Effects of vegetation canopy structure on remotely sensed canopy temperatures
(Previously announced in STAR as N79-33530)
Kimes, D. S.↗
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Inversion of vegetation canopy reflectance models for estimating agronomic variables. V - Estimation of leaf area index and average leaf angle using measured canopy reflectances
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Goel, N. S.↗
Relations between canopy reflectance, photosynthesis and transpiration - Links between optics, biophysics and canopy architecture
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Sellers, P. J.↗
Ground-based canopy transmittance and satellite remotely sensed measurements for estimation of coniferous forest canopy structure
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Lathrop, Richard G., Jr.↗
Transonic wind-tunnel investigation of effects of windshield shape and canopy location on the aerodynamic characteristics of canopy-body combinations
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Cornette, Elden S↗
SLICER Airborne Laser Altimeter Characterization of Canopy Structure and Sub-canopy Topography for the BOREAS Northern and Southern Study Regions: Instrument and Data Product Description
SLICER data were acquired in support of BOREAS at all of the TF sites in the SSA and NSA, and along transects between the study areas. Data were acquired on 5 days between 18-Jul and 30-Jul-1996. Each coverage of a tower site is typically 40 km in length, with a minimum of 3 and a maximum of 10 lines across each tower oriented in a variety of azimuths. The SLICER data were acquired simultaneously with ASAS hyperspectral, multiview angle images. The SLICER Level 3 products consist of binary files for each flight line with a data record for each laser shot composed of 13 parameters and a 600-byte waveform that is the raw record of the backscatter laser energy reflected from Earth's surface. The SLICER data are stored in a combination of ASCII and binary data files.
Hall, Forrest G.↗
Boreal canopy surfaces from spaceborne stereogrammetry
Surface elevation estimates from high resolution spaceborne image (HRSI) stereogrammetry are used to examine fine-scaled structure of boreal forest canopies. These data can depict detailed spatial patterns of vertical forest structure at remote sites across the circumpolar domain where these estimates would otherwise be unavailable. This work examines where these estimates are most effective at describing vertical forest structure to explain which canopy surfaces they represent. We evaluated the variation in canopy surface estimates captured from four general types of HRSI digital surface models (DSMs) across the full range of boreal canopy cover. These DSMs, classified into 4 types by grouping them according to the acquisition's (1) sun elevation angle (low or high) and (2) seasonality-driven ground surface condition (snow presence/absence), vary with acquisition characteristics and the details of this variation continues to be studied. We explored some of this variation by comparing the distributions of differences in boreal canopy percentile heights derived from reference small footprint lidar in Tanana Valley, Alaska with canopy surface elevations derived from these 4 types of HRSI DSMs. We examined how canopy surface estimates from HRSI DSMs differ according to acquisition characteristics and canopy cover, and ultimately which canopy surfaces are represented in these DSMs. Our results help clarify which boreal canopy surfaces are representative of those captured with HRSI DSMs. They show that in the Tanana Valley (1) DSMs grouped by sun elevation angle and ground surface condition provide different surface estimates of boreal canopies; (2) the two DSM types that appear to most differently capture boreal forest canopy surfaces are DSMs from snow-free images acquired at sun elevation angles <30° (Low sun elev. & snow-free) and those with snow-cover at sun elevation angles ≥30° (High sun elev. & snow-free); (3) DSMs with snow most often do not capture upper canopy surfaces; (4) the “Low sun elev. & snow-free” DSMs resolve surfaces that are most representative of upper canopy surfaces (dense forests >60% cover, 70th–80th percentile heights); and (5) in the most dense forests (>80% cover) where canopy gaps are least likely to bias downward the average surface estimates, the snow-free DSM types are representative of 70th - 80th percentile heights (“Low sun elev. & snow-free”) and 60th–70th percentile heights (“High sun elev. & snow-free”). The combination of horizontal structure (canopy cover) and acquisition characteristics affect the boreal vertical structure (canopy surface height) estimates from spaceborne stereogrammetry. These effects should be considered when analyzing products derived from HRSI DSMs, and as part of a comprehensive approach to spaceborne remote sensing of circumpolar boreal forests.
