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At least 1,153 records · Page 64
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Interannual Variations and Trends in Global Land Surface Phenology Derived from Enhanced Vegetation Index During 1982-2010

Land swiace phenology is widely retrieved from satellite observations at regional and global scales, and its long-term record has been demonstmted to be a valuable tool for reconstructing past climate variations, monitoring the dynamics of terrestrial ecosystems in response to climate impacts, and predicting biological responses to future climate scenarios. This srudy detected global land surface phenology from the advanced very high resolution radiometer (AVHRR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) data from 1982 to 2010. Based on daily enhanced vegetation index at a spatial resolution of 0.05 degrees, we simulated the seasonal vegetative trajectory for each individual pixel using piecewise logistic models, which was then used to detect the onset of greenness increase (OGI) and the length of vegetation growing season (GSL). Further, both overall interannual variations and pixel-based trends were examIned across Koeppen's climate regions for the periods of 1982-1999 and 2000-2010, respectively. The results show that OGI and OSL varied considerably during 1982-2010 across the globe. Generally, the interarmual variation could be more than a month in precipitation-controlled tropical and dry climates while it was mainly less than 15 days in temperature-controlled temperate, cold, and polar climates. OGI, overall, shifted early, and GSL was prolonged from 1982 to 2010 in most climate regions in North America and Asia while the consistently significant trends only occurred in cold climate and polar climate in North America. The overall trends in Europe were generally insignificant. Over South America, late OGI was consistent (particularly from 1982 to 1999) while either positive or negative OSL trends in a climate region were mostly reversed between the periods of 1982-1999 and 2000-2010. In the Northern Hemisphere of Africa, OGI trends were mostly insignificant, but prolonged GSL was evident over individual climate regions during the last 3 decades. OGI mainly showed late trends in the Southern Hemisphere of Africa while GSL was reversed from reduced GSL trends (1982-1999) to prolonged trends (2000-2010). In Australia, GSL exhibited considerable interannual variation, but the consistent trend lacked presence in most regions. Finally, the proportion of pixels with significant trends was less than I% in most of climate regions although it could be as large as 10%.

remote sensing↗
NASA NTRS2016

Monitoring Interannual Variation in Global Crop Yield Using Long-Term AVHRR and MODIS Observations

Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) data have been extensively applied for crop yield prediction because of their daily temporal resolution and a global coverage. This study investigated global crop yield using daily two band Enhanced Vegetation Index (EVI2) derived from AVHRR (1981-1999) and MODIS (2000-2013) observations at a spatial resolution of 0.05deg (approx.5 km). Specifically, EVI2 temporal trajectory of crop growth was simulated using a hybrid piecewise logistic model (HPLM) for individual pixels, which was used to detect crop phenological metrics. The derived crop phenology was then applied to calculate crop greenness defined as EVI2 amplitude and EVI2 integration during annual crop growing seasons, which was further aggregated for croplands in each country, respectively. The interannual variations in EVI2 amplitude and EVI2 integration were combined to correlate to the variation in cereal yield from 1982-2012 for individual countries using a stepwise regression model, respectively. The results show that the confidence level of the established regression models was higher than 90% (P value < 0.1) in most countries in the northern hemisphere although it was relatively poor in the southern hemisphere (mainly in Africa). The error in the yield predication was relatively smaller in America, Europe and East Asia than that in Africa. In the 10 countries with largest cereal production across the world, the prediction error was less than 9% during past three decades. This suggests that crop phenology-controlled greenness from coarse resolution satellite data has the capability of predicting national crop yield across the world, which could provide timely and reliable crop information for global agricultural trade and policymakers.

