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Homomorphic deconvolution signal processing enhances information obtained in high-resolution soil-depth measurements by radar. Proposed technique is expected to increase accuracy with which soil-layer depths are gaged. Intended use with subsurface-interface radar sounding, in which subsurface features of soils are mapped.
The 'Osher' scheme was introduced by Osher (1981). It represents an upwind finite-difference method for hyperbolic systems of conservation laws, including the Euler equations. In studies conducted by Osher (1981) and Osher and Solomon (1982), the method was applied to the nonisentropic form of the Euler equations in one dimension and the isentropically restricted form in two spatial dimensions, both in Cartesian coordinates. Chakravarthy and Osher (1982) have shown an approach for extending the Osher scheme to the Euler equations written for general geometries, taking into account the use of mappings to arbitrary curvilinear coordinate systems. The present investigation is concerned with the high resolution extension of the Osher scheme to second-order accuracy. Results are presented for several example problems, giving attention to quasi-one-dimensional Laval nozzle flow, a one-dimensional shock tube problem, and supersonic flow over a cylinder.
Inherent in the method used by CCRS for the radiometric calibration of LANDSAT-4 MSS data is the possibility for the user to convert the corrected digital values to the absolute scene radiance of the target under observation. The generation of the constants needed for this final conversion requires both the pre-launch and post-launch radiometric calibration constants as supplied by NASA. Results of some preliminary comparative studies of the radiometric properties of the LANDSAT-4 MSS versus earlier satellites in the LANDSAT series are presented as well as early observations on the stability of the calibration data, within one scene, within one orbit, and over a period of several months. Residual striping in the corrected products is estimated. The method used to perform precision processing of the LANDSAT MSS data for generating geocoded or map compatible LANDSAT MSS products in the Unviersal Transverse Mercator projection is also reviewed. LANDSAT-4 MSS precision processed products are evaluated for geodetic accuracy, and are compared to similar products from the previous LANDSAT satellites to assess the orbit independent registration accuracy.
Data acquired by synthetic aperture radar (SAR) and LANDSAT multispectral scanner (MSS) were processed and analyzed to derive forest-related resources inventory information. The SAR data were acquired by using the NASA aircraft X-band SAR with linear (HH, VV) and cross (HV, VH) polarizations and the SEASAT L-band SAR. After data processing and data quality examination, the three polarization (HH, HV, and VV) data from the aircraft X-band SAR were used in conjunction with LANDSAT MSS for multisensor data classification. The results of accuracy evaluation for the SAR, MSS and SAR/MSS data using supervised classification show that the SAR-only data set contains low classification accuracy for several land cover classes. However, the SAR/MSS data show that significant improvement in classification accuracy is obtained for all eight land cover classes. These results suggest the usefulness of using combined SAR/MSS data for forest-related cover mapping. The SAR data also detect several small special surface features that are not detectable by MSS data.
The Image-Based Information System (IBIS) was used to automate the cross country movement (CCM) mapping model developed by the Defense Mapping Agency (DMA). Existing terrain factor overlays and a CCM map, produced by DMA for the Fort Lewis, Washington area, were digitized and reformatted into geometrically registered images. Terrain factor data from Slope, Soils, and Vegetation overlays were entered into IBIS, and were then combined utilizing IBIS-programmed equations to implement the DMA CCM model. The resulting IBIS-generated CCM map was then compared with the digitized manually produced map to test similarity. The numbers of pixels comprising each CCM region were compared between the two map images, and percent agreement between each two regional counts was computed. The mean percent agreement equalled 86.21%, with an areally weighted standard deviation of 11.11%. Calculation of Pearson's correlation coefficient yielded +9.997. In some cases, the IBIS-calculated map code differed from the DMA codes: analysis revealed that IBIS had calculated the codes correctly. These highly positive results demonstrate the power and accuracy of IBIS in automating models which synthesize a variety of thematic geographic data.
