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At least 109 records · Page 6

Spectral estimators of absorbed photosynthetically active radiation in corn canopies

Most models of crop growth and yield require an estimate of canopy leaf area index (LAI) or absorption of radiation. Relationships between photosynthetically active radiation (PAR) absorbed by corn canopies and the spectral reflectance of the canopies were investigated. Reflectance factor data were acquired with a Landsat MSS band radiometer. From planting to silking, the three spectrally predicted vegetation indices examined were associated with more than 95 percent of the variability in absorbed PAR. The relationships developed between absorbed PAR and the three indices were evaluated with reflectance factor data acquired from corn canopies planted in 1979 through 1982. Seasonal cumulations of measured LAI and each of the three indices were associated with greater than 50 percent of the variation in final grain yields from the test years. Seasonal cumulations of daily absorbed PAR were associated with up to 73 percent of the variation in final grain yields. Absorbed PAR, cumulated through the growing season, is a better indicator of yield than cumulated leaf area index. Absorbed PAR may be estimated reliably from spectral reflectance data of crop canopies.

Gallo, K. P.↗

Measurement and Modeling of the Optical Scattering Properties of Crop Canopies

The specular reflection process is shown to be a key aspect of radiation transfer by plant canopies. Polarization measurements are demonstrated as the tool for determining the specular and diffuse portions of the canopy radiance. The magnitude of the specular fraction of the reflectance is significant compared to the magnitude of the diffuse fraction. Therefore, it is necessary to consider specularly reflected light in developing and evaluating light-canopy interaction models for wheat canopies. Models which assume leaves are diffuse reflectors correctly predict only the diffuse fraction of the canopy reflectance factor. The specular reflectance model, when coupled with a diffuse leaf model, would predict both the specular and diffuse portions of the reflectance factor. The specular model predicts and the data analysis confirms that the single variable, angle of incidence of specularly reflected sunlight on the leaf, explains much of variation in the polarization data as a function of view-illumination directions.

Vanderbilt, V. C.↗

Measuring plant canopy structure

The potential of three systems to quantify plant canopy structure, key input data to canopy reflectance models is examined. The results show an optical radar system is potentially capable of providing the most fundamental type of structural data, the area, and the direction of the normal of each small piece of foliage in each cube of space in the canopy. To decrease the size of the data set of canopy measurements needed to statistically characterize the structure of a plant canopy, it is proposed that the statistical methods of bootstrapping be employed and that plans of large caopies be measured one at a time.

Vanderbilt, V. C.↗

Comparison of leaf and canopy reflectance of subarctic forests

Near-surface and aerial reflectance of foliage and canopies of subarctic forests were measured in central Alaska near Fairbanks. Bi-directional and hemispherical radiometric data were recorded over wavelengths ranging from 0.285 to 2.8 microns with emphasis on Landsat TM (Thematic Mapper) bands. Comparison of near-surface and aerial data indicates that the canopy of some species such as black spruce and aspen have reflectance values similar to their respective foliage. Other species such as birch have large differences. Canopy structure and understory vegetation appear to be the primary factors that control whether the reflectance of canopy and foliage are similar or different. The results suggest that radiation reflected from the canopy of some forest species will be close to laboratory measurements of foliage after atmospheric corrections.

Dean, K. G.↗

Canopy reflectance modeling in a tropical wooded grassland

Geometric/optical canopy reflectance modeling and spatial/spectral pattern recognition are used to study the form and structure of savanna in West Africa. An invertible plant canopy reflectance model is tested for its ability to estimate the amount of woody vegetation cover in areas of sparsely wooded grassland from remotely sensed data. Dry woodlands and wooded grasslands, commonly referred to as savannas, are important ecologically and economically in Africa, and cover approximately forty percent of the continent by some estimates. The Sahelian and Sudanian savanna make up the important and sensitive transition zone between the tropical forests and the arid Saharan region. The depletion of woody cover, used for fodder and fuel in these regions, has become a very severe problem for the people living there. LANDSAT Thematic Mapper (TM) data is used to stratify woodland and wooded grassland into areas of relatively homogeneous canopy cover, and then by applying an invertible forest canopy reflectance model to estimate directly the height and spacing of the trees in the stands. Since height and spacing are proportional to biomass in some cases, a successful application of the segmentation/modeling techniques will allow direct estimation of woody biomass, as well as cover density, over significant areas of these valuable and sensitive ecosystems. Sahelian savanna sites in the Gourma area of Mali being used by the NASA/GIMMS project (Global Inventory Modeling and Monitoring System, at Goddard Space Flight Center), in conjunction with CIPEA/Mali (Centre International pour l'Elevage en Afrique) will be used for testing the canopy model. The model will also be tested in a Sudanian zone crop/woodland area in the Region of Segou, Mali.