Crop phenology↗
NASA NTRS2013

Geostationary Enhanced Temporal Interpolation for CERES Flux Products

The Clouds and the Earth's Radiant Energy System (CERES) instruments on board the Terra and Aqua spacecraft continue to provide an unprecedented global climate record of the earth's top-of-atmosphere (TOA) energy budget since March 2000. A critical step in determining accurate daily averaged flux involves estimating the flux between CERES Terra or Aqua overpass times. CERES employs the CERES-only (CO) and the CERES geostationary (CG) temporal interpolation methods. The CO method assumes that the cloud properties at the time of the CERES observation remain constant and that it only accounts for changes in albedo with solar zenith angle and diurnal land heating, by assuming a shape for unresolved changes in the diurnal cycle. The CG method enhances the CERES data by explicitly accounting for changes in cloud and radiation between CERES observation times using 3-hourly imager data from five geostationary (GEO) satellites. To maintain calibration traceability, GEO radiances are calibrated against Moderate Resolution Imaging Spectroradiometer (MODIS) and the derived GEO fluxes are normalized to the CERES measurements. While the regional (1 deg latitude x 1 deg longitude) monthly-mean difference between the CG and CO methods can exceed 25 W m(sub -2) over marine stratus and land convection, these regional biases nearly cancel in the global mean. The regional monthly CG shortwave (SW) and longwave (LW) flux uncertainty is reduced by 20%, whereas the daily uncertainty is reduced by 50% and 20%, respectively, over the CO method, based on comparisons with 15-min Geostationary Earth Radiation Budget (GERB) data.

Doelling, David R.↗
NASA NTRS2019

Deep Learning Method for Detecting Precursors to Adverse Events

With the recent advancements in Deep Learning methods, the ability to model large complex heterogeneous data sets are fundamentally changing industry and research. Coupled with hardware improvements, and ease of implementation, a wide variety of deep neural network architectures can quickly be developed to solve a sweeping range of problems such as: object detection in images, automatic healthcare diagnosis using heterogenous data sources, real time language translating and sentence prediction, upscaling low resolution images, and forecasting of multivariate timeseries. Generally, many of these architectures outperform classical machine learning approaches in their respective tasks, however, this typically comes at a cost of interpretability. These black box algorithms generally suffer from lack of transparency in both model complexity as well as the rationale behind the prediction. This lack of comprehension, is driving an emerging area of interest in “Explainable AI”. An algorithm called: “Deep Temporal Multiple Instance Learning”1 was a recently developed to identify precursors to adverse events and has been applied in the aviation domain. The deep learning architecture is designed to capture the evolution of the probability of the outcome over the time preceding the adverse event using a multiple instance learning approach as illustrated in Figure 1. Precursors are defined when the probability of the event has exceeded a threshold at some point in the timeseries, at which point, a sensitivity analysis is performed to determine contributing factors. The contributing factors are used to explain and define the precursor during the periods where the probability score is high. The identified contributing factors are then presented to subject matter experts to provide objective insights into the leading factors associated with the particular adverse event. The algorithm has been tested on flight data from a commercial airline and has the ability to discover precursors to known adverse events that take the form of safety critical operations, such as unstable approach events on final approach. Apart from detecting precursors to adverse events, the converse can also be leveraged to discover corrective actions. These positive actions manifest themselves as periods in the timeseries when the precursor score has been lowered from an elevated state; meaning that if the system had been left uncorrected, it would have eventually reached the adverse event state. Characterizing these state changes can help identify successful interventions that may not have been known before. Policy makers and procedure designers can use this additional knowledge to craft more safety and efficient resilient procedures for future operations and therefore improve the overall performance of the National Airspace.

Matthews, Bryan L.↗
NASA NTRS2021

Grand Teton Ecological Forecasting: Assessing Forage Change and Winter Habitat Availability for Bighorn Sheep that Employ a High-Elevation Overwintering Strategy to Identify Areas for Intervention

Grand Teton National Park provides habitat for a small native population of approximately 125 bighorn sheep (Ovis canadensis). The reduction in population of this species is attributed to loss of low elevation habitat, changing local environmental and climatic conditions, and increased disturbance from backcountry recreation. In response to these changes, this population of sheep employs a unique high-elevation wintering strategy in which they amass large fat stores in the summer and expend as little energy as possible in the winter while foraging on high elevation wind-swept and snow-free areas. For this project, DEVELOP partnered with Grand Teton National Park and used NASA Earth observations including Landsat 8 Operational Land Imager (OLI), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 5 Thematic Mapper (TM), and Terra Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover data to assess habitat suitability. Landcover change analyzed between 1987 and 2020 indicated shifting trends in grass and forb cover and tree cover. These trends persisted in the 2031 prediction, with grass cover decreasing and tree cover increasing, which translates to a loss of overall favorable habitat for bighorn sheep. Snow cover analyzed between 2001 and 2020 indicated similar unfavorable trends for the sheep with a decrease in barren areas, important for winter foraging. Finally, habitat suitability was modeled for 2020 and predicted to 2031 to determine habitat gains and losses for this species across the landscape. Overall, the results predicted decreases in suitable habitat and indicated that while these sheep are highly adaptable, strategies to manage suitable bighorn habitat may need to be employed rapidly to effectively conserve this species.