An algorithm is examined that uses VISSR Atmospheric Sounder (VAS) 11- and 12-micron (split-window) data to derive column-integrated water content (IWC) at mesoscale resolution. The algorithm is physically based and derives its first-guess information from radiosonde data. The procedure is applied first to a test case data set and then to the 19 June 1986 study day from the Cooperative Huntsville Meteorological Experiment (COHMEX). Ground truth data for verifying results from the technique include IWC from National Weather Service and COHMEX radiosondes, the Multispectral Atmospheric Mapping Sensor (MAMS), and a special set of VAS soundings (12 channel) using an independent retrieval method. Results from the test case show reasonable accuracy with the rms errors as low as +/- 3.8 mm. On the 19 June case study day IWC analyses depict reasonable gradients and exhibit good spatial and temporal continuity. Furthermore, they provide insight into preferred regions for cumulus cloud and thunderstorm formation. On the average, a mean absolute retrieval error of 2.4 mm (an 8.1 percent error) and a rms error of +/- 2.9 mm are obtained on the case study day. These results compare favorably with those from existing VAS IWC techniques. Overall, the findings indicate that the technique has excellent potential to depict mesoscale moisture variations.
Ozone measurements from the Total Ozone Mapping Spectrometer on the Nimbus 7 satellite are compared with ground-based measurements from five Dobson stations at northern latitudes to evaluate the accuracy of the TOMS data, particularly in regions north of 50 deg N. The measurements from the individual stations show mean differences from -2.5 percent up to plus 8.3 percent relative to TOMS measurements and two of the ground stations, Oslo and Longyearbyen, show a significant drift of plus 1.2 percent and plus 3.7 percent per year, respectively. It can be shown from nearly simultaneous measurements in two different wavelength double pairs at Oslo that at least 2 percent of the differences result from the use of the CC' wavelength double pair instead of the standard AD wavelength double pair. Since all Norwegian stations used the CC' wavelength double pair exclusively a similar error can be assumed for Tromso and Longyearbyren. A comparison between the tropospheric ozone content in TOMS data and from ECC ozonesonde measurements at Ny-Alesund and Bear Island shows that the amount of tropospheric ozone in the standard profiles used in the TOMS algorithm is too low, which leads to an error of about 2 percent in total ozone. Particularly at high solar zenith angles (greater than 80 deg), Dobson measurements become unreliable. They are up to 20 percent lower than TOMS measurements averaged over solar zenith angles of 88 deg to 89 deg.
Prelaunch and postlaunch calibration results for the Meteor 3/total ozone mapping spectrometer (TOMS) instrument are presented here. Ozone amounts are retrieved from measurements of Earth albedo in the 312- to 380-nm range. The accuracy of albedo measurements is primarily tied to knowledge of the reflective properties of diffusers used in the calibrations and to the instrument's wavelength selection. These and other important prelaunch calibrations are presented. Their estimated accuracies are within the bounds necessary to determine column ozone to better than 1%. However, postlaunch validation results indicate some prelaunch calibration uncertainties may be larger than originally estimated. Instrument calibrations have been maintained postlaunch to within a corresponding 1% error in retrieved ozone. Onboard calibrations, including wavelength monitoring and a three-diffuser solar measurement system, are described and specific results are presented. Other issues, such as the effects of orbital precession on calibration and recent chopper wheel malfunctions, are also discussed.
