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At least 1,657 records · Page 92

New Directions in Tropical Phenology

Earth’s most speciose biomes are in the tropics, yet tropical plant phenology remains poorly understood. Tropical phenological data are comparatively scarce and viewed through the lens of a ‘temperate phenological paradigm’ expecting phenological traits to respond to strong, predictably annual shifts in climate (e.g., between subfreezing and frost-free periods). Digitized herbarium data greatly expand existing phenological data for tropical plants; and circular data, statistics, and models are more appropriate for analyzing tropical (and temperate) phenological datasets. Phylogenetic information, which remains seldom applied in phenological investigations, provides new insights into phenological responses of large groups of related species to climate. Consistent combined use of herbarium data, circular statistical distributions, and robust phylogenies will rapidly advance our understanding of tropical – and temperate – phenology.

tropical phenology↗

ERTS-B applications to Minnesota resource management

The author has identified the following significant results. The shape, pattern, and extent of surface water (e.g. lakes) can be readily mapped. Comparing detailed maps of several lakes in Itasca County with the areas classified as water by the LANDSAT data shows that some lakes have changed considerably since they were mapped. Due to several droughts this year (1976), the water level in most lakes has dropped. At this time, it seems feasible that LANDSAT digital tape data estimate lake water level change, due to the 1976 drought conditions.

Sizer, J. E.↗

Remote sensing of particulate concentrations in water

Determination of residual radiance is essential in remote sensing measurements of suspended solids in the absence of real-time ground-truth data. Some typical background corrections are presented for Lake Superior and the spectral distribution of the residual radiance is determined from three major categories of turbidity in the lake. The results tested with Landsat 2 digital tape data indicate that for large bodies of water general information on atmospheric scattering, water clarity, and optical properties of suspended solids enables one to estimate the concentrations of particulates to within + or - 0.5 mg/liter in the absence of real-time ground-truth data.

Sydor, M.↗

Enhanced Video-Oculography System

A previously developed video-oculography system has been enhanced for use in measuring vestibulo-ocular reflexes of a human subject in a centrifuge, motor vehicle, or other setting. The system as previously developed included a lightweight digital video camera mounted on goggles. The left eye was illuminated by an infrared light-emitting diode via a dichroic mirror, and the camera captured images of the left eye in infrared light. To extract eye-movement data, the digitized video images were processed by software running in a laptop computer. Eye movements were calibrated by having the subject view a target pattern, fixed with respect to the subject s head, generated by a goggle-mounted laser with a diffraction grating. The system as enhanced includes a second camera for imaging the scene from the subject s perspective, and two inertial measurement units (IMUs) for measuring linear accelerations and rates of rotation for computing head movements. One IMU is mounted on the goggles, the other on the centrifuge or vehicle frame. All eye-movement and head-motion data are time-stamped. In addition, the subject s point of regard is superimposed on each scene image to enable analysis of patterns of gaze in real time.

Moore, Steven T.↗

Forest Resource Information System (FRIS)

The technological and economical feasibility of using multispectral digital image data as acquired from the LANDSAT satellites in an ongoing operational forest information system was evaluated. Computer compatible multispectral scanner data secured from the LANDSAT satellites were demonstrated to be a significant contributor to ongoing information systems by providing the added dimensions of synoptic and repeat coverage of the Earth's surface. Major forest cover types of conifer, deciduous, mixed conifer-deciduous and non-forest, were classified well within the bounds of the statistical accuracy of the ground sample. Further, when overlayed with existing maps, the acreage of cover type retains a high level of positional integrity. Maps were digitized by a graphics design system, overlayed and registered onto LANDSAT imagery such that the map data with associated attributes were displayed on the image. Once classified, the analysis results were converted back to map form as a cover type of information. Existing tabular information as represented by inventory is registered geographically to the map base through a vendor provided data management system. The notion of a geographical reference base (map) providing the framework to which imagery and tabular data bases are registered and where each of the three functions of imagery, maps and inventory can be accessed singly or in combination is the very essence of the forest resource information system design.

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Application of HCMM data to regional geologic analysis for mineral and energy resource evaluation

The effects of topographic elevation and slope on thermal images were examined using representative field obstructions of the solar and sky radiation and a simple linearized thermal model. The forms are easily adapted for analysis of HCMM images using the DMA digital terrain data. From a representative set of field observations, it was found that flux variations with elevation can cause changes in the mean diurnal temperature gradient from -4 deg to -14 deg per km evaluated at 2000 m. Changes in the temperature difference gradient of 1 to 2 C per km are also produced which is equivalent to an effective thermal inertia gradient of 100 W s to the 1/2 power/sq m K/1 per km. Exposed bedrock on topographic ridges will appear to have a lower thermal inertia due to the additional effect.

