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At least 325 records · Page 18

Airborne spectral Measurements of Surface-Atmosphere Anisotropy for Several Surfaces and Ecosystem over Southern Africa

The Cloud Absorption Radiometer (CAR) was flown aboard the University of Washington Convair CV-580 research aircraft and took measurements on 23 flights between August 15 and September 16. On 12 of those flights, BRF measurements were obtained over different natural surfaces and ecosystem in southern Africa. The BRF measurements were done to characterize surface anisotropy in support of SAFARI 2000 science objectives principally to validate products from NASA's EOS satellites, and to parameterize and validate BRF models. In this paper we present results of BRFs taken over two EOS validation sites: Skukuza tower, South Africa (25.0 deg S, 31.5 deg E) and Mongu tower, Zambia (15.4 deg S, 23.3 deg E). Additional sites are also considered and include, Maun tower, Botswana (20.0 deg S, 23.5 deg E), Sowa Pan, Botswana (20.6 deg S, 26.2 deg E) and Etosha Pan, Namibia (19.0 deg S, 16.0 deg E). The CAR is capable of measuring scattered light in fourteen spectral bands. The scan mirror, rotating at 100 rpm, directs the light into a Dall-Kirkham telescope where the beam is split into nine paths. Eight light beams pass through beam splitters, dichroics, and lenses to individual detectors (0.34-1.27 micrometers), and finally are registered by eight data channels. They are sampled simultaneously and continuously. The ninth beam passes through a spinning filter wheel to an InSb detector cooled by a Stirling cycle cooler. Signals registered by the ninth data channel are selected from among six spectral channels (1.55-2.30 micrometers). The filter wheel can either cycle through all six spectral bands at a prescribed interval (usually changing filter every fifth scan line), or lock onto any one of the six spectral bands and sample it continuously. To measure the BRF of the surface-atmosphere system, the University of Washington CV-580 had to bank at a comfortable roll angle of approximately 20 degrees and fly in a circle about 3 km in diameter above the surface for roughly two minutes. Replicated observations (multiple circular orbits) were acquired over selected surfaces so that average BRF smooth out small-scale surface and atmospheric inhomogeneities. At an altitude of 600 m above the targeted surface area and with a 1 deg IFOV, the pixel resolution is about 10 m at nadir and about 270 m at an 80 deg viewing angle from the CAR.

Gatebe, Charles K.↗

Airborne Spectral Measurements of Ocean Anisotropy during CLAMS

The Cloud Absorption Radiometer (CAR) aboard the University of Washington Convair CV-580 research aircraft obtained bidirectional reflectance-distribution function (BRDF) of Atlantic Ocean and Dismal Swamp between July 10 and August 2, 2001. The BRDF measurements (15 in total, 8 uncontaminated by clouds) obtained under a variety of sun angles and wind conditions, will be used to characterize ocean anisotropy in support of Chesapeake Lighthouse and Aircraft Measurements for Satellites (CLAMS) science objectives principally to validate products from NASA's EOS satellites, and to parameterize and validate BRDF models of the ocean. In this paper we present results of BRDF of the Ocean under different sun angles and wind conditions. The CAR is capable of measuring scattered light in fourteen spectral bands. The scan mirror, rotating at 100 rpm, directs the light into a Dall-Kirkham telescope where the beam is split into nine paths. Eight light beams pass through beam splitters, dichroics, and lenses to individual detectors (0.34-1.27 micron), and finally are registered by eight data channels. They are sampled simultaneously and continuously. The ninth beam passes through a spinning filter wheel to an InSb detector cooled by a Stirling cycle cooler. Signals registered by the ninth data channel are selected from among six spectral channels (1.55-2.30 micron). The filter wheel can either cycle through all six spectral bands at a prescribed interval (usually changing filter every fifth scan line), or lock onto any one of the six spectral bands and sample it continuously. To measure the BRF of the surface-atmosphere system, the University of Washington CV-580 had to fly in a circle about 3 km in diameter above the surface for roughly two minutes. Replicated observations (multiple circular orbits) were acquired over selected surfaces so that average BRF smooth out small-scale surface and atmospheric inhomogeneities. At an altitude of 600 m above the targeted surface area and with a 1 degree IFOV, the pixel resolution is about 10 m at nadir and about 270 m at an 80 deg. viewing angle from the CAR.