Simonett, D.↗

Canopy reflectance modeling in a tropical wooded grassland

Geometric/optical canopy reflectance modeling and spatial/spectral pattern recognition is used to study the form and structure of savanna in West Africa. An invertible plant canopy reflectance model is tested for its ability to estimate the amount of woody vegetation from remotely sensed data in areas of sparsely wooded grassland. Dry woodlands and wooded grasslands, commonly referred to as savannas, are important ecologically and economically in Africa, and cover approximately forty percent of the continent by some estimates. The Sahel and Sudan savannas make up the important and sensitive transition zone between the tropical forests and the arid Sahara region. The depletion of woody cover, used for fodder and fuel in these regions, has become a very severe problem for the people living there. LANDSAT Thematic Mapper (TM) data is used to stratify woodland and wooded grassland into areas of relatively homogeneous canopy cover, and then an invertible forest canopy reflectance model is applied to estimate directly the height and spacing of the trees in the stands. Because height and spacing are proportional to biomass in some cases, a successful application of the segmentation/modeling techniques will allow direct estimation of tree biomass, as well as cover density, over significant areas of these valuable and sensitive ecosystems. The model being tested in sites in two different bioclimatic zones in Mali, West Africa, will be used for testing the canopy model. Sudanian zone crop/woodland test sites were located in the Region of Segou, Mali.

Simonett, David↗

Preliminary report on measurements of forest canopies with C-band radar scatterometer at NASA/NSTL

This paper presents preliminary results of C-band radar scatterometer measurements of forest canopies of southeastern forests in the vicinity of NASA/NSTL. The results are as follows: radar backscattering coefficients (BSCs) of deciduous forests are higher than those of coniferous forests at a large incidence angle by ranging measurement, the VV polarization BSCs obtain peak value at the first few meters from the canopy top and decrease rather quickly, while the HH polarization BSCs obtain peak value at longer distances from the canopy top and decrease rather slowly through the canopy; and tree canopies with higher attenuations have higher BSCs for all three polarizations, with VV polarization containing the largest differential (2.2 dB).

Wu, S.-T.↗

Forest biomass, canopy structure, and species composition relationships with multipolarization L-band synthetic aperture radar data

The effect of forest biomass, canopy structure, and species composition on L-band synthetic aperature radar data at 44 southern Mississippi bottomland hardwood and pine-hardwood forest sites was investigated. Cross-polarization mean digital values for pine forests were significantly correlated with green weight biomass and stand structure. Multiple linear regression with five forest structure variables provided a better integrated measure of canopy roughness and produced highly significant correlation coefficients for hardwood forests using HV/VV ratio only. Differences in biomass levels and canopy structure, including branching patterns and vertical canopy stratification, were important sources of volume scatter affecting multipolarization radar data. Standardized correction techniques and calibration of aircraft data, in addition to development of canopy models, are recommended for future investigations of forest biomass and structure using synthetic aperture radar.

Sader, Steven A.↗

Tersail - A numerical model for combined analysis of vegetation canopy bidirectional reflectance and thermal emissions

A modification of the Tergra model (Soer, 1977) is presented, which incorporates the scattering from arbitrarily inclined leaves canopy reflectance model (Verhoef and Bunnik, 1981) for the calculation of albedo and canopy resistance. The combined model, known as Tersail, is capable of simulating the relationship between the bidirectional reflectance and the thermal response of a canopy. The accuracy of the model is tested using data over wheat canopies in Phoenix, Arizona, showing that the model is a good simulator of canopy temperatures under a variety of conditions.

Hope, Allen S.↗

Canopy bidirectional reflectance dependence on leaf orientation

The dependence of the bidirectional reflectance (BR) on the inclination and azimuthal orientation of a leaf is analyzed, with the primary assumption that, in terms of both obscuration and shadowing, the entire canopy consists of the same leaves. The BR patterns of a dense canopy are examined as a function of canopy architecture. It is assumed that the leaves are opaque Lambertian reflectors, having identical orientation and relfecting properties throughout the canopy, and distributed randomly with respect to the the irradiation field and the viewing direction. Analytical expressions are presented and analyzed for the BR factor. It is noted that maximal BR occurs at large viewing zenith angles. A complex and often steep dependence of the BR on azimuthal location is reported, noting that the BR thus depends on the leaf azimuth as well as the zenith angle. It is concluded that the question of azimuthal distribution has to be addressed when conducting model inversions to infer canopy characteristics and architecture.

