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At least 73 records · Page 4

Feasibility of airborne detection of laser-induced fluorescence emissions from green terrestrial plants

The present investigation provides a demonstration of the feasibility of the airborne detection of the laser-induced fluorescence spectral emissions from living terrestrial grasses, shrubs, and trees using existing levels of lidar technology. Airborne studies were performed to ascertain system requirements necessary to detect laser-induced fluorescence from living terrestrial plants, to assess the practical acquisition of useful single-shot laser-induced fluorescence (LIF) waveforms over vegetative canopies, and to determine the comparative suitability of laser system, airborne platform, and terrestrial environmental parameters. The field experiment was conducted on May 3, 1982, over the northern portion of Wallops Island, VA. Attention is given to airborne lidar results and the description of laboratory investigations.

Hoge, F. E.

Ten Years of Land Cover Change on the California Coast Detected using Landsat Satellite Image Analysis

Landsat satellite imagery was analyzed to generate a detailed record of 10 years of vegetation disturbance and regrowth for Pacific coastal areas of Marin and San Francisco Counties. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) methodology, a transformation of Tasseled-Cap data space, was applied to detected changes in perennial coastal shrubland, woodland, and forest cover from 1999 to 2009. Results showed several principal points of interest, within which extensive contiguous areas of similar LEDAPS vegetation change (either disturbed or restored) were detected. Regrowth areas were delineated as burned forest areas in the Point Reyes National Seashore (PRNS) from the 1995 Vision Fire. LEDAPS-detected disturbance patterns on Inverness Ridge, PRNS in areas observed with dieback of tanoak and bay laurel trees was consistent with defoliation by sudden oak death (Phytophthora ramorum). LEDAPS regrowth pixels were detected over much of the predominantly grassland/herbaceous cover of the Olema Valley ranchland near PRNS. Extensive restoration of perennial vegetation cover on Crissy Field, Baker Beach and Lobos Creek dunes in San Francisco was identified. Based on these examples, the LEDAPS methodology will be capable of fulfilling much of the need for continual, low-cost monitoring of emerging changes to coastal ecosystems.

Land Cover Change

Investigation of the detection and monitoring of forest insect infestation in the Sierra Nevada Mountains of California

The author has identified the following significant results. Significant progress has been made in detecting insect outbreaks from ERTS-1 data during this period. It is possible to differentiate forested areas with heavy damage from those with little or no damage. The analysis is made with color infrared positive transparencies and prints. Enlargement of the transparencies makes it possible to detect and map areas of three degrees of tree mortality into heavy, medium, and light. It was also noted that shadows cast by massive rock domes closely resemble natural lakes.

Hall, R. C.

Mapping Boreal Forest Spruce Beetle Health Status at the Individual Crown Scale Using Fused Spectral and Structural Data

The frequency and severity of spruce bark beetle outbreaks are increasing in boreal forests leading to widespread tree mortality and fuel conditions promoting extreme wildfire. Detection of beetle infestation is a forest health monitoring (FHM) priority but is hampered by the challenges of detecting early stage (“green”) attack from the air. There is indication that green stage might be detected from vertical gradients of spectral data or from shortwave infrared information distributed within a single crown. To evaluate the efficacy of discriminating “non-infested”, “green”, and “dead” health statuses at the landscape scale in Alaska, USA, this study conducted spectral and structural fusion of data from: (1) Unoccupied aerial vehicle (UAV) multispectral (6 cm) + structure from motion point clouds (~700 pts per sq. m); and (2) Goddard Lidar Hyperspectral Thermal (G-LiHT) hyperspectral (400 to 1000 nm, 0.5 m) + SWIR-band lidar (~32 pts per sq.m). We achieved 78% accuracy for all three health statuses using spectral + structural fusion from either UAV or G-LiHT and 97% accuracy for non-infested/dead using G-LiHT. We confirm that UAV 3D spectral (e.g., greenness above versus below median height in crown) and lidar apparent reflectance metrics (e.g., mean reflectance at 99th percentile height in crown), are of high value, perhaps capturing the vertical gradient of needle degradation. In most classification exercises, UAV accuracy was lower than G-LiHT indicating that collecting ultra-high spatial resolution data might be less important than high spectral resolution information. While the value of passive optical spectral information was largely confined to the discrimination of non-infested versus dead crowns, G-LiHT hyperspectral band selection (~400, 675, 755, and 940 nm) could inform future FHM mission planning regarding optimal wavelengths for this task. Interestingly, the selected regions mostly did not align with the band designations for our UAV multispectral data but do correspond to, e.g., Sentinel-2 red edge bands, suggesting a path forward for moderate scale bark beetle detection when paired with suitable structural data.

