Depth perception and head movements
Relation of depth perception to head movement, and binocular and monocular vision
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Results for “depth”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Misperceptions of angular velocities influence the perception of rigidity in the kinetic depth effect
Accuracy in discriminating rigid from nonrigid motion was investigated for orthographic projections of three-dimension rotating objects. In 3 experiments the hypothesis that magnitudes of angular velocity are misperceived in the kinetic depth effect was tested, and in 4 other experiments the hypothesis that misperceiving angular velocities leads to misperceiving rigidity was tested. The principal findings were (a) the magnitude of perceived angular velocity is derived heuristically as a function of a property of the first-order optic flow called deformation and (b) perceptual performance in discriminating rigid from nonrigid motion is accurate in cases when the variability of the deformations of the individual triplets of points of the stimulus displays favors this interpretation and not accurate in other cases.
NASA Center ARC↗
Computing depth maps from descent imagery
This paper addresses the generation depth maps from the descent images.
descent imagery motion estimate depth recovery pla↗
Effects of High-frequency Wind Sampling on Simulated Mixed Layer Depth and Upper Ocean Temperature
Effects of high-frequency wind sampling on a near-global ocean model are studied by forcing the model with a 12 hourly averaged wind product and its 24 hourly subsamples in separate experiments. The differences in mixed layer depth and sea surface temperature resulting from these experiments are examined, and the underlying physical processes are investigated. The 24 hourly subsampling not only reduces the high-frequency variability of the wind but also affects the annual mean wind because of aliasing. While the former effect largely impacts mid- to high-latitude oceans, the latter primarily affects tropical and coastal oceans. At mid- to high-latitude regions the subsampled wind results in a shallower mixed layer and higher sea surface temperature because of reduced vertical mixing associated with weaker high-frequency wind. In tropical and coastal regions, however, the change in upper ocean structure due to the wind subsampling is primarily caused by the difference in advection resulting from aliased annual mean wind, which varies with the subsampling time. The results of the study indicate a need for more frequent sampling of satellite wind measurement and have implications for data assimilation in terms of identifying the nature of model errors.
mixed layered depth↗
Intercomparison of Desert Dust Optical Depth from Satellite Measurements
This work provides a comparison of satellite retrievals of Saharan desert dust aerosol optical depth (AOD) during a strong dust event through March 2006. In this event, a large dust plume was transported over desert, vegetated, and ocean surfaces. The aim is to identify the differences between current datasets. The satellite instruments considered are AATSR, AIRS, MERIS, MISR, MODIS, OMI, POLDER, and SEVIRI. An interesting aspect is that the different algorithms make use of different instrument characteristics to obtain retrievals over bright surfaces. These include multi-angle approaches (MISR, AATSR), polarisation measurements (POLDER), single-view approaches using solar wavelengths (OMI, MODIS), and the thermal infrared spectral region (SEVIRI, AIRS). Differences between instruments, together with the comparison of different retrieval algorithms applied to measurements from the same instrument, provide a unique insight into the performance and characteristics of the various techniques employed. As well as the intercomparison between different satellite products, the AODs have also been compared to co-located AERONET data. Despite the fact that the agreement between satellite and AERONET AODs is reasonably good for all of the datasets, there are significant differences between them when compared to each other, especially over land. These differences are partially due to differences in the algorithms, such as assumptions about aerosol model and surface properties. However, in this comparison of spatially and temporally averaged data, it is important to note that differences in sampling, related to the actual footprint of each instrument on the heterogeneous aerosol field, cloud identification and the quality control flags of each dataset can be an important issue.
desert dust↗
Aeronet-based Microphysical and Optical Properties of Smoke-dominated Aerosol near Source Regions and Transported over Oceans, and Implications for Satellite Retrievals of Aerosol Optical Depth
Smoke aerosols from biomass burning are an important component of the global aerosol cycle. Analysis of Aerosol Robotic Network (AERONET) retrievals of size distribution and refractive index reveals variety between biomass burning aerosols in different global source regions, in terms of aerosol particle size and single scatter albedo (SSA). Case studies of smoke transported to coastal/island AERONET sites also mostly lie within the range of variability at near-source sites. Two broad families of aerosol properties are found, corresponding to sites dominated by boreal forest burning (larger, broader fine mode, with midvisible SSA 0.95), and those influenced by grass, shrub, or crop burning with additional forest contributions (smaller, narrower particles with SSA 0.88-0.9 in the midvisible). The strongest absorption is seen in southern African savanna at Mongu (Zambia), with average SSA 0.85 in the midvisible. These can serve as candidate sets of aerosol microphysicaloptical properties for use in satellite aerosol optical depth (AOD) retrieval algorithms. The models presently adopted by these algorithms over ocean are often insufficiently absorbing to represent these biomass burning aerosols. A corollary of this is an underestimate of AOD in smoke outflow regions, which has important consequences for applications of these satellite datasets.
