Jesús Delegido

Evaluation of Sentinel-2 Red-Edge Bands for Empirical Estimation of Green LAI and Chlorophyll Content

ESA’s upcoming satellite Sentinel-2 will provide Earth images of high spatial, spectral and temporal resolution and aims to ensure continuity for Landsat and SPOT observations. In comparison to the latter sensors, Sentinel-2 incorporates three new spectral bands in the red-edge region, which are centered at 705, 740 and 783 nm. This study addresses the importance of these new bands for the retrieval and monitoring of two important biophysical parameters: green leaf area index (LAI) and chlorophyll content (Ch). With data from several ESA field campaigns over agricultural sites (SPARC, AgriSAR, CEFLES2) we have evaluated the efficacy of two empirical methods that specifically make use of the new Sentinel-2 bands. First, it was shown that LAI can be derived from a generic normalized difference index (NDI) using hyperspectral data, with 674 nm with 712 nm as best performing bands. These bands are positioned closely to the Sentinel-2 B4 (665 nm) and the new red-edge B5 (705 nm) band. The method has been applied to simulated Sentinel-2 data. The resulting green LAI map was validated against field data of various crop types, thereby spanning a LAI between 0 and 6, and yielded a RMSE of 0.6. Second, the recently developed “Normalized Area Over reflectance Curve” (NAOC), an index that derives Ch from hyperspectral data, was studied on its compatibility with simulated Sentinel-2 data. This index integrates the reflectance curve between 643 and 795 nm, thereby including the new Sentinel-2 bands in the red-edge region. We found that these new bands significantly improve the accuracy of Ch estimation. Both methods emphasize the importance of red-edge bands for operational estimation of biophysical parameters from Sentinel-2.

Retrieval of Vegetation Biophysical Parameters Using Gaussian Process Techniques

This paper evaluates state-of-the-art parametric and nonparametric approaches for the estimation of leaf chlorophyll content (Chl), leaf area index, and fractional vegetation cover from space. The parametric approach involves comparison of established and generic narrowband vegetation indices (VIs) and the Normalized Area Over reflectance Curve method, which calculates the continuum spectral region sensitive to Chl. However, as not all available bands take part in these spectral algorithms, it remains unclear whether optimal estimations are achieved. Alternatively, the nonparametric approach is based on Gaussian process (GP) techniques and allows inclusion of all bands. GP builds a nonlinear regression as a linear combination of spectra mapped to a high-dimensional space. Moreover, GP provides an indication of the most contributing bands for each parameter, a weight for the most relevant spectra contained in the training data set, and a confidence estimate of the retrieval. GP has previously demonstrated to be competitive in accuracy with support vector regression and neural networks. Results from hyperspectral Compact High Resolution Imaging Spectrometer data over the Spanish Barrax test site show that GP outperformed the VIs in assessing the vegetation properties when using at least four out of the 62 bands. GP identified most contributing bands in the red and red edge and, to a lower extent, in the blue and NIR parts of the spectrum. Since the proposed GP method is able to build robust relationships between the parameter of interest and only a few bands, it is a promising approach for multispectral data as well.

Upward and downward solar-induced chlorophyll fluorescence yield indices of four tree species as indicators of traffic pollution in Valencia.

Passive steady-state chlorophyll fluorescence (Fs) provides a direct diagnosis of the functional status of vegetation photosynthesis. With the prospect of mapping Fs using remote sensing techniques, field measurements are mandatory to understand to which extent Fs allows detecting plant stress in different environments. Trees of four common species in Valencia were classified in either a low or a high local traffic exposure class based on their leaf magnetic value. Upward and downward hyperspectral fluorescence yield (FY) and indices based on the two Fs peaks (at 687 and 741 nm) were calculated. FY indices of P. canariensis and P. x acerifolia were significantly different between the two traffic exposure classes defined, but not for C. australis nor M. alba. While chlorophyll content could not indicate the difference between low and high traffic exposure, the FY(687)/FY(741) peak ratio increased significantly (p < 0.05) for both leaf sides for the higher traffic exposure class.

