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NASA NTRS1993

Relationships between pigment composition variation and reflectance for plant species from a coastal savannah in California

Advances in imaging spectroscopy have indicated that remotely sensed reflectance measurements of the plant canopy may be used to identify and qualify some classes of canopy biochemicals; however, the manner in which differences in biochemical compositions translate into differences is not well understood. Most frequently, multiple linear regression routines have been used to correlate narrow band reflectance values with measured biochemical concentrations. Although some success has been achieved with such methods for given data sets, the bands selected by multiple regression are not consistent between data sets, nor is it always clear what physical or biological basis underlies the correlation. To examine the relationship between biochemical concentration and leaf reflectance signal we chose to focus on the visible spectrum where the primary biochemical absorbances are due to photosynthetic pigments. Pigments provide a range of absorbance features, occur over a range of concentrations in natural samples, and are ecophysiologically important. Concentrations of chlorophyll, for example, have been strongly correlated to foliar nitrogen levels within a species and to photosynthetic capacity across many species. In addition pigments effectively absorb most of the photosynthetically active radiation between 400-700 nm, a spectral region for which silicon detectors have good signal/noise characteristics. Our strategy has been to sample a variety of naturally occurring species to measure leaf reflectance and pigment compositions. We hope to extend our understanding of pigment reflectance effects to interpret small overlapping absorbances of other biochemicals in the infrared region. For this reason, selected samples were also tested to determine total nitrogen, crude protein, cellulose, and lignin levels. Leaf reflectance spectra measured with AVIRIS bandwidths and wavelengths were compared between species and within species and for differences between seasons, for changes in the the shape of the spectra. We attempt to statistically correlate these shape changes with differences in pigment compositions. In parallel with our comparisons of pigment composition and leaf reflectance, we have modified the PROSPECT leaf reflectance model to test the contributions of pigments or pigment group concentrations. PROSPECT considers a leaf as a multi-layer dielectric plane with an uneven surface. Jacquemoud adapted the basic analysis of Allen for surface effects, a leaf thickness factor, and the absorption of water and chlorophyll (actually all pigments) and the plant matrix. Our modifications to PROSPECT in the forward direction include breaking out the pigment concentration parameter into separate components for chlorophyll a and b and a number of xanthophylls and carotenes, and introducing a shift and convolution function to model the spread and shift from their in vitro measurements to their in vivo state. Further, we have considered how the matrix elements (i.e., all biochemicals and structural effects not modeled explicity) vary with species.

Ustin, Susan L.↗

NASA NTRS1975

Soil, water, and vegetation conditions in south Texas

The author has identified the following significant results. To distinguish dead from live vegetation, spectrophotometrically measured infinite reflectance of dead and live corn (Zea mays L.) leaves were compared over the 0.5 to 2.5 micron waveband. Dead leaf reflectance was reached over the entire 0.5 to 2.5 micron waveband by stacking only two to three leaves. Live leaf reflectance was attained by stacking two leaves for the 0.5 to 0.75 micron waveband (chlorophyll absorption region), eight leaves for the 0.75 to 1.35 micron waveband (near infrared region), and three leaves for the 1.35 to 2.5 micron waveband (water absorption region). LANDSAT-1 MSS digital data for 11 December 1973 overpass were used to estimate the sugar cane acreage in Hidalgo County. The computer aided estimate was 22,100 acres compared with the Texas Crop and Livestock Reporting Service estimate of 20,500 acres for the 1973-'74 crop year. Although there were errors of omission from harvested fields that were identified as bare soil and some citrus and native vegetation that were mistakenly identified as sugar cane, the mapped location of sugar cane fields in the county compared favorably with their location on the thematic map generated by the computer.

Wiegand, C. L.↗

NASA NTRS2023

Structural Complexity Biases Vegetation Greenness Measures

Vegetation ‘greenness’ characterized by spectral vegetation indices (VIs) is an integrative measure of vegetation leaf abundance, biochemical properties and pigment composition. Surprisingly, satellite observations reveal that several major VIs over the US Corn Belt are higher than those over the Amazon rainforest, despite the forests having a greater leaf area. This contradicting pattern underscores the pressing need to understand the underlying drivers and their impacts to prevent misinterpretations. Here we show that macroscale shadows cast by complex forest structures result in lower greenness measures compared with those cast by structurally simple and homogeneous crops. The shadow-induced contradictory pattern of VIs is inevitable because most Earth-observing satellites do not view the Earth in the solar direction and thus view shadows due to the sun–sensor geometry. The shadow impacts have important implications for the interpretation of VIs and solar-induced chlorophyll fluorescence as measures of global vegetation changes. For instance, a land-conversion process from forests to crops over the Amazon shows notable increases in VIs despite a decrease in leaf area. Our findings highlight the importance of considering shadow impacts to accurately interpret remotely sensed VIs and solar-induced chlorophyll fluorescence for assessing global vegetation and its changes.