forest structure↗
Investigation of the Loads on a Conventional Front and Rear Sliding Canopy
As one phase of a comprehensive canopy load investigation, conventional front and rear sliding canopies which are typified by installation on the SB2C-4E airplane, were tested in the Langley full-scale tunnel to determine the pressure distributions and the aerodynamic loads on the canopies. A preliminary analysis of the results of these tests is presented in this report. Plots are presented that show the distribution of pressure at four longitudinal stations through each canopy for a range of conditions selected to determine the effects of varying canopy position, yaw, lift coefficient, and power. The results indicate that the maximum loads, based on the external-internal pressure differential, for the front and rear canopies were obtained with the airplane simulating the high speed flight condition. The highest loading on the front canopy was in the exploding direction for the configuration with the front and rear canopies closed. The highest loads on the rear canopy were in the crushing direction with the front canopy open and the rear canopy closed. For most of the simulated flight conditions, the highest loads on the front canopy, per unit area, were over twice as great as the highest loads on the rear canopy when the comparison was made for the most critical canopy configuration in each case. The external pressure distribution over the front and rear canopies, which were fairly symmetrical to 0 degree angle of yaw, were greatly distorted at other yaw attitudes, particularly for the propeller operating conditions. These distorted pressure distributions resulted in local exploding and crushing loads on both canopies which were often considerably higher than the average canopy loads.
Dexter, Howard E.↗
Use of spectral analogy to evaluate canopy reflectance sensitivity to leaf optical property
The spectral variation of canopy reflectance is mostly governed by the absorption properties of the elements, hence the leaves, since their intrinsic scattering properties show very little spectral variation. The relationship between canopy reflectance and leaf reflectance measured at the red edge over sugar beet canopies was used to simulate canopy reflectance from leaf reflectance spectra measured over the whole spectral domain. The results show that the spectral analogies found allows accurate reconstruction of canopy reflectance spectra. Explicit assumptions about the very low spectral variation of leaf intrinsic scattering properties are thus indirectly justified. The sensitivity of canopy reflectance (rho(sub c)) to leaf optical properties can then be investigated from concurrent spectral variations of canopy (delta rho(sub c)/delta lambda) and leaf reflectance (delta rho(sub l)/delta lambda): (delta rho(sub c))/(delta rho(sub l)) = ((delta rho(sub c))/(delta lambda) ((delta rho( sub l))/(delta lambda))(sup -1)). This expression is strictly valid only when the optical properties of the soil background or the other vegetation elements such as bark are either spectrally flat or do not contribute significantly to canopy reflectance. Simulations using the SAIL and PROSPECT models demonstrate that the sensitivity of canopy reflectance to leaf reflectance is significant for large vegetation cover fractions in spectral domains where absorption is low. In these conditions, multiple, scattering enhances the leaf absorption features by a factor that can be greater than 2.0. To override the limitations of the SAIL model for the description of the canopy architecture, we tested the previous findings on experimental data. Concurrent canopy and leaf reflectance spectra were measured for a range of sugar beet canopies. The results show good agreement with the theoretical findings. Conclusions are drawn about the applicability of these findings, with particular attention to the potential detectability of leaf biochemical composition from canopy reflectance sensed from space.
Baret, Frederic↗
Discrete anisotropic radiative transfer modelling of solar-induced chlorophyll fluorescence: Structural impacts in geometrically explicit vegetation canopies
Solar-induced fluorescence (SIF) is a subtle but informative optical signal of vegetation photosynthesis. Remotely sensed SIF integrates environmental, physiological and structural changes that alter photosynthesis at leaf, plant and canopy scales. Radiative transfer models are ideally suited to investigate the complex sources of variability in the SIF signal to guide the interpretation of SIF retrievals from airborne and space-borne platforms. Here, we coupled the Fluspect-Cx model of leaf optical properties and chlorophyll-a fluorescence with the Discrete Anisotropic Radiative Transfer (DART) model to upscale SIF from individual leaves to three-dimensional (3D) structurally explicit canopies. For one-dimensional homogeneous (turbid-like) canopies, DART-SIF was nearly identical to SIF simulated in two existing models, SCOPE and mSCOPE (RMSE <0.221 W./sq.m.μm.sr). DART simulations in geometrically explicit 3D canopies offered four important insights regarding the influence of vegetation structure on the multi-angular top-of-canopy SIF signal. First, changes in the 3D canopy architecture of maize crops, represented by leaf density (leaf area index), and plant clumping (canopy closure) had a larger impact on SIF than the modelled photosynthetic efficiency distinction between sun-adapted and shade-adapted foliage. Second, clumping of leaves at the crop and stand levels was identified as one of the key driving factors of multi-angular anisotropy of red and far-red SIF (686 and 740 nm) for both maize and eucalyptus canopies. Third, non-photosynthetic woody material had a significant impact on top-of-canopy SIF in modelled 3D forest stands. Wood shadowing decreased the photosynthetically active radiation absorbed by green leaves, and consequently the SIF emissions, by 10% in sparse and 17% in dense eucalyptus stands. The wood obstruction (blocking) effect, quantified as a relative difference of SIF escape probabilities from canopies with and without wood in the nadir viewing direction, decreased far-red SIF by 4–6% but it had a smaller and sometimes positive influence (by less than 2%) on red SIF. Fourth, DART 3D radiative budget profiles revealed that the majority of the SIF signal from a dense eucalyptus stand originated from the top 25% of the simulated canopy. Interestingly, the introduction of bark-covered woody elements did not alter the simulated balance and omnidirectional escape factor of red SIF in this upper canopy part but did raise significantly both of them in case of far-red SIF. These results demonstrate the importance of 3D radiative transfer and radiative budget simulations for investigating SIF interactions in structurally complex plant canopies and for a better understanding of spatiotemporal and multi-angular remote sensing SIF observations.