Satellite imagery datasets and regional climate model results are intercompared for evaluation of model accuracy in the simulation of cloud cover. Both monthly average individual simulation times are analyzed. To provide a consistent comparison, satellite data are first mapped into the model's geographic projection, grid domain, and resolution. It is found that September 1988 monthly average cloud fraction results from the modeled simulations correspond to observations, in both spatial pattern and magnitude, with bias less than +/- 20% cloud fraction over the entire inland West. Agreement in the pattern of cloud fraction also is evident for monthly average cloud fraction in July, but there is no negative bias of 10%-30% cloud fraction in the model diagnosis of cloud cover. Correlations between the spatial distributions of model-derived and observed cloud fractions are found to exceed 0.80 for certain geographic regions of the West, and these correlations are largest over mountainous areas during summer. Case studies of a series of daily cloud cover demonstrate the ability of the model to simulate the effects of frontal passage on cloud distribution. The ability of the RegCM1 to simulate daily cloud fraction and diurnal cloud evolution is somewhat weak for the summer convective season. It is anticipated that a more recent version of the regional climate model may improve the simulation of summer season cloud cover, through changes in cloud parameterization and improvements in model resolution.
The topography of the Long Valley caldera, California, was sampled using airborne laser altimetry in 1993, 1995, and 1997 to test the feasibility of using airborne laser altimetry for monitoring deformation of volcanic origin. Results show the laser altimeters are able to resolve subtle topographic features such as a gradual slope and to detect small transient changes in lake elevation. Crossover and repeat pass analyses of laser tracks indicate decimeter-level vertical precision is obtained over flat and low-sloped terrain for altimeter systems performing waveform digitization. Comparisons with complementary, ground-based CPS data at a site close to Bishop airport indicate that the laser and GPS-derived elevations agree to within the error inherent in the measurement and that horizontal locations agree to within the radius of the laser footprint. A comparison of the data at two sites, one where no change and the other where the maximum amount of vertical uplift is expected, indicates approximately 10 cm of relative uplift occurred 1993-1997, in line with predictions from continuous CPS measurements in the region. Extensive terrain mapping flights during the 1995 and 1997 missions demonstrate some of the unique abilities of laser altimetry; the straightforward creation of high resolution, high accuracy digital elevation models of overflown terrain, and the ability to determine ground topography in the presence of significant ground cover such as dense tree canopies. These capabilities make laser altimetry an attractive technique for quantifying topographic change of volcanic origin, especially in forested regions of the world where other remote sensing instruments have difficulty detecting the underlying topography.
The topography of the Long Valley caldera, California, was sampled using airborne laser altimetry in 1993, 1995, and 1997 to test the feasibility of using airborne laser altimetry for monitoring deformation of volcanic origin. Results show the laser altimeters are able to resolve subtle topographic features such as a gradual slope and to detect small transient changes in lake elevation. Crossover and repeat pass analyses of laser tracks indicate decimeter-level vertical precision is obtained over flat and low-sloped terrain for altimeter systems performing waveform digitization. Comparisons with complementary, ground-based GPS data at a site close to Bishop airport indicate that the laser and GPS-derived elevations agree to within the error inherent in the measurement and that horizontal locations agree to within the radius of the laser footprint. A comparison of the data at two sites, one where no change and the other where the maximum amount of vertical uplift is expected, indicates approximately 10 cm of relative uplift occurred 1993-1997, in line with predictions from continuous GPS measurements in the region. Extensive terrain mapping flights during the 1995 and 1997 missions demonstrate some of the unique abilities of laser altimetry; the straightforward creation of high resolution, high accuracy digital elevation models of overflown terrain, and the ability to determine ground topography in the presence of significant ground cover such as dense tree canopies. These capabilities make laser altimetry an attractive technique for quantifying topographic change of volcanic origin, especially in forested regions of the world where other remote sensing instruments have difficulty detecting the underlying topography.
In June 2009 the Lunar Reconnaissance Orbiter (LRO) spacecraft was launched to the Moon. The payload consists of 7 science instruments selected to characterize sites for future robotic and human missions. Among them, the Lunar Orbiter Laser Altimeter (LOLA) was designed to obtain altimetry, surface roughness, and reflectance measurements. The primary phase of lunar exploration lasted one year, following a 3-month commissioning phase. On completion of its exploration objectives, the LRO mission transitioned to a science mission. After 7 years in lunar orbit, the LOLA instrument continues to map the lunar surface. The LOLA dataset is one of the foundational datasets acquired by the various LRO instruments. LOLA provided a high-accuracy global geodetic reference frame to which past, present and future lunar observations can be referenced. It also obtained high-resolution and accurate global topography that were used to determine regions in permanent shadow at the lunar poles. LOLA further contributed to the study of polar volatiles through its unique measurement of surface brightness at zero phase, which revealed anomalies in several polar craters that may indicate the presence of water ice. In this paper, we describe the many LOLA accomplishments to date and its contribution to lunar and planetary science.
