Search NASA⌕ Search

SEARCH · Search NASA

Results for “ground surface”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

View Angle Effects on MODIS Snow Mapping in Forests

Binary snow maps and fractional snow cover data are provided routinely from MODIS (Moderate Resolution Imaging Spectroradiometer). This paper investigates how the wide observation angles of MODIS influence the current snow mapping algorithm in forested areas. Theoretical modeling results indicate that large view zenith angles (VZA) can lead to underestimation of fractional snow cover (FSC) by reducing the amount of the ground surface that is viewable through forest canopies, and by increasing uncertainties during the gridding of MODIS data. At the end of the MODIS scan line, the total modeled error can be as much as 50% for FSC. Empirical analysis of MODIS/Terra snow products in four forest sites shows high fluctuation in FSC estimates on consecutive days. In addition, the normalized difference snow index (NDSI) values, which are the primary input to the MODIS snow mapping algorithms, decrease as VZA increases at the site level. At the pixel level, NDSI values have higher variances, and are correlated with the normalized difference vegetation index (NDVI) in snow covered forests. These findings are consistent with our modeled results, and imply that consideration of view angle effects could improve MODIS snow monitoring in forested areas.

MODIS↗
NASA NTRS2014

Intensity-Modulated Continuous-Wave Laser Absorption Spectrometer at 1.57 Micrometer for Atmospheric CO2 Measurements

Understanding the earth's carbon cycle is essential for diagnosing current and predicting future climates, which requires precise global measurements of atmospheric CO2 through space missions. The Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) space mission will provide accurate global atmospheric CO2 measurements to meet carbon science requirements. The joint team of NASA Langley Research Center and ITT Exelis, Inc. proposes to use the intensity-modulated, continuous-wave (IM-CW) laser absorption spectrometer (LAS) approach for the ASCENDS mission. Prototype LAS instruments have been developed and used to demonstrate the power, signal-to-noise ratio, precision and accuracy, spectral purity, and stability of the measurement and the instrument needed for atmospheric CO2 observations from space. The ranging capability from laser platform to ground surfaces or intermediate backscatter layers is achieved by transmitted range-encoded IM laser signals. Based on the prototype instruments and current lidar technologies, space LAS systems and their CO2 column measurements are analyzed. These studies exhibit a great potential of using IM-CW LAS system for the active space CO2 mission ASCENDS.

Lin, Bing↗
NASA NTRS2014

Intensity-Modulated Continuous-Wave Lidar at 1.57 Micrometer for Atmospheric CO2 Measurements

Understanding the earth's carbon cycle is essential for diagnosing current and predicting future climates, which requires precise global measurements of atmospheric CO2 through space missions. The Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) space mission will provide accurate global atmospheric CO2 measurements to meet carbon science requirements. The joint team of NASA Langley Research Center and ITT Exelis, Inc proposes to use the intensity-modulated, continuous-wave (IM-CW) lidar approach for the ASCENDS mission. Prototype instruments have been developed and used to demonstrate the power, signal-to-noise ratio, precision and accuracy, spectral purity, and stability of the measurement and the instrument needed for atmospheric CO2 observations from space. The ranging capability from laser platform to ground surfaces or intermediate backscatter layers is achieved by transmitted range-encoded IM laser signals. Based on the prototype instruments and current lidar technologies, space lidar systems and their CO2 column measurements are analyzed. These studies exhibit a great potential of using IM-CW lidar system for the active space CO2 mission ASCENDS.

Lin, Bing↗
NASA NTRS2014

Fine Particulate Matter Predictions Using High Resolution Aerosol Optical Depth (AOD) Retrievals

To date, spatial-temporal patterns of particulate matter (PM) within urban areas have primarily been examined using models. On the other hand, satellites extend spatial coverage but their spatial resolution is too coarse. In order to address this issue, here we report on spatial variability in PM levels derived from high 1 km resolution AOD product of Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm developed for MODIS satellite. We apply day-specific calibrations of AOD data to predict PM(sub 2.5) concentrations within the New England area of the United States. To improve the accuracy of our model, land use and meteorological variables were incorporated. We used inverse probability weighting (IPW) to account for nonrandom missingness of AOD and nested regions within days to capture spatial variation. With this approach we can control for the inherent day-to-day variability in the AOD-PM(sub 2.5) relationship, which depends on time-varying parameters such as particle optical properties, vertical and diurnal concentration profiles and ground surface reflectance among others. Out-of-sample "ten-fold" cross-validation was used to quantify the accuracy of model predictions. Our results show that the model-predicted PM(sub 2.5) mass concentrations are highly correlated with the actual observations, with out-of- sample R(sub 2) of 0.89. Furthermore, our study shows that the model captures the pollution levels along highways and many urban locations thereby extending our ability to investigate the spatial patterns of urban air quality, such as examining exposures in areas with high traffic. Our results also show high accuracy within the cities of Boston and New Haven thereby indicating that MAIAC data can be used to examine intra-urban exposure contrasts in PM(sub 2.5) levels.