Zbyněk Malenovský↗
Quantifying Mangrove Canopy Regrowth and Recovery After Hurricane Irma With Large-Scale Repeat Airborne Lidar in the Florida Everglades
Hurricane Irma caused significant damages to mangrove forested wetlands in south Florida, including defoliation, tree snapping, and uprooting. Previous studies have used optical satellite imagery to estimate large-scale forest disturbance and resilience patterns. However, satellite images alone cannot provide measurements of vertical mangrove structure. In this study, we used dense point cloud data collected by NASA Goddard’s LiDAR, Hyperspectral, and Thermal (G-LiHT) airborne imager before (March 2017) and after (December 2017 and March 2020) Hurricane Irma to quantify the recovery, or lack thereof, of the three-dimensional (3D) mangrove forest structure. Recent resilience and vulnerability models developed from Landsat time series following the storm were used to group the lidar data into distinct disturbance-recovery classes. We then analyzed lidar-based forest canopy within each of the recovery classes to test a suite of forest structural characteristics. Our results indicate that 77.0 % of the survey area experienced canopy height loss three months after Hurricane Irma, whereby the majority of canopy height loss occurred in areas with the tallest mangrove forests (i.e., 15–25 m tall). Our analysis shows that the mangrove canopy height in South Florida increased by an average 0.26 m from December 2017 to March 2020, with most of the forest (84.7 % of the survey area) experiencing canopy height regrowth. However, only 38.1 % of the survey area has recovered to pre-storm canopy height. The distribution of canopy height was significantly altered by Hurricane Irma in the low and intermediate resilience classes, but were not significantly different 2.5 years later. Indeed, in areas of low resilience, little to no vertical change has occurred suggesting the absence of canopy regrowth and natural regeneration. Conversely, mangroves in high resilience class, which are dominated by shorter canopies (<5 m), were not heavily damaged by the storm and have maintained the same structural attributes as those before Hurricane Irma. Our findings highlight that hurricane disturbances significantly alter mangrove forest canopy structure, but recovery of vertical structure varies by resilience classes, species composition, and canopy height.
Lidar↗
Measurement of Effective Canopy Temperature: The Missing Link to Modeling Transpiration in Controlled Environments
The objectives were to apply energy balance principles to plant canopies, and to determine which parameters are essential for predicting plant canopy transpiration (E) in controlled environments. Transpiration was accurately measured in a gas-exchange system. Absorbed radiation (R(sub abs)) by the canopy was measured with a net radiometer and calculated from short and long-wave radiation components. Average canopy foliar temperature T(sub L) can be measured with an infrared radiometer, but since T(sub L) is seldom uniform, a weighed average measurement of T(sub L) must be made. The effective canopy temperature T(sub C) is that temperature that balances the energy flux between absorbed radiation and latent heat L(sub E) and sensible heat (H) fluxes. TC should exactly equal air temperature T(sub A) when L(sub E) equals R(sub abs). When unnecessary thermal radiation from the lighting system is removed by a water filter, the magnitude of L(sub E) from transpiration approaches Rabs and T(sub C) is close to T(sub A). Unlike field models, we included the energy used in photosynthesis and found that up to 10% of Rabs was used in photosynthesis. We calculated aerodynamic conductance for H from measurements of wind speed and canopy height using the wind profile equation. Canopy aerodynamic conductance ranged from.03 to.04 m/s for wind speeds from.6 to 1 m/s; thus a 0.1 C canopy to air temperature difference results in a sensible heat flux of about 4 W/sq m, which is only 1% of R(sub abs). We examined the ability of wide angle infrared transducers to accurately integrate T(sub L) from the top to the bottom of the canopy. We measured evaporation from the hydroponic media to be approximately 1 micro mol/sq m s or 10% of R(sub abs). This result indicates that separating evaporation from transpiration is more important than exact measurement of canopy temperature.
