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At least 505 records · Page 28

Examples of Level Products Possible from Existing Assets

How do patterns of human environmental and infectious diseases respond to leading environmental changes, particularly to urban growth and change and the associated impacts of urbanization? We use HyspIRI high spatial resolution, multispectral, and multitemporal TIR data to track energy balance and energy flux characteristics for changing land covers/land uses through time to provide synoptic views of impacts on surface energy fluxes, emissivity and temperature and HyspIRI data in conjunction with spatial growth models to project land cover/land use changes in the future to assess impacts on natural and human ecosystems. We use multispectral thermal IR land cover maps at a high spatial resolution (60m) on a weekly basis for long-term validation of surface energy responses and changes in emissivity and integration of HyspIRI TIR data with spatial modeling to assess changes in land cover/land use through time and subsequent changes in thermal energy responses

Quattrochi, Dale A.↗

The X-ray Mirrors for the Astro-E2 Mission

The X-Ray telescopes (XRT) for the US/Japan collaborative mission Astro-E2 will be of the same basic design as those built for the original Astro-E mission which failed to reach orbit in Feb. 2000. The NASA/GSFC X-ray Astrophysics Branch will again provide the five lightweight, broad-band mirrors for the mission. X-ray calibrations of the mirrors delivered for the original Astro-E instrument showed spatial resolutions characterized by Half-Power Diameters (HPD) in the range of 1.8 - 2.2 minutes of arc, essentially independent of photon energy in the soft X-ray band. For the mission Astro-E2, both funding constraints and management decisions drastically limit any design modifications, so reflector fabrication and assembly procedures have remained largely unchanged. Nevertheless, in view of the importance in scientific return of attaining even a modest improvement in the spatial resolution of these mirrors, we have carefully considered the various sources of spatial error and, whenever possible, incorporated promising modifications. In this paper, we discuss our current understanding of the various error components as well as the small changes we have been able to implement.

Chan, Kai-Wing↗

The magnetic field of the earth - Performance considerations for space-based observing systems

Basic problems inherent in carrying out observations of the earth magnetic field from space are reviewed. It is shown that while useful observations of the core and crustal fields are possible at the peak of the solar cycle, the greatest useful data volume is obtained during solar minimum. During the last three solar cycles, the proportion of data with a planetary disturbance index of less than 2 at solar maximum was in the range 0.4-0.8 in comparison with solar minimum. It is found that current state of the art orbit determination techniques should eliminate orbit error as a problem in gravitational field measurements from space. The spatial resolution obtained for crustal field anomalies during the major satellite observation programs of the last 30 years are compared in a table. The relationship between observing altitude and the spatial resolution of magnetic field structures is discussed. Reference is made to data obtained using the Magsat, the Polar Orbiting Geophysical Observatory (POGO), and instruments on board the Space Shuttle.

Webster, W. J., Jr.↗

Remote Sensing Product Verification and Validation at the NASA Stennis Space Center

Remote sensing data product verification and validation (V&V) is critical to successful science research and applications development. People who use remote sensing products to make policy, economic, or scientific decisions require confidence in and an understanding of the products' characteristics to make informed decisions about the products' use. NASA data products of coarse to moderate spatial resolution are validated by NASA science teams. NASA's Stennis Space Center (SSC) serves as the science validation team lead for validating commercial data products of moderate to high spatial resolution. At SSC, the Applications Research Toolbox simulates sensors and targets, and the Instrument Validation Laboratory validates critical sensors. The SSC V&V Site consists of radiometric tarps, a network of ground control points, a water surface temperature sensor, an atmospheric measurement system, painted concrete radial target and edge targets, and other instrumentation. NASA's Applied Sciences Directorate participates in the Joint Agency Commercial Imagery Evaluation (JACIE) team formed by NASA, the U.S. Geological Survey, and the National Geospatial-Intelligence Agency to characterize commercial systems and imagery.

