Search NASA⌕ Search

SEARCH · Search NASA

Results for “Sensor spatial resolution”

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 487 records · Page 27

Spatial structure, sampling design and scale in remotely-sensed imagery of a California savanna woodland

This article describes research related to sampling techniques for establishing linear relations between land surface parameters and remotely-sensed data. Predictive relations are estimated between percentage tree cover in a savanna environment and a normalized difference vegetation index (NDVI) derived from the Thematic Mapper sensor. Spatial autocorrelation in original measurements and regression residuals is examined using semi-variogram analysis at several spatial resolutions. Sampling schemes are then tested to examine the effects of autocorrelation on predictive linear models in cases of small sample sizes. Regression models between image and ground data are affected by the spatial resolution of analysis. Reducing the influence of spatial autocorrelation by enforcing minimum distances between samples may also improve empirical models which relate ground parameters to satellite data.

Mcgwire, K.↗

Summer Arctic ice concentrations and characteristics from SAR and SSM/I data

The extent and concentration of the Summer minima provide indirect information about the long term ability of the perennial portion of the ice pack to survive the Arctic atmosphere and ocean system. Both active and passive microwave data were used with some success for monitoring the ice cover during the Summer, but they both suffer from similar problems caused by the presence of meltponding, surface wetness, flooding, and freeze/thaw cycles associated with periodic changes in surface air temperatures. A comparative analysis of ice conditions in the Arctic region using coregistered ERS-1 SAR (Synthetic Aperture Radar) and SSM/I (Special Sensor Microwave/Imager) data was made. The analysis benefits from complementary information from the two systems, the good spatial resolution of SAR data, and the good time resolution of and global coverage by SSM/I data. The results show that in many areas ice concentrations derived from SAR data are significantly different (usually higher) than those derived from passive microwave data. Additional insights about surface conditions can be inferred depending on the nature of the discrepancies.

Comiso, Joey C.↗

Aerosol Direct Radiative Effect at the Top of the Atmosphere Over Cloud Free Ocean Derived from Four Years of MODIS Data

A four year record of MODIS spaceborne data provides a new measurement tool to assess the aerosol direct radiative effect at the top of the atmosphere. MODIS derives the aerosol optical thickness and microphysical properties from the scattered sunlight at 0.55-2.1 microns. The monthly MODIS data used here are accumulated measurements across a wide range of view and scattering angles and represent the aerosol s spectrally resolved angular properties. We use these data consistently to compute with estimated accuracy of +/-0.6W/sq m the reflected sunlight by the aerosol over global oceans in cloud free conditions. The MODIS high spatial resolution (0.5 km) allows observation of the aerosol impact between clouds that can be missed by other sensors with larger footprints. We found that over the clear-sky global ocean the aerosol reflected 5.3+/-0.6W/sq m with an average radiative efficiency of 49+/-2W/sq m per unit optical thickness. The seasonal and regional distribution of the aerosol radiative effects are discussed. The analysis adds a new measurement perspective to a climate change problem dominated so far by models.

Remer, L. A.↗

Development of an End-to-End Demonstration Readout Chain for Athena-X-IFU

The X-IFU (X-ray Integral Field Unit) of the Athena (Advanced Telescope for High-ENergy Astrophysics) telescope, scheduled for launch in the early 2030's, will provide X-ray spectroscopy data with unprecedented spectral and spatial resolution. This will be achieved by a 3 kilo-pixel array of TES (transition-edge sensor) microcalorimeters. The complete detection chain is under development by a large international collaboration. The detector array will be provided by NASA Goddard Space Flight Center, the cold TDM (time domain multiplexing) electronics by NIST, the cold amplifier by VTT, the cold focal-plane assembly by SRON, the warm front-end electronics by APC, and the DRE (digital readout electronics) by IRAP. In order to perform an end-to-end demonstration of the X-IFU readout chain, a 50 mK test bench is being developed at IRAP in collaboration with CNES. The test bench is based on a two-stage ADR cryostat from Entropy GmbH and a 1024-pixel array from Goddard associated with its cold TDM readout from NIST. The setup will initially be validated using a warm electronic chain from NIST and Goddard. We will describe the complete system being installed in the cryostat and the first results obtained with these electronics. We will also review the status of the integration of the DRE prototype in the demonstration chain and the way forward in the integration and testing of the complete X-IFU readout chain.

