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Exploiting Dark Information Resources to Create New Value Added Services to Study Earth Science Phenomena
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Exploiting Measurement Uncertainty Estimation in Evaluation of GOES-R ABI Image Navigation Accuracy Using Image Registration Techniques
In evaluating GOES-R Advanced Baseline Imager (ABI) image navigation quality, upsampled sub-images of ABI images are translated against downsampled Landsat 8 images of localized, high contrast earth scenes to determine the translations in the East-West and North-South directions that provide maximum correlation. The native Landsat resolution is much finer than that of ABI, and Landsat navigation accuracy is much better than ABI required navigation accuracy and expected performance. Therefore, Landsat images are considered to provide ground truth for comparison with ABI images, and the translations of ABI sub-images that produce maximum correlation with Landsat localized images are interpreted as ABI navigation errors. The measured local navigation errors from registration of numerous sub-images with the Landsat images are averaged to provide a statistically reliable measurement of the overall navigation error of the ABI image. The dispersion of the local navigation errors is also of great interest, since ABI navigation requirements are specified as bounds on the 99.73rd percentile of the magnitudes of per pixel navigation errors. However, the measurement uncertainty inherent in the use of image registration techniques tends to broaden the dispersion in measured local navigation errors, masking the true navigation performance of the ABI system. We have devised a novel and simple method for estimating the magnitude of the measurement uncertainty in registration error for any pair of images of the same earth scene. We use these measurement uncertainty estimates to filter out the higher quality measurements of local navigation error for inclusion in statistics. In so doing, we substantially reduce the dispersion in measured local navigation errors, thereby better approximating the true navigation performance of the ABI system.
Phytoplankton Algorithms and Data Assimilation: Preparing a Pre-launch Path to Exploit PACE Spectral Data
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Exploiting 1064 nm Measurements to Improve CALIOP Aerosol Type Identification
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Exploiting the Convergence of Evidence in Satellite Data for Advanced Weather Index Insurance Design
The goal of drought-related weather index insurance (WII) is to protect smallholder farmers against the risk of weather shocks and to increase their agricultural productivity. Estimates of precipitation and vegetation greenness are the two dominant satellite datasets. However, ignoring additional moisture- and energy-related processes that influence the response of vegetation to rainfall leads to an incomplete representation of the hydrologic cycle. This study evaluates the added value of considering multiple independent satellite-based variables to design, calibrate, and validate weather insurance indices on the African continent. The satellite data include two rainfall datasets, soil moisture, the evaporative stress index (ESI), and vegetation greenness. We limit artificial advantages by resampling all datasets to the same spatial (0.25°) and temporal (monthly) resolution, although datasets with a higher spatial resolution might have an added value, if considered as the single source of information for localized applications. A higher correlation coefficient between the moisture-focused variables and the normalized difference vegetation index (NDVI), an indicator for vegetation vigor, provides evidence for the datasets’ capability to capture agricultural drought conditions on the ground. The Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) rainfall dataset, soil moisture, and ESI show higher correlations with the (lagged) NDVI in large parts of Africa, for different land covers and various climate zones, than the African Rainfall Climatology, version 2 (ARC2), rainfall dataset, which is often used in WII. A comparison to drought years as reported by farmers in Ethiopia, Senegal, and Zambia indicates a high “hit rate” of all satellite-derived anomalies regarding the detection of severe droughts but limitations regarding moderate drought events.
Exploiting OMI NO2 Satellite Observations to Infer Fossil-fuel CO2 Emissions from U.S. Megacities
Fossil-fuel CO2 emissions and their trends in eight U.S. megacities during 2006–2017 are inferred by combining satellite-derived NOX emissions with bottom-up city-specific NOX-to-CO2 emission ratios. A statistical model is fit to a collection NO2 plumes observed from the Ozone Monitoring Instrument (OMI), and is used to calculate top-down NOX emissions. Decreases in OMI-derived NOX emissions are observed across the eight cities from 2006 to 2017 (−17% in Miami to −58% in Los Angeles), and are generally consistent with long-term trends of bottom-up inventories (−25% in Miami to −49% in Los Angeles), but there are some interannual discrepancies. City-specific NOX-to-CO2 emission ratios, used to calculate inferred CO2, are estimated through annual bottom-up inventories of NOX and CO2 emissions disaggregated to 1 × 1 km2 resolution. Over the study period, NOX-to-CO2 emission ratios have decreased by ~40% nationwide (−24% to −51% for our studied cities), which is attributed to a faster reduction in NOX when compared to CO2 due to policy regulations and fuel type shifts. Combining top-down NOX emissions and bottom-up NOX-to-CO2 emission ratios, annual fossil-fuel CO2 emissions are derived. Inferred OMI-based top-down CO2 emissions trends vary between +7% in Dallas to −31% in Phoenix. For 2017, we report annual fossil-fuel CO2 emissions to be: Los Angeles 113 ± 49 Tg/yr; New York City 144 ± 62 Tg/yr; and Chicago 55 ± 24 Tg/yr. A study in the Los Angeles area, using independent methods, reported a 2013–2016 average CO2 emissions rate of 104 Tg/yr and 120 Tg/yr, which suggests that the CO2 emissions from our method are in good agreement with other studies' top-down estimates. We anticipate future remote sensing instruments – with better spatial and temporal resolution – will better constrain the NOX-to-CO2 ratio and reduce the uncertainty in our method.