Stanley, Thomas M.↗

Early Results from the MODIS Atmosphere Cloud Algorithms

The Moderate Resolution Imaging Spectroradiometer (MODIS) is one of five instruments aboard the Terra Earth Observing System platform launched in December 1999. With 36 spectral bands from the visible through the infrared, and spatial resolution from 250m to 1km, the instrument provides an unprecedented opportunity for global cloud studies. A comprehensive set of remote sensing algorithms for cloud masking and retrieval of cloud physical and optical properties have been developed by members of the MODIS atmosphere team. The archived products from these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, as well as fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud top physical parameters (temperature, pressure, emissivity), cloud phase, cloud optical parameters (optical depth, effective particle radius, water path), visible cirrus reflectance, a contrail flag, and other derived parameters. All products are archived into two categories: pixel-level retrievals at a 1 km or 5 km spatial resolution at nadir (referred to as Level-2 products) and 1 degree global gridded statistics (Level-3 products). An overview of the MODIS atmosphere algorithms and products, their status, validation activities, and early level-2 and -3 results will be presented.

Platnick, S.↗

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↗

Cloud and Radiation Studies during SAFARI 2000

Though the emphasis of the Southern Africa Regional Science Initiative 2000 (SAFARI-2000) dry season campaign was largely on emission sources and transport, the assemblage of aircraft (including the high altitude NASA ER-2 remote sensing platform and the University of Washington CV-580, UK MRF C130, and South African Weather Bureau JRA in situ aircrafts) provided a unique opportunity for cloud studies. Therefore, as part of the SAFARI initiative, investigations were undertaken to assess regional aerosol-cloud interactions and cloud remote sensing algorithms. In particular, the latter part of the experiment concentrated on marine boundary layer stratocumulus clouds off the southwest coast of Africa. Associated with cold water upwelling along the Benguela current, the Namibian stratocumulus regime has received limited attention but appears to be unique for several reasons. During the dry season, outflow of continental fires and industrial pollution over this area can be extreme. From below, upwelling provides a rich nutrient source for phytoplankton (a source of atmospheric sulphur through DMS production as well as from decay processes). The impact of these natural and anthropogenic sources on the microphysical and optical properties of the stratocumulus is unknown. Continental and Indian Ocean cloud systems of opportunity were also studied during the campaign. Aircraft flights were coordinated with NASA Terra Satellite overpasses for synergy with the Moderate Resolution Imaging Spectroradiometer (MODIS) and other Terra instruments. An operational MODIS algorithm for the retrieval of cloud optical and physical properties (including optical thickness, effective particle radius, and water path) has been developed. Pixel-level MODIS retrievals (11 km spatial resolution at nadir) and gridded statistics of clouds in th SAFARI region will be presented. In addition, the MODIS Airborne Simulator flown on the ER-2 provided high spatial resolution retrievals (50 m at nadir). These retrievals will be discussed and compared with in situ observations.

Platnick, Steven↗

High-Resolution Gridded Level 3 Aerosol Optical Depth Data from MODIS

The state-of-art satellite observations of atmospheric aerosols over the last two decades from NASA's MODIS instruments have been extensively utilized in climate change and air quality research and applications. The operational algorithms now produce level 2 aerosol data at varying spatial resolutions (1, 3, and 10 km) and level 3 data at 1 degree. The local and global applications have been benefited from the coarse resolution gridded data sets (i.e., level 3, 1 degree), as it is easier to use since data volume is low and, several online and offline tools are readily available to access and analyze the data with minimal computing resources. At the same time, researchers who require data at much finer spatial scales have to go through a challenging process of obtaining, processing, and analyzing larger volumes of data sets that require high-end computing resources and coding skills. Therefore, we have created a high spatial resolution (HRG, 0.1x0.1 degree) daily and monthly aerosol optical depth (AOD) product by combining two MODIS operational algorithms, namely Deep Blue (DB) and Dark Target (DT). The new HRG AODs meets the accuracy requirements of level 2 AOD data and provide either the same or more spatial coverage on daily and monthly scales. The data sets are provided in daily and monthly files through open Ftp server with python scripts to read and map the data. The reduced data volume with an easy to use format and tools to access the data will encourage more users to utilize the data for research and applications.

aerosol↗

Dual-Mode Laser Velocimeter

Reversible lens system provides two velocity ranges. Laser velocimeter modified to provide two velocity ranges by adding rotatable assembly containing two lenses. In one orientation, beam waists narrow, and two beams intersect at relatively large angle, providing low velocity range with high spatial resolution. In reversed orientation beam waists are wider, and beams intersect at smaller angle to produce more-widely-spaced fringes in larger region, providing high velocity range with lower spatial resolution.