S Beaumont↗

Exploring rock-regolith interfaces in Jezero crater with Mars 2020 SHERLOC

The Perseverance rover successfully landed in Jezero crater, Mars in February 2021 at the Octavia E. Butler landing site and began its mission to explore and sample an ancient crater lake basin. Principal goals of the Mars 2020 mission include characterizing the geology of Mars and seeking signs of ancient microbial life via the spacecraft cameras and spectroscopic instruments onboard. The Scanning Habitable Environments with Raman and Luminescence for Organics and Chemicals (SHERLOC) instrument is a deep UV Raman spectrometer that utilizes a 248.6nm pulsed laser. Part of SHERLOC is a color camera known as the Wide Angle Topographic Sensor for Operations and eNgineering (WATSON). The SHERLOC suite provides coordinated, spectroscopic and imaging capabilities at high spatial resolution, to detect minerals and organic molecules in microtextural context. By pairing high spatial resolution (~100 μm) resonance Raman and native fluorescence spectroscopy with microscopic imaging in a novel spacecraft capability, SHERLOC enables texture-specific molecular composition measurements of rock and regolith targets on Mars. Coordinated rock-regolith observations illuminate unique insights into weathering processes and thereby to primary properties of rocks in Jezero crater. This work describes the potential of rock-regolith interfaces to preserve unique records of geological processes in Jezero crater and can powerfully supplement observations of the more general rock record on Mars. Linking observations of local rock texture with associated regolith reveals important lithologic information based on the interrelationship between differential weathering behavior and mineralogy, grain size, and cement chemistry. Preliminary observations indicate that the polygonally fractured lithotype common near the Octavia E. Butler landing site may weather by granular disintegration and/or surface creep, a relation that can be uniquely observed at the rock-regolith interface. SHERLOC -specific observations of microtextural and elemental composition transitions presented here trace rock-regolith boundaries at multiple indurated surfaces adjacent to regolith. At these locales, grain-scale based examinations suggest chemical weathering could be related to a variably distributed coating or rind on dark rock targets that may be mafic in composition. Granule deposits overlying widely distributed fine-grained material are also observable. Mineral identifications of each phase are presented, with cross-scale comparisons to the remote insights gained by the SuperCam instrument.

Emily L. Cardarelli↗

Validation of Remotely Sensed and Modeled Soil Moisture at Forested and Unforested Sites