AERONET↗
Improvement of Aerosol Optical Depth Retrieval from MODIS Spectral Reflectance over the Global Ocean Using New Aerosol Models Archived from AERONET Inversion Data and Tri-axial Ellipsoidal Dust Database
New over-ocean aerosol models are developed by integrating the inversion data from the Aerosol Robotic Network (AERONET) sun/sky radiometers with a database for the optical properties of tri-axial ellipsoid particles. The new aerosol models allow more accurate retrieval of aerosol optical depth (AOD) from the Moderate Resolution Imaging Spectroradiometer (MODIS) in the case of high AOD (AOD greater than 0.3). The aerosol models are categorized by using the fine-mode fraction (FMF) at 550 nm and the singlescattering albedo (SSA) at 440 nm from the AERONET inversion data to include a variety of aerosol types found around the globe. For each aerosol model, the changes in the aerosol optical properties (AOPs) as functions of AOD are considered to better represent aerosol characteristics. Comparisons of AODs between AERONET and MODIS for the period from 2003 to 2010 show that the use of the new aerosol models enhances the AOD accuracy with a Pearson coefficient of 0.93 and a regression slope of 0.99 compared to 0.92 and 0.85 calculated using the MODIS Collection 5 data. Moreover, the percentage of data within an expected error of +/-(0.03 + 0.05xAOD) is increased from 62 percent to 64 percent for overall data and from 39 percent to 51 percent for AOD greater than 0.3. Errors in the retrieved AOD are further characterized with respect to the Angstrom exponent (AE), scattering angle, SSA, and air mass factor (AMF). Due to more realistic AOPs assumptions, the new algorithm generally reduces systematic errors in the retrieved AODs compared with the current operational algorithm. In particular, the underestimation of fine-dominated AOD and the scattering angle dependence of dust-dominated AOD are significantly mitigated as results of the new algorithm's improved treatment of aerosol size distribution and dust particle nonsphericity.
aerosol optical depth↗
Evaluating Nighttime CALIOP 0.532 micron Aerosol Optical Depth and Extinction Coefficient Retrievals
NASA Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP) Version 3.01 5-km nighttime 0.532 micron aerosol optical depth (AOD) datasets from 2007 are screened, averaged and evaluated at 1 deg X 1 deg resolution versus corresponding/co-incident 0.550 micron AOD derived using the US Navy Aerosol Analysis and Prediction System (NAAPS), featuring two-dimensional variational assimilation of quality-assured NASA Moderate Resolution Imaging Spectroradiometer (MODIS) and Multi-angle Imaging Spectroradiometer (MISR) AOD. In the absence of sunlight, since passive radiometric AOD retrievals rely overwhelmingly on scattered radiances, the model represents one of the few practical global estimates available from which to attempt such a validation. Daytime comparisons, though, provide useful context. Regional-mean CALIOP vertical profiles of night/day 0.532 micron extinction coefficient are compared with 0.523/0.532 micron ground-based lidar measurements to investigate representativeness and diurnal variability. In this analysis, mean nighttime CALIOP AOD are mostly lower than daytime (0.121 vs. 0.126 for all aggregated data points, and 0.099 vs. 0.102 when averaged globally per normalised 1 deg. X 1 deg. bin), though the relationship is reversed over land and coastal regions when the data are averaged per normalised bin (0.134/0.108 vs. 0140/0.112, respectively). Offsets assessed within single bins alone approach +/- 20 %. CALIOP AOD, both day and night, are higher than NAAPS over land (0.137 vs. 0.124) and equal over water (0.082 vs. 0.083) when averaged globally per normalised bin. However, for all data points inclusive, NAAPS exceeds CALIOP over land, coast and ocean, both day and night. Again, differences assessed within single bins approach 50% in extreme cases. Correlation between CALIOP and NAAPS AOD is comparable during both day and night. Higher correlation is found nearest the equator, both as a function of sample size and relative signal magnitudes inherent at these latitudes. Root mean square deviation between CALIOP and NAAPS varies between 0.1 and 0.3 globally during both day/night. Averaging of CALIOP along-track AOD data points within a single NAAPS grid bin improves correlation and RMSD, though day/night and land/ocean biases persist and are believed systematic. Vertical profiles of extinction coefficient derived in the Caribbean compare well with ground-based lidar observations, though potentially anomalous selection of a priori lidar ratios for CALIOP retrievals is likely inducing some discrepancies. Mean effective aerosol layer top heights are stable between day and night, indicating consistent layer-identification diurnally, which is noteworthy considering the potential limiting effects of ambient solar noise during day.