On the Semi-Automatic Retrieval of Biophysical Parameters Based on Spectral Index Optimization

Regression models based on spectral indices are typically empirical formulae enabling the mapping of biophysical parameters derived from Earth Observation (EO) data. Due to its empirical nature, it remains nevertheless uncertain to what extent a selected regression model is the most appropriate one, until all band combinations and curve fitting functions are assessed. This paper describes the application of a Spectral Index (SI) assessment toolbox in the Automated Radiative Transfer Models Operator (ARTMO) package. ARTMO enables semi-automatic retrieval and mapping of biophysical parameters from optical remote sensing observations. The SI toolbox facilitates the assessment of biophysical parameter retrieval accuracy of established as well as new and generic SIs. For instance, based on the SI formulation used, all possible band combinations of formulations with up to ten bands can be defined and evaluated. Several options are available in the SI assessment: calibration/validation data partitioning, the addition of noise and the definition of curve fitting models. To illustrate its functioning, all two-band combinations according to simple ratio (SR) and normalized difference (ND) formulations as well as various fitting functions (linear, exponential, power, logarithmic, polynomial) have been assessed. HyMap imaging spectrometer (430–2490 nm) data obtained during the SPARC-2003 campaign in Barrax, Spain, have been used to extract leaf area index (LAI) and leaf chlorophyll content (LCC) estimates. For both SR and ND formulations the most sensitive regions have been identified for two-band combinations of green (539–570 nm) with longwave SWIR (2421–2453 nm) for LAI (r2: 0.83) and far-red (692 nm) with NIR (1340 nm) or shortwave SWIR (1661–1686 nm) for LCC (r2: 0.93). Polynomial, logarithmic and linear fitting functions led to similar best correlations, though spatial differences emerged when applying the functions to HyMap imagery. We suggest that a systematic SI assessment is a strong requirement in the quality assurance approach for accurate biophysical parameter retrieval.

Retrieval of chlorophyll content and LAI of crops using hyperspectral techniques: application to PROBA/CHRIS data

Hyperspectral/multiangular data allow the retrieval of important vegetation properties at canopy level, such as the Leaf Area Index (LAI) and Leaf Chlorophyll Content. Current methods are based on the relationship between biophysical properties and retrievals from those spectral bands (from the complete hyperspectral/multiangular information) where specific absorption features are present within the considered spectral range. Furthermore, new sensors such as PROBA/CHRIS provide continuous hyperspectral reflectance measurements that can be considered as a continuous function of wavelength. The mathematical analysis of these continuous functions allows a new way of exploiting the relationships between spectral reflectance and biophysical variables by more powerful and stable mathematical tools, in particular for the retrieval of LAI and chlorophyll content. Within the overall context of the European Space Agency (ESA) Spectra Barrax Campaign (SPARC) experiment, an extensive field study was carried out in La Mancha, Spain, simultaneously to the overflight of airborne imaging spectrometers (AHS, HyMAP, ROSIS) and the overpass of CHRIS‐PROBA and MERIS sensors. During the SPARC‐2003 and SPARC‐2004 campaigns, numerous ground measurements were made in the Barrax study area (covering LAI, fCover, leaf chlorophyll a+b, leaf water content and leaf biomass), together with other complementary data, and a total of 17 CHRIS‐PROBA images were acquired. Representative points have been selected from a total of nine different crops, and also retrieved from the CHRIS‐PROBA images acquired within the days of the field campaign. About 250 reflectance spectra from five different observation angles have been analysed. Hyperspectral reflectance spectra have been adjusted by means of third‐degree polynomial functions between 500 nm and 750 nm, and correlations observed between LAI values and the coefficients of these polynomials yielded LAI as a result of the mathematical fitting. On the other hand, the area under the spectral reflectance curves has been calculated in the interval from 600 nm to 700 nm, the region of the red spectral interval where strong absorption features for chlorophyll have been observed, though areas under the curves are also strongly correlated to the chlorophyll content of the crops. Furthermore, a linear relationship between these areas and the chlorophyll content is proposed in this work. This relationship allows the retrieval of leaf chlorophyll by satellite data, based on the spectral information. Both of the proposed methods are almost independent of the observation angles employed. The high number of in situ measurements acquired simultaneously to satellite overpasses, and the broad available range of data, have allowed validation of both methods, with a large number of data and in a statistically consistent manner.

Rheological characterization of easy-to-disperse (ETD) Carbopol hydrogels

Experimental determinations of apparent viscosity were used to investigate the rheological behaviour of easy-to-disperse (ETD) Carbopol 2001, 2020 and 2050 hydrogels, involving different polymer concentrations, degrees of neutralization, agitation times and shear rates. Mathematical expressions were obtained, based on the power law, to allow calculation of the viscosity of each system, for the different variables studied. These equations proved valid within the 5.5-7.5 pH range, i.e., the pH interval of greatest interest in pharmaceutics and cosmetics. The rheological behaviours of the three types of ETD hydrogels were investigated comparatively and with respect to Carbopol 940, i.e., one of the most widely utilized hydrogels.