Janice Cessna

The application of remote sensing in geobotanical exploration for metal sulfides

A field study was conducted in Mineral, VA in 1980-82 to test the suitability of remote sensing techniques for geobotanical exploration. It was found that on trees growing over lead sulfide deposits, buds opened later and leaves were smaller than on trees growing on soils with background levels of lead and copper. This difference in leaf growth could be detected in remotely sensed data. In the spring, the smaller leaf size of metal-stressed trees resulted in a greater contribution from the soil and bark to the total reflectance imaged by the sensor. In the fall, the leaves of metal-stressed oaks sensed earlier than surrounding vegetation, which was also detected in remotely sensed data. It is concluded that vegetation growing on lead sulfide deposits has a shorter growing season than surrounding vegetation on unmineralized soil and that remotely sensed data collected at either end of the growing season can be used to locate geobotanical anomalies associated with these deposits.

Masuoka, E. J.

Automating Anomaly Detection for Target systems at Spallation Neutron Source

The Spallation Neutron Source (SNS) at Oak Ridge National Laboratory, produces the world’s most intense pulse neutrons beams. An accelerated proton beam is directed into a mercury target to generate neutrons via spallation. The target system accounted for over 40% of the overall downtime of the facility in 2022. Thus, early detection in anomalies in the target systems can enable taking corrective actions to avoid failures and reduce downtime. Fault prognostics and anomaly detection in accelerators, both at SNS and outside, has largely focused on the beam side. This paper presents one the first studies exploring leveraging machine learning to automate the detection of anomalies in the target system. The target system consists of over 30 different interconnected subsystems, and the present work focuses on the mercury process system as a use case. Analyzing data from 28 process variables from 2022 and 2023, tree-based and reconstruction-based algorithms are employed to detect anomalies in archived data. The algorithms detected previously unreported anomalies, several of which were deemed alert worthy by human experts, particularly those found by reconstruction-based algorithms. Using data from each production run in the accelerator increased the generalizability of the models in time. Efforts are now underway to implement a workflow for incorporating human feedback to update the models and evaluating performance on unseen data. The models will eventually be integrated into the existing System Tracking and Reliability system with a web interface for automated anomaly detection and reporting along with a pathway for incorporating human feedback for model updates.

Raj, Anant [ORNL] (ORCID:0000000306711244)

Local concurrent error detection and correction in data structures using virtual backpointers

A new technique, based on virtual backpointers, for local concurrent error detection and correction in linked data structures is presented. Two new data structures, the Virtual Double Linked List, and the B-tree with Virtual Backpointers, are described. For these structures, double errors can be detected in 0(1) time and errors detected during forward moves can be corrected in 0(1) time. The application of a concurrent auditor process to data structure error detection and correction is analyzed, and an implementation is described, to determine the effect on mean time to failure of a multi-user shared database system. The implementation utilizes a Sequent shared memory multiprocessor system operating on a shared databased of Virtual Double Linked Lists.

Li, C. C.

Local concurrent error detection and correction in data structures using virtual backpointers

A new technique, based on virtual backpointers, for local concurrent error detection and correction in linked data strutures is presented. Two new data structures, the Virtual Double Linked List, and the B-tree with Virtual Backpointers, are described. For these structures, double errors can be detected in 0(1) time and errors detected during forward moves can be corrected in 0(1) time. The application of a concurrent auditor process to data structure error detection and correction is analyzed, and an implementation is described, to determine the effect on mean time to failure of a multi-user shared database system. The implementation utilizes a Sequent shared memory multiprocessor system operating on a shared database of Virtual Double Linked Lists.