aerosol optical depth↗
Influence of Observed Diurnal Cycles of Aerosol Optical Depth on Aerosol Direct Radiative Effect
The diurnal variability of aerosol optical depth (AOD) can be significant, depending on location and dominant aerosol type. However, these diurnal cycles have rarely been taken into account in measurement-based estimates of aerosol direct radiative forcing (ADRF) or aerosol direct radiative effect (ADRE). The objective of our study was to estimate the influence of diurnal aerosol variability at the top of the atmosphere ADRE estimates. By including all the possible AERONET sites, we wanted to assess the influence on global ADRE estimates. While focusing also in more detail on some selected sites of strongest impact, our goal was to also see the possible impact regionally.We calculated ADRE with different assumptions about the daily AOD variability: taking the observed daily AOD cycle into account and assuming diurnally constant AOD. Moreover, we estimated the corresponding differences in ADREs, if the single AOD value for the daily mean was taken from the the Moderate Resolution Imaging Spectroradiometer (MODIS) Terra or Aqua overpass times, instead of accounting for the true observed daily variability. The mean impact of diurnal AOD variability on 24 h ADRE estimates, averaged over all AERONET sites, was rather small and it was relatively small even for the cases when AOD was chosen to correspond to the Terra or Aqua overpass time. This was true on average over all AERONET sites, while clearly there can be much stronger impact in individual sites. Examples of some selected sites demonstrated that the strongest observed AOD variability (the strongest morning afternoon contrast) does not typically result in a significant impact on 24 h ADRE. In those cases, the morning and afternoon AOD patterns are opposite and thus the impact on 24 h ADRE, when integrated over all solar zenith angles, is reduced. The most significant effect on daily ADRE was induced by AOD cycles with either maximum or minimum AOD close to local noon. In these cases, the impact on 24 h ADRE was typically around 0.1-0.2W/sq m (both positive and negative) in absolute values, 5-10% in relative ones.
optical depth↗
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↗
Assessment of 10 Year Record of Aerosol Optical Depth from OMI UV Observations
The Ozone Monitoring Instrument (OMI) onboard the EOS-Aura satellite provides information on aerosol optical properties by making use of the large sensitivity to aerosol absorption in the near-ultraviolet (UV) spectral region. Another important advantage of using near UV observations for aerosol characterization is the low surface albedo of all terrestrial surfaces in this spectral region that reduces retrieval errors associated with land surface reflectance characterization. In spite of the 13 × 24 square kilometers coarse sensor footprint, the OMI near UV aerosol algorithm (OMAERUV) retrieves aerosol optical depth (AOD) and single-scattering albedo under cloud-free conditions from radiance measurements at 354 and 388 nanometers. We present validation results of OMI AOD against space and time collocated Aerosol Robotic Network measured AOD values over multiple stations representing major aerosol episodes and regimes. OMAERUV's performance is also evaluated with respect to those of the Aqua-MODIS Deep Blue and Terra-MISR AOD algorithms over arid and semi-arid regions in Northern Africa. The outcome of the evaluation analysis indicates that in spite of the "row anomaly" problem, affecting the sensor since mid-2007, the long-term aerosol record shows remarkable sensor stability.
aerosol optical depth↗
Comparisons of In-Situ Snow Depth Measurements with Airborne Data
Theme is the comparison of in-situ snow depth measurements with airborne data.