Soil moisture is an important driver for forest ecosystems, influencing fire occurrence and extent, insect and pathogen impacts, and tree growth, which creates a need for regular, globally extensive soil moisture information that only satellite-based sensors or models can achieve. However, the reliability of soil moisture measurements in forests is not well understood due to a lack of suitable validation sites (especially relative to unforested ecosystems) and interference caused by high vegetation water content on remotely sensed measurements; although recent studies have started to address this gap [1], [2], [3], [4]. Here we validate the performance of multiyear remotely sensed (SMAP/Sentinel), remotely sensed data assimilation modelled (SMAP-L4), and modelled (NLDAS) surface and root zone (0-1 m) soil moisture datasets with data from in-situ sensors at 39 National Ecological Observatory Network (NEON) sites throughout the contiguous US. Due to differences in spatial resolution, NEON soil moisture (~0.2 km measurement zone) correlations were expected to be stronger with the SMAP/Sentinel product (3 km resolution) than with coarser resolution SMAP-L4 (9 km resolution) or NLDAS products (13 km resolution). However, given the sensitivity of satellite measurements to vegetation water content we expected a deterioration in the correlations based on remotely sensed measurements (SMAP/Sentinel and SMAP-L4) as aboveground biomass increased, whereas the model-based data (NLDAS) was expected to be largely insensitive to vegetation type. We recognize that the SMAP/Sentinel product was developed for unforested regions, therefore our application is outside its primary use case. Soil moisture is measured at up to 8 depths in five soil plots spaced up to 40 m apart at each NEON terrestrial site. Correlation parameters were calculated for the three remotely sensed and modelled data products relative to in-situ measurement following Entekhabi et al. [5]. The datasets comprised 94 (SMAP-L4), 28 (SMAP/Sentinel), and 106 (NLDAS) sites-years for surface soils and 13 (SMAP-L4) and 14 (NLDAS) site-years for the root zone. At unforested sites, the performance of the three remotely sensed and modelled data products was similar for surface soils (Table 1). For example, unbiased RMSD (ubRMSD), which SMAP uses as its primary performance metric [6], ranged from 0.05 to 0.06 m3 m-3 (Table 1), indicating the ability of all three products to track changes in soil moisture over time. The performance of the three products deteriorated at forested sites, however, while the difference in performance was modest for SMAP-L4 and NLDAS, the deterioration in SMAP/Sentinel performance was substantial. For instance, SMAP/Sentinel ubRMSD increased from 0.06 to 0.11 m3 m-3 and absolute mean difference (Abs MD; which includes measurement bias and spatial representativeness errors) increased from 0.06 to 0.16 m3 m-3, indicating both a reduction in ability to track temporal changes and absolute amounts of soil moisture in forest ecosystems. SMAP-L4 and NLDAS had lower unbiased RMSD for root zone (0-1 m) than surface soils at both forested and unforested sites (Tables 1 and 2; SMAP/Sentinel does not produce a root zone measurement). However, in most cases the correlation coefficient (r) was lower for the root zone than surface soils, suggesting the lower unbiased RMSD may be attributed to greater temporal stability of soil moisture in the root zone rather than improved data product performance. Mean difference and absolute mean difference, which encompass measurement bias and spatial representativeness errors, were greater for root zone than surface soils at unforested sites for both data products, but the opposite was generally true at forested sites. As with surface soils, there was relatively little change in the performance of SMAP-L4 and NLDAS between the unforested and forested sites. In summary, all three data products were able to adequately represent soil moisture at unforested sites, at least when aggregating across sites. However, while the performance of all three products deteriorated at forested sites, SMAP-L4 and NLDAS maintained sufficient performance to remain suitable for some use cases (ubRMSD <0.06 m3 m-3 and RMSD <0.13 m3 m-3). In contrast, the relatively poorer performance of the SMAP/Sentinel product at forested sites seems insufficient for most use cases (ubRMSD >0.1 m3 m-3 and RMSD >0.2 m3 m-3). We attribute the large reduction in the performance of the SMAP/Sentinel product in forests to its use of C-band wavelengths, which are particularly sensitive to vegetation interference, and apparently outweighed any gains provided by its higher spatial resolution. A combined SMAP/NISAR soil moisture product may provide improved performance relative to SMAP/Sentinel due to NISAR’s use of L-band wavelengths, which are less sensitive to vegetation (NISAR is scheduled for launch in early 2024).

Edward Ayres↗

A Principal-Component-Based Radiative Transfer Model (PCRTM) for Hyperspectral Shortwave and Longwave Satellite Sensors and Its Applications

The radiative transfer model (RTM) or forward model is an essential component in satellite remote sensing. For modern hyperspectral remote sensors, fast and accurate RTMs are needed due to a large number of spectral dimensions and high spatial resolutions. We will describe a Principal Component-based radiative transfer model (PCRTM) which can simulate the top-of-atmosphere (TOA) radiance or reflectance spectra 250 nm to 2000 micrometers quickly and accurately. The PCRTM has been demonstrated to be extremely accurate, compared to the line-by-line RTM benchmarks, and the former is several orders more computationally efficient than the latter. We will demonstrate how the PCRTM and the associated inversion algorithms are used to infer atmospheric temperature, moisture, and trace gas profiles, as well as cloud and surface properties from hyperspectral IR sounders such as Atomspheric Infrared Souder (AIRS) and Cross-track Infrared Sounder (CrIS). High-quality climate records for a 20-year duration have been derived from these IR hyperspectral data. Finally, we will show some examples of using PCRTM to retrieve cloud properties from Earth Surface Mineral Dust Source Investigation (EMIT) and its applicability of PCRTM to future missions such as the CLARREO (Climate Absolute Radiance and Refractivity Observatory) Pathfinder (CPF) CPF and the Surface Biology and Geology (SBG).