Remote sensing↗
NASA NTRS2022

Flood Monitoring Using Enhanced Resolution Passive Microwave Data: A Test Case Over Bangladesh

Monitoring floods is a major issue in water resources management and risk mitigation, especially in the Global South. Optical and radar observations, even providing a fine spatial resolution, are still limited by cloud cover interaction or insufficient temporal resolution. On the other hand, passive microwave (PMW) sensors collect information on a daily frequency with minor cloud cover interaction, but they have been historically limited in terms of spatial resolution. Here, we evaluate the capability of an enhanced spatial resolution PMW dataset (3.125 km) in monitoring spatio-temporal evolution of flood events, focusing on a major flood event that occurred in October 2005 in Bangladesh. We apply an algorithm aimed to remove the seasonal variability of surface temperature from the PMW timeseries, exploiting the difference in emissivity between dry and water-covered pixels. We assess the capability of the algorithm in capturing flood evolution and extension through the comparison with quantities obtained from optical data collected by the Moderate Resolution Imaging Spectroradiometer (MODIS) and water level measurements. We also compare the enhanced product with the historical coarser resolution dataset by means of a variogram-based analysis to evaluate the improvements in terms of spatial representation. Finally, we evaluate the possibility to extract the water fraction within a single pixel by using an Advanced Microwave Scanning Radiometer—Earth Observing System (AMSR-E) emissivity dataset and compare the estimates with MODIS-derived water fractions. Our results show that the enhanced PMW product outperforms the coarser one when compared to flood mapped from optical data based on information content, indicating that it is possible to integrate such a product into the mapping of floods at a global scale on a daily basis.

flood detection↗
NASA NTRS2026

Using Satellite Surface Temperature Data to Monitor Urban Heat Island

Exposure to heat is a growing concern nationwide. Temperatures can be elevated in cities compared to surrounding rural areas, referred to as an “urban heat island” (UHI) effect, which is intensified during heat waves. The lack of dense networks of air temperature measurements results in few studies on urban heat. Now, a vast amount of high spatial and temporal satellite data on land surface temperature is available. We identified satellite datasets with the longest surface temperature records but different spatial and temporal resolutions: Landsat (1985-current, biweekly at 60 m and 100 m spatial resolution) and the Moderate Resolution Imaging Spectroradiometer (MODIS) data from the Terra and Aqua satellites (2000-current, daily at 1 km spatial resolution). We investigated how satellites with different spatial and temporal resolutions detect UHI effects differently. We hypothesized that 1) a dataset’s spatial resolution impacts the precision of detected UHIs spatially, since high spatial resolution Landsat data better captures spatial variability in temperature, and 2) daily surface temperature data can detect temporal patterns of UHIs and heatwave frequencies. We analyzed Landsat and MODIS satellite data in the Washington, D.C. and Baltimore region. We found that Landsat describes higher spatial variability of the UHI effect than MODIS data. However, MODIS data shows more consistent seasonal surface temperature patterns than Landsat when compared to in situ air temperature measurements. MODIS data was also able to consistently measure the frequency of heat waves. This study demonstrates the value of NASA satellite data for urban heat and climate change studies.

landsat↗
NASA NTRS1977

The Photicon

The Photicon is a novel imaging optical detector utilizing a conventional semitransparent photocathode, imaging electrostatic optics, microchannel plates, and a crossed-wire-grid position-sensitive charge detector. Its sensitivity to single optical photons over a two-dimensional area, high-resolution imaging, and timing capability render it useful for recording scintillations from X-ray image converters in X-ray astronomy. A digital word indicating the position of a single photon event is produced; the image can be stored in an array or serially. Spatial resolution to 20 microns in a 25 mm diam active area detector is reported, and modifications to achieve a spectral range of 120-730 nm are mentioned.