sea ice↗
Assessment of OMI Near-UV Aerosol Optical Depth over Land
This is the first comprehensive assessment of the aerosol optical depth (AOD) product retrieved from the near-UV observations by the Ozone Monitoring Instrument (OMI) onboard the Aura satellite. The OMI-retrieved AOD by the ultraviolet (UV) aerosol algorithm (OMAERUV version 1.4.2) was evaluated using collocated Aerosol Robotic Network (AERONET) level 2.0 direct Sun AOD measurements over 8 years (2005-2012). A time series analysis of collocated satellite and ground-based AOD observations over 8 years shows no discernible drift in OMI's calibration. A rigorous validation analysis over 4 years (2005-2008) was carried out at 44 globally distributed AERONET land sites. The chosen locations are representative of major aerosol types such as smoke from biomass burning or wildfires, desert mineral dust, and urban/industrial pollutants. Correlation coefficient (p) values of 0.75 or better were obtained at 50 percent of the sites with about 33 percent of the sites in the analysis reporting regression line slope values larger than 0.70 but always less than unity. The combined AERONET-OMAERUV analysis of the 44 sites yielded a p of 0.81, slope of 0.79, Y intercept of 0.10, and 65 percent OMAERUV AOD falling within the expected uncertainty range (largest of 30 percent or 0.1) at 440 nanometers. The most accurate OMAERUV retrievals are reported over northern Africa locations where the predominant aerosol type is desert dust and cloud presence is less frequent. Reliable retrievals were documented at many sites characterized by urban-type aerosols with low to moderate AOD values, concentrated in the boundary layer. These results confirm that the near-ultraviolet observations are sensitive to the entire aerosol column. A simultaneous comparison of OMAERUV, Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue, and Multiangle Imaging Spectroradiometer (MISR) AOD retrievals to AERONET measurements was also carried out to evaluate the OMAERUV accuracy in relation to those of the standard aerosol satellite products. The outcome of the comparison indicates that OMAERUV, MODIS Deep Blue, and MISR retrieval accuracies in arid and semiarid environments are statistically comparable.
aerosol optical depth↗
Dust Aerosol, Clouds, and the Atmospheric Optical Depth Record over 5 Mars Years of the Mars Exploration Rover Mission
Dust aerosol plays a fundamental role in the behavior and evolution of the Martian atmosphere. The first five Mars years of Mars Exploration Rover data provide an unprecedented record of the dust load at two sites. This record is useful for characterization of the atmosphere at the sites and as ground truth for orbital observations. Atmospheric extinction optical depths have been derived from solar images after calibration and correction for time-varying dust that has accumulated on the camera windows. The record includes local, regional, and globally extensive dust storms. Comparison with contemporaneous thermal infrared data suggests significant variation in the size of the dust aerosols, with a 1 micrometer effective radius during northern summer and a 2 micrometer effective radius at the onset of a dust lifting event. The solar longitude (L (sub s)) 20-136 degrees period is also characterized by the presence of cirriform clouds at the Opportunity site, especially near LS = 50 and 115 degrees. In addition to water ice clouds, a water ice haze may also be present, and carbon dioxide clouds may be present early in the season. Variations in dust opacity are important to the energy balance of each site, and work with seasonal variations in insolation to control dust devil frequency at the Spirit site.
Atmospheric depth↗
Climatology of the Aerosol Optical Depth by Components from the Multi-Angle Imaging Spectroradiometer (MISR) and Chemistry Transport Models
The Multi-angle Imaging Spectroradiometer (MISR) Joint Aerosol (JOINT_AS) Level 3 product has provided a global, descriptive summary of MISR Level 2 aerosol optical depth (AOD) and aerosol type information for each month over 16+ years since March 2000. Using Version 1 of JOINT_AS, which is based on the operational (Version 22) MISR Level 2 aerosol product, this study analyzes, for the first time, characteristics of observed and simulated distributions of AOD for three broad classes of aerosols: spherical nonabsorbing, spherical absorbing, and nonspherical - near or downwind of their major source regions. The statistical moments (means, standard deviations, and skew-nesses) and distributions of AOD by components derived from the JOINT_AS are compared with results from two chemistry transport models (CTMs), the Goddard Chemistry Aerosol Radiation and Transport (GOCART) and SPectral RadIatioN-TrAnSport (SPRINTARS). Overall, the AOD distributions retrieved from MISR and modeled by GOCART and SPRINTARS agree with each other in a qualitative sense. Marginal distributions of AOD for each aerosol type in both MISR and models show considerable high positive skewness, which indicates the importance of including extreme AOD events when comparing satellite retrievals with models. The MISR JOINT_AS product will greatly facilitate comparisons between satellite observations and model simulations of aerosols by type.