aerosol optical depth↗
NASA NTRS2013

High Resolution Aerosol Data from MODIS Satellite for Urban Air Quality Studies

The Moderate Resolution Imaging Spectroradiometer (MODIS) provides daily global coverage, but the 10 km resolution of its aerosol optical depth (AOD) product is not suitable for studying spatial variability of aerosols in urban areas. Recently, a new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was developed for MODIS which provides AOD at 1 km resolution. Using MAIAC data, the relationship between MAIAC AOD and PM(sub 2.5) as measured by the 27 EPA ground monitoring stations was investigated. These results were also compared to conventional MODIS 10 km AOD retrievals (MOD04) for the same days and locations. The coefficients of determination for MOD04 and for MAIAC are R(exp 2) =0.45 and 0.50 respectively, suggested that AOD is a reasonably good proxy for PM(sub 2.5) ground concentrations. Finally, we studied the relationship between PM(sub 2.5) and AOD at the intra-urban scale (10 km) in Boston. The fine resolution results indicated spatial variability in particle concentration at a sub-10 kilometer scale. A local analysis for the Boston area showed that the AOD-PM(sub 2.5) relationship does not depend on relative humidity and air temperatures below approximately 7 C. The correlation improves for temperatures above 7 - 16 C. We found no dependence on the boundary layer height except when the former was in the range 250-500 m. Finally, we apply a mixed effects model approach to MAIAC aerosol optical depth (AOD) retrievals from MODIS to predict PM(sub 2.5) concentrations within the greater Boston area. With this approach we can control for the inherent day-to-day variability in the AOD-PM(sub 2.5) relationship, which depends on time-varying parameters such as particle optical properties, vertical and diurnal concentration profiles and ground surface reflectance. Our results show that the model-predicted PM(sub 2.5) mass concentrations are highly correlated with the actual observations (out-of-sample R(exp 2) of 0.86). Therefore, adjustment for the daily variability in the AOD-PM(sub 2.5) relationship provides a means for obtaining spatially-resolved PM(sub 2.5) concentrations.

remote sensing↗
NASA NTRS2013

Optimized Radar Remote Sensing for Levee Health Monitoring

Radar remote sensing offers great potential for high resolution monitoring of ground surface changes over large areas at one time to detect movement on and near levees and for location of seepage through levees. Our NASA-funded projects to monitor levees in the Sacramento Delta and the Mississippi River have developed and demonstrated methods to use radar remote sensing to measure quantities relevant to levee health and of great value to emergency response. The DHS-funded project will enable us is to define how to optimally monitor levees in this new way and set the stage for transition to using satellite SAR (synthetic aperture radar) imaging for better temporal and spatial coverage at lower cost to the end users.

radar remote sensing↗
NASA NTRS2015

A Particle Batch Smoother Approach to Snow Water Equivalent Estimation

This paper presents a newly proposed data assimilation method for historical snow water equivalent SWE estimation using remotely sensed fractional snow-covered area fSCA. The newly proposed approach consists of a particle batch smoother (PBS), which is compared to a previously applied Kalman-based ensemble batch smoother (EnBS) approach. The methods were applied over the 27-yr Landsat 5 record at snow pillow and snow course in situ verification sites in the American River basin in the Sierra Nevada (United States). This basin is more densely vegetated and thus more challenging for SWE estimation than the previous applications of the EnBS. Both data assimilation methods provided significant improvement over the prior (modeling only) estimates, with both able to significantly reduce prior SWE biases. The prior RMSE values at the snow pillow and snow course sites were reduced by 68%-82% and 60%-68%, respectively, when applying the data assimilation methods. This result is encouraging for a basin like the American where the moderate to high forest cover will necessarily obscure more of the snow-covered ground surface than in previously examined, less-vegetated basins. The PBS generally outperformed the EnBS: for snow pillows the PBSRMSE was approx.54%of that seen in the EnBS, while for snow courses the PBSRMSE was approx.79%of the EnBS. Sensitivity tests show relative insensitivity for both the PBS and EnBS results to ensemble size and fSCA measurement error, but a higher sensitivity for the EnBS to the mean prior precipitation input, especially in the case where significant prior biases exist.