Xu Liu↗

On-Orbit Spatial Characterization of MODIS with ASTER Aboard the Terra Spacecraft

This letter presents a novel approach for on-orbit characterization of MODerate resolution Imaging Spectroradiometer (MODIS) band-to-band registration (BBR) using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) aboard the Terra spacecraft. The spatial resolution of ASTER spectral bands is much higher than that of MODIS, making it feasible to characterize MODIS on-orbit BBR using their simultaneous observations. The ground target selected for on-orbit MODIS BBR characterization in this letter is a water body, which is a uniform scene with high signal contrast relative to its neighbor areas. A key step of this approach is to accurately localize the measurements of each MODIS band in an ASTER measurement plane coordinate (AMPC). The ASTER measurements are first interpolated and aggregated to simulate the measurements of each MODIS band. The best measurement match between ASTER and each MODIS band is obtained when the measurement difference reaches its weighted minimum. The position of each MODIS band in the AMPC is then used to calculate the BBR. The results are compared with those derived from MODIS onboard Spectro-Radiometric Calibration Assembly. They are in good agreement, generally less than 0.1 MODIS pixel. This approach is useful for other sensors without onboard spatial characterization capability. Index Terms Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), band-to-band registration (BBR), MODerate resolution Imaging Spectroradiometer (MODIS), spatial characterization.

Xie, Yong↗

Direct experimental constraints on the spatial extent of a neutrino wavepacket

Despite their high relative abundance in our Universe, neutrinos are the least understood fundamental particles of nature. In fact, the quantum properties of neutrinos emitted in experimentally relevant sources are theoretically contested and the spatial extent of the neutrino wavepacket is only loosely constrained by reactor neutrino oscillation data with a spread of 13 orders of magnitude. Here we present a method to directly access this quantity by precisely measuring the energy width of the recoil daughter nucleus emitted in the radioactive decay of beryllium-7. The final state in the decay process contains a recoiling lithium-7 nucleus, which is entangled with an electron neutrino at creation. The lithium-7 energy spectrum is measured to high precision by directly embedding beryllium-7 radioisotopes into a high-resolution superconducting tunnel junction that is operated as a cryogenic sensor. Under this approach, we set a lower limit on the Heisenberg spatial uncertainty of the recoil daughter of 6.2 pm, which implies that the final-state system is localized at a scale more than a thousand times larger than the nucleus itself. From this measurement, the first, to our knowledge, direct lower limit on the spatial extent of a neutrino wavepacket is extracted. These results may have implications in several areas including the theoretical understanding of neutrino properties, the nature of localization in weak nuclear decays and the interpretation of neutrino physics data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Achieving precise multiparameter measurements with distributed optical fiber sensor using wavelength diversity and deep neural networks

The development of advanced distributed optical fiber sensing systems that are capable of performing accurate and spatially resolved multiparameter measurements is of great interest to a wide range of scientific and industrial applications. Here, in this paper, we propose and experimentally demonstrate a wavelength diversity based advanced distributed optical fiber sensor system to accomplish multiparameter sensing while greatly enhancing measurement accuracy. A suite of deep neural network (DNN) algorithms are developed and verified for data denoising, rapid Brillouin frequency shift estimation, and vibration data event classification. As a proof-of-concept, we demonstrate the effectiveness of the proposed advanced wavelength diversity distributed fiber sensor system assisted by DNN for simultaneous, independent measurements of static strain, temperature, and acoustic vibrations over a 25 km long sensing fiber at 3 m spatial resolution. These results suggest the potential for an intelligent multiparameter monitoring system with enhanced performance in advanced structural health monitoring applications.