Li, Chung-Chi Jim

Analysis of Retinal Vascular Branching in Human Subjects Undergoing 70-Day Head-Down Tilt by NASAs VESGEN Software

Significant risks for visual impairment were discovered recently in astronauts following spaceflight, especially after long-duration missions. We hypothesize that microgravity-induced fluid shifts result in pathological changes within the retinal vasculature that precede visual and other ocular impairments. We therefore are analyzing retinal vessels in healthy subjects before and after head-down tilt (HDT), a ground-based microgravity analog with NASA's VESsel GENeration Analysis (VESGEN) software. Methods. Spectralis® infrared (IR) fundus images were collected from both eyes of 6 subjects before and after 70 days of bed rest at 6 degree HDT (NASA Campaign 11). For our retrospective study, branching patterns in arterial and venous trees are mapped by VESGEN into vessel branching generations (Gx) that are quantified by parameters such as densities of vessel length (Lv), area (Av), number (Nv) and fractal dimension (Df) as described previously for diabetic retinopathy (IOVS 51(1):498). Results are further assigned by VESGEN into groups of large (G1-3), medium (G4-6) and small (G≥7) vessels. Results. All subjects remained asymptomatic throughout duration of HDT. To date, we have analyzed one IR image from each of the 12 eyes. Interestingly, two groups of the masked study population identified by VESGEN are distinguished by the presence or absence of small veins (G≥7). For example, L≥7 and Av≥7 are 2.7+/-1.3 E-4 px/px2 and 7.2+/-3.6 E-4 px2/px2 in 6 retinas, but 0 in the other 6 retinas. Nonetheless, the space-filling properties of the entire venous trees were remarkably uniform by all parameters, such as Df = 1.56+/-0.02 for 6 retinas with G≥7 and 1.55+/-0.02 for retinas without G≥7. No small arteries (G≥7) were detected. Conclusions. For our preliminary masked analysis, two groups of venous trees with and without small veins (G≥7) were clearly revealed by VESGEN. Upon completing all images and unmasking the subject status of before and after HDT, we will determine whether differences in the presence or absence of small veins are important correlates, and perhaps reliable predictors, of other ocular and physiological adaptations to prolonged head-down tilt and microgravity. Clinical methods for examining adaptive microvascular remodeling in the retina to microgravity space flight are not currently established.

Fractal

The Kepler Mission: A Search for Terrestrial Planets - Development Status

We have embarked on a mission to detect terrestrial planets. The space mission has been optimized to search for earth-size planets (0.5 to 10 earth masses) in the habitable zone (HZ) of solar-like stars. Given this design, the mission will necessarily be capable of not only detecting Earth analogs, but a wide range of planetary types and characteristics ranging from Mercury-size objects with orbital periods of days to gas-giants in decade long orbits that have undeniable signatures even with only one transit detected. The mission is designed to survey the full range of spectral-type dwarf stars. The approach is to detect the periodic signal of transiting planets. Three or more transits of a star exceeding a combined threshold of eight sigma with a statistically consistent period, brightness change and duration provide a rigorous method of detection. From the relative brightness change the planet size can be calculated. From the period the orbital size can be calculated and its location relative to the HZ determined. Presented here are: the mission goals, the top level system design requirements derived from these goals that drive the flight system design, a number of the trades that have lead to the mission concept, expected photometric performance dependence on stellar brightness and spectral type based on the system 'noise tree' analysis. Updated estimates are presented of the numbers of detectable planets versus size, orbit, stellar spectral type and distances based on a planet frequency hypothesis. The current project schedule and organization are given.