Kellogg, E.↗
NASA NTRS2010

JMISR INteractive eXplorer

MISR (Multi-angle Imaging SpectroRadiometer) INteractive eXplorer (MINX) is an interactive visualization program that allows a user to digitize smoke, dust, or volcanic plumes in MISR multiangle images, and automatically retrieve height and wind profiles associated with those plumes. This innovation can perform 9-camera animations of MISR level-1 radiance images to study the 3D relationships of clouds and plumes. MINX also enables archiving MISR aerosol properties and Moderate Resolution Imaging Spectroradiometer (MODIS) fire radiative power along with the heights and winds. It can correct geometric misregistration between cameras by correlating off-nadir camera scenes with corresponding nadir scenes and then warping the images to minimize the misregistration offsets. Plots of BRF (bidirectional reflectance factor) vs. camera angle for points clicked in an image can be displayed. Users get rapid access to map views of MISR path and orbit locations and overflight dates, and past or future orbits can be identified that pass over a specified location at a specified time. Single-camera, level-1 radiance data at 1,100- or 275- meter resolution can be quickly displayed in color using a browse option. This software determines the heights and motion vectors of features above the terrain with greater precision and coverage than previous methods, based on an algorithm that takes wind direction into consideration. Human interpreters can precisely identify plumes and their extent, and wind direction. Overposting of MODIS thermal anomaly data aids in the identification of smoke plumes. The software has been used to preserve graphical and textural versions of the digitized data in a Web-based database.

Nelson, David L.↗
NASA NTRS2000

Transesophageal echocardiography: first-line imaging for aortic diseases

Transesophageal echocardiography (TEE) is now commonly used to evaluate the thoracic aorta, because it is widely available and provides high-resolution images and flow information by Doppler. This article reviews the essential features on TEE of acute and chronic aortic diseases, such as aortic dissection, aneurysm, and atherosclerosis, and discusses its strengths, weaknesses, and indications.

NASA Program Biomedical Research and Countermeasur↗
NASA NTRS2016

Thinking Outside of the Blue Marble: Novel Ocean Applications Using the VIIRS Sensor

While planning for future space-borne sensors will increase the quality, quantity, and duration of ocean observations in the years to come, efforts to extend the limits of sensors currently in orbit can help shed light on future scientific gains as well as associated uncertainties. Here, we present several applications that are unique to the polar orbiting Visual Infrared Imaging Radiometer Suite (VIIRS), each of which challenge the threshold capabilities of the sensor and provide lessons for future missions. For instance, while moderate resolution polar orbiters typically have a one day revisit time, we are able to obtain multiple looks of the same area by focusing on the extreme zenith angles where orbital views overlap, and pair these observations with those from other sensors to create pseudo-geostationary data sets. Or, by exploiting high spatial resolution (imaging) channels and analyzing patterns of synoptic covariance across the visible spectrum, we can obtain higher spatial resolution bio-optical products. Alternatively, non-traditional products can illuminate important biological interactions in the ocean, such as the use of the Day-Night-Band to provide some quantification of phototactic behavior of marine life along light polluted beaches, as well as track the location of marine fishing vessel fleets along ocean fronts. In this talk, we explore ways to take full advantage of the capabilities of existing sensors in order to maximize insights for future missions.

ocean color↗
DOE OSTI2026

Enhancing X-ray Sensitivity via the Antenna Effect in Quantum Shells with Multiexciton Emission