Vegetation indices↗

NASA NTRS2000

BOREAS TE-10 Leaf Chemistry Data

The BOREAS TE- 10 team collected several data sets in support of its efforts to characterize and interpret information on the reflectance, transmittance, gas exchange, chlorophyll content, carbon content, hydrogen content, and nitrogen content of boreal vegetation. This data set describes the relationship between sample location, age, chlorophyll content, and C-H-N concentrations at several sites in the SSA conducted during the growing seasons of 1994 and 1996. The data are stored in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Center (DAAC).

Hall, Forrest G.↗

NASA NTRS1993

The red edge in arid region vegetation: 340-1060 nm spectra

The remote sensing study of vegetated regions of the world has typically been focused on the use of broad-band vegetation indices such as NDVI. Various modifications of these indices have been developed in attempts to minimize the effect of soil background, e.g., SAVI, or to reduce the effect of the atmosphere, e.g., ARVI. Most of these indices depend on the so-called 'red edge,' the sharp transition between the strong absorption of chlorophyll pigment in visible wavelengths and the strong scattering in the near-infrared from the cellular structure of leaves. These broadband indices tend to become highly inaccurate as the green canopy cover becomes sparse. The advent of high spectral resolution remote sensing instrument such as the Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) has allowed the detection of narrow spectral features in vegetation and there are reports of detection of the red edge even for pixels with very low levels of green vegetation cover by Vane et al. and Elvidge et al., and to characterize algal biomass in coastal areas. Spectral mixing approaches similar to those of Smith et al. can be extended into the high spectral resolution domain allowing for the analysis of more endmembers, and potentially, discrimination between material with narrow spectral differences. Vegetation in arid regions tends to be sparse, often with small leaves such as the creosote bush. Many types of arid region vegetation spend much of the year with their leaves in a senescent state, i.e., yellow, with lowered chlorophyll pigmentation. The sparseness of the leaves of many arid region plants has the dual effect of lowering the green leaf area which can be observed and of allowing more of the sub-shrub soil to be visible which further complicates the spectrum of a region covered with arid region vegetation. Elvidge examined the spectral characteristics of dry plant materials showing significant differences in the region of the red edge and the diagnostic ligno-cellulose absorptions at 2090 nm and 2300 nm. Ray et al. detected absorption at 2100 nm in AVIRIS spectra of an abandoned field known to be covered by a great deal of dead plant litter. In order to better study arid region vegetation remote sensing data, it is necessary to better characterize the reflectance spectra of in situ, living, arid region plants.

Ray, Terrill W.↗

NASA NTRS1994

Effects of radiation quality, intensity, and duration on photosynthesis and growth

Differences in radiation quality from the six most common electric lamps have little effect on photosynthetic rate. Radiation quality primarily alters growth because of changes in branching or internode elongation, which change radiation absorption. Growth and yield in wheat appear to be insensitive to radiation quality. Growth and yield in soybeans can be slightly increased under high pressure sodium (HPS) lamps compared to metal halide lamps, in spite of greatly reduced chlorophyll concentrations under HPS lamps. Daily integrated photosynthetic photon flux (mol m(exp -2)d(exp -1)) most directly determines leaf anatomy and growth. Photosynthetic photon flux (PPF) levels of 800 (mu)mol m(exp -2)s(exp -1) are adequate to simulate field daily-integrated PPF levels for both short and long day plants, but plant canopies can benefit from much higher PPF levels.