Gunter, William D., Jr.↗

Estimating Ground-Level PM(sub 2.5) Concentrations in the Southeastern United States Using MAIAC AOD Retrievals and a Two-Stage Model

Previous studies showed that fine particulate matter (PM(sub 2.5), particles smaller than 2.5 micrometers in aerodynamic diameter) is associated with various health outcomes. Ground in situ measurements of PM(sub 2.5) concentrations are considered to be the gold standard, but are time-consuming and costly. Satellite-retrieved aerosol optical depth (AOD) products have the potential to supplement the ground monitoring networks to provide spatiotemporally-resolved PM(sub 2.5) exposure estimates. However, the coarse resolutions (e.g., 10 km) of the satellite AOD products used in previous studies make it very difficult to estimate urban-scale PM(sub 2.5) characteristics that are crucial to population-based PM(sub 2.5) health effects research. In this paper, a new aerosol product with 1 km spatial resolution derived by the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was examined using a two-stage spatial statistical model with meteorological fields (e.g., wind speed) and land use parameters (e.g., forest cover, road length, elevation, and point emissions) as ancillary variables to estimate daily mean PM(sub 2.5) concentrations. The study area is the southeastern U.S., and data for 2003 were collected from various sources. A cross validation approach was implemented for model validation. We obtained R(sup 2) of 0.83, mean prediction error (MPE) of 1.89 micrograms/cu m, and square root of the mean squared prediction errors (RMSPE) of 2.73 micrograms/cu m in model fitting, and R(sup 2) of 0.67, MPE of 2.54 micrograms/cu m, and RMSPE of 3.88 micrograms/cu m in cross validation. Both model fitting and cross validation indicate a good fit between the dependent variable and predictor variables. The results showed that 1 km spatial resolution MAIAC AOD can be used to estimate PM(sub 2.5) concentrations.

aerosol optical depth↗

A 40th deg and order gravitational field model for Mars

Understanding the origin and evolution of major photographic features on Mars, such as the hemispheric dichotomy and Tharsis rise, will require improved resolution of that planet's gravitational and topographic fields. The highest resolution gravity model for Mars published to date was derived from Doppler tracking data from the Mariner 9 and Viking 1 and 2 spacecraft, and is of 18th degree and order. That field has a maximum spatial resolution of approx. 600 km, which is comparable to that of the best topographic model. The resolution of previous gravity models was limited not by data density, but rather by the computational resources available at the time. Because this restriction is no longer a limitation, the Viking and Mariner data sets were reanalyzed and a gravitational field was derived complete to the 40th degree and order with a corresponding maximum spatial resolution of 300 km where the data permit.

Zuber, M. T.↗

Thermal Emission From Saturn's Polar Cyclones

We have used data from the Cassini Composite Infrared Spectrometer to map the temperatures in Saturn's polar cyclones at the highest spatial resolution obtained during the Cassini mission. We find temperature contrasts of 7 K in the upper troposphere within 1.4° of both poles, roughly 50 percent larger than earlier measurements at lower spatial resolution. The polar hot spots weaken with depth, disappearing near 500 mbar. In the stratosphere, the polar hot spot becomes broader, extending 4° from the poles, and weakens with altitude disappearing near 1 mbar. A thermal relaxation model shows that the tropospheric hot spot is consistent with adiabatic heating from subsidence with a vertical velocity of about −0.05 mm/s above 500 mbar. The observed temperature gradients imply that the winds in the polar cyclone decay with increasing altitude over roughly three pressure scale heights above the 200‐mbar level.

Polar↗

Recent Developments in Transition-Edge Strip Detectors for Solar X-Rays

LMSAL and NIST are developing position-sensitive x-ray strip detectors based on Transition Edge Sensor (TES) microcalorimeters optimized for solar physics. By combining high spectral (E/ delta E approximately equals 1600) and temporal (single photon delta t approximately equals 10 micro s) resolutions with imaging capabilities, these devices will be able to study high-temperature (>l0 MK) x-ray lines as never before. Diagnostics from these lines should provide significant new insight into the physics of both microflares and the early stages of flares. Previously, the large size of traditional TESs, along with the heat loads associated with wiring large arrays, presented obstacles to using these cryogenic detectors for solar missions. Implementing strip detector technology at small scales, however, addresses both issues: here, a line of substantially smaller effective pixels requires only two TESs, decreasing both the total array size and the wiring requirements for the same spatial resolution. Early results show energy resolutions of delta E(sub fwhm) approximately equals 30 eV and spatial resolutions of approximately 10-15 micron, suggesting the strip-detector concept is viable.

