Data compression for data archival, browse or quick-look

Soon after space and Earth science data is collected, it is stored in one or more archival facilities for later retrieval and analysis. Since the purpose of the archival process is to keep an accurate and complete record of data, any data compression used in an archival system must be lossless, and protect against propagation of error in the storage media. A browse capability for space and Earth science data is needed to enable scientists to check the appropriateness and quality of particular data sets before obtaining the full data set(s) for detailed analysis. Browse data produced for these purposes could be used to facilitate the retrieval of data from an archival facility. Quick-look data is data obtained directly from the sensor for either previewing the data or for an application that requires very timely analysis of the space or Earth science data. Two main differences between data compression techniques appropriate to browse and quick-look cases, are that quick-look can be more specifically tailored, and it must be limited in complexity by the relatively limited computational power available on space platforms

Evaluation of Risk Management Methods for Satsuma Mandarin

Simulation of production budgets were used to compare net discounted returns and the distribution of returns under alternative risk-mitigation scenarios. Results indicate that the combination of freeze protection and crop insurance increases expected net discounted 20-year returns while decreasing the downside risk. Break-even prices ranged from $.257 to$.289 per pound. Crop insurance returns were constant across price.Satsuma oranges, freeze protection, crop insurance, production budget, simulation, Crop Production/Industries, Farm Management, Risk and Uncertainty, C63, D81, Q12,

Geobase Information System Impacts on Space Image Formats

As Geobase Information Systems increase in number, size and complexity, the format compatability of satellite remote sensing data becomes increasingly more important. Because of the vast and continually increasing quantity of data available from remote sensing systems the utility of these data is increasingly dependent on the degree to which their formats facilitate, or hinder, their incorporation into Geobase Information Systems. To merge satellite data into a geobase system requires that they both have a compatible geographic referencing system. Greater acceptance of satellite data by the user community will be facilitated if the data are in a form which most readily corresponds to existing geobase data structures. The conference addressed a number of specific topics and made recommendations

Remote sensing applications to hydrologic modeling in the southern Sierra Nevada and portions of the San Joaquin Valley, volume 1

The author has identified the following significant results. Characteristics of LANDSAT MSS imagery present problems in using satellite radiation measurements to estimate the shortwave albedo of an alpine snow cover. Every 15 minute USGS quadrangle contains over 100,000 pixels which poses a computation problem if each pixel is to be evaluated individually. The sampling interval may be sufficiently great to mask some effects of terrain and vegetation on reflectance. Three frames of LANDSAT imagery are needed for complete coverage of the study area, yet less than one third of the area coverage from each frame covers an area of interest. Because of distortions inherent in the imagery, information regarding spacecraft altitude, attitude, and position must be statistically derived with respect to ground control points in the image whose geodetic locations are known. An inspection of shade points indicates that up to one third of the most heavily snow covered areas may saturate in bands 4 through 6. LANDSAT's 9 day repeat cycle is not optimum for snow cover reflectance modeling because the most pronounced changes in albedo occur most nearly following a new snowfall. Such a snowfall, occurring between overpasses, is inadequately represented by extrapolation from the previous overpasses

Determining the Presence of Fecal Coliform Bacteria in Private Water Well Samples of Texas

Individual water well samples were collected and screened from private water wells. These samples were screened on-site for the presence of fecal coliform bacteria. Once all samples were screened, results were compiled and percent fecal coliform bacteria contamination determined. To date, a total of 3,319 water well samples have been screened for the presence of fecal coliform bacteria. The presence of fecal coliform bacteria has been found in 250 of the samples

Current recommendations/practices for anonymising data from clinical trials in order to make it available for sharing:A scoping review

BACKGROUND/AIMS: There are increasing pressures for anonymised datasets from clinical trials to be shared across the scientific community, and differing recommendations exist on how to perform anonymisation prior to sharing. We aimed to systematically identify, describe and synthesise existing recommendations for anonymising clinical trial datasets to prepare for data sharing. METHODS: We systematically searched MEDLINE(®), EMBASE and Web of Science from inception to 8 February 2021. We also searched other resources to ensure the comprehensiveness of our search. Any publication reporting recommendations on anonymisation to enable data sharing from clinical trials was included. Two reviewers independently screened titles, abstracts and full text for eligibility. One reviewer extracted data from included papers using thematic synthesis, which then was sense-checked by a second reviewer. Results were summarised by narrative analysis. RESULTS: Fifty-nine articles (from 43 studies) were eligible for inclusion. Three distinct themes are emerging: anonymisation, de-identification and pseudonymisation. The most commonly used anonymisation techniques are: removal of direct patient identifiers; and careful evaluation and modification of indirect identifiers to minimise the risk of identification. Anonymised datasets joined with controlled access was the preferred method for data sharing. CONCLUSIONS: There is no single standardised set of recommendations on how to anonymise clinical trial datasets for sharing. However, this systematic review shows a developing consensus on techniques used to achieve anonymisation. Researchers in clinical trials still consider that anonymisation techniques by themselves are insufficient to protect patient privacy, and they need to be paired with controlled access

Fractional snow cover in the Colorado and Rio Grande basins, 1995-2002

A cloud-masked fractional snow-covered area (SCA) product gridded at 1 km was developed from the advanced very high resolution radiometer for the Colorado River and upper Rio Grande basins for 1995-2002. Cloud cover limited SCA retrievals on any given 1-km2 pixel to on average once per week. There were sufficient cloud-free scenes to map SCA over at least part of the basins up to 21 days per month, with 3 months having only two scenes sufficiently cloud free to process. In the upper Colorado and upper Grande, SCA peaked in February-March. Maxima were 1-2 months earlier in the lower Colorado. Averaged over a month, as much as 32% of the upper Colorado and 5.5% of the lower Colorado were snow covered. Snow cover persisted longest at higher elevations for both wet and dry years. Interannual variability in snow cover persistence reflected wet-dry year differences. Compared with an operational (binary) SCA product produced by the National Operational Hydrologic Remote Sensing Center, the current products classify a lower fraction of pixels as having detectable snow and being cloud covered (5.5% for SCA and 6% for cloud), with greatest differences in January and June in complex, forested terrain. This satellite-derived subpixel determination of snow cover provides the potential for enhanced hydrologic forecast abilities in areas of complex, snow-dominated terrain. As an example, we merged the SCA product with interpolated ground-based snow water equivalent (SWE) to develop a SWE time series. This interpolated, masked SWE peaked in April, after SCA peaked and after some of the lower-elevation snow cover had melted. Copyright 2008 by the American Geophysical Union