Gatebe, C. K.↗

Software for Use with Optoelectronic Measuring Tool

A computer program has been written to facilitate and accelerate the process of measurement by use of the apparatus described in "Optoelectronic Tool Adds Scale Marks to Photographic Images" (KSC-12201). The tool contains four laser diodes that generate parallel beams of light spaced apart at a known distance. The beams of light are used to project bright spots that serve as scale marks that become incorporated into photographic images (including film and electronic images). The sizes of objects depicted in the images can readily be measured by reference to the scale marks. The computer program is applicable to a scene that contains the laser spots and that has been imaged in a square pixel format that can be imported into a graphical user interface (GUI) generated by the program. It is assumed that the laser spots and the distance(s) to be measured all lie in the same plane and that the plane is perpendicular to the line of sight of the camera used to record the image

Ballard, Kim C.↗

150 Shades of Green: Using the Full Spectrum of Remote Sensing Reflectance to Elucidate Color Shifts in the Ocean

This article proposes a simple and intuitive classification system by which to define full spectral remote sensing reflectance (Rrs(λ)) data with a quantitative output that enables a more manageable handling of spectral information for aquatic science applications. The weighted harmonic mean of the Rrs(λ) wavelengths outputs an Apparent Visible Wavelength (in units of nanometers), representing a one-dimensional geophysical metric of color that is inherently correlated to spectral shape. This dimensionality reduction of spectral information combined with the output along a continuum of wavelength values offers a robust and user-friendly means to describe and analyze spectral Rrs(λ) in terms of spatial and temporal trends and variability. The uncertainty in the algorithm's estimation of spectral shape is demonstrated on a global scale, in addition to the utility of the algorithm to discern spectral-spatial-temporal trends in the ocean, on a per-pixel basis for the entire 22 year continuous ocean color (SeaWiFS and MODIS-Aqua) time-series. This technique can be applied to datasets of varying multi- and hyper-spectral resolutions, providing continuity between heritage and future satellite sensors, and further enabling an effective means of elucidating similarities or differences in complex spectral signatures within the constraints of two dimensions. This straightforward means of conceptualizing multi-dimensional variability can help maximize the potential of the spectral information embedded in remote sensing data.

ocean color↗

Pixel Based Model for High Latitude Dust Detection

High Latitude Dust (HLD, ≥ 50°𝑁 𝑎𝑛𝑑 ≥ 40°𝑆 ) load has implications on the energy budget, ocean biodiversity and economy on a regional and global scale. Current methods of dust detection rely on spectral sensitivity at visible (RGB) and infrared wavelengths. The characteristics of HLD vary according to the sediments and sedimentary processes operating on the land surface that are the source of the dust particles. Leveraging machine learning (ML) methods, we propose a new detection method based on convolutional neural network (CNN) using true color images.

Priftis, Georgios↗

GEONEX: Progressive Conditional Generative Adversarial Training Using Transfer learning

Obtaining accurate segmentation on large scale images is an open problem in deep learning. The main problem is the amount of labeled data that exists for large scale images. Traditionally, the common solution to this problem is to crop the large images into smaller images to increase the amount of available data and train a Conditional Generative Adversarial Network (CGAN). CGANs are currently the state of the art in image to image translation and provide better accuracy than the traditional method of training a encoder based conv-net architecture to minimize the loss at each pixel. This method can produce noisy and discontinuous images with inaccurate results. We seek to solve this problem by utilizing the concepts of transfer learning and progressive training to create a CGAN that can segment large scale images with a limited amount of labeled data. In transfer learning we recognize that many learned features are applicable to many classes from multiple domains. This introduces the concept of feature reusability, which is the basis for finetuning. Progressive training got its start in training models on the same images at different resolutions. In this work we instead train a GAN on increasing image scales by transferring the weights from the smaller scales to the larger scales. The learned features at the smaller scales are continually reused and applied to larger scales to create a CGAN that can perform accurate segmentation on large scale images. We apply this method to detect building footprints on very high-resolution overhead imagery (e.g Digital Globe and high resolution airborne platforms).