Rausch, Adam J.↗

Detecting Early Warning Signals of Tree Mortality in Boreal North America Using Multiscale Satellite Data

Increasing tree mortality from global change drivers such as drought and biotic infestations is a widespread phenomenon, including in the boreal zone where climate changes and feedbacks to the Earth system are relatively large. Despite the importance for science and management communities, our ability to forecast tree mortality at landscape to continental scales is limited. However, two independent information streams have the potential to inform and improve mortality forecasts: repeat forest inventories and satellite remote sensing. Time series of tree-level growth patterns indicate that productivity declines and related temporal dynamics often precede mortality years to decades before death. Plot-level productivity, in turn, has been related to satellite-based indices such as the Normalized difference vegetation index (NDVI). Here we link these two data sources to show that early warning signals of mortality are evident in several NDVI-based metrics up to 24 years before death. We focus on two repeat forest inventories and three NDVI products across western boreal North America where productivity and mortality dynamics are influenced by periodic drought. These data sources capture a range of forest conditions and spatial resolution to highlight the sensitivity and limitations of our approach. Overall, results indicate potential to use satellite NDVI for early warning signals of mortality. Relationships are broadly consistent across inventories, species, and spatial resolutions, although the utility of coarse-scale imagery in the heterogeneous aspen parkland was limited. Longer-term NDVI data and annually remeasured sites with high mortality levels generate the strongest signals, although we still found robust relationships at sites remeasured at a typical 5 year frequency. The approach and relationships developed here can be used as a basis for improving forest mortality models and monitoring systems.

heat↗

Dynamic Moss Observed with Hi-C

The High‐resolution Coronal Imager (Hi‐C), flown on 11 July 2012, has revealed an unprecedented level of detail and substructure within the solar corona. Hi‐C imaged a large active region (AR11520) with 0.2‐0.3'' spatial resolution and 5.5s cadence over a 5 minute period. An additional dataset with a smaller FOV, the same resolution, but with a higher temporal cadence (1s) was also taken during the rocket flight. This dataset was centered on a large patch of 'moss' emission that initially seemed to show very little variability. Image processing revealed this region to be much more dynamic than first thought with numerous bright and dark features observed to appear, move and disappear over the 5 minute observation. Moss is thought to be emission from the upper transition region component of hot loops so studying its dynamics and the relation between the bright/dark features and underlying magnetic features is important to tie the interaction of the different atmospheric layers together. Hi‐C allows us to study the coronal emission of the moss at the smallest scales while data from SDO/AIA and HMI is used to give information on these structures at different heights/temperatures. Using the high temporal and spatial resolution of Hi‐C the observed moss features were tracked and the distribution of displacements, speeds, and sizes were measured. This allows us to comment on both the physical processes occurring within the dynamic moss and the scales at which these changes are occurring.

Alexander, Caroline↗

Exploring the Mineralogy of the Moon with M3

From the initial era or lunar exploration, we have learned that many processes active on the early Moon are common to most terrestrial planets, including the record of early and late impact bombardment. Since most major geologic activity ceased on the Moon approx. 3 Gy ago, the Moon's surface provides a record of the earliest era of terrestrial planet evolution. The type and composition of minerals that comprise a planetary surface are a direct result of the initial composition and subsequent thermal and physical processing. Lunar mineralogy seen today is thus a direct record of the early evolution of the lunar crust and subsequent geologic processes. Specifically, the distribution and concentration of specific minerals is closely tied to magma ocean products, lenses of intruded or remelted plutons, basaltic volcanism and fire-fountaining, and any process (e.g. cratering) that might redistribute or transform primary and secondary lunar crustal materials. The Moon Mineralogy Mapper (M3, or "m-cube") is a state-of-the-art imaging spectrometer that will fly on Chandrayaan-1, the Indian Space Research Organization (ISRO) mission to be launched late 2007 to early 2008. M3 is one of several foreign instruments chosen by ISRO to be flown on Chandrayaan-1 to complement the strong ISRO payload package. M3 was selected through a peer-review process as part of NASA s Discovery Program. It is under the oversight of PI Carle Pieters at Brown University and is being built by an experienced team at the Jet Propulsion Laboratory. Data analysis and calibration are carried out by a highly qualified and knowledgeable Science Team. To characterize diagnostic properties of lunar minerals, M3 acquires high spectral resolution reflectance data from 700 to 3000 nm (optional to 430 nm). M3 operates as a pushbroom spectrometer with a slit oriented orthogonal to the S/C orbital motion. Measurements are obtained simultaneously for 640 cross track spatial elements and 261 spectral elements. This translates to 70 m/pixel spatial resolution from a nominal 100 km polar orbit for Chandrayaan-1 . The primary science goal of M3 is to characterize and map lunar surface mineralogy in the context of its geologic evolution as outlined above. This translates into several sub-topics that focus on exploring the mineral character of the highland crust, characterizing the diversity basaltic volcanism, and identifying potential volatile concentrations near the poles. The primary exploration goal is to assess and map lunar mineral resources at high spatial resolution to support planning for future, targeted missions.