Monje, O. A.↗
Characterization of Canopy Layering in Forested Ecosystems Using Full Waveform Lidar
Canopy structure, the vertical distribution of canopy material, is an important element of forest ecosystem dynamics and habitat preference. Although vertical stratification, or "canopy layering," is a basic characterization of canopy structure for research and forest management, it is difficult to quantify at landscape scales. In this paper we describe canopy structure and develop methodologies to map forest vertical stratification in a mixed temperate forest using full-waveform lidar. Two definitions-one categorical and one continuous-are used to map canopy layering over Hubbard Brook Experimental Forest, New Hampshire with lidar data collected in 2009 by NASA's Laser Vegetation Imaging Sensor (LVIS). The two resulting canopy layering datasets describe variation of canopy layering throughout the forest and show that layering varies with terrain elevation and canopy height. This information should provide increased understanding of vertical structure variability and aid habitat characterization and other forest management activities.
lidar↗
Anisotropy of thermal infrared exitance in sunflower canopies
Anisotropy of thermal infrared exitance above and within a relatively closed fully irrigated sunflower canopy is detailed. Azimuthal variation in thermal infrared exitance above canopies was weakly (statistically) related to solar position and was comparable to or larger than errors in satellite-based canopy estimates. Anisotropy within canopies was significantly lower and decreased with canopy closure and depth into the canopy. Measured azimuthal isotropy within canopies supports the use of this assumption in radiative transfer models. Significant differences in canopy temperature measurements were found depending upon whether the instruments were within or above the canopy. These differences could produce errors of 20-35 percent in latent energy estimates during periods of high evapotranspiration (ET) and greater errors in periods of restricted ET.
Tha Paw u, Kyaw↗
The influence of elevated CO2 on non-structural carbohydrate distribution and fructan accumulation in wheat canopies
We grew 2.4 m2 wheat canopies in a large growth chamber under high photosynthetic photon flux (1000 micromoles m-2 s-1) and using two CO2 concentrations, 360 and 1200 micromoles mol-1. Photosynthetically active radiation (400-700 nm) was attenuated slightly faster through canopies grown in 360 micromoles mol-1 than through canopies grown in 1200 micromoles mol-1, even though high-CO2 canopies attained larger leaf area indices. Tissue fractions were sampled from each 5-cm layer of the canopies. Leaf tissue sampled from the tops of canopies grown in 1200 micromoles mol-1 accumulated significantly more total non-structural carbohydrate, starch, fructan, sucrose, and glucose (p < 0.05) than for canopies grown in 360 micromoles mol-1. Non-structural carbohydrate did not significantly increase in the lower canopy layers of the elevated CO2 treatment. Elevated CO2 induced fructan synthesis in all leaf tissue fractions, but fructan formation was greatest in the uppermost leaf area. A moderate temperature reduction of 10 degrees C over 5 d increased starch, fructan and glucose levels in canopies grown in 1200 micromoles mol-1, but concentrations of sucrose and fructose decreased slightly or remained unchanged. Those results may correspond with the use of fructosyl-residues and release of glucose when sucrose is consumed in fructan synthesis.