EnBS↗
NASA NTRS2016

Light Detection and Ranging (LIDAR) From Space - Laser Altimeters

Light detection and ranging, or lidar, is like radar but atoptical wavelengths. The principle of operation and theirapplications in remote sensing are similar. Lidars havemany advantages over radars in instrument designs andapplications because of the much shorter laser wavelengthsand narrower beams. The lidar transmitters and receiveroptics are much smaller than radar antenna dishes. Thespatial resolution of lidar measurement is much finer thanthat of radar because of the much smaller footprint size onground. Lidar measurements usually give a better temporalresolution because the laser pulses can be much narrowerthan radio frequency (RF) signals. The major limitation oflidar is the ability to penetrate clouds and ground surfaces.

Sun, Xiaoli↗
NASA NTRS2021

A Machine Learning Approach to Objective Identification of Dust in Satellite Imagery

Airborne dust has broad adverse effects on human activity, including aviation, human health, and agriculture. Remote sensing observations are used to detect dust and aerosols in the atmosphere using long established techniques. False color Red-Green-Blue (RGB) imagery using band differences sensitive to dust absorption (Dust RGB) is currently used operationally to assist forecasters and decision-makers in identifying dust at night, but there are still limitations, subjectivity, and nuances to image interpretation making night-time dust identification difficult even for experts. This study applies machine learning to the problem of night-time dust detection with a simple random forest (RF) model using Geostationary Operational Environmental Satellite-16 (GOES-16) Advanced Baseline Imager (ABI) infrared imagery, band differences sensitive to dust absorption, and Dust RGB color components as inputs to the model. The RF model achieves an Area-Under-Curve (AUC) of 0.97 with a standard deviation of 0.04 for dust cases. For images with dust present, the model correctly labels 85% of dust pixels and 99.96% of no-dust pixels for all dust images in the validation data set. The addition of a single null case to the training data set drastically reduces error in labeling no-dust pixels as dust from 45% to 14.5%. Application of the machine learning model to the April 13–14, 2019 dust event demonstrates the ability of the model to identify dust during night-time hours when visual dust detection is limited by the cooling ground surface characteristics.

dust↗
NASA NTRS2021

Storm Surge and Ponding Explain Mangrove Dieback in Southwest Florida Following Hurricane Irma

Mangroves buffer inland ecosystems from hurricane winds and storm surge. However, their ability to withstand harsh cyclone conditions depends on plant resilience traits and geomorphology. Using airborne lidar and satellite imagery collected before and after Hurricane Irma, we estimated that 62% of mangroves in southwest Florida suffered canopy damage, with largest impacts in tall forests (>10 m). Mangroves on well-drained sites (83%) resprouted new leaves within one year after the storm. By contrast, in poorly-drained inland sites, we detected one of the largest mangrove diebacks on record (10,760 ha), triggered by Irma. We found evidence that the combination of low elevation (median = 9.4 cm asl), storm surge water levels (>1.4 m above the ground surface), and hydrologic isolation drove coastal forest vulnerability and were independent of tree height or wind exposure. Our results indicated that storm surge and ponding caused dieback, not wind. Tidal restoration and hydrologic management in these vulnerable, low-lying coastal areas can reduce mangrove mortality and improve resilience to future cyclones.

David Lagomasino↗
NASA NTRS2022

General Services Administration Reclamation Yard, SWMU 010, 2021 Groundwater Monitoring Report