Bugbee, Bruce↗

NASA NTRS2003

Foliar Reflectance and Fluorescence Responses for Corn and Soybean Plants Under Nitrogen Stress

We are investigating the use of spectral indices derived from actively induced fluorescence spectra and passive optical spectra. We examined the influence of photosynthetic pigment, carbon (C) and nitrogen (N) content on the spectral fluorescence and passive optical property characteristics of mature, upper leaves from plants provided different N fertilizer application rates: 20%, 50%, 100% and 150% of recommended N levels. A suite of optical, fluorescence, and biophysical measurements were collected on leaves from field grown corn (Zea mays L.) and soybean plants (Glycine max L.) grown in pots (greenhouse + ambient sunlight. Steady state laser-induced fluorescence emission spectra (5 nm resolution) were obtained from adaxial and abaxial surfaces resulting from excitation at single wavelengths (280, 380 or 360, and 532 nm). For emission spectra produced by each of these excitation wavelengths, ratios of emission peaks were calculated, including the red far-red chlorophyll fluorescence (ChlF) ratio (F685/F740) and the far-red/green (F740/F525) ratio. High resolution (< 3 nm) optical spectra (350-2500 nm) of reflectance, transmittance, and absorptance were also acquired for both adaxial and abaxial leaf surfaces. Species differences were demonstrated for several optical parameters. A 'red edge' derivative ratio determined from transmittance spectra [as the maximum first deivative, between 650-750 nm, normalized to the value at 744 nm, or Dmax/D744], was strongly associated with the C/N ratio (r(exp 2) = 0.90, P +/- 0.001). This ratio, calculated from reflectance spectra, was inversely related to chlorophyll b content (r(exp 2) = 0.91, P +/- 0.001) as was the ChlF (F685/F740) ratio obtained with 532 nm excitation (r(exp 2) = 0.76, P +/- 0.01). Discrimination of N treatment groups was possible with specific fluorescence band ratios (e.g., F740/F525 obtained with 380 nm excitation). Higher ChlF and blue-green emissions were measured from the abaxial leaf surfaces. Abaxial surfaces also produced higher reflectances, in general, in the 400-800 nm spectrum.

Middleton, E. M.↗

NASA NTRS2001

Remote Sensing of Cloud, Aerosol, and Water Vapor Properties from MODIS

MODIS is an earth-viewing cross-track scanning spectroradiometer launched on the Terra satellite in December 1999. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands from 0.415 to 14.235 microns with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). These bands have been carefully selected to enable advanced studies of land, ocean, and atmospheric processes. In this presentation I will review the comprehensive set of remote sensing algorithms that have been developed for the remote sensing of atmospheric properties using MODIS data, placing primary emphasis on the principal atmospheric applications of: (1) developing a cloud mask for distinguishing clear sky from clouds, (2) retrieving global cloud radiative and microphysical properties, including cloud top pressure and temperature, effective emissivity, cloud optical thickness, thermodynamic phase, and effective radius, (3) monitoring tropospheric aerosol optical thickness over the land and ocean and aerosol size distribution over the ocean, (4) determining atmospheric profiles of moisture and temperature, and (5) estimating column water amount. The physical principles behind the determination of each of these atmospheric products will be described, together with an example of their application using MODIS observations. All products are archived into two categories: pixel-level retrievals (referred to as Level-2 products) and global gridded products at a latitude and longitude resolution of 1 deg (Level-3 products). An overview of the MODIS atmosphere algorithms and products, status, validation activities, and early level-2 and -3 results will be presented. Finally, I will present some highlights from the land and ocean algorithms developed for processing global MODIS observations, including: (1) surface reflectance, (2) vegetation indices, leaf area index, and FPAR, (3) albedo and nadir BRDF-adjusted reflectance, (4) normalized water-leaving radiance, (5) chlorophyll-a concentration, and (6) sea surface temperature.

King, Michael D.↗

NASA NTRS2000

BOREAS TE-10 Photosynthetic Response Data

The Boreal Ecosystem-Atmospheric Study (BOREAS) TE-10 (Terrestrial Ecology) team collected several data sets in support of its efforts to characterize and interpret information on the gas exchange, reflectance, transmittance, chlorophyll content, carbon content, hydrogen content, nitrogen content, and photosynthetic response of boreal vegetation. This data set contains measurements of quantitative parameters and leaf photosynthetic response to increases in light conducted in the SSA during the growing seasons of 1994 and 1996 using an oxygen electrode system. Leaf photosynthetic responses were not collected in 1996. The data are stored in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Hall, Forrest G.↗