The major flood events in the United States in the past few years have made it apparent that many floodplain maps being used by State governments are outdated and inaccurate. In response, many Stated have begun to update their Federal Emergency Management Agency (FEMA) Digital Flood Insurance Rate Maps. Accurate topographic data is one of the most critical inputs for floodplain analysis and delineation. Light detection and ranging (LIDAR) altimetry is one of the primary remote sensing technologies that can be used to obtain high-resolution and high-accuracy digital elevation data suitable for hydrologic and hydraulic (H&H) modeling, in part because of its ability to "penetrate" various cover types and to record geospatial data from the Earth's surface. However, the posting density or spacing at which LIDAR collects the data will affect the resulting accuracies of the derived bare Earth surface, depending on terrain type and land cover type. For example, flat areas are thought to require higher or denser postings than hilly areas to capture subtle changes in the topography that could have a significant effect on flooding extent. Likewise, if an area has dense understory and overstory, it may be difficult to receive LIDAR returns from the Earth's surface, which would affect the accuracy of that bare Earth surface and thus would affect flood model results. For these reasons, NASA and FEMA have partnered with the State of North Carolina and with the U.S./Mexico Foundation in Texas to assess the effect of LIDAR point density on the characterization of topographic variation and on H&H modeling results for improved floodplain mapping. Research for this project is being conducted in two areas of North Carolina and in the City of Brownsville, Texas, each with a different type of terrain and varying land cover/land use. Because of various project constraints, LIDAR data were acquired once at a high posting density and then decimated to coarser postings or densities. Quality assurance/quality control analyses were performed on each dataset. Cross sections extracted form the high density and then the decimated datasets were individually input into an H&H model to determine the model's sensitivity to topographic variation and the effect of that variation on the resulting water profiles. Additional analysis was performed on the Brownsville, Texas, LIDAR data to determine the percentage of returns that "penetrated" various types of canopy or vegetative cover. It is hoped that the results of these studies will benefit state and local communities as they consider the post spacing at which to acquire LIDAR data (which affects cost) and will benefit FEMA as the Agency assesses the use of different technologies for updating National Flood Insurance Program and related products.
This paper presents a detailed analysis of the accuracy and performance of line marching algorithms executing on a GPU. In the context of an accurate Global Navigation Satellite System(GNSS) quality of service simulation, horizon sky-plots are a useful tool to determine satellite visibility in the presence of obstructions from objects, such as buildings or dense foliage. In order to accurately model satellite visibility at a point of interest on a map, a horizon plot can identify the viewing angles at which objects are blocking the sky. This computation requires traversing a line starting at the point of interest on a 2D altitude map, moving outward for every azimuth angle. To explore the performance of this computation, we propose a new dynamic stopping condition for the traversal of the line, benefiting from objects close to the point of interest. We compare the accuracy of common line marching algorithms, and consider their parallel performance when developed in CUDA. We find that our proposed stopping condition for line marching provides a significant improvement in performance in urban canyon sky-plots, as compared to previous work. Additionally, these results show that simpler algorithms, such as the digital differential analyzer line algorithm, are better suited for GPUs than more sophisticated schemes such as Bresenham’s algorithm, specifically in the context of sky-plothorizon computations. The trade-off between accuracy and performance is analyzed and providing guidance that depends on the targeted goal of the GNSS application.