Microwave Photoelasticity: Exploiting Multiple Resonances to Measure Stress Changes within Yttria-Partially-Stabilized-Zirconia
The NASA Glenn Research Center is developing non-destructive-testing (NDT) methods to enable the measurement of stresses embedded in optically opaque materials using microwave radiation in a free-space quasi-optical system. This methodology tracks microwave resonances observed in reflected scattering parameters extracted from materials under load. In this paper, we report the successful measurement of the stress-optic-coefficient of bulk yttria-partially stabilized zirconia (YTZP) ceramic of C = 1.42 x 10-4 ± 6.65 x 10-6 (1/GPa), across W-Band (80-100 GHz), and determined that this result is independent of sample thickness. The primary goal of this research is to establish a methodology to quantify and assess the life expectancy of ceramic thermal and environmental barrier coating (TBCs/EBCs). Bulk YTZP samples can undergo multiple resonances within a contiguous measurement bandwidth, each corresponding to an integer multiple wave number ∝. This allows for the acquisition and analysis of multiple stress measurement points within a single sample. As an additional benefit, one can approximate the refractive index of YTZP across a wide bandwidth by observing multiple resonances produced by a set of samples with varying thicknesses. Using this approach, the refractive index of bulk YTZP was found to be n = 5.80 ± 0.043 across the 85-115 GHz frequency band.
Peruvian Amazon Ecological Conservation: Assessing Land Cover Changes in the Peruvian Amazon to Identify Exploitative Agriculture Using Nasa Eo and PerúSat-1
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Peruvian Amazon Ecological Conservation: Assessing Land Cover Changes in the Peruvian Amazon to Identify Exploitative Agriculture Using NASA EO and PerúSAT-1/Pronostico Ecológico en la Amazonía Peruana: Evaluando Cambios de Cobertura en La Selva Amazónica Peruana para Identificar Explotación Agricola Utilizando Observaciones Terrestres de NASA y PerúSAT-1
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Exploiting non-linear scales in galaxy–galaxy lensing and galaxy clustering: A forecast for the dark energy survey
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Exploiting Earth Observations to Enable Groundwater Modeling in the Data-Sparse Region of Goulbi Maradi, Niger
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Broadband, highly reflective thermal protection systems, exploiting photonic additives
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Network Penetration Testing and Research
This paper will focus the on research and testing done on penetrating a network for security purposes. This research will provide the IT security office new methods of attacks across and against a company's network as well as introduce them to new platforms and software that can be used to better assist with protecting against such attacks. Throughout this paper testing and research has been done on two different Linux based operating systems, for attacking and compromising a Windows based host computer. Backtrack 5 and BlackBuntu (Linux based penetration testing operating systems) are two different "attacker'' computers that will attempt to plant viruses and or NASA USRP - Internship Final Report exploits on a host Windows 7 operating system, as well as try to retrieve information from the host. On each Linux OS (Backtrack 5 and BlackBuntu) there is penetration testing software which provides the necessary tools to create exploits that can compromise a windows system as well as other operating systems. This paper will focus on two main methods of deploying exploits 1 onto a host computer in order to retrieve information from a compromised system. One method of deployment for an exploit that was tested is known as a "social engineering" exploit. This type of method requires interaction from unsuspecting user. With this user interaction, a deployed exploit may allow a malicious user to gain access to the unsuspecting user's computer as well as the network that such computer is connected to. Due to more advance security setting and antivirus protection and detection, this method is easily identified and defended against. The second method of exploit deployment is the method mainly focused upon within this paper. This method required extensive research on the best way to compromise a security enabled protected network. Once a network has been compromised, then any and all devices connected to such network has the potential to be compromised as well. With a compromised network, computers and devices can be penetrated through deployed exploits. This paper will illustrate the research done to test ability to penetrate a network without user interaction, in order to retrieve personal information from a targeted host.