GEONEX↗

Measurement of Dynamic Geologic Processes at Subpixel Scales

Methods have recently been developed for the utilization of remotely sensed image data in the measurement of terrain displacements resulting from geologic processes. In optical imagery, measurements precise to a fraction of a pixel are achieved by statistical image matching.

optical imagery interferometry terrain displacemen↗

Evaluation of Thematic Mapper Performance as Applied to Hydrocarbon Exploration

The role data from the first three LANDSAT satellites have in geologic exploration and their current level of acceptance is reviewed and the advantages of LANDSAT 4 TM data over MSS data are discussed. Specially enhanced Thematic Mapper imager can make a very significant contribution to the oil and gas and mineral exploration industries. The TM's increased spatial resolution enables the production of larger scale imagery, which greatly increases the amount of geomorphic and structural information interpretable. TM's greater spectral resolution, combined with the smaller, more homogeneous pixels, should enable a far greater confidence in mapping lithologies and detecting geobotanical anomalies from space. The results from its applications to hydrocarbon and mineral exploration promise to bring the majority of the geologic exploration community into that final stage of acceptance and routine application of the satellite data.

Everett, J. R.↗

Satellite mapping of Nile Delta coastal changes

Multitemporal, multispectral scanner (MSS) landsat data have been used to monitor erosion and sedimentation along the Rosetta Promontory of the Nile Delta. These processes have accelerated significantly since the completion of the Aswan High Dam in 1964. Digital differencing of four MSS data sets, using standard algorithms, show that changes observed over a single year period generally occur as strings of single mixed pixels along the coast. Therefore, these can only be used qualitatively to indicate areas where changes occur. Areas of change recorded over a multi-year period are generally larger and thus identified by clusters of pixels; this reduces errors introduced by mixed pixels. Satellites provide a synoptic perspective utilizing data acquired at frequent time intervals. This permits multiple year monitoring of delta evolution on a regional scale.

Blodget, H. W.↗

A Novel Method for Estimating Shortwave Direct Radiative Effect of Above-Cloud Aerosols Using CALIOP and MODIS Data

This paper describes an efficient and unique method for computing the shortwave direct radiative effect (DRE) of aerosol residing above low-level liquid-phase clouds using CALIOP and MODIS data. It addresses the overlap of aerosol and cloud rigorously by utilizing the joint histogram of cloud optical depth and cloud top pressure while also accounting for subgrid-scale variations of aerosols. The method is computationally efficient because of its use of grid-level cloud and aerosol statistics, instead of pixel-level products, and a pre-computed look-up table based on radiative transfer calculations. We verify that for smoke over the southeast Atlantic Ocean the method yields a seasonal mean instantaneous (approximately 1:30PM local time) shortwave DRE of above cloud aerosol (ACA) that generally agrees with more rigorous pixel-level computation within 4 percent. We also estimate the impact of potential CALIOP aerosol optical depth (AOD) retrieval bias of ACA on DRE. We find that the regional and seasonal mean instantaneous DRE of ACA over southeast Atlantic Ocean would increase, from the original value of 6.4 W m(-2) based on operational CALIOP AOD to 9.6 W m(-2) if CALIOP AOD retrieval are biased low by a factor of 1.5 (Meyer et al., 2013) and further to 30.9 W m(-2) if CALIOP AOD retrieval are biased low by a factor of 5 as suggested in (Jethva et al., 2014). In contrast, the instantaneous ACA radiative forcing efficiency (RFE) remains relatively invariant in all cases at about 53 W m(-2) AOD(-1), suggesting a near linear relation between the instantaneous RFE and AOD. We also compute the annual mean instantaneous shortwave DRE of light-absorbing aerosols (i.e., smoke and polluted dust) over global oceans based on 4 years of CALIOP and MODIS data. We find that the variability of the annual mean shortwave DRE of above-cloud light-absorbing aerosol is mainly driven by the optical depth of the underlying clouds. While we demonstrate our method using CALIOP and MODIS data, it can also be extended to other satellite data sets, as well as climate model outputs.