SPRINTARS↗
An Evaluation of MODIS-Retrieved Aerosol Optical Depth over a Mountainous AERONET Site in the Southeastern US
The literature shows that aerosol optical depth (AOD) derived from the MODIS Collection 5 (C5) dark target algorithm has been extensively validated by spatiotemporal collocation with AERONET sites on both global and regional scales.Although generally comparing well over the eastern US region, poor performance over mountains in other regions indicate the need to evaluate the MODIS product over a mountain site. This study compares MODIS C5 AOD at 550nm to AOD measured at the Appalachian State University AERONET site in Boone, NC over 30 months between August 2010 and September 2013. For the combined Aqua and Terra datasets, although more than 70% of the 500 MODIS AOD measurements agree with collocated AERONET AOD to within error envelope of +/- (0.05 + 15%), MODIS tends to have a low bias (0.02-0.03). The agreement between MODIS and AERONET AOD does not depend on MODIS quality assurance confidence (QAC) value. However, when stratified by satellite, MODIS-Terra data does not perform as well as Aqua, with especially poor correlation (r = 0.39) for low aerosol loading conditions (AERONET AOD less than 0.15).Linear regressions between Terra and AERONET possess statistically-different slopes for AOD < 0.15 and AOD > or = 0.15. AERONET AOD measured only during MODIS overpass hours is highly correlated with daily-averaged AERONET AOD. MODIS monthly-averaged AOD also tracks that of AERONET over the study period. These results indicate that MODIS is sensitive to the day-to-day variability, as well as the annual cycle of AOD over the Appalachian State AERONET site. The complex topography and high seasonality in AOD and vegetation indices allow us to specifically evaluate MODIS dark target algorithm surface albedo and aerosol model assumptions at a regionally-representative SE US mountain site.
air quality↗
Reducing Multisensor Satellite Monthly Mean Aerosol Optical Depth Uncertainty: 1. Objective Assessment of Current AERONET Locations
Various space-based sensors have been designed and corresponding algorithms developed to retrieve aerosol optical depth (AOD), the very basic aerosol optical property, yet considerable disagreement still exists across these different satellite data sets. Surface-based observations aim to provide ground truth for validating satellite data; hence, their deployment locations should preferably contain as much spatial information as possible, i.e., high spatial representativeness. Using a novel Ensemble Kalman Filter (EnKF)- based approach, we objectively evaluate the spatial representativeness of current Aerosol Robotic Network (AERONET) sites. Multisensor monthly mean AOD data sets from Moderate Resolution Imaging Spectroradiometer, Multiangle Imaging Spectroradiometer, Sea-viewing Wide Field-of-view Sensor, Ozone Monitoring Instrument, and Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar are combined into a 605-member ensemble, and AERONET data are considered as the observations to be assimilated into this ensemble using the EnKF. The assessment is made by comparing the analysis error variance (that has been constrained by ground-based measurements), with the background error variance (based on satellite data alone). Results show that the total uncertainty is reduced by approximately 27% on average and could reach above 50% over certain places. The uncertainty reduction pattern also has distinct seasonal patterns, corresponding to the spatial distribution of seasonally varying aerosol types, such as dust in the spring for Northern Hemisphere and biomass burning in the fall for Southern Hemisphere. Dust and biomass burning sites have the highest spatial representativeness, rural and oceanic sites can also represent moderate spatial information, whereas the representativeness of urban sites is relatively localized. A spatial score ranging from 1 to 3 is assigned to each AERONET site based on the uncertainty reduction, indicating its representativeness level.
aerosol optical depth↗
Refined Use of Satellite Aerosol Optical Depth Snapshots to Constrain Biomass Burning Emissions in the GOCART Model
Simulations of biomass burning (BB) emissions in global chemistry and aerosol transport models depend on external inventories, which provide location and strength of burning aerosol sources. Our previous work (Petrenko et al., 2012) shows that satellite snapshots of aerosol optical depth (AOD) near the emitted smoke plume can be used to constrain model-simulated AOD, and effectively, the assumed source strength. We now refine the satellite-snapshot method and investigate applying simple multiplicative emission correction factors for the widely used Global Fire Emission Database version 3 (GFEDv3) emission inventory can achieve regional-scale consistency between MODIS AOD snapshots and the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model. The model and satellite AOD are compared over a set of more than 900 BB cases observed by the MODIS instrument during the 2004, and 2006-2008 biomass burning seasons. The AOD comparison presented here shows that regional discrepancies between the model and satellite are diverse around the globe yet quite consistent within most ecosystems. Additional analysis of including small fire emission correction shows the complimentary nature of correcting for source strength and adding missing sources, and also indicates that in some regions other factors may be significant in explaining model-satellite discrepancies. This work sets the stage for a larger intercomparison within the Aerosol Inter-comparisons between Observations and Models (AeroCom) multi-model biomass burning experiment. We discuss here some of the other possible factors affecting the remaining discrepancies between model simulations and observations, but await comparisons with other AeroCom models to draw further conclusions.
aerosol optical depth↗