Brakke, Thomas W.↗

Polarization of light reflected by crop canopies

This paper presents an analysis of polarization measurements acquired over corn and soybean crop canopies. Simultaneous plant physiological data and canopy polarization and reflectance data were collected before and after the tasseling development stage of the corn canopy, and before and during a period when the soybean canopy was water stressed. A simple model based upon the hypothesis that leaves specularly reflect light according to the Fresnel equations relates the observed bidirectional effects to the architectural and phenological conditions of the canopy.

Rondeaux, Genevieve↗

Vegetation canopy PAR absorptance and the normalized difference vegetation index - An assessment using the SAIL model

Relationships are studied between the normalized-difference vegetation index (NDVI) and absorbed photosynthetically active radiation (APAR) in a vegetation canopy. The SAIL model of bidirectional canopy radiative transfer is employed to compare NDVI measurements that are instantaneous with diurnally integrated canopy APAR capacity. The NDVI measurements - taken at solar-zenith angles of more than 60 deg and sensor views of less than 40 deg from nadir - give stable near-linear estimates of diurnal APAR capacity. Discrepancies in the relations between APAR and NDVI are associated with variations in the optical properties of the canopy and with background spectral reflectance. The results are significant for the practical use of these remote sensing techniques but suggest that instantaneous observations can be used to characterize the diurnally integrated APAR in vegetation canopies.

Goward, Samuel N.↗

Microwave backscattering and emission model for grass canopies

A two-layer model is developed that treats the grass canopy as a collection of randomly oriented elliptical dielectric discs over a layer of thatch with underlying soil surface. The distorted Born approximation in conjunction with the Peake formulation is used to calculate the backscattering coefficient and the emissivity from the canopy. Two particular features of this model which are unique for grass canopies are the variation of the canopy structure and the presence of the thatch layer. The basic parameters in the model such as the size and orientation of grass blades, dielectric constant of soil and vegetation, and thickness and water content of the thatch layer have been obtained from ground truth data. To interpret the available experimental observations of grasslands, numerical results from both passive and active models at L-band (1.4 GHz) are generated and various scattering and emission properties of the grass canopies are discussed.

Saatchi, Sasan S.↗

Canopy Cover Predictions using Ground Observations and Remotely Sensed Data

Maps of vegetation status are needed at many scales, from the field level to monitor ecosystem condition to the global level to understand the carbon cycle. Status is quantified by such variables as leaf area index, biomass, and fraction of canopy cover. Current methods of predicting vegetation variables use remote sensing data to provide a spatially exhaustive data source. In a study in western Montana, several hundred ground observations made by the US Forest Service on tenth-acre conifer plots were used to develop aspatial regression and geostatistical prediction models. Normalized Difference Vegetation Index (NDVI) values from Landsat Thematic Mapper images were used as ancillary data. These models were then used to predict canopy cover at unsampled locations in a 97 square kilometer region on the boundary of the Flathead National Forest and the Bob Marshall Wilderness. Independent data from two dates six years apart were used for validation. Given the assumption that actual canopy cover remained relatively unchanged within this time period, partial validation can be achieved by measuring the correspondence of the two maps. This criterion results in ranking the aspatial regression maps as less accurate than the geostatistically generated maps. The geostatistical approach emphasizes ground measurements more heavily than does aspatid regression. Geostatistical simulations of canopy cover also provide a means of describing uncertainty about the patterns of canopy cover.

Dungan, Jennifer L.↗

Adaptation to high CO2 concentration in an optimal environment: radiation capture, canopy quantum yield and carbon use efficiency

The effect of elevated [CO2] on wheat (Triticum aestivum L. Veery 10) productivity was examined by analysing radiation capture, canopy quantum yield, canopy carbon use efficiency, harvest index and daily C gain. Canopies were grown at either 330 or 1200 micromoles mol-1 [CO2] in controlled environments, where root and shoot C fluxes were monitored continuously from emergence to harvest. A rapidly circulating hydroponic solution supplied nutrients, water and root zone oxygen. At harvest, dry mass predicted from gas exchange data was 102.8 +/- 4.7% of the observed dry mass in six trials. Neither radiation capture efficiency nor carbon use efficiency were affected by elevated [CO2], but yield increased by 13% due to a sustained increase in canopy quantum yield. CO2 enrichment increased root mass, tiller number and seed mass. Harvest index and chlorophyll concentration were unchanged, but CO2 enrichment increased average life cycle net photosynthesis (13%, P < 0.05) and root respiration (24%, P < 0.05). These data indicate that plant communities adapt to CO2 enrichment through changes in C allocation. Elevated [CO2] increases sink strength in optimal environments, resulting in sustained increases in photosynthetic capacity, canopy quantum yield and daily C gain throughout the life cycle.