47 OTHER INSTRUMENTATION↗

Intelligent Devices - Sensors and Actuators - A KSC Perspective

The primary objective of this workshop is to identify areas of advancement in sensor measurements and technologies that will help to define standard practices and procedures that will better enable the infusion into flight programs of sensors with improved capabilities but limited or no flight heritage. These standards would be crucial to demonstrating a methodology for validating current models while also creating the possibility of being able to have sufficient data to either update these models (e. g., spatial or temporal resolution, etc.) or develop new models based on the ability to simulate the new measured physical parameters. The workshop is also intended to narrow the gap between sensor measurements (and techniques), data processing techniques and the ability to make use of that data by gathering together experts in the field for a short workshop. This collaboration will unite NASA and other government agencies with contractor capabilities industry-wide to prevent duplication, spawn synergistic growth in sensor technology, help analysts make good engineering decisions and help focus new sensor maturation efforts to better meet future flight program customers' needs. This is the first such workshop designed to specifically address establishing a standardized protocol/methodology for demonstrating the technology readiness of non-flight heritage sensor systems. While other similar workshops are held covering many areas of interest to the sensor development community, no other meeting is specific enough to address this vital but often overlooked topic. By encouraging cross-fertilization of ideas from instrument experts from many different backgrounds, it is hoped that this workshop will initiate innovative new ideas and concepts in sensor development, calibration and validation. It is anticipated this workshop will repeat periodically as needed.

Mata, Carlos T.↗

Deflection Measurements of a Thermally Simulated Nuclear Core Using a High-Resolution CCD-Camera

Space fission systems under consideration for near-term missions all use compact. fast-spectrum reactor cores. Reactor dimensional change with increasing temperature, which affects neutron leakage. is the dominant source of reactivity feedback in these systems. Accurately measuring core dimensional changes during realistic non-nuclear testing is therefore necessary in predicting the system nuclear equivalent behavior. This paper discusses one key technique being evaluated for measuring such changes. The proposed technique is to use a Charged Couple Device (CCD) sensor to obtain deformation readings of electrically heated prototypic reactor core geometry. This paper introduces a technique by which a single high spatial resolution CCD camera is used to measure core deformation in Real-Time (RT). Initial system checkout results are presented along with a discussion on how additional cameras could be used to achieve a three- dimensional deformation profile of the core during test.

Stanojev, B. J.↗

IKONOS Spatial Resolution and Image Interpretability Characterization

This paper contains research from five individual projects to characterize the spatial performance of the IKONOS commercial imaging sensor. The end result of the projects is determination of the spatial image quality of IKONOS data prodicts in terms of the National Imagery Interpretability Rating Scale (NIIRS), the system Modulation Transfer Function (MTF), the system stability over the first year, the characteristics of the Space Imaging MTF Compensation (MTFC) procedure, and the application-specific capabilities of IKONOS imagery. Both panchromatic and multispectral imagery were evaluated. Major conclusions of this work are that the system was stable im imaging performance during the first year of operation, tha its MTF meets the specification for the NASA Scientific Data Purchase program, that the initial MTFC processing appears to be transposed in the in-track and the cross-track directions, that the MTFC results in a noise amplification of 2x to 4x in addition to sharpening the imagery, and that IKONOS panchromatic imagery achieves an average NIIRS rating of 4.5.

Ryan, Robert↗

Functional Flight Test Report for Positive Systems' ADAR System 5500 Sensor SN8 Linear

This report describes results of the functional flight test conducted with the Positive Systems' ADAR 5500 sensor system (serial number 8, linear configuration) near Winslow, Arizona on June 30 and July 1, 1999. The in-flight test is one component of the NASA Scientific Data Purchase (SDP) Validation and Verification (V&V) process. It allows to measure characteristics of the entire sensor system affected by both performance of the sensor during a flight and post-flight image processing. The following characteristics were analyzed: changes of dark digital numbers (DN's), radiometric linearity, signal-to-noise ratio (SNR), spatial resolution, and geolocation accuracy. The measured characteristics were compared with the image product specifications defined in the Positive Systems' SDP contract. Dependence of the dark DN's on several factors was analyzed, but no significant correlation was found. However, the observed changes in dark DN's were relatively small, which justifies usage of a constant value in the dark DN subtraction procedure during post-processing. Dependence of measured at-sensor, in-band radiance (in arbitrary units) on measured in-band ground reflectance is very well described by a linear function - The sensor fulfills the linearity requirement. Measured SNR values lower than the contract specifications, but accuracy of that test was possibly affected by non-uniformity of the employed gray-scale panels. The SNR values are generally sufficiently high for most applications. SNR can also be improved during standard flights by using longer exposure times. Full width at half maximum (FWHM) of an edge response derived line spread function was used as a measure of spatial resolution. FWHM was generally smaller than twice the ground sample distance (GSD), in agreement with the contract specifications. Accuracy of the geolocation information, which is provided for the particular images in a metadata file, was found to meet contract requirements as well.

