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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 91 records · Page 5

Estimation of penetration of forest canopies by Interferometric SAR measurements

In contrast to traditional Synthetic Aperture Radar (SAR), an Interferometric SAR (INSAR) yields two additional measurements: the phase difference and the correlation between the two interferometric channels. The phase difference has been used to estimate topographic height. For homogeneous surfaces, the correlation depends on the system signal-to-noise (SNR) ratio, the interferometer parameters, and the local slope. In the presence of volume scattering, such as that encountered in vegetation canopies, the correlation between the two channels is also dependent on the degree of penetration of the radiation into the scattering medium. In this paper, we propose a method for removing system and slope effects in order to obtain the decorrelation due to penetration alone. The sensitivities and accuracy of the proposed method are determined by Monte Carlo experiments, and we show that the proposed technique has sufficient sensitivity to provide penetration measurements for airborne SAR systems. Next, we provide a theoretical model to estimate the degree of penetration in a way which is independent of the details of the scattering medium. We also present a model for the correlation from non-homogeneous layers. We assess the sensitivity of the proposed inversion technique to these inhomogeneous situations. Finally, we present a comparison of the interferometric results against in situ data obtained by an airborne laser profilometer which provides a direct measurement of tree height and an estimate of the vegetation density profile in the forested areas around Mt. Adams, WA.

Rodriguez, Ernesto↗

Detection of hidden mineral deposits by airborne spectral analysis of forest canopies

Data from field surveys and biogeochemical tests conducted in Maine, Montana, and Washington strongly correlate with results obtained using high resolution airborne spectroradiometer which detects an anomalous spectral waveform that appears definitely associated with sulfide mineralization. The spectral region most affected by mineral stress is between 550 nm and 750 nm. Spectral variations observed in the field occur on the wings of the red chlorophyll band centered at about 690 nm. The metal-stress-induced variations on the absorption band wing are most successfully resolved in the high spectral resolution field data using a waveform analysis technique. The development of chlorophyll pigments was retarded in greenhouse plants doped with copper and zinc in the laboratory. The lowered chlorophyll production resulted in changes on the wings of the chlorophyll bands of reflectance spectra of the plants. The airborne spectroradiometer system and waveform analysis remains the most sensitive technique for biogeochemical surveys.

Collins, W.↗

Improved instrumentation for monitoring the diurnal and seasonal cycles in the dielectric properties of forest canopies

The design and implementation of a dielectric measurement system that facilitates the automated and continuous in situ monitoring of the dielectric properties of several canopy constituents is presented. This system utilizes the same coaxial line reflection coefficient measurement technique as the portable dielectric probe (PDP) while incorporating several features that facilitate the automated monitoring of canopy dielectric properties. The new system is capable of continuously monitoring the dielectric properties of the canopy constituents in a near-simultaneous fashion. The implementation of a data logger as a user interface has increased the number of measurements that the instrument is able to store in memory while significantly improving system reliability.

Guerra, Abel G.↗

BOREAS TE-12 Incoming PAR Through the Forest Canopy Data

The Boreal Ecosystem-Atmospheric Study (BOREAS) TE-12 (Terrestrial Ecology) team collected photosynthetically active radiation (PAR) data sets in support of its efforts to characterize and interpret information on shoot geometry, leaf optical properties, leaf water potential, and leaf gas exchange. The data were collected at the Southern Study Area-Old Black Spruce (SSA-OBS) site from 04-Jul-1996 to 25-Jul-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.↗

A First-Order Radiative Transfer Model for Microwave Radiometry of Forest Canopies at L-Band

In this study, a new first-order radiative transfer (RT) model is developed to more accurately account for vegetation canopy scattering by modifying the basic r-co model (the zero-order RT solution). In order to optimally utilize microwave radiometric data in soil moisture (SM) retrievals over moderately to densely vegetated landscapes, a quantitative understanding of the relationship between scattering mechanisms within vegetation canopies and the microwave brightness temperature is desirable. A first-order RT model is used to investigate this relationship and to perform a physical analysis of the scattered and emitted radiation from vegetated terrain. The new model is based on an iterative solution (successive orders of scattering) of the RT equations up to the first order. This formulation adds a new scattering term to the i-w model. The additional term represents emission by particles (vegetation components) in the vegetation layer and emission by the ground that is scattered once by particles in the layer. The new model is tested against 1.4 GHz brightness temperature measurements acquired over deciduous trees by a truck-mounted microwave instrument system called ComRAD in 2007. The model predictions are in good agreement with the data and they give quantitative understanding for the influence of first-order scattering within the canopy on the brightness temperature. The model results show that the scattering term is significant for trees and modifications are necessary to the T-w model when applied to dense vegetation. Numerical simulations also indicate that the scattering term has a negligible dependence on SM and is mainly a function of the angle and polarization of the microwave observation.