This report presents a summary of the groundwater monitoring activities that occurred in November and December 2021 at General Services Administration Reclamation Yard, Solid Waste Management Unit 010, located at the John F. Kennedy Space Center (KSC), Florida. The site is monitored under KSC’s Resource Conservation and Recovery Act Corrective Action Program. This approach also meets the requirements of Chapter 62-780, Florida Administrative Code. For the purposes of this report, two separate plumes, known as the Polychlorinated Biphenyl (PCB)/Volatile Organic Aromatic (VOA) Plume and the Chlorinated Volatile Organic Compound (VOC) Plume, were identified for this site. The contaminants of concern (COCs) for the PCB/VOA Plume consists of PCBs, 1,2,4-trichlorobenzene, and breakdown products of 1,2,4-trichlorobenzene. The COCs for the Chlorinated VOC Plume are tetrachloroethene, trichloroethene, cis-1,2-dichloroethene, and vinyl chloride. The activities presented in this report include two field events: (1) November 2021 – PCB/VOA Plume groundwater sampling via Direct Push Technology – 70 groundwater samples were collected from 10 locations at varying intervals; and (2) December 2021 – Site-wide semi-annual water level measurements of 54 monitoring wells, redevelopment of 5 monitoring wells, and sampling of 35 monitoring wells. Results for the PCB/VOA plume demonstrated COCs have not rebounded since the 2018 source removal, with groundwater cleanup target levels (GCTLs) exceeded in the 10-30 ft. below ground surface interval only. In the Chlorinated VOC plume area, there were no detections of COCs above a GCTL for at least the second consecutive sampling event for the sampled wells. Cleanup objectives have been met, and it is recommended that VOC monitoring be discontinued. Underground injection control parameters will continue to be monitored in three wells until those analytes return to background concentrations.

GSA Reclamation Yard↗
NASA NTRSDate not supplied

Dust Machine Learning Probability and Assessment

- NASA SPoRT introduced the "Dust RGB" via NASA satellites to demonstrate GOES-R ABI capabilities and then evaluated the impact in operations (Fuell et al. 2016) - The Dust RGB allows for continued dust detection at night, but the cooling ground surface limits the effectiveness as night progresses. - SPoRT has developed a 'Machine Learning' (ML) model using a physically-based approach which can correctly label 85% of dust pixels and 99% of no-dust pixels

Dust↗
NASA NTRS2023

Contractor Support Building #7 Per- and Polyfluoroalkyl Substances (PFAS) Site Assessment Work Plan

This Work Plan documents the proposed field sampling activities for a per- and polyfluoroalkyl substances (PFAS) Site Assessment at the Contractor Support Building (CSB) #7 at Kennedy Space Center (KSC). The Work Plan provides a background of the historical activities that occurred at CSB #7, and the limited environmental investigations performed at CSB #7. The proposed Site Assessment activities at CSB #7 include the advancement of a soil lithologic boring to 60 feet below ground surface, the installation of a staff gauge in site surface water, perform direct push groundwater sampling at eight locations, and collect four surface water samples. Sampling details, depths, and locations are presented in the Work Plan. The Work Plan was presented to the KSC Remediation Team in the form of an Advance Data Package in February 2023. Following STRIVES approval, the CSB #7 PFAS Site Assessment Work Plan will be formally submitted to the Florida Department of Environmental Protection.

Howard Franklin Fowler↗
NASA NTRS2023

Former SLF Fire and Rescue Building SWMU #120 Per- and Polyfluoroalkyl Substances (PFAS) Site Assessment Work Plan

This Work Plan documents the proposed field sampling activities for a per- and polyfluoroalkyl substances (PFAS) Site Assessment at the Former Space Shuttle Landing Facility (SLF) Fire and Rescue Building (FRB) at Kennedy Space Center (KSC). The Work Plan provides a background of the historical activities that occurred at the SLF FRB, and the limited environmental investigations performed at the SLF FRB. The proposed Site Assessment activities at SLF FRB includes the collection of soil samples from eight locations, the advancement of a soil lithologic boring to 60 feet below ground surface, the installation of a staff gauge in site surface water, the installation of four monitoring wells, perform direct push groundwater sampling at seven locations, and collect one surface water sample. Sampling details, depths, and locations are presented in the Work Plan. The Work Plan was presented to the KSC Remediation Team in the form of an Advance Data Package in February 2023. Following STRIVES approval, the SLF FRB PFAS Site Assessment Work Plan will be formally submitted to the Florida Department of Environmental Protection.