NASA NTRS2016

LED Lighting and Plant Growth: Supplemental LED Effects on Development

The growth of plants aboard the International Space Station (ISS) will play a pivotal role in advancing human space exploration to further uncharted destinations. Not only will plants be useful for oxygen production and carbon dioxide reduction, they will also serve as a supplemental food source for the astronaut diet. Research indicates that the most efficient way for these crops to be grown is by using electric lighting – specifically light-emitting diodes (LED) due to their several unique advantages. One of these advantages includes the potential for selecting certain wavelengths. By isolating certain lights, the effects of specific wavelengths on plant growth can be made clearer. This research project examined plant morphology, chlorophyll, biomass production, and nutrient synthesis in ‘Outredgeous’ red romaine lettuce grown under six LED light treatments of white (W), W + blue (B), W + green (G), W + red (R), W + far red (FR), and a Heliospectra lamp (Helio) (-composed of B+G+R+FR LEDs without W LEDS-). It was consistently found that the lettuce grown under the Helio, W + FR, W + R, and W + G treatments all showed improved physiology in terms of shoot length, shoot diameter, fresh mass, and dry mass relative to the W control. The Helio, W + FR, and W + G treatments exhibited significantly larger leaf areas while the Helio and W + FR treatments also produced more leaves on average at 28 days after planting (DAP). The W (control) and W + B treatments showed the highest accumulation of chlorophyll at 28 DAP. In conclusion, lettuce grown under the Helio treatment may be the overall most beneficial for supplementing the astronaut diet in terms of total edible biomass produced in a 28 day crop cycle.

LED↗

NASA NTRS2000

BOREAS TE-10 Leaf Gas Exchange Data

The Boreal Ecosystem-Atmospheric Study (BOREAS) TE-10 (Terrestrial Ecology) team collected several data sets in support of its efforts to characterize and interpret information on the reflectance, transmittance, gas exchange, chlorophyll content, carbon content, hydrogen content, and nitrogen content of boreal vegetation. This data set contains measurements of assimilation, stomatal conductance, transpiration, internal CO2 concentration, and water use efficiency conducted in the Southern Study Area (SSA) during the growing seasons of 1994 and 1996 using a portable gas exchange system. The data are stored in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Hall, Forrest G.↗

NASA NTRS2015

Selection of Leafy Green Vegetable Varieties for a Pick-and-Eat Diet Supplement on ISS

Several varieties of leafy vegetables were evaluated with the goal of selecting those with the best growth, nutrition, and organoleptic acceptability for ISS. Candidate species were narrowed to commercially available cultivars with desirable growth attributes for space (e.g., short stature and rapid growth). Seeds were germinated in controlled environment chambers under conditions similar to what might be found in the Veggie plant growth chamber on ISS. Eight varieties of leafy greens were grown: 'Tyee' spinach, 'Flamingo' spinach, 'Outredgeous' Red Romaine lettuce, 'Waldmann's Dark Green' leaf lettuce, 'Bull's Blood' beet, 'Rhubarb' Swiss chard, 'Tokyo Bekana' Chinese cabbage, and Mizuna. Plants were harvested at maturity and biometric data on plant height, diameter, chlorophyll content, and fresh mass were obtained. Tissue was ground and extractions were performed to determine the tissue elemental content of Potassium (K), Magnesium (Mg), Calcium (Ca) and Iron (Fe). Following the biometric/elemental evaluation, four of the eight varieties were tested further for levels of anthocyanins, antioxidant (ORAC-fluorescein) capacity, lutein, zeaxanthin, and Vitamin K. For sensory evaluation, 'Outredgeous' lettuce, Swiss chard, Chinese cabbage, and Mizuna plants were grown, harvested when mature, packaged under refrigerated conditions, and sent to the JSC Space Food Systems Laboratory. Tasters evaluated overall acceptability, appearance, color intensity, bitterness, flavor, texture, crispness and tenderness. All varieties received acceptable scores with overall ratings greater than 6 on a 9-point hedonic scale. Chinese cabbage was the highest rated, followed by Mizuna, 'Outredgeous' lettuce, and Swiss chard. Based on our results, the selected varieties of Chinese cabbage, lettuce, Swiss chard and Mizuna seem suitable for a pick-and-eat scenario on ISS with a ranking based on all factors analyzed to help establish priority.