NASA Discipline Life Support Systems↗
Stochastic Transport Theory for Investigating the Three-Dimensional Canopy Structure from Space Measurements
Radiation reflected from vegetation canopies exhibits high spatial variation. Satellite-borne sensors measure the mean intensities emanating from heterogeneous vegetated pixels. The theory of radiative transfer in stochastic media provides the most logical linkage between satellite observations and the three-dimensional canopy structure through a closed system of simple equations which contains the mean intensity and higher statistical moments directly as its unknowns. Although this theory has been a highly active research field in recent years, its potential for satellite remote sensing of vegetated surfaces has not been fully realized because of the lack of models of a canopy pair-correlation function that the stochastic radiative transfer equations require. The pair correlation function is defined as the probability of finding simultaneously phytoelements at two points. This paper presents analytical and Monte Carlo generated pair correlation functions. Theoretical and numerical analyses show that the spatial correlation between phytoelements is primarily responsible for the effects of the three-dimensional canopy structure on canopy reflective and absorptive properties. The pair correlation function, therefore, is the most natural and physically meaningful measure of the canopy structure over a wide range of scales. The stochastic radiative transfer equations naturally admit this measure and thus provide a powerful means to investigate the three-dimensional canopy structure from space. Canopy reflectances predicted by the stochastic equations are assessed by comparisons with the PARABOLA measurements from coniferous and broadleaf forest stands in the BOREAS Southern Study Areas. The pair correlation functions are derived from data on tree structural parameters collected during field campaigns conducted at these sites. The simulated canopy reflectances compare well with the PARABOLA data.
Huang, Dong↗
Coming of Age: Polarization as a Probe of Plant Canopy Water Status
We tested the hypothesis that the relative water content (RWC) of the sunlit leaves in a plant canopy may be estimated from polarized canopy imagery. Recently (IGARSS, July 27-31, 2015, Milan, Italy), we reported the results of laboratory polarization measurements of single detached leaves during dry down. We found that RWC was linearly related to the ratio of the reflectance of the interior of the leaf and the leaf transmittance. Here we report application of the laboratory results to estimate RWC for sunlit leaves in a plant canopy. Using a commercial-off-the-shelf (COTS) Nikon 810 camera with Nikkor 300 mm lens and Polaroid type HN-22 linear polarizer, we photographed in the principle plane a plant canopy displaying a gradient of water stress and collected, at each of multiple points along the gradient, two images, one with the polarization filter oriented for maximum scene response and a second with the filter oriented for minimum scene response. We converted the digital values in the two images to reflectance factor with reference to images of a white, flat, horizontal Spectralon surface. We classified the polarization imagery, identifying reflecting leaves, transmitting leaves, other sunlit vegetation and shadows. For each image pair we normalized the leaf internal reflectance by dividing by the cosine of the angle of incidence of the sunlight on the leaf, selected the leaf maximum transmittance in the scene and divided to obtain the ratio reflectance/transmittance, which we compared with leaf RWC. We determined the leaf relative water content by harvesting a section of leaf and immediately placing it in a sealed container in an ice chest. Later in the laboratory the leaf sample was weighed, rehydrated, weighed, dried and again weighed. RWC was determined using the standard formula. Our experimental results support our hypothesis, suggesting that the RWC of sunlit leaves in a plant canopy may be estimated from analysis of polarization imagery collected by a COTS camera system. Unlike remotely sensed estimates of canopy equivalent water thickness, our estimates of the RWC of sunlit canopy leaves provide leaf physiological information. We propose RWC estimates based upon sunlit leaves are more relevant to assessing the water status of a plant canopy than would be RWC estimates based upon large FOV canopy measurements.
estimates↗
High-Resolution Forest Canopy Height Estimation in an African Blue Carbon Ecosystem
Mangrove forests are one of the most productive and carbon dense ecosystems that are only found at tidally inundated coastal areas. Forest canopy height is an important measure for modeling carbon and biomass dynamics, as well as land cover change. By taking advantage of the flat terrain and dense canopy cover, the present study derived digital surface models (DSMs) using stereophotogrammetric techniques on high-resolution spaceborne imagery (HRSI) for southern Mozambique. A mean-weighted ground surface elevation factor was subtracted from the HRSI DSM to accurately estimate the canopy height in mangrove forests in southern Mozambique. The mean and H100 tree height measured in both the field and with the digital canopy model provided the most accurate results with a vertical error of 1.18-1.84 m, respectively. Distinct patterns were identified in the HRSI canopy height map that could not be discerned from coarse shuttle radar topography mission canopy maps even though the mode and distribution of canopy heights were similar over the same area. Through further investigation, HRSI DSMs have the potential of providing a new type of three-dimensional dataset that could serve as calibration/validation data for other DSMs generated from spaceborne datasets with much larger global coverage. HSRI DSMs could be used in lieu of Lidar acquisitions for canopy height and forest biomass estimation, and be combined with passive optical data to improve land cover classifications.
HRSI↗