GLORIA - A globally representative hyperspectral in situ dataset for optical sensing of water quality.

The development of algorithms for remote sensing of water quality (RSWQ) requires a large amount of in situ data to account for the bio-geo-optical diversity of inland and coastal waters. The GLObal Reflectance community dataset for Imaging and optical sensing of Aquatic environments (GLORIA) includes 7,572 curated hyperspectral remote sensing reflectance measurements at 1 nm intervals within the 350 to 900 nm wavelength range. In addition, at least one co-located water quality measurement of chlorophyll a, total suspended solids, absorption by dissolved substances, and Secchi depth, is provided.

An insight into spectral composition of light available for photosynthesis via remotely assessed absorption coefficient at leaf and canopy levels.

Non-invasive comparative analysis of the spectral composition of energy absorbed by crop species at leaf and plant levels was carried out using the absorption coefficient retrieved from leaf and plant reflectance as an informative metric. In leaves of three species with contrasting leaf structures and photosynthetic pathways (maize, soybean, and rice), the blue, green, and red fractions of leaf absorption coefficients were 48, 20, and 32%, respectively. The fraction of green light in the total budget of light absorbed at the plant level was higher than at the leaf level approaching the size of the red fraction (24% green vs.

Foliar absorption coefficient derived from reflectance spectra: A gauge of the efficiency of in situ light-capture by different pigment groups.

The absorption of Photosynthetically Active Radiation (PAR) by different foliar pigments defines the amount of energy available for photosynthesis and also the need for photoprotection. Both characteristics reveal essential information about productivity, development, and stress acclimation of plants. Here we present an approach for the estimation of the efficiency by three foliar pigment groups (chlorophylls, carotenoids, and anthocyanins) at capturing light, via the absorption coefficient derived from leaf reflectance spectra.

Towards a generic approach to remote non-invasive estimation of foliar carotenoid-to-chlorophyll ratio.

Changes of chlorophyll (Chl) and carotenoid (Car) contents and their ratio (Car/Chl) represent a sensitive indicator of vegetation photosynthetic activity, developmental changes, and stress responses. The goal of this study was to design methods for estimating Car/Chl in plants across species, seasonal changes and ontogenetic phases requiring no species-specific parameterization. Four tree species (maple, chestnut, beech, and elm), wild vine shrub, and two crops species (maize and soybean) featuring contrasting leaf structure and photosynthetic pathways, a wide variation of pigment content and composition were studied.

Non-invasive quantification of foliar pigments: Possibilities and limitations of reflectance- and absorbance-based approaches.

Established reflectance-based approaches for estimation of foliar pigment contents assume close relationship between leaf absorbance and reflectance. Complex organization and high pigment content of leaves may lead to violation of the essential assumptions under Kubleka-Munk theory relating reflectance and absorbance. We compared relationships of absorbance and reciprocal reflectance vs.

In situ optical properties of foliar flavonoids: Implication for non-destructive estimation of flavonoid content.

Flavonoids are a ubiquitous multifunctional group of phenolics of paramount importance for the terrestrial plants involved in protection from biotic and abiotic stresses, color and chemical signaling and other functions. Deciphering of in situ absorption of foliar Flv is important but was thought to be impossible due to a strong overlap with other pigments, complex in situ chemistry of Flv and sophisticated leaf optics. We deduced in situ absorbance of foliar Flv and introduced a concept of specific absorbance spectrum indicative of each pigment group contribution to light absorption and provided a rationale for the choice of spectral bands for non-destructive assessment of Flv in leaves with variable content of other pigments including anthocyanins.

Simple and robust methods for remote sensing of canopy chlorophyll content: a comparative analysis of hyperspectral data for different types of vegetation.

Canopy chlorophyll content (CCC) is an essential ecophysiological variable for photosynthetic functioning. Remote sensing of CCC is vital for a wide range of ecological and agricultural applications. The objectives of this study were to explore simple and robust algorithms for spectral assessment of CCC.

Efficiency of chlorophyll in gross primary productivity: A proof of concept and application in crops.

One of the main factors affecting vegetation productivity is absorbed light, which is largely governed by chlorophyll. In this paper, we introduce the concept of chlorophyll efficiency, representing the amount of gross primary production per unit of canopy chlorophyll content (Chl) and incident PAR. We analyzed chlorophyll efficiency in two contrasting crops (soybean and maize).