Kurum, Mehmet↗

A First-Order Radiative Transfer Model for Microwave Radiometry of Forest Canopies at L-Band

In this study, a first-order radiative transfer (RT) model is developed to more accurately account for vegetation canopy scattering by modifying the basic Tau-Omega model (the zero-order RT solution). In order to optimally utilize microwave radiometric data in soil moisture (SM) retrievals over vegetated landscapes, a quantitative understanding of the relationship between scattering mechanisms within vegetation canopies and the microwave brightness temperature is desirable. The first-order RT model is used to investigate this relationship and to perform a physical analysis of the scattered and emitted radiation from vegetated terrain. This model is based on an iterative solution (successive orders of scattering) of the RT equations up to the first order. This formulation adds a new scattering term to the . model. The additional term represents emission by particles (vegetation components) in the vegetation layer and emission by the ground that is scattered once by particles in the layer. The model is tested against 1.4-GHz brightness temperature measurements acquired over deciduous trees by a truck-mounted microwave instrument system called ComRAD in 2007. The model predictions are in good agreement with the data, and they give quantitative understanding for the influence of first-order scattering within the canopy on the brightness temperature. The model results show that the scattering term is significant for trees and modifications are necessary to the . model when applied to dense vegetation. Numerical simulations also indicate that the scattering term has a negligible dependence on SM and is mainly a function of the incidence angle and polarization of the microwave observation. Index Terms Emission,microwave radiometry, scattering, soil, vegetation.

Kurum, Mehmet↗

Estimation of Penetration of Forest Canopies by Interferometric SAR Measurements

In contrast to traditional Synthetic Aperture Radar (SAR), and Interferometric SAR (INSAR) yields two additional measurements: the phase difference and the correlation between the two interferometric channels. The phase difference has been used to estimate topographic height. A method is proposed for removing system and slope effects. A model is provided to estimate the degree of radiation penetration.

Forestry↗

Regional Mapping of Forest Canopy Water Content and Biomass Using AIRSAR Images over BOREAS Study Area

In recent years, monitoring vegetation biomass over various climate zones has become the primary focus of several studies interested in assessing the role of the ecosystem responses to climate change and human activities. Airborne and spaceborne synthetic-aperture radar (SAR) systems provide a useful tool to directly estimate biomass due to its sensitivity structure and moisture characteristics.

Forestry↗

A Novel Framework for Multi-Path Data Fusion in Earth Observation and New Observing Strategies: Applications to Predicting Forest Canopy Height

Exponential growth of data from Earth Observation (EO) assets has necessitated the development of sophisticated methods for data interpretation and management. NASA’s New Observing Strategy (NOS) approach aims to coordinate operations among complex heterogenous systems of constellations, requiring advanced Artificial Intelligence and Machine Learning (AI/ML) techniques. Despite significant advancements in AI/ML across various domains, the EO and machine learning for satellite (SatML) fields remain fragmented, often relying on adapted techniques rather than domain-specific solutions. We present a novel end-to-end data fusion framework tailored specifically for EO and SatML, addressing this gap by facilitating rapid development of AI/ML applications. This framework, called, Multimodal Earth Observation Workflow for Machine Learning (MEOW-ML), sup- ports the entire AI/ML lifecycle, from dataset manipulation, to model training, evaluation, and logging, and is designed to expedite the development of next-generation NOS deployments and SOTA in EO. We apply our framework to predict canopy height model (CHM) derived from lidar data. We integrate multiple data modalities through a hierarchical, multi-path model architecture, effectively identifying and leveraging the unique strengths of each data source to enhance predictive accuracy. Our experiments demonstrate that the multi-path architecture outperforms traditional single-path models and provides significant advantages in both accuracy and computational efficiency.

Mark Moussa↗