Watson, K.↗

SU-E-T-206: Improving Radiotherapy Toxicity Based On Artificial Neural Network (ANN) for Head and Neck Cancer Patients

Purpose/Objective(s): The aim of this study is to build the estimator of toxicity using artificial neural network (ANN) for head and neck cancer patients Materials/Methods: An ANN can combine variables into a predictive model during training and considered all possible correlations of variables. We constructed an ANN based on the data from 73 patients with advanced H and N cancer treated with external beam radiotherapy and/or chemotherapy at our institution. For the toxicity estimator we defined input data including age, sex, site, stage, pathology, status of chemo, technique of external beam radiation therapy (EBRT), length of treatment, dose of EBRT, status of post operation, length of follow-up, the status of local recurrences and distant metastasis. These data were digitized based on the significance and fed to the ANN as input nodes. We used 20 hidden nodes (for the 13 input nodes) to take care of the correlations of input nodes. For training ANN, we divided data into three subsets such as training set, validation set and test set. Finally, we built the estimator for the toxicity from ANN output. Results: We used 13 input variables including the status of local recurrences and distant metastasis and 20 hidden nodes for correlations. 59 patients for training set, 7 patients for validation set and 7 patients for test set and fed the inputs to Matlab neural network fitting tool. We trained the data within 15% of errors of outcome. In the end we have the toxicity estimation with 74% of accuracy. Conclusion: We proved in principle that ANN can be a very useful tool for predicting the RT outcomes for high risk H and N patients. Currently we are improving the results using cross validation.

60 APPLIED LIFE SCIENCES↗

Use of remote sensing for land use policy formulation

Multispectral scanning, infrared imagery, thematic mapping, and spectroradiometry from LANDSAT, GOES, and ground based instruments are being used to determine conifer distribution, maximum and minimum temperatures, topography, and crop diseases in Michigan's lower Peninsula. Image interpretation and automatic digital processing information from LANDSAT data are employed to classify and map the coniferous forests. Radiant temperature data from GOES were compared to temperature readings from the climatological station network. Digital data from LANDSAT is being used to develop techniques for detecting, monitoring, and modeling land surface change. Improved reflectance signatures through spectroradiometry aided in the detection of viral diseases in blueberry fields and vineyards. Soil survey maps from aerial reconnaissance are included as well as information on education, conferences, and awards.

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Synopsis of current satellite snow mapping techniques, with emphasis on the application of near-infrared data

The Skylab EREP S192 Multispectral Scanner data have provided for the first time an opportunity to examine the reflectance characteristics of snowcover in several spectral bands extending from the visible into the near-infrared spectral region. The analysis of the S192 imagery and digital tape data indicates a sharp drop in reflectance of snow in the near-infrared, with snow becoming essentially nonreflective in Bands 11 (1.55-1.75 micron) and 12 (2.10-2.35 micron). Two potential applications to snow mapping of measurements in the near-infrared spectral region are possible: (1) the use of a near-infrared band in conjunction with a visible band to distinguish automatically between snow and water droplet clouds; and (2) the use of one or more near-infrared bands to detect areas of melting snow.

Barnes, J. C.↗

Snow survey from space, with emphasis on the results of the analysis of Skylab EREP S192 multispectral scanner data

The Skylab EREP S192 multispectral scanner data have provided an opportunity to examine the reflectance characteristics of snow cover in several spectral bands extending from the visible into the near infrared spectral region to about 2 microns. The analysis of the S192 imagery and digital tape data from five EREP passes, two from the SL-2 mission and three from the SL-4 mission, indicates a sharp drop in reflectance of snow in the near infrared, with snow becoming essentially nonreflective in Bands 11 (1.55-1.75 microns) and 12 (2.10-2.35 microns). The results are in good agreement with the results of laboratory experiments. Two potential applications to snow mapping of measurements in the near infrared spectral region are possible: (1) the use of a near infrared band in conjunction with a visible band to distinguish automatically between snow and water droplet clouds, and (2) the use of one or more near infrared bands to detect areas of melting snow.