Productivity, absorbed photosynthetically active radiation, and light use efficiency in crops: implications for remote sensing of crop primary production.

Vegetation productivity metrics such as gross primary production (GPP) at the canopy scale are greatly affected by the efficiency of using absorbed radiation for photosynthesis, or light use efficiency (LUE). Thus, close investigation of the relationships between canopy GPP and photosynthetically active radiation absorbed by vegetation is the basis for quantification of LUE. We used multiyear observations over irrigated and rainfed contrasting C3 (soybean) and C4 (maize) crops having different physiology, leaf structure, and canopy architecture to establish the relationships between canopy GPP and radiation absorbed by vegetation and quantify LUE.

Non-destructive estimation of foliar carotenoid content of tree species using merged vegetation indices.

Leaf pigment content is an important indicator of plant status and can serve to assess the vigor and photosynthetic activity of plants. The application of spectral information gathered from laboratory, field and remote sensing-based spectrometers to non-destructively assess total chlorophyll (Chl) content of higher plants has been demonstrated in earlier studies. However, the precise estimation of carotenoid (Car) content with non-destructive spectral measurements has so far not reached accuracies comparable to the results obtained for Chl content.

Estimation of vegetation photosynthetic capacity from space-based measurements of chlorophyll fluorescence for terrestrial biosphere models.

Photosynthesis simulations by terrestrial biosphere models are usually based on the Farquhar's model, in which the maximum rate of carboxylation (Vcmax ) is a key control parameter of photosynthetic capacity. Even though Vcmax is known to vary substantially in space and time in response to environmental controls, it is typically parameterized in models with tabulated values associated to plant functional types. Remote sensing can be used to produce a spatially continuous and temporally resolved view on photosynthetic efficiency, but traditional vegetation observations based on spectral reflectance lack a direct link to plant photochemical processes.

Estimation of chlorophyll-a concentration in turbid productive waters using airborne hyperspectral data.

Algorithms based on red and near infra-red (NIR) reflectances measured using field spectrometers have been previously shown to yield accurate estimates of chlorophyll-a concentration in turbid productive waters, irrespective of variations in the bio-optical characteristics of water. The objective of this study was to investigate the performance of NIR-red models when applied to multi-temporal airborne reflectance data acquired by the hyperspectral sensor, Airborne Imaging Spectrometer for Applications (AISA), with non-uniform atmospheric effects across the dates of data acquisition. The results demonstrated the capability of the NIR-red models to capture the spatial distribution of chlorophyll-a in surface waters without the need for atmospheric correction.

NIR-red reflectance-based algorithms for chlorophyll-a estimation in mesotrophic inland and coastal waters: Lake Kinneret case study.

A variety of models have been developed for estimating chlorophyll-a (Chl-a) concentration in turbid and productive waters. All are based on optical information in a few spectral bands in the red and near-infra-red regions of the electromagnetic spectrum. The wavelength locations in the models used were meticulously tuned to provide the highest sensitivity to the presence of Chl-a and minimal sensitivity to other constituents in water.

Tracking plant physiological properties from multi-angular tower-based remote sensing.

Imaging spectroscopy is a powerful technique for monitoring the biochemical constituents of vegetation and is critical for understanding the fluxes of carbon and water between the land surface and the atmosphere. However, spectral observations are subject to the sun-observer geometry and canopy structure which impose confounding effects on spectral estimates of leaf pigments. For instance, the sun-observer geometry influences the spectral brightness measured by the sensor.

Algorithms for remote estimation of chlorophyll-a in coastal and inland waters using red and near infrared bands.

Remote sensing algorithms that use red and NIR bands for the estimation of chlorophyll-a concentration [Chl] can be more effective in inland and coastal waters than algorithms that use blue and green bands. We tested such two-band and three-band red-NIR algorithms using comprehensive synthetic data sets of reflectance spectra and inherent optical properties related to various water parameters and a very consistent in situ data set from several lakes in Nebraska, USA. The two-band algorithms tested with MERIS bands were Rrs(708)/Rrs(665) and Rrs(753)/Rrs(665).

Nondestructive estimation of anthocyanins and chlorophylls in anthocyanic leaves.