Pieters, C. M.↗

High-resolution imaging of rain systems with the advanced microwave precipitation radiometer

An advanced Microwave Precipitation Radiometer (AMPR) has been developed and flown in the NASA ER-2-high-altitude aircraft for imaging various atmospheric and surface processes, primarily the internal structure of rain clouds. The AMPR is a scanning four-frequency total power microwave radiometer that is externally calibrated with high-emissivity warm and cold loads. Separate antenna systems allow the sampling of the 10.7- and 19.35-GHz channels at the same spatial resolution, while the 37.1- and 85.5-GHz channels utilize the same multifrequency feedhorn as the 19.35-GHz channel. Spatial resolutions from an aircraft altitude of 20-km range from 0.6 km at 85.5 GHz to 2.8 km at 19.35 and 10.7 GHz. All channels are sampled every 0.6 km in both along-track and cross-track directions, leading to a contiguous sampling pattern of the 85.5-GHz 3-dB beamwidth footprints, 2.3X oversampling of the 37.1-GHz data, and 4.4X oversampling of the 19.35- and 10.7-GHz data. Radiometer temperature sensitivities range from 0.2 to 0.5 C. Details of the system are described, including two different calibration systems and their effect on the data collected. Examples of oceanic rain systems are presented from Florida and the tropical west Pacific that illustrate the wide variety of cloud water, rainwater, and precipitation-size ice combinations that are observable from aircraft altitudes.

Spencer, Roy W.↗

A New Hybrid Spatio-temporal Model for Estimating Daily Multi-year PM2.5 Concentrations Across Northeastern USA Using High Resolution Aerosol Optical Depth Data

The use of satellite-based aerosol optical depth (AOD) to estimate fine particulate matter PM(sub 2.5) for epidemiology studies has increased substantially over the past few years. These recent studies often report moderate predictive power, which can generate downward bias in effect estimates. In addition, AOD measurements have only moderate spatial resolution, and have substantial missing data. We make use of recent advances in MODIS satellite data processing algorithms (Multi-Angle Implementation of Atmospheric Correction (MAIAC), which allow us to use 1 km (versus currently available 10 km) resolution AOD data.We developed and cross validated models to predict daily PM(sub 2.5) at a 1X 1 km resolution across the northeastern USA (New England, New York and New Jersey) for the years 2003-2011, allowing us to better differentiate daily and long term exposure between urban, suburban, and rural areas. Additionally, we developed an approach that allows us to generate daily high-resolution 200 m localized predictions representing deviations from the area 1 X 1 km grid predictions. We used mixed models regressing PM(sub 2.5) measurements against day-specific random intercepts, and fixed and random AOD and temperature slopes. We then use generalized additive mixed models with spatial smoothing to generate grid cell predictions when AOD was missing. Finally, to get 200 m localized predictions, we regressed the residuals from the final model for each monitor against the local spatial and temporal variables at each monitoring site. Our model performance was excellent (mean out-of-sample R(sup 2) = 0.88). The spatial and temporal components of the out-of-sample results also presented very good fits to the withheld data (R(sup 2) = 0.87, R(sup)2 = 0.87). In addition, our results revealed very little bias in the predicted concentrations (Slope of predictions versus withheld observations = 0.99). Our daily model results show high predictive accuracy at high spatial resolutions and will be useful in reconstructing exposure histories for epidemiological studies across this region.

Air pollution↗