Nutrition↗

NASA NTRS2020

Evaluating impacts of snow, surface water, soil and vegetation on empirical vegetation and snow indices for the Utqiaġvik tundra ecosystem in Alaska with the LVS3 model

Satellite observations for the Arctic and boreal region may contain information of vegetation, soil, snow, snowmelt, and/or other surface water bodies. We investigated the impacts of vegetation, soil, snow and surface water on empirical vegetation/snow indices on a tundra ecosystem area located around Utqiaġvik (formerly Barrow) of Alaska with the Moderate Resolution Imaging Spectrometer (MODIS) images in 2001–2014. Empirical vegetation indices, such as normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), the index of near infrared of vegetation (NIRv), and modified EVI (EVI2), have been used to monitor vegetation. Normalized difference snow index (NDSI) has been widely applied to monitor snow. The vegetation cover fraction (VGCF), the soil cover fraction (SOILCF), the snow cover fraction (SNOWCF), the surface water body cover fraction (WaterBodyCF), the fractional absorption of photosynthetically active radiation (PAR) by vegetation chlorophyll (fAPARchl), the fractional absorption of PAR by non-chlorophyll components of the vegetation (fAPARnon-chl), and the fractional absorption of PAR by the entire canopy (fAPARcanopy) are retrieved with the MODIS images and a coupled Leaf-Vegetation-Soil-Snow-Surface water body radiative transfer model, LVS3. The vegetation indices (NDVI, EVI, EVI2 and NIRv) differ from VGCF, fAPARchl, fAPARnon-chl, and fAPARcanopy. In addition to vegetation, we find that soil, snow and surface water also have impacts on vegetation indices NDVI, EVI (EVI2), and NIRv. Presence of snow makes lower the observed values of NDVI, EVI2 and NIRv. After snowmelt is gone, the vegetation indices (NDVI, EVI, EVI2 and NIRv) linearly decrease with SOILCF and WaterBodyCF, and WaterBodyCF has stronger impacts on these vegetation indices than SOILCF. The relationship between EVI and snow is complicated. NDSI non-linearly increases with SNOWCF, but linearly increases with sum of SNOWCF and WaterBodyCF (sum = 0.5893 × NDSI +0.4342, R2 = 0.976). NDSI linearly decreases with VGCF, and the relationship between NDSI and SOILCF is complex. Retrievals of VGCF, fAPARchl, fAPARnon-chl and fAPARcanopy with the LVS3 model provide alternatives for vegetation monitoring and ecological modeling.

Qingyuan Zhang↗

NASA NTRS1988

Prediction of leaf chemistry by the use of visible and near infrared reflectance spectroscopy

The chemical content of dry, ground leaf material sampled from deciduous and conifer tree species from sites in Alaska, Wisconsin, and California was estimated using visible and shortwave IR spectroscopy. Seven chemical components - sugar, starch, protein, cellulose, total chlorophyll, lignin, and total nitrogen - were analyzed by wet chemical methods and their concentrations regressed against log 1/rho and first and second differences of log 1/rho (where rho is measured reflectance) at wavelengths selected by stepwise regression. Predictions of chemical concentrations based on cross validation suggest that this technique may be useful for extracting vegetation canopy biochemical information by remote sensing.

Card, Don H.↗

NASA NTRS2006

Chlorophyll Fluorescence Emissions of Vegetation Canopies From High Resolution Field Reflectance Spectra

A two-year experiment was performed on corn (Zea mays L.) crops under nitrogen (N) fertilization regimes to examine the use of hyperspectral canopy reflectance information for estimating chlorophyll fluorescence (ChlF) and vegetation production. Fluorescence of foliage in the laboratory has proven more rigorous than reflectance for correlation to plant physiology. Especially useful are emissions produced from two stable red and far-red chlorophyll ChlF peaks centered at 685V10 nm and 735V5 nm. Methods have been developed elsewhere to extract steady state solar induced fluorescence (SF) from apparent reflectance of vegetation canopies/landscapes using the Fraunhofer Line Depth (FLD) principal. Our study utilized these methods in conjunction with field-acquired high spectral resolution canopy reflectance spectra obtained in 2004 and 2005 over corn crops, as part of an ongoing multi-year experiment at the USDA/Agriculture Research Service in Beltsville, MD. A spectroradiometer (ASD-FR Fieldspec Pro, Analytical Spectral Devices, Inc., Boulder, CO) was used to measure canopy radiances 1 m above plant canopies with a 22deg field of view and a 0deg nadir view zenith angle. Canopy and plant measurements were made at the R3 grain fill reproductive stage on 3-4 replicate N application plots provided seasonal inputs of 280, 140, 70, and 28 kg N/ha. Leaf level measurements were also made which included ChlF, photosynthesis, and leaf constituents (photosynthetic pigment, carbon (C), and N contents). Crop yields were determined at harvest. SIF intensities for ChlF were derived directly from canopy reflectance spectra in specific narrowband regions associated with atmospheric oxygen absorption features centered at 688 and 760 nm. The red/far-red S F ratio derived from these field reflectance spectra successfully discriminated foliar pigment levels (e.g., total chlorophyll, Chl) associated with N application rates in both corn crops. This canopy-level spectral ratio was also positively correlated to the foliar C/N ratio (r = 0.89, n = go), as was a leaf-level steady state fluorescence ratio (Fs/Chl, r = 0.92). The latter ratio was inversely correlated with crop grain yield (Kg 1 ha) (r = 0.9). This study has relevance to future passive satellite remote sensing approaches to monitoring C dynamics from space.

