeneous stands, particularly if the stands are partly defoliated or long-lived.     

Relationships of leaf nitrogen concentration and canopy nitrogen density with spectral features parameters and narrow-band spectral indices calculated from field winter wheat (Triticum aestivum L.) spectra

Remote sensing is a promising tool that provides quantitative and timely information for crop stress detection over large areas. Nitrogen (N) is one of the important nutrient elements influencing grain yield and quality of winter wheat (Triticum aestivum L.). In this study, canopy spectral parameters were evaluated for N status assessment in winter wheat. A winter wheat field experiment with 25 different cultivars was conducted at the China National Experimental Station for Precision Agriculture, Beijing, China. Wheat canopy spectral reflectance over 350–2500 nm at different stages was measured with an ASD FieldSpec Pro 2500 spectrometer (Analytical Spectral Devices, Boulder, CO, USA) fitted with a 25° field of view (FOV) fibre optic adaptor. Thirteen narrow-band spectral indices, three spectral features parameters associated with the absorption bands centred at 670 and 980 nm and another three related to reflectance maximum values located at 560, 920, 1690 and 2230 nm were calculated and correlated with leaf N concentration (LNC) and canopy N density (CND). The results showed that CND was a more sensitive parameter than LNC in response to the variation of canopy-level spectral parameters. The correlation coefficient values between LNC and CND, on the one hand, and narrow-band spectral indices and spectral features parameters, on the other hand, varied with the growth stages of winter wheat, with no predominance of a single spectral parameter as the best variable. The differences in correlation results for the relationships of CND and LNC with narrow-band spectral indices and spectral features parameters decreased with wheat plant developing from Feekes 4.0 to Feekes 11.1. The red edge position (REP) was demonstrated to be a good indicator for winter wheat LNC estimation. The absorption band depth (ABD) normalized to the area of absorption feature (NBD) at 670 nm (NBD670) was the most reliable indicator for winter wheat canopy N status assessment.     

The Pasterze Glacier,Austria

The remote sensing of foliar biochemical concentration assumes that leaf biochemical absorption features will be manifest in canopy reflectance. This is a reasonable assumption providing the effect of a given change in foliar biochemical concentration has a similar effect on both leaf and canopy reflectance. A comparison between canopy and leaf reflectance was made to determine if canopy effects (composite of leaf area index, biomass, structure, multiple scattering and shadow) could alter the leaf biochemical information in canopy reflectance spectra. Differences in leaf biochemical concentrations and leaf biomass were induced by the application of fertilisers to large plots of slash pine (Pinus elliottii var elliottii) in Florida, U.S.A. The reflectance of plot canopies was measured using the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). The reflectance of samples of leaves drawn from each plot were measured using a laboratory spectrometer. The differences between airborne and laboratory reflectance ratios (fertilised/control spectra) were used to isolate the effects of the canopy in AVIRIS reflectance spectra. From this study it was concluded that the canopy influenced leaf reflectance substantially at wavelengths beyond the water absorption feature at 1400nrn and leaf biochemical information was transmitted virtually unchanged from the leaf to the canopy in near-infrared wavelengths.