Barnes, J. C.↗

Landscape Evolution, A Comparison of Form and Process

This project's goals were to collect, analyze and interpret 3-dimensional physiographic data for understanding the processes responsible for landscape modification. The primary landforms to be studied were Neogene cinder cones in Arizona (San Francisco Volcanic Field (SFVF), Coconino and Kaibab National Forests, Arizona). We also obtained and are still analyzing digital topographic data for the Long Valley-White Mountains area of California, which display Quaternary normal fault scarps, as well as extensive evidence of degradation. The work resulted in a large database of measured rates of downslope transport of slope debris. It was hypothesized that the work would increase our understanding of process-response models of hillslope degradation, and of the effects of climate change and other parameters on degradation rates. In greater detail, our primary goal was to compare evolutionary sequences of hillslopes, as exemplified by the topography of landforms of the same type but of different ages, with measurements of the surficial processes active on the landforms. Assuming that other parameters, such as hillslope materials and vegetation are held constant, and that the effects of changing climate are negligible, then the sediment transport rates measured today on the landforms should be the same as those calculated from the inversion of landform topography by use of a diffusion-type model. However, if the effects of changing climate or other factors are not negligible, then the observed transport rates would differ from those which must be invoked to explain the current topography. We hypothesized in fact that because degradation on the event scale is highly transient and localized, we would find a wide divergence between modern, measured transport rates, and rates calculated by global landform inversion or modeling. Because of the length of time involved in collection of sufficient data on current degradation rates, we are still continuing to analyse and interpret the data. Completion of the work will increase our understanding of the potential effects of anthropogenic climate and surficial change on the Earth's solid surface, and possibly allow us to constrain paths of hill-slope evolution following anthropogenic modifications, as well as compare the short-term with the long-term rates of hillslope degradation.

Bursik, Marcus I.↗

Evaluation of multispectral middle infrared aircraft images for lithologic mapping in the East Tintic Mountains, Utah

Six channels of multispectral middle infrared (8 to 14 micron) aircraft scanner data were acquired over the East Tintic mining district, Utah. This area has high relief and moderate vegetation and consists mainly of Tertiary silicic igneous rocks and Paleozoic quartzite and carbonate rocks that have been locally hydrothermally altered. These digital-image data were computer processed to create a color-composite image based on principal component transformations. Color differences in this image are related to the spectral differences in the surface material and allow discrimination of several rock types, depending primarily on their silica content. When combined with a visible and near infrared color-composite image from a previous flight, with limited field checking, it is possible to discriminate quartzite, carbonate rocks, quartz latitic and quartz monzonitic rocks, latitic and monzonitic rocks, silicified altered rocks, argillized altered rocks, and vegetation.

Kahle, A. B.↗

Deep learning applications in visual data for benign and malignant hematologic conditions: a systematic review and visual glossary

Deep learning (DL) is a subdomain of artificial intelligence algorithms capable of automatically evaluating subtle graphical features to make highly accurate predictions, which was recently popularized in multiple imaging-related tasks. Because of its capabilities to analyze medical imaging such as radiology scans and digitized pathology specimens, DL has significant clinical potential as a diagnostic or prognostic tool. Coupled with rapidly increasing quantities of digital medical data, numerous novel research questions and clinical applications of DL within medicine have already been explored. Similarly, DL research and applications within hematology are rapidly emerging, although these are still largely in their infancy. Given the exponential rise of DL research for hematologic conditions, it is essential for the practising hematologist to be familiar with the broad concepts and pitfalls related to these new computational techniques. This narrative review provides a visual glossary for key deep learning principles, as well as a systematic review of published investigations within malignant and non-malignant hematologic conditions, organized by the different phases of clinical care. In order to assist the unfamiliar reader, this review highlights key portions of current literature and summarizes important considerations for the critical understanding of deep learning development and implementations in clinical practice.

60 APPLIED LIFE SCIENCES↗

Improving Cloud Detection in Satellite Images of Coral Reef Environments Using Space Shuttle Photographs and High-Definition Television

Coral reefs worldwide are suffering from severe and rapid degradation (Bryant et A, 1998; Hoegh-Guldberg, 1999). Quick, consistent, large-scale assessment is required to assess and monitor their status (e.g., USDOC/NOAA NESDIS et al., 1999). On-going systematic collection of high resolution digital satellite data will exhaustively complement the relatively small number of SPOT, Landsat 4-5, and IRS scenes acquired for coral reefs the last 20 years. The workhorse for current image acquisition is the Landsat 7 ETM+ Long Term Acquisition Plan (Gasch et al. 2000). Coral reefs are encountered in tropical areas and cloud contamination in satellite images is frequently a problem (Benner and Curry 1998), despite new automated techniques of cloud cover avoidance (Gasch and Campana 2000). Fusion of multidate acquisitions is a classical solution to solve the cloud problems. Though elegant, this solution is costly since multiple images must be purchased for one location; the cost may be prohibitive for institutions in developing countries. There are other difficulties associated with fusing multidate images as well. For example, water quality or surface state can significantly change through time in coral reef areas making the bathymetric processing of a mosaiced image strenuous. Therefore, another strategy must be selected to detect clouds and improve coral reefs mapping. Other supplemental data could be helpful and cost-effective for distinguishing clouds and generating the best possible reef maps in the shortest amount of time. Photographs taken from the 1960s to the present from the Space Shuttle and other human-occupied spacecraft are one under-used source of alternative multitemporal data (Lulla et al. 1996). Nearly 400,000 photographs have been acquired during this period, an estimated 28,000 of these taken to date are of potential value for reef remote sensing (Robinson et al. 2000a). The photographic images can be digitized into three bands (red, green and blue) and processed for various applications (e.g., Benner and Curry 1998, Nedeltchev 1999, Glasser and Lulla 2000, Robinson et al. 2000c, Webb et al, in press).