Howard Franklin Fowler↗
NASA NTRSDate not supplied

The ARADS Project as an Astrobiological Survey Mission Prototype

An astrobiological survey prior to human arrival will be important for preservation of signs of any existing or past evidence of Martian life, to reduce the risk of unintentional forward contamination of Martian environments in which terrestrial microbes might be able to gain a foothold (e.g., [1]), and to potentially protect the health of any human crews and enable their safe return to Earth. Evaluating for the presence of life and biosignatures may become a critical-path Mars exploration precursor in the not-so-far future, circa 2030-35. The near-subsurface, with its potential combination of volatiles, vapor exchange with the surface, and shelter from surface radiation, will be a primary initial target for in-situ astrobiological investigation. Sample acquisition, drilling and sample handling are key elements of robotic missions that target the subsurface [2], as well as near-surface ground ice deposits. In the mid 2000s, the Mars Astrobiology Field Laboratory (AFL) was proposed as a follow-on mission concept to the Mars Science Laboratory (MSL)/Curiosity rover mission [3]. The AFL would have included precision drilling to 2m, automated sample handling and remote processing of cores. However, the AFL concept needed further development and maturation. The Atacama Rover Astrobiology Drilling Studies (ARADS) project concept [4] was in part AFL-inspired. The 2014 ARADS concept included a medium sized rover, with habitability instruments, including the Phoenix Wet Chemistry Laboratory (WCL) [5], and an enhanced version of the ExoMars Mars Organic Molecule Analyzer (MOMA) Laser Desorption-Linear Ion Trap Mass Spectrometer (LITMS) [6]. ARADS likewise included two biosignature detection instruments -- the Signs of Life Detector (SOLID) immunoassay instrument [7,8] and the Chemical Laptop-derived [9] Planetary In-Situ Capillary Electrophoresis System (PISCES), while mitigating Planetary Protection-relevant contamination issues [10]. ARADS project objectives were to demonstrate the potential science return for such a mission in the context of the search for evidence of life, and technically to demonstrate the feasibility of roving with drilling missions to Mars. ARADS technology goals targeted analog-site demonstrations of automated drilling and sampling, integrated with its mobile habitability and biosignature detection instruments. And ARADS science operations goals developed remote science, contamination mitigation, and communications methods to enable simulating AFL-like science operations with time delays, directed by a remote science team[11]. Five subsequent Mars analog site field demonstrations (in Chile’s hyperarid Atacama Desert, 2016-19) provided a step-by-step development pathway for the ARADS platform’s science capabilities and systems integration, culminating in an integrated remote roving mission simulation in the final ARADS year (2019).

biosignatures↗
NASA NTRS1991

ULF magnetic signatures at the earth surface due to ground water flow - A possible precursor to earthquakes

Magnetic field fluctuations at the earth's surface at less than 1 Hz are shown to result from motion with a peak velocity of about 4 cm/s of ground water (about 4 S/m) at about 5 km depth. Surface field changes can occur due to either divergence free fluid motion with transverse spatial wavelengths of a few tens of km, and/or homogeneous flow which displaces local inhomogeneities in the earth magnetic field.

Draganov, A. B.↗
NASA NTRS1986

Evaluation of a surface/vegetation parameterization using satellite measurements of surface temperature

Ground measurements of surface-sensible heat flux and soil moisture for a wheat-growing area of Beauce in France were compared with the values derived by inverting two boundary layer models with a surface/vegetation formulation using surface temperature measurements made from NOAA-AVHRR. The results indicated that the trends in the surface heat fluxes and soil moisture observed during the 5 days of the field experiment were effectively captured by the inversion method using the remotely measured radiative temperatures and either of the two boundary layer methods, both of which contain nearly identical vegetation parameterizations described by Taconet et al. (1986). The sensitivity of the results to errors in the initial sounding values or measured surface temperature was tested by varying the initial sounding temperature, dewpoint, and wind speed and the measured surface temperature by amounts corresponding to typical measurement error. In general, the vegetation component was more sensitive to error than the bare soil model.

Taconet, O.↗
NASA NTRS1989

A composite study of Florida thunderstorms, using radar, cloud-to-ground lightning, and surface winds

Two thunderstorms occurring in Florida during the summer of 1987 are studied in order to determine the location of cloud-to-ground (CG) lightning in terms of surface winds and radar reflectivity. Composites of radar, CG lightning locations, and surface winds during the development, mature, and dissipation stages of the storms are presented and analyzed. The relationship between lightning and radar reflectivity is examined. It is noted that the main CG lightning activity region is on the upshear side of the storm in the reflectivity gradient where upward motion is between the convergent gust front and reflectivity center, and lightning avoids areas of maximum reflectivity.

Watson, Andrew I.↗