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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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42 records · Page 3

Polar cloud and surface classification using AVHRR imagery - An intercomparison of methods

Six Advanced Very High-Resolution Radiometer local area coverage (AVHRR LAC) arctic scenes are classified into ten classes. Three different classifiers are examined: (1) the traditional stepwise discriminant analysis (SDA) method; (2) the feed-forward back-propagation (FFBP) neural network; and (3) the probabilistic neural network (PNN). More than 200 spectral and textural measures are computed. These are reduced to 20 features using sequential forward selection. Theoretical accuracy of the classifiers is determined using the bootstrap approach. Overall accuracy is 85.6 percent, 87.6 percent, and 87.0 percent for the SDA, FFBP, and PNN classifiers, respectively, with standard deviations of approximately 1 percent.

Welch, R. M.↗

Statistical Approaches for the Definition of Landslide Rainfall Thresholds and their Uncertainty Using Rain Gauge and Satellite Data

Models for forecasting rainfall-induced landslides are mostly based on the identification of empirical rainfall thresholds obtained exploiting rain gauge data. Despite their increased availability, satellite rainfall estimates are scarcely used for this purpose. Satellite data should be useful in ungauged and remote areas, or should provide a significant spatial and temporal reference in gauged areas. In this paper, the analysis of the reliability of rainfall thresholds based on rainfall remote sensed and rain gauge data for the prediction of landslide occurrence is carried out. To date, the estimation of the uncertainty associated with the empirical rainfall thresholds is mostly based on a bootstrap resampling of the rainfall duration and the cumulated event rainfall pairs (D,E) characterizing rainfall events responsible for past failures. This estimation does not consider the measurement uncertainty associated with D and E. In the paper, we propose (i) a new automated procedure to reconstruct ED conditions responsible for the landslide triggering and their uncertainties, and (ii) three new methods to identify rainfall threshold for the possible landslide occurrence, exploiting rain gauge and satellite data. In particular, the proposed methods are based on Least Square (LS), Quantile Regression (QR) and Nonlinear Least Square (NLS) statistical approaches. We applied the new procedure and methods to define empirical rainfall thresholds and their associated uncertainties in the Umbria region (central Italy) using both rain-gauge measurements and satellite estimates. We finally validated the thresholds and tested the effectiveness of the different threshold definition methods with independent landslide information. The NLS method among the others performed better in calculating thresholds in the full range of rainfall durations. We found that the thresholds obtained from satellite data are lower than those obtained from rain gauge measurements. This is in agreement with the literature, where satellite rainfall data underestimate the 'ground' rainfall registered by rain gauges.

landslide prediction↗

Deep HST imaging of distant weak radio and field galaxies

We present deep Hubble Space Telescope (HST) Wide-Field Camera (WFC) V- and I-band images of three distant weak radio galaxies with z = 0.311-2.390 and seven field galaxies with z = 0.131-0.58. The images were deconvolved with both the Lucy and multiresolution CLEAN methods, which yield a restoring Full Width at Half Maximum (FWHM) of less than or equal to 0.2 sec, (nearly) preserve photons and signal-to-noise ratio at low spatial frequencies, and produce consistent light profiles down to our 2 sigma surface brightness sensitivity limit of V approximately 27.2 and I approximately 25.9 mag/sq arcsec. Multi-component image modeling was used to provide deconvolution-independent estimates of structural parameters for symmetric galaxies. We present 12-band (m(sub 2750) UBVRIgriJHK) photometry for a subset of the galaxies and bootstrap the unknown FOC/48 zero point at 2750 A in three independent ways (yielding m(sub 2750) = 21.34 +/- 0.09 mag for 1.0 e(-)/s). Two radio galaxies with z = 0.311 and 0.528, as well as one field galaxy with z = 0.58, have the colors and spectra of early-type galaxies, and a(exp 1/4)-like light profiles in the HST images. The two at z greater than 0.5 have little or no color gradients in V - I and are likely giant ellipticals, while the z = 0.311 radio galaxy has a dim exponential disk and is likely an S0. Six of the seven field galaxies have light profiles that indicate (small) inner bulges following a(exp 1/4) laws and outer exponential disks, both with little or no color gradients. These are (early-type) spiral galaxies with z = 0.131-0.528. About half have faint companions or bars. One shows lumpy structure, possibly a merger. The compact narrow-line galaxy 53W002 at z = 2.390 has less than or = 30% +/- 10% of its HST V and I flux in the central kiloparsec (due to its weak Active Galactic Nucleus (AGN)). Most of its light (V approximately equal to 23.3) occurs in a symmetric envelope with a regular a(exp 1/4)-like profile of effective radius a approximately equal to 1.1 sec (approximately equal to 12 kpc for H(sub 0) = 50, q(sub 0) = 0.1. Its (HST) V - I color varies at most from approximately 0.3 mag at a approximately equal to 0.2 sec to approximately 1.2 mag at a approximately greater than 0.4 sec, and possibly to approximately greater than 2.2 mag at a approximately greater than 1.2 sec. Together with its I - K color (approximately equal to 2.5 mag for a approximately greater than 1.0 sec-2.0 sec), this is consistent with an aging stellar population approximately 0.3-0.5 Gyr old in the galaxy center (a approx. less than 2 kpc radius), and possibly approximately 0.5-1.0 Gyr old at a approximately greater than 10 kpc radius. While its outer part may thus have started to collapse at z = 2.5-4, its inner part still is aligned with its redshifted Ly(alpha) cloud and its radio axis, possibly caused by star formation associated with the radio jet, or by reflection from its AGN cone.