CALIOP and MODIS↗

Image-Based Failure Assessment of Li-Ion Batteries

In energy storage materials, strong electrochemical-mechanical coupling and highly anisotropic material properties contribute to the formation and propagation of micro-cracking during charge/discharge cycling, resulting in reduced performance and service life. In this work, a digital twin is created to investigate the performance of a heterogeneous Li-ion battery cathode and simulate degradation accumulation. Pixel-based model construction is used to represent the complex material geometries from microstructural images supplied by the National Renewable Energy Laboratory (NREL). Because of the expected large deformation and crack opening, the reproducing kernel particle method (RKPM), a meshfree method with discretization at the image pixels, is used to approximate the field variables: electrostatic potential, concentration, and displacement. An interface modified reproducing kernel (IM-RK) is constructed by scaling a smooth kernel function with an interface-distance function to achieve strategic discontinuity types (i.e. weak discontinuities for strain discontinuities and strong discontinuities for cracks) and alleviate Gibbs oscillations near these transition zones. Applications to the heterogeneous microstructures of Li-ion battery cathodes will be presented to demonstrate the effectiveness of the proposed methods. IM-RK is additionally used to inform how crack evolution in turn affects the coupled electro-chemo-mechanical behavior of the Li-ion battery cathode.

image-based modeling↗

Diurnal and Seasonal Cold Lands Signatures in SSM/I-scale Microwave Radiometry of the North Slope of Alaska

In this paper, we explore scaling and data assimilation-related issues associated with utilizing passive microwave satellite observations of Cold Lands-in this case, the climatologically and ecologically sensitive arctic tundra. Our approach expands on our earlier work using a one-year dataset from the Radiobrightness Energy Balance Experiment-3 (REBEX-3). REBEX-3 featured a tower-based SSM/I (Special Sensor Microwave/Imager) simulator deployed on the North Slope of Alaska in 1994-95. Two findings are significant here. First, a comparison of tower and satellite signatures at 19 and 37 GHz strongly suggested that the North Slope is radiometrically homogeneous for spatial scales up to SSM/I footprints (approximately 25 km), an unusual and valuable characteristic for monitoring and retrieving land surface conditions. And second, at the plot scale, signatures of snow/no-snow and freeze/thaw transitions were identifiable for tussock tundra land cover, so that even snow-free frozen tundra could be unambiguously distinguished from tundra covered with dry snow, another unusual and valuable characteristic. We present results from analyzing satellite brightness signatures of selected North Slope pixels corresponding to instrumented sites along a transect from the Brooks Range to the Arctic Ocean. A custom EASE (Equal Area Scalable Earth)-Grid processor was used to extract SSMJI data for every orbit with observations of this region during the 1994-95 year. The resulting high temporal-resolution (4-8 points/day), gridded data were then analyzed for evidence of the same diurnal and seasonal signatures seen at the plot scale (through micrometeorological and/or brightness data). Differences between satellite and tower brightness observations are quantified for various conditions at the REBEX-3 site. Such differences from the less-frequent and/or larger-scale satellite observations represent a form of input 'noise' in data assimilation applications. For the other sites, the performance of snow/no-snow and freeze/thaw discriminators vs. ground truth represents an opportunity to gauge the homogeneity of other pixels.

Kim, Edward J.↗

A New Measurement of the Bulk Flow of X-Ray Luminous Clusters of Galaxies

We present new measurements of the large-scale bulk flows of galaxy clusters based on five-year WMAP data and a significantly expanded X-ray cluster catalog. Our method probes the flow via measurements of the kinematic Sunyaev-Zel'dovich (SZ) effect produced by the hot gas in moving clusters. It computes the dipole in the cosmic microwave background data at cluster pixels, which preserves the SZ component while integrating down other contributions. Our improved catalog of over 1000 clusters enables us to further investigate possible systematic effects and, thanks to a higher median cluster redshift, allows us to measure the bulk flow to larger scales. We present a corrected error treatment and demonstrate that the more X-ray luminous clusters, while fewer in number, have much larger optical depth, resulting in a higher dipole and thus a more accurate flow measurement. This results in the observed correlation of the dipole derived at the aperture of zero monopole with the monopole measured over the cluster central regions. This correlation is expected if the dipole is produced by the SZ effect and cannot be caused by unidentified systematics (or primary cosmic microwave background anisotropies). We measure that the flow is consistent with approximately constant velocity out to at least [similar, equals]800 Mpc. The significance of the measured signal peaks around 500 h -1 70 Mpc, most likely because the contribution from more distant clusters becomes progressively more diluted by the WMAP beam. However, at present, we cannot rule out that these more distant clusters simply contribute less to the overall motion.

