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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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Multiangle, multispectral remote sensing observations, such as those anticipated from the Earth Observing System (EOS) Multi-angle Imaging SpectroRadiometer (MISR), can significantly improve our ability to constrain aerosol properties from space.
This paper presents the above three processing steps starting from an accurate and efficient project of multi-angle MISR image data to the ellipsoid surface, followed by a mathematical derivation which separates the cloud motion and height, and finally an automatic image matching and ray intersection algorithm for high resolution cloud top height retrieval.
An Airborne Multi-angle Imaging SpectroRadiometer (AirMISR) instrument has been developed to assist in validation of the Earth Observing System (EOS) MISR experiment.
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A new technique is described for retrieving aerosol over ocean water and the associated ocean color using multiangle satellite observations. Unlike current satellite aerosol retrieval algorithms which only utilize observations at red wavelengths and longer, with the assumption that these wavelengths have a negligible ocean (water-leaving radiance), this new algorithm uses all available spectral bands and simultaneously retrieves both aerosol properties and the spectral ocean color. We show some results of case studies using MISR data, performed over different water conditions (coastal water, blooms, and open water).
The self‐assembly of amphiphilic bottlebrush block copolymers (BCPs), featuring backbones densely grafted with two types of side chains, is less well understood compared to linear BCPs. In particular, the solution self‐assembly of tapered bottlebrush BCPs—cone‐shaped BCPs with hydrophilic or hydrophobic tips—remains unexplored. This study investigates eight tapered and four cylindrical bottlebrush BCPs with varied ratios of hydrophobic polystyrene (PS) and hydrophilic poly(acrylic acid) (PAA) side chains, synthesized via sequential addition of macromonomers using ring‐opening metathesis polymerization (SAM‐ROMP). Self‐assembled nanostructures formed in water were analyzed using cryogenic transmission electron microscopy, small‐angle neutron scattering, and dynamic light scattering. Most BCPs generated multiple nanostructures with surface protrusions, including spherical micelles, cylindrical micelles, and vesicles, alongside transitional forms like ellipsoids and semi‐vesicles. Coarse‐grained molecular dynamics simulations supported the experimental findings, which revealed two distinct self‐assembly pathways. The first involved micelle fusion, producing elliptical and cylindrical aggregates, sometimes forming Y‐junctions. The second pathway featured micelle maturation into semivesicles, which developed into vesicles or large compound vesicles. This work provides the first experimental evidence of vesicle formation via semivesicles in bottlebrush BCPs and demonstrates the significant influence of cone directionality on self‐assembly behavior in these cone‐shaped polymeric amphiphiles.
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This talk discusses a method for creating low-volume versions of massive geophysical data sets that approximately retain high-resolution data structure.
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We are in the early stages of work on EPA task to investigate the effects of fires on air quality in North America, led by Jennifer Logan of Harvard University. JPL's contribution to this study is to find thousands of smoke plumes in satellite images of North America, and derive statistics about their geographic distribution, extent, orientation, and injection height.
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Support Vector Machines (SVMs) are a type of supervised learning algorith,, other examples of which are Artificial Neural Networks (ANNs), Decision Trees, and Naive Bayesian Classifiers. Supervised learning algorithms are used to classify objects labled by a 'supervisor' - typically a human 'expert.'.
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Techniques for passive remote sensing of aerosol optical and microphysical properties from space include visible, near and shortwave-infrared imaging (e.g., from MODIS), multiangle intensity imaging (e.g., ATSR-2, AATSR, MISR), near-ultraviolet mapping (e.g., TOMSIOMI), and polarimetry (e.g., POLDER, APS). Each of these methods has unique strengths. In this paper, we present a concept for integrating these approaches into a unified sensor. Design goals include spectral coverage from the near-UV to the shortwave infrared; intensity and polarimetric imaging simultaneously at multiple view angles; global coverage within a few days; kilometer to sub-kilometer spatial resolution; and measurement of the degree of linear polarization (DOLP) for a subset of the spectral complement with an uncertainty of 0.5% or less.