Non-NASA Center↗

Eo-1 Hyperion Measures Canopy Drought Stress In Amazonia

The central, south and southeast portions of the Amazon Basin experience a period of decreased cloud cover and precipitation from June through November. There are likely important effects of seasonal and interannual rainfall variation on forest leaf area index, canopy water stress, productivity and regional carbon cycling in the Amazon. While both ground and spaceborne studies of precipitation continue to improve, there has been almost no progress made in observing forest canopy responses to rainfall variability in the humid tropics. This shortfall stems from the large stature of the vegetation and great spatial extent of tropical forests, both of which strongly impede field studies of forest responses to water availability. Those few studies employing satellite measures of canopy responses to seasonal and interannual drought (e.g., Bohlman et al. 1998, Asner et al. 2000) have been limited by the spectral resolution and sampling available from Landsat and AVHRR sensors. We report on a study combining the first landscape-level, managed drought experiment in Amazon tropical forest with the first spaceborne imaging spectrometer observations of this experimental area. Using extensive field data on rainfall inputs, soil water content, and both leaf and canopy responses, we test the hypothesis that spectroscopic signatures unique to hyperspectral observations can be used to quantify relative differences in canopy stress resulting from water availability.

Asner, Gregory P.↗

Algorithm for Detection of Ground and Canopy Cover in Micropulse Photon-Counting Lidar Altimeter Data in Preparation for the ICESat-2 Mission

NASA's Ice, Cloud and Land Elevation Satellite-II (ICESat-2) mission is a decadal survey mission (2016 launch). The mission objectives are to measure land ice elevation, sea ice freeboard, and changes in these variables, as well as to collect measurements over vegetation to facilitate canopy height determination. Two innovative components will characterize the ICESat-2 lidar: 1) collection of elevation data by a multibeam system and 2) application of micropulse lidar (photon-counting) technology. A photon-counting altimeter yields clouds of discrete points, resulting from returns of individual photons, and hence new data analysis techniques are required for elevation determination and association of the returned points to reflectors of interest. The objective of this paper is to derive an algorithm that allows detection of ground under dense canopy and identification of ground and canopy levels in simulated ICESat-2 data, based on airborne observations with a Sigma Space micropulse lidar. The mathematical algorithm uses spatial statistical and discrete mathematical concepts, including radial basis functions, density measures, geometrical anisotropy, eigenvectors, and geostatistical classification parameters and hyperparameters. Validation shows that ground and canopy elevation, and hence canopy height, can be expected to be observable with high accuracy by ICESat-2 for all expected beam energies considered for instrument design (93.01%-99.57% correctly selected points for a beam with expected return of 0.93 mean signals per shot (msp), and 72.85%-98.68% for 0.48 msp). The algorithm derived here is generally applicable for elevation determination from photoncounting lidar altimeter data collected over forested areas, land ice, sea ice, and land surfaces, as well as for cloud detection.

Algorithms↗

El Nino Drought Increased Canopy Turnover in Amazon Forests

Amazon droughts, including the 2015-2016 El Ni~no, may reduce forest net primary productivityand increase canopy tree mortality, thereby altering both the short- and the longtermnet forest carbon balance. Given the broad extent of drought impacts, inventory plots oreddy flux towers may not capture regional variability in forest response to drought. We used multi-temporal airborne Lidar data and field measurements of coarse woodydebris to estimate patterns of canopy turnover and associated carbon losses in intact and fragmentedforests in the central Brazilian Amazon between 2013-2014 and 2014-2016. Average annualized canopy turnover rates increased by 65% during the drought period inboth intact and fragmented forests. The average size and height of turnover events was similarfor both time intervals, in contrast to expectations that the 2015-2016 El Ni~no droughtwould disproportionally affect large trees. Lidar biomass relationships between canopyturnover and field measurements of coarse woody debris were modest (R2 0.3), given similarcoarse woody debris production and Lidar-derived changes in canopy volume from singletree and multiple branch fall events. Our findings suggest that El Ni~no conditions accelerated canopy turnover in central Amazonforests, increasing coarse woody debris production by 62% to 1.22 Mg C ha1(exp) yr1(exp) indrought years.

ecosystem models↗