Windhorst, R. A.↗

Evaluation of the CEAS trend and monthly weather data models for soybean yields in Iowa, Illinois, and Indiana

The CEAS models evaluated use historic trend and meteorological and agroclimatic variables to forecast soybean yields in Iowa, Illinois, and Indiana. Indicators of yield reliability and current measures of modeled yield reliability were obtained from bootstrap tests on the end of season models. Indicators of yield reliability show that the state models are consistently better than the crop reporting district (CRD) models. One CRD model is especially poor. At the state level, the bias of each model is less than one half quintal/hectare. The standard deviation is between one and two quintals/hectare. The models are adequate in terms of coverage and are to a certain extent consistent with scientific knowledge. Timely yield estimates can be made during the growing season using truncated models. The models are easy to understand and use and are not costly to operate. Other than the specification of values used to determine evapotranspiration, the models are objective. Because the method of variable selection used in the model development is adequately documented, no evaluation can be made of the objectivity and cost of redevelopment of the model.

French, V.↗

Verification of a New NOAA/NSIDC Passive Microwave Sea-Ice Concentration Climate Record

A new satellite-based passive microwave sea-ice concentration product developed for the National Oceanic and Atmospheric Administration (NOAA)Climate Data Record (CDR) programme is evaluated via comparison with other passive microwave-derived estimates. The new product leverages two well-established concentration algorithms, known as the NASA Team and Bootstrap, both developed at and produced by the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC). The sea ice estimates compare well with similar GSFC products while also fulfilling all NOAA CDR initial operation capability (IOC) requirements, including (1) self describing file format, (2) ISO 19115-2 compliant collection-level metadata,(3) Climate and Forecast (CF) compliant file-level metadata, (4) grid-cell level metadata (data quality fields), (5) fully automated and reproducible processing and (6) open online access to full documentation with version control, including source code and an algorithm theoretical basic document. The primary limitations of the GSFC products are lack of metadata and use of untracked manual corrections to the output fields. Smaller differences occur from minor variations in processing methods by the National Snow and Ice Data Center (for the CDR fields) and NASA (for the GSFC fields). The CDR concentrations do have some differences from the constituent GSFC concentrations, but trends and variability are not substantially different.

Passive Microwave↗

A Modified NASA Team Sea Ice Algorithm for the Antarctic

A recent comparative study of the NASA Team and Bootstrap passive microwave sea ice algorithms revealed significantly different sea ice concentration retrievals in some parts of the Antarctic. The study identified potential reasons for the discrepancies including the influence of sea ice temperature variability on the Bootstrap retrievals and the influence of ice surface reflectivity on the horizontally polarized emissivity in the NASA Team retrievals. In this study, we present a modified version of the NASA Team algorithm which reduces the error associated with the use of horizontally polarized radiance data, while retaining the relative insensitivity to ice temperature variations provided by radiance ratios. By retaining the 19 GHz polarization as an independent variable, we also maintain a relatively large dynamic range in sea ice concentration. The modified algorithm utilizes the 19 GHz polarization (PR19) and both gradient ratios, GRV and GRH defined by (37V-19V)/(37V+19V) and (37H-19H)/(37H+19H), respectively, rather than just GRV used in the current NASA Team algorithm. A plot of GRV versus GRH shows that the preponderance of points lie along a quadratic curve, whereas those points affected by surface reflectivity anomalies deviate from this curve. This serves as a method of identifying the problems points. The 19H brightness temperature of these problem points is increased so they too fall along quadratic curve. Sea ice concentrations derived from AVHRR imagery illustrate the extent to which this method reduces the error associated with surface layering.

Cavalieri, Donald J.↗