Quantum shells (QSs) with efficient multiexciton emission can generate multiple excitons per particle under high-energy excitation, thereby improving exciton utilization under intense X-ray exposure and offering strong potential for X-ray-based scintillation applications. However, these QSs are typically composed of low-atomic-number (Z) elements, which substantially limits their X-ray absorption efficiency and leads to poor X-ray sensitivity. Here, we overcome this fundamental limitation by introducing a high-Z antenna-sensitization strategy that couples QSs to heavy-element molecular absorbers, which act as X-ray harvesting centers and funnel energy into the QSs via efficient interfacial transfer. By combining enhanced X-ray absorption with efficient interfacial energy transfer and improved exciton utilization, we achieve more than an order-of-magnitude increase in multiexciton-driven QS radioluminescence (RL) relative to pristine shells. Additionally, a high X-ray imaging resolution of 25.2 lp mm –1 was achieved, exceeding the performance of most previously reported X-ray imaging scintillators. These findings offer a promising design strategy for advancing QS-based materials toward high-performance X-ray imaging applications.

antenna effect↗
DOE OSTI2014

Breaking the limits of structural and mechanical imaging of the heterogeneous structure of coal macerals

The correlation between local mechanical (elasto-plastic) and structural (composition) properties of coal presents significant fundamental and practical interest for coal processing and the development of rheological models of coal to coke transformations and for advancing novel approaches. Here, we explore the relationship between the local structural, chemical composition and mechanical properties of coal using a combination of confocal micro-Raman imaging and band excitation atomic force acoustic microscopy (BE-AFAM) for a bituminous coal. This allows high resolution imaging (10s of nm) of mechanical properties of the heterogeneous (banded) architecture of coal and correlating them to the optical gap, average crystallite size, the bond-bending disorder of sp2 aromatic double bonds and the defect density. This methodology hence allows the structural and mechanical properties of coal components (lithotypes, microlithotypes, and macerals) to be understood, and related to local chemical structure, potentially allowing for knowledge-based modelling and optimization of coal utilization processes.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Ultrahigh-resolution scanning microwave impedance microscopy of moiré lattices and superstructures

Two-dimensional heterostructures composed of layers with slightly different lattice vectors exhibit new periodic structure known as moiré lattices, which, in turn, can support novel correlated and topological phenomena. Moreover, moiré superstructures can emerge from multiple misaligned moiré lattices or inhomogeneous strain distributions, offering additional degrees of freedom in tailoring electronic structure. High-resolution imaging of the moiré lattices and superstructures is critical for understanding the emerging physics. Here, we report the imaging of moiré lattices and superstructures in graphene-based samples under ambient conditions using an ultrahigh-resolution implementation of scanning microwave impedance microscopy. Although the probe tip has a gross radius of ~100 nm, spatial resolution better than 5 nm is achieved, which allows direct visualization of the structural details in moiré lattices and the composite super-moiré. We also demonstrate artificial synthesis of novel superstructures, including the Kagome moiré arising from the interplay between different layers.

36 MATERIALS SCIENCE↗
NASA NTRS1986

The development and test of multi-anode microchannel array detector systems. Part 2: Soft X-ray detectors

Multi-Anode Microchannel Array (MAMA) detector systems with formats of 256 x 1024 pixels and active areas of 6 x 26 square mm are now under evaluation at visible, ultraviolet and soft x-ray wavelengths. Very-large-format versions of the MAMA detectors with formats of 2048 x 2048 pixels and active areas of 52 x 52 square mm are under development for use in the NASA Goddard Space Flight Center's Space Telescope Imaging Spectrograph (STIS). Open-structure versions of these detectors with CsI photocathodes can provide a high-resolution imaging capability at extreme ultraviolet (EUV) and soft x-ray wavelengths and can deliver a maximum count rate from each array in excess of 1 million counts s-1. In addition, these detector systems have the unique capability to determine the arrival time of a detected photon to an accuracy of 100 ns or better. The construction, mode-of-operation and performance characteristics of the MAMA detectors are described and the program for the development of the very-large-format detectors is outlined.