Kashlinsky, A.↗

Geometric accuracy of LANDSAT-4 MSS image data

Analyses of the LANDSAT-4 MSS image data of North Georgia provided by the EDC in CCT-p formats reveal that errors of approximately + or - 30 m in the raw data can be reduced to about + or - 55 m based on rectification procedures involving the use of 20 to 30 well-distributed GCPs and 2nd or 3rd degree polynomial equations. Higher order polynomials do not appear to improve the rectification accuracy. A subscene area of 256 x 256 pixels was rectified with a 1st degree polynomial to yield an RMSE sub xy value of + or - 40 m, indicating that USGS 1:24,000 scale quadrangle-sized areas of LANDSAT-4 data can be fitted to a map base with relatively few control points and simple equations. The errors in the rectification process are caused by the spatial resolution of the MSS data, by errors in the maps and GCP digitizing process, and by displacements caused by terrain relief. Overall, due to the improved pointing and attitude control of the spacecraft, the geometric quality of the LANDSAT-4 MSS data appears much improved over that of LANDSATS -1, -2 and -3.

Welch, R.↗

Geometric Accuracy of LANDSAT-4 MSS Image Data

Analyses of the LANDSAT-4 MSS image data of North Georgia provided by the EDC in CTT-p formats reveal that errors of approximately + or - 30 m in the raw data can be reduced to about + or - 55 m based on rectification procedures involving the use of 20 to 30 well-distributed GCPs and 2nd or 3rd degree polynomial equations. Higher order polynomials do not appear to improve the rectification accuracy. A subscene area of 256 by 256 pixels was rectified with a 1st degree polynomial to yield an RMSE sub xy value of + or - 40 m, indicating that USGS 1:24,000 scale quadrangle-sized areas of LANDSAT-4 data can be fitted to a map base with relatively few control points and simple equations. The errors in the rectification process are caused by the spatial resolution of the MSS data, by errors in the maps and GCP digitizing process, and by displacements caused by terrain relief. Overall, due to the improved pointing and attitude control of the spacecraft, the geometric quality of the LANDSAT-4 MSS data appears much improved over that of LANDSAT-1, -2 AND -3.

Welch, R.↗

Utilization of spaceborne SAR data for mapping

Recent developments in automated processing of digital SEASAT SAR imagery have made feasible the generation of large-scale high-resolution maps. Standard preprocessing of raw data into digital images results in geometrically distorted imagery. Computer algorithms have been developed for unsupervised pixel location, geometric rectification, and mosaicking of multiple-image frames without ground control points. These algorithms utilize knowledge of the spacecraft trajectory data, the imaging geometry, and the coherent properties of the sensor to generate the required processing parameters. This paper discusses the advantages as well as the inherent limitations of this technique, analyzes the associated errors, and presents results using SEASAT SAR imagery. Also discussed are the results of the recent shuttle imaging radar (SIR-A) experiment as well as a follow-on experiment (SIR-B) planned for 1984.

Curlander, J. C.↗

Surface-material maps of Viking landing sites on Mars

Researchers mapped the surface materials at the Viking landing sites on Mars to gain a better understanding of the materials and rock populations at the sites and to provide information for future exploration. The maps extent to about 9 m in front of each lander and are about 15 m wide - an area comparable to the area of a pixel in high resolution Viking Orbiter images. The maps are divided into the near and far fields. Data for the near fields are from 1/10 scale maps, umpublished maps, and lander images. Data for the far fields are from 1/20 scale contour maps, contoured lander camera mosaics, and lander images. Rocks are located on these maps using stereometric measurements and the contour maps. Frequency size distribution of rocks and the responses of soil-like materials to erosion by engine exhausts during landings are discussed.

Moore, H. J.↗

FIFI: The MPE Garching/UC Berkeley Far-Infrared Imaging Fabry-Perot Interferometer

We describe the performance characteristics of the MPE Garching/UC Berkeley Far-Infrared Imaging Fabry-Perot Interferometer (FIFI) for the Kuiper Airborne Observatory (KAO). The spectrometer features two or three cryogenic tunable Fabry-Perot filters in series giving spectral resolution R of up to 10(exp 5) in the range of 40 microns less than lambda less than 200 microns, and an imaging 5x5 array of photoconductive detectors with variable focal plane plate scale. The instrument works at background limited sensitivity of up to 2 x 10(exp -19) W cm(exp -2) Hz(exp -1/2) per pixel per resolution element at R = 10(exp 5) on the KAO.

Geis, Norbert↗