Andrefeouet, Serge↗

Free-moving Quantitative Gamma-ray Imaging

The ability to map and estimate the activity of radiological source distributions in unknown three-dimensional environments has applications in the prevention and response to radiological accidents or threats as well as the enforcement and verification of international nuclear non-proliferation agreements. Such a capability requires well-characterized detector response functions, accurate time-dependent detector position and orientation data, a digitized representation of the surrounding 3D environment, and appropriate image reconstruction and uncertainty quantification methods. We have previously demonstrated 3D mapping of gamma-ray emitters with free-moving detector systems on a relative intensity scale using a technique called Scene Data Fusion (SDF). Here we characterize the detector response of a multi-element gamma-ray imaging system using experimentally benchmarked Monte Carlo simulations and perform 3D mapping on an absolute intensity scale. We present experimental reconstruction results from hand-carried and airborne measurements with point-like and distributed sources in known configurations, demonstrating quantitative SDF in complex 3D environments.

47 OTHER INSTRUMENTATION↗

LANDSAT-D investigations in snow hydrology

Work undertaken during the contract and its results are described. Many of the results from this investigation are available in journal or conference proceedings literature - published, accepted for publication, or submitted for publication. For these the reference and the abstract are given. Those results that have not yet been submitted separately for publication are described in detail. Accomplishments during the contract period are summarized as follows: (1) analysis of the snow reflectance characteristics of the LANDSAT Thematic Mapper, including spectral suitability, dynamic range, and spectral resolution; (2) development of a variety of atmospheric models for use with LANDSAT Thematic Mapper data. These include a simple but fast two-stream approximation for inhomogeneous atmospheres over irregular surfaces, and a doubling model for calculation of the angular distribution of spectral radiance at any level in an plane-parallel atmosphere; (3) incorporation of digital elevation data into the atmospheric models and into the analysis of the satellite data; and (4) textural analysis of the spatial distribution of snow cover.

Dozier, J.↗

Effects of head-down bed rest on complex heart rate variability: Response to LBNP testing

Head-down bed rest is used to model physiological changes during spaceflight. We postulated that bed rest would decrease the degree of complex physiological heart rate variability. We analyzed continuous heart rate data from digitized Holter recordings in eight healthy female volunteers (age 28-34 yr) who underwent a 13-day 6 deg head-down bed rest study with serial lower body negative pressure (LBNP) trials. Heart rate variability was measured on a 4-min data sets using conventional time and frequency domain measures as well as with a new measure of signal 'complexity' (approximate entropy). Data were obtained pre-bed rest (control), during bed rest (day 4 and day 9 or 11), and 2 days post-bed rest (recovery). Tolerance to LBNP was significantly reduced on both bed rest days vs. pre-bed rest. Heart rate variability was assessed at peak LBNP. Heart rate approximate entropy was significantly decreased at day 4 and day 9 or 11, returning toward normal during recovery. Heart rate standard deviation and the ratio of high- to low-power frequency did not change significantly. We conclude that short-term bed rest is associated with a decrease in the complex variability of heart rate during LBNP testing in healthy young adult women. Measurement of heart rate complexity, using a method derived from nonlinear dynamics ('chaos theory'), may provide a sensitive marker of this loss of physiological variability, complementing conventional time and frequency domain statistical measures.

Goldberger, Ary L.↗

Interpretation of HCMM images: A regional study

Potential users of HCMM data, especially those with only a cursory background in thermal remote sensing are familiarized with the kinds of information contained in the images that can be extracted with some reliability solely from inspection of such standard products as those generated at NASA/GSFC and now achieved in the National Space Science Data Center. Visual analysis of photoimagery is prone to various misimpressions and outright errors brought on by unawareness of the influence of physical factors as well as by sometimes misleading tonal patterns introduced during photoprocessing. The quantitative approach, which relies on computer processing of digital HCMM data, field measurements, and integration of rigorous mathematical models, can usually be used to identify, compensate for, or correct the contributions from at least some of the natural factors and those associated with photoprocessing. Color composite, day-IR, night-IR and visible images of California and Nevada are examined.

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