The anthocyanin and chlorophyll contents in leaves provide valuable information about the physiological status of plants. Thus, there is a need for accurate, efficient, and practical methodologies to estimate these biochemical parameters of vegetation. In this study, we tested the performance and accuracy of several nondestructive, reflectance-based techniques for estimating anthocyanin and chlorophyll contents in leaves of four unrelated species, European hazel (Corylus avellana), Siberian dogwood (Cornus alba =Swida alba), Norway maple (Acer platanoides), and Virginia creeper (Parthenocissus quinquefolia), with widely variable pigment content and composition.

Non-destructive determination of maize leaf and canopy chlorophyll content.

The objective of this study was to develop a rapid non-destructive technique to estimate total chlorophyll (Chl) content in a maize canopy using Chl content in a single leaf. The approach was (1) to calibrate and validate a reflectance-based non-destructive technique to estimate leaf Chl in maize; (2) to quantify the relative contribution of each leaf Chl to the total Chl in the canopy; and (3) to establish a relationship between leaf Chl content and total Chl in a maize canopy. The Red Edge Chlorophyll Index CI(red edge)=(R(NIR)/R(red edge))-1 based on reflectances, R, in the red edge (720-730nm) and near infrared (770-800nm) was found to be an accurate measure of maize leaf Chl.

Effect of bio-optical parameter variability and uncertainties in reflectance measurements on the remote estimation of chlorophyll-a concentration in turbid productive waters: modeling results.

Most algorithms for retrieving chlorophyll-a concentration (Chla) from reflectance spectra assume that bio-optical parameters such as the phytoplankton specific absorption coefficient (aPhi*) or the chlorophyll-a fluorescence quantum yield (eta) are constant. Yet there exist experimental data showing large ranges of variability for these quantities. The main objective of this study was to analyze the sensitivity of two Chla algorithms to variations in bio-optical parameters and to uncertainties in reflectance measurements.

Apple flavonols during fruit adaptation to solar radiation: spectral features and technique for non-destructive assessment.

Spectral properties of flavonols of three varieties (Golden Delicious, Antonovka, and Renet Simirenko) of anthocyanin-free apple fruit were investigated with reflectance spectroscopy. The results of spectral and biochemical analyses suggested that fruit reflectance in a broad spectral range 365-430 nm is strongly dependent on and, in sunlit fruit surfaces, governed by flavonols. The build up of peel flavonols (mainly rutin and other quercetin glycosides) resulted in a dramatic decrease of fruit reflectance in this range, flattening of the spectrum, and extending the region with low reflectance (4-5%) to ca.

Effect of bio-optical parameter variability on the remote estimation of chlorophyll-a concentration in turbid productive waters: experimental results.

The analytical development and underlying hypothesis of a three-band algorithm for estimating chlorophyll-a concentration ([Chla]) in turbid productive waters are presented. The sensitivity of the algorithm to the spectral location of the bands used is analyzed. A large set of experimental observations ([Chla] varied between 4 and 217 mg m(-3) and turbidity between 2 and 78 nephelometric turbidity units) was used to calibrate and validate the algorithm.

Wide Dynamic Range Vegetation Index for remote quantification of biophysical characteristics of vegetation.

The Normalized Difference Vegetation Index (NDVI) is widely used for monitoring, analyzing, and mapping temporal and spatial distributions of physiological and biophysical characteristics of vegetation. It is well documented that the NDVI approaches saturation asymptotically under conditions of moderate-to-high aboveground biomass. While reflectance in the red region (rho(red)) exhibits a nearly flat response once the leaf area index (LAI) exceeds 2, the near infrared (NIR) reflectance (PNIR) continue to respond significantly to changes in moderate-to-high vegetation density (LAI from 2 to 6) in crops.

Relationships between leaf chlorophyll content and spectral reflectance and algorithms for non-destructive chlorophyll assessment in higher plant leaves.

Leaf chlorophyll content provides valuable information about physiological status of plants. Reflectance measurement makes it possible to quickly and non-destructively assess, in situ, the chlorophyll content in leaves. Our objective was to investigate the spectral behavior of the relationship between reflectance and chlorophyll content and to develop a technique for non-destructive chlorophyll estimation in leaves with a wide range of pigment content and composition using reflectance in a few broad spectral bands.