Middleton, E. M.↗

NASA NTRS2021

Simulation of Solar-Induced Chlorophyll Fluorescence from 3D Canopies with the Dart Model

The potential of solar-induced chlorophyll fluorescence (SIF) to monitor photosynthesis and plant stress has attracted considerable interest in SIF remote sensing (RS). However, canopy SIF and RS observations are impacted by topography, vegetation three dimension (3D) structure, leaf orientation, non foliar elements (e.g., tree woody skeleton), ... Physically based downscaling of canopy SIF RS data to leaf-level (i.e., to leaf photosynthesis) requires 3D radiative transfer (RT) models simulating canopy SIF and its observation. These models are necessary to better exploit the potential of SIF, by linking leaf SIF and SIF in RS observations as a function of canopy 3D architecture and experimental configurations (sun and viewing directions, etc.). The Discrete Anisotropic Radiative Transfer (DART) model is a comprehensive 3D radiative transfer (RT) model for urban and natural landscapes. This paper presents its SIF modeling for vegetation simulated with facets, its validation with the SCOPE/mSCOPE 1D models, and its recent extension to SIF modelling for landscapes simulated with 3D turbid medium.

radiative transfer↗

NASA NTRS2021

Simulation of Solar-Induced Chlorophyll Fluorescence from 3D Canopies with the Dart Model

Radiative transfer↗

NASA NTRS2021

Assessing impacts of canopy 3D structure on chlorophyll fluorescence radiance and radiative budget of deciduous forest stands using DART

Although remote sensing (RS) of solar-induced chlorophyll fluorescence (SIF) is increasingly used as a valuable source of information about vegetation photosynthetic activity, the RS SIF observations are significantly influenced by canopy-specific structural features (i.e., canopy architecture including leaf area index and presence of woody components), atmospheric conditions during their acquisition (e.g., proportion of direct and diffuse irradiance) and observational geometric configurations (e.g., sun and viewing directions). Radiative transfer (RT) models have the potential to provide a better understanding of the canopy structural effects on the SIF emission and RS signals. Here, we used the DART model to assess the daily influence, from morning to evening, of forest 3D architecture on SIF nadir radiance, emission, escape factor and nadir yield of eight 100 m × 100 m forest study plots established in a temperate deciduous forest of the Smithsonian Environmental Research Center (Edgewater, MD, USA). The 3D architecture of each plot was derived from airborne LiDAR. DART simulations of these 3D forest plots and their 1D (i.e., vertical profile of sun-adapted and shade-adapted leaves) and 0D (i.e., homogeneous layer of sun-adapted leaves above an homogeneous layer of shade-adapted leaves) abstractions were compared to assess the relative errors (ε1D−3D and ε0D−3D) associated with horizontal and vertical structural heterogeneity, respectively. Forest 3D structure, especially horizontal heterogeneity, had a great influence on forest nadir SIF radiance, resulting in ε1D−3D up to 55% at 8:00 and 18:00 (i.e., for oblique sun directions). The key indicators of this impact, in the descending order of importance, were the SIF escape factor (ε1D−3D up to 40%), the attenuation of incident photosynthetically active radiation (ε1D−3D less than 5%), and the SIF emission yield (ε1D−3D less than 2%). The influence of forest architecture on the nadir SIF escape factor and SIF yield (ε1D−3D up to 40%) varied over time, with differences in forest stand structure, and per spectral domain, being always larger between 640 and 700 nm than between 700 and 850 nm. In addition, woody elements demonstrated a large influence on forest SIF radiance due to their “shading” effect (ε up to 17%) and their “blocking” effect (ε ≈ 10%), both of them higher for far-red than for red SIF. These results underline the importance of 3D forest canopy architecture, especially 2D heterogeneity, and inclusion of woody elements in RT modeling used for interpretation of the RS SIF signal, and subsequently for the estimation of gross primary production and detection of vegetation stress.

Omar Regaieg↗