Koch, David

Use of remote sensing for land use policy formulation

Progress in studies for using remotely sensed data for assessing crop stress and in crop estimation is reported. The estimation of acreage of small forested areas in the southern lower peninsula of Michigan using LANDSAT data is evaluated. Damage to small grains caused by the cereal leaf beetle was assessed through remote sensing. The remote detection of X-disease of peach and cherry trees and of fire blight of pear and apple trees was investigated. The reliability of improving on standard methods of crop production estimation was demonstrated. Areas of virus infestation in vineyards and blueberry fields in western and southwestern Michigan were identified. The installation and systems integration of a microcomputer system for processing and making available remotely sensed data are described.

Source record

Historical evidence for a connection between volcanic eruptions and climate change

The times of historical volcanic aerosol clouds were compared with changes in atmospheric temperatures on regional, hemispheric, and global scales. These involve either a direct comparison of individual significant eruption years with temperature records, or a comparison of eruption years with composited temperature records for several years before and after chosen sets of eruptions. Some studies have challenged the connection between individual eruptions and climate change. Mass and Portman (1989) recently suggested that the volcanic signal was present, but smaller than previously thought. In a study designed to test the idea that eruptions could cause small changes in climate, Hansen and other (1978) chose one of the best monitored eruptions at the time, the 1963 eruption of Agung volcano on the island of Bali. Using a simple radiation-balance model, in which an aerosol cloud in the tropics was simulated, this basic pattern of temperature change in the tropics and subtropics was reproduced. There may be natural limits to the atmospheric effects of any volcanic eruption. Self-limiting physical and chemical effects in eruption clouds were proposed. Model results suggest that aerosol microphysical processes of condensation and coagulation produce larger aerosols as the SO2 injection rate is increased. The key to discovering the greatest effects of volcanoes on short-term climate may be to concentrate on regional temperatures where the effects of volcanic aerosol clouds can be amplified by perturbed atmospheric circulation patterns, especially changes in mid-latitudes where meridional circulation patterns may develop. Such climatic perturbations can be detected in proxy evidence such as decreases in tree-ring widths and frost damage rings in climatically sensitive parts of the world, changes in treelines, weather anomalies such as unusually cold summers, severity of sea-ice in polar and subpolar regions, and poor grain yields and crop failures.

Rampino, Michael R.

Climatic impact of volcanic eruptions

Studies have attempted to 'isolate' the volcanic signal in noisy temperature data. This assumes that it is possible to isolate a distinct volcanic signal in a record that may have a combination of forcings (ENSO, solar variability, random fluctuations, volcanism) that all interact. The key to discovering the greatest effects of volcanoes on short-term climate may be to concentrate on temperatures in regions where the effects of aerosol clouds may be amplified by perturbed atmospheric circulation patterns. This is especially true in subpolar and midlatitude areas affected by changes in the position of the polar front. Such climatic perturbation can be detected in proxy evidence such as decrease in tree-ring widths and frost rings, changes in the treeline, weather anomalies, severity of sea-ice in polar and subpolar regions, and poor grain yields and crop failures. In low latitudes, sudden temperature drops were correlated with the passage overhead of the volcanic dust cloud (Stothers, 1984). For some eruptions, such as Tambora, 1815, these kinds of proxy and anectdotal information were summarized in great detail in a number of papers and books (e.g., Post, 1978; Stothers, 1984; Stommel and Stommel, 1986; C. R. Harrington, in press). These studies lead to the general conclusion that regional effects on climate, sometimes quite severe, may be the major impact of large historical volcanic aerosol clouds.

Rampino, Michael R.

Multipolarization P-, L-, and C-band radar for coastal zone mapping - The Louisiana example

Multipolarization P-, L-, and C-band airborne SAR data sets were acquired over a coastal zone and a forested wetland of southern Louisiana. The data sets were used with field-collected surface-parameter data in order to determine the value of SAR systems in assessing and mapping coastal-zone surface features. The coastal-zone surface features in this study are sediments, sediment distribution, and the formation of new isles and banks. Results of the data analysis indicate that the P-band radar with 68-cm wavelength is capable of detecting the submerged sediment if the area is very shallow (i.e., a water depth of less than one meter). The penetration capability of P-band radar is also demonstrated in the forested wetland area. The composition and condition of the ground surface can be detected, as well as the standing water beneath dense tree leaves.