Timothy, J. G.↗
NASA NTRS2000

Long-Term Time Variability in the X-Ray Pulse Shape of the Crab Nebula Pulsar

This is the final performance report for our grant 'Long-Term Time Variability in the X-Ray Pulse Shape of the Crab Nebula Pulsar.' In the first year of this grant, we received the 50,000-second ROSAT (German acronym for X-ray satellite) High Resolution Images (HRI) observation of the Crab Nebula pulsar. We used the data to create a 65-ms-resolution pulse profile and compared it to a similar pulse profile obtained in 1991. No statistically significant differences were found. These results were presented at the January 1998 meeting of the American Astronomical Society. Since then, we have performed more sensitive analyses to search for potential changes in the pulse profile shape between the two data sets. Again, no significant variability was found. In order to augment this long (six-year) baseline data set, we have analyzed archival observations of the Crab Nebula pulsar with the Rossi X-Ray Timing Explorer (RXTE). While these observations have shorter time baselines than the ROSAT data set, their higher signal-to-noise offers similar sensitivity to long-term variability. Again, no significant variations have been found, confirming our ROSAT results. This work was done in collaboration with Prof. Stephen Eikenberry, Cornell University. These analyses will be included in Cornell University graduate student Dae-Sik Moon's doctoral thesis.

Fazio, Giovanni G.↗
NASA NTRS2001

Degradation of MODIS Optics and its Reflective Solar Bands Calibration

The MODerate Resolution Imaging Spectroradiometer (MODIS) has 36 spectral bands with wavelength ranging from 0.41 micron to 14.5 micron and spatial resolution between 0.25, 0.5, and 1.0 km at Nadir. Its ProtoFlight Model (PFM) on the NASA EOS Terra spacecraft has been providing global coverage of the Land, Ocean, and Atmosphere for the science community since the instrument opened its Nadir door on 24 February 2000. The MODIS optical system consists of a 2-sided paddle wheel scan mirror, a fold mirror, a primary mirror, and other aft optics. The sensor's 20 reflective solar bands from 0.41 to 2.1 micron are calibrated on-orbit by a solar diffuser (SD) and a solar diffuser stability monitor (SDSM). In addition to SD, degradation of the MODIS optics in the reflective solar bands has been observed, including variations in degradation between the two sides of the MODIS scan mirror. During MODIS first year of on-orbit operation, the overall degradations at the shortest wavelength (0.41 micron) are about 3% for SD, and in excess of 10% for the MODIS system. In this paper, we will present our degradation analysis results and discuss their impact on the reflective solar bands' on-orbit calibration.

Xiong, X.↗
NASA NTRS2007

The Transition of NASA EOS Datasets to WFO Operations: A Model for Future Technology Transfer

The collocation of a National Weather Service (NWS) Forecast Office with atmospheric scientists from NASA/Marshall Space Flight Center (MSFC) in Huntsville, Alabama has afforded a unique opportunity for science sharing and technology transfer. Specifically, the NWS office in Huntsville has interacted closely with research scientists within the SPORT (Short-term Prediction and Research and Transition) Center at MSFC. One significant technology transfer that has reaped dividends is the transition of unique NASA EOS polar orbiting datasets into NWS field operations. NWS forecasters primarily rely on the AWIPS (Advanced Weather Information and Processing System) decision support system for their day to day forecast and warning decision making. Unfortunately, the transition of data from operational polar orbiters or low inclination orbiting satellites into AWIPS has been relatively slow due to a variety of reasons. The ability to integrate these high resolution NASA datasets into operations has yielded several benefits. The MODIS (MODerate-resolution Imaging Spectrometer ) instrument flying on the Aqua and Terra satellites provides a broad spectrum of multispectral observations at resolutions as fine as 250m. Forecasters routinely utilize these datasets to locate fine lines, boundaries, smoke plumes, locations of fog or haze fields, and other mesoscale features. In addition, these important datasets have been transitioned to other WFOs for a variety of local uses. For instance, WFO Great Falls Montana utilizes the MODIS snow cover product for hydrologic planning purposes while several coastal offices utilize the output from the MODIS and AMSR-E instruments to supplement observations in the data sparse regions of the Gulf of Mexico and western Atlantic. In the short term, these datasets have benefited local WFOs in a variety of ways. In the longer term, the process by which these unique datasets were successfully transitioned to operations will benefit the planning and implementation of products and datasets derived from both NPP and NPOESS. This presentation will provide a brief overview of current WFO usage of satellite data, the transition of datasets between SPORT and the N W S , and lessons learned for future transition efforts.

Darden, C.↗