Stanley, Tom↗

Evaluation and Validation of Case 2 Algorithms in Chesapeake Bay

The high temporal and spatial resolution of satellite ocean color observations will prove invaluable for monitoring the health of coastal ecosystems where physical and biological variability demands sampling scales beyond that possible by ship. However, ocean color remote sensing of Case 2 waters is a challenging undertaking due to the optical complexity of the water. The focus of this SIMBIOS support has been to provide in situ optical measurements form Chesapeake Bay (CB) and adjacent mid-Atlantic bight (MAB) waters for use in algorithm development and validation efforts to improve the satellite retrieval of chlorophyll (chl a) in Case 2 waters. CB provides a valuable site for validation of data from ocean color sensors for a number of reasons. First, the physical dimensions of the Bay (greater than 6,500 square kilometers) make retrievals from satellites with a spatial resolution of approximately 1 kilometer (i.e., SeaWiFS) or less (i.e., MODIS) reasonable for most of the ecosystem. Second, CB is highly influenced by freshwater flow from major rivers, making it a classic Case 2 water body with significant concentrations of chlorophyll, particulates and chromophoric dissolved organic matter (CDOM) that highly impact the shape of reflectance spectra. Finally, past and ongoing research efforts provided an expensive data set of optical observations that support the goal of this project.

Harding, Lawrence W., Jr.↗

Characterization of an architecture for front-end pixel binning in an integrating pixel array detector

Optimization of an area detector involves compromises between various parameters like frame rate, read noise, dynamic range and pixel size. We have implemented and tested a novel front-end binning design in a photon-integrating hybrid pixel array detector using the MM-PAD- 2.0 pixel architecture. In this architecture, the pixels can be optionally binned in a 2 x 2 pixel configuration using a network of switches to selectively direct the output of 4 sensor pixels to a single amplifier input. Doing this allows a trade-off between frame rate and spatial resolution. Tests show that the binned pixels perform well, but with some degradation on performance as compared to an un-binned pixel. The increased parasitic input capacitance does reduce the signal collected per x-ray as well as increases the noise of the pixel. Here, the increase in noise is, however, less than the factor of 2 increase one would observe for binning in post-processing. Spatial scans across the binned pixels show that no measured signal intensity is lost at the inner binning unit boundaries. In the high flux regime, at a 2 x 2 pixel wide beam spot (FWHM) size, binned mode responds linearly up to a photon flux of 10 7 x-rays/s, and performs comparably with un-binned mode up to a photon flux of 10 8 x-rays/s. While this study demonstrates a proof of concept for front-end binning in integrating detectors, we also identify changes to this early-stage prototype which can further improve the performance of binning pixel structures.

47 OTHER INSTRUMENTATION↗

Model Evaluation by Measurements from Collocated Remote Sensors in Complex Terrain

Model improvement efforts involve an evaluation of changes in model skill in response to changes in model physics and parameterization. When using wind measurements from various remote sensors to determine model forecast accuracy, it is important to understand the effects of measurement-uncertainty differences among the sensors resulting from differences in the methods of measurement, the vertical and temporal resolution of the measurements, and the spatial variability of these differences. Here we quantify instrument measurement variability in 80-m wind speed during WFIP2 and its impact on the calculated errors and the change in error from one model version to another. Here the model versions tested involved updates in model physics from HRRRv1 to HRRRv4, and reductions in grid interval from 3 km to 750 m. Model errors were found to be 2–3 m s –1 . Differences in errors as determined by various instruments at each site amounted to about 10% of this value, or 0.2–0.3 m s –1 . Changes in model skill due to physics or grid-resolution updates also differed depending on the instrument used to determine the errors; most of the instrument-to-instrument differences were ~0.1 m s –1 , but some reached 0.3 m s –1 . All instruments at a given site mostly showed consistency in the sign of the change in error. In two examples, though, the sign changed, illustrating a consequence of differences in measurements: errors determined using one instrument may show improvement in model skill, whereas errors determined using another instrument may indicate degradation. This possibility underscores the importance of having accurate measurements to determine the model error.

54 ENVIRONMENTAL SCIENCES↗