Wu, Shih-Tseng

Hybrid data-driven and model-informed online tool wear detection in milling machines

Precision machining tool wear is responsible for low product throughput and quality. Monitoring the tool wear online is vital to prevent degradation in machining quality. However, direct real-time tool wear measurement is not practical. This paper presents residual-based anomaly detection models, combining a hybrid model comprised of a physics-based model and a data-driven model (a decision tree or a neural network) to predict signals of interest (e.g., power or forces) under nominal conditions, followed by Page’s cumulative sum test for detecting tool wear on-line using the computer numerical control machine measurements. The most informative features are ranked using dynamic programming and its approximation variants from real-time measurements and machine settings, such as the width of cut, depth of cut, feed rate and spindle speed, that serve as inputs to the predictive models. The baseline nominal model is incrementally updated with experimental data via a gradient boosted adaptation model to generate the residuals that account for discrepancies between the actual machine data under normal conditions and the baseline nominal model predictions. The hybrid model is validated against 20 Mazak milling machine experimental tests and one Haas run-to-failure experiment. The proposed anomaly detector is applied to synthetic data from simulations of the physics-based model at different operating conditions, measurement noise levels, and tool wear levels, and the methods were able to achieve an overall 92% accuracy in data with 1% noise. The anomaly detection methods based on hybrid model reduced the false alarms of either the data-driven or physical-based models alone, and are found to be capable of good online detection of tool wear.

Online anomaly detection

An accumulation method for early fault warning and its application to wind turbine systems

Unexpected failures in engineering systems lead to expensive maintenance actions and should be avoided if at all possible. This is particularly true for wind turbine systems for which unexpected failures not only demand costly repairs but also cause long downtime. Motivated by this need, we present an accumulation method for fault early warning and failure anticipation. Here, our research shows that one critical element allowing the ability of early warning is to accumulate the small-magnitude symptoms resulting from gradual changes in an engineering system like wind turbines. Our idea is inspired by the classical cumulative sum method, or CUSUM, but we have to redesign the accumulation mechanism for tackling unique challenges in wind turbine data. The new accumulation method is applied to two real wind turbine datasets, one with gearbox failures and the other with generator failures, and demonstrates superior performance as compared with CUSUM.

17 WIND ENERGY

Is the Sun a Long Period Variable

The inventory of atmospheric radiocarbon exhibits quasi-periodic variations of mean period of bar-lambda=269 years over the entire 9000 year record. But the period is inconstant and subject to random variability (sigma m exp. 1/2 = 119 years). The radiocarbon maxima correspond to the quasiperiodic extension of the Maunder minimum throughout the Holocene and resolve the long-standing issue of Maunder cyclicity. The radiocarbon maxima are amplitude modulated by the approx. 2300 year period and thus vary significantly in peak value. The approx. 2300 year period in turn appears to not be modulated by the secular geomagnetic variation. Detection of a Maunder-like sequence of minima in tree ring growth of Bristlecone pine and its correlation with the Maunder (1890, 1922) cyclicity in the radiocarbon record supports the inference that solar forcing of the radiocarbon record is accompanied by a corresponding forcing of growth of timberline Bristlecone pine. Because of the random component of the Maunder period, prediction of climate, if tied to the Maunder cycle other than probabilistically, is significantly hindered. For the mean Maunder period of 269 years, the probability is 67 percent that a given climatic maximum lies anywhere between 150 and 388 years.

Sonett, Charles P.

Forest Damage Assessment

Thematic Mapper (TM) is an advanced scanning instrument aboard Landsat 4 & 5 originally developed by NASA, now operated as a commercial remote sensing system. The TM detects radiation reflected and emitted from earth objects such as trees in seven bands of the spectrum. Since each object has its own unique spectral "signature" the TM can distinguish among surface features and generate computer processed imagery, specific features of importance to resources managers.

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