Integrated satellite data fusion and mining for monitoring lake water quality status of the Albufera de Valencia in Spain

Lake eutrophication is a critical issue in the interplay of water supply, environmental management, and ecosystem conservation. Integrated sensing, monitoring, and modeling for a holistic lake water quality assessment with respect to multiple constituents is in acute need. The aim of this paper is to develop an integrated algorithm for data fusion and mining of satellite remote sensing images to generate daily estimates of some water quality parameters of interest, such as chlorophyll a concentrations and water transparency, to be applied for the assessment of the hypertrophic Albufera de Valencia. The Albufera de Valencia is the largest freshwater lake in Spain, which can often present values of chlorophyll a concentration over 200 mg m(-3) and values of transparency (Secchi Disk, SD) as low as 20 cm. Remote sensing data from Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat Thematic Mapper (TM) and Enhance Thematic Mapper (ETM+) images were fused to carry out an integrative near-real time water quality assessment on a daily basis. Landsat images are useful to study the spatial variability of the water quality parameters, due to its spatial resolution of 30 m, in comparison to the low spatial resolution (250/500 m) of MODIS. While Landsat offers a high spatial resolution, the low temporal resolution of 16 days is a significant drawback to achieve a near real-time monitoring system. This gap may be bridged by using MODIS images that have a high temporal resolution of 1 day, in spite of its low spatial resolution. Synthetic Landsat images were fused for dates with no Landsat overpass over the study area. Finally, with a suite of ground truth data, a few genetic programming (GP) models were derived to estimate the water quality using the fused surface reflectance data as inputs. The GP model for chlorophyll a estimation yielded a R(2) of 0.94, with a Root Mean Square Error (RMSE) = 8 mg m(-3), and the GP model for water transparency estimation using Secchi disk showed a R(2) of 0.89, with an RMSE = 4 cm. With this effort, the spatiotemporal variations of water transparency and chlorophyll a concentrations may be assessed simultaneously on a daily basis throughout the lake for environmental management.

Viscous synergism in carrageenans (κ and λ) and locust bean gum mixtures : Influence of adding sodium carboxymethylcellulose

Synergistic interactions between locust bean gum (LBG) and two types of carrageenans (κ and λ) are studied. Viscous synergism index, I v as a function of concentration ratioz=ćLBG/ćcar, and shear rate were obtained for every mixture. In both binary systems the values of this index decrease with increasing shear rate. For the LBG + κ mixtures, I vpresented a maximum at a concentration ratio z≅60/40, which would be considered the optimum proportion of gums in the mixture. However, for the LBG + λ system, I v increased with z in the whole interval considered, i.e., the highest synergism corresponded to the lowest proportion of carrageenan. The addition of sodium carboxymethylcellulose (NaCMC) to the binary systems modified the above results. For LBG + κ + NaCMC mixtures, the maximum Ivvalues were similar to those corresponding to LBG + κ system, but the concentration ratio at which these maxima are produced shifted to a lesser proportion of locust bean gum (z ≅40/60). Moreover, the presence of NaCMC in the other ternary system totally eliminated the possible interaction between LBG and λ-carrageenan.

Influence of shear rate and concentration ratio on viscous synergism. Application to xanthan—Iocust bean gum— NaCMC mixtures Influencia de la velocidad de cizalla y la relación de concentraciones en la sinergia viscosa. Aplicación a mezclas de xantana-garrofín-CMCNa

A method is described that allows the development of an empirical approach to quantify synergistic interactions and their variations with shear rate. The approach is based on the definition of a viscous synergism index, I v. The method is applied to xanthan-locust bean gum gels, and an equation is developed for relating the synergism index to shear rate, γ, and the locust bean gum/xanthan gum concentration ratio, z. The value of at which that function has a maximum, I M V, is calculated. This value of z provided an estimation of the proportion of gums at which maximum synergism occurs. A decreasing exponential dependence of these I M V on γ is shown. The influence of the addition of a fixed proportion of a third gum (NaCMC) is also analyzed. The results obtained for the higher γ values are analogous to those of other authors.

A laboratory experiment on inferring Poiseuille's law for undergraduate students

In this paper a laboratory experiment is proposed to infer Poiseuilles law. A simple set-up based on two flasks joined by a detachable tube allows one to measure using tubes of different radii and different lengths. One of the flasks is connected to a vacuum pump to control the pressure differential between the tube extremes. The influence on the flow of different radii, lengths, pressures and viscosities can be studied in a didactic way by measuring the flow rate for each of these variables. The experiment can be performed getting together the students in groups, so that each group concentrates on the effect on the flow of a specific variable, leaving the rest fixed. After putting together all these results the law of Poiseuille can be obtained as a very good approach.