Terrain Relative Navigation (TRN) was a critical enabling Entry, Descent, and Landing (EDL) technology that enabled Mars 2020 mission Perseverance rover to land at Jezero crater. TRN pro-vides real-time, autonomous, map-relative position determination and generates a landing target based on a priori knowledge of hazards. The required performance for TRN was to land within 60m of the selected target. The required 60m was sub-allocated to various error sources in three major categories: targeting error, knowledge error, and control error. The targeting error is the error in selecting an appropriate landing target and the knowledge of the target on the surface. It includes the Lander Vision System (LVS) position localization with respect the ground, the synchronization between the Lander Vision System measurement and the main Navigation filter, and errors associated with the LVS Reference Map and Safe Target Selec-tion (STS). The knowledge error is the contribution of knowledge growth from the synchronization with LVS to touchdown. The control error encompasses how accurately the system could stay on the desired reference trajectory. The TRN error budget uses a combination of analysis, simulation, and hardware test-ing results to bound the various error contributions obtained during the verification and validation process. This paper first presents a description the TRN system, focusing on the architecture of LVS and STS. The paper then gives detailed overview of the TRN error budget, with a description of the major error contribu-tions in each of the three categories. Next, the paper gives the results for three versions of the error budget, pre-launch, in-flight pre-landing, and post-landing. The paper compares the pre-flight analysis, the pre-landing analysis using in-flight data during cruise, to the post-landing analysis of the TRN performance. Pre-landing analysis best estimate of the landing performance was 33m, compared to the 60m require-ment. Post-landing analysis estimated a landing accuracy of 8.53m or better, much better than the 33m pre-landing estimate. The actual post-landing imagery calculated the distance of the rover to the targeted location to be 5m. The post-landing analysis closely bounds the image-based assessment of landing accu-racy, indicating the success of the error budget architecture in bounding the landing accuracy, as well as the fidelity of the simulations used to model and predict performance.
NASA’s Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) was launched in September, 2018. The satellite carries a single instrument, ATLAS (Advanced Topographic Laser Altimeter System), a green wavelength, photon-counting lidar, enabling global measurement and monitoring of elevation with a primary focus on the cryosphere. Although bathymetric mapping was not one of the design goals for ATLAS, pre-launch work by our research team showed the potential to map bathymetry with ICESat-2, using data from MABEL (Multiple Altimeter Beam Experimental Lidar), NASA’s high-altitude airborne ATLAS emulator, and adapting the laser-radar equation for ATLAS specific parameters. However, many of the sensor variables were only approximations, which limited a full assessment of the bathymetric mapping capabilities of ICESat-2 during pre-launch studies. Following the successful launch, preliminary analyses of the geolocated photon returns have been conducted for a number of coastal sites, revealing several salient examples of seafloor detection in water depths of up to ~40 m. The geolocated seafloor photon returns cannot be taken as bathymetric measurements, however, since the algorithm used to generate them is not designed to account for the refraction that occurs at the air–water interface or the corresponding change in the speed of light in the water column. This paper presents the first early on-orbit validation of ICESat-2 bathymetry and quantification of the bathymetric mapping performance of ATLAS using data acquired over St. Thomas, U.S. Virgin Islands. A refraction correction, developed and tested in this work, is applied, after which the ICESat-2 bathymetry is compared against high-accuracy airborne topo-bathymetric lidar reference data collected by the U.S. Geological Survey (USGS) and the National Oceanic and Atmospheric Administration (NOAA). The results show agreement to within 0.43—0.60 m root mean square error (RMSE) over 1 m grid resolution for these early on-orbit data. Refraction-corrected bottom return photons are then inspected for four coastal locations around the globe in relation to Visible Infrared Imaging Radiometer Suite (VIIRS) K(d)(490) data to empirically determine the maximum depth mapping capability of ATLAS as a function of water clarity. It is demonstrated that ATLAS has a maximum depth mapping capability of nearly 1 Secchi in depth for water depths up to 38 m and K(d)(490) in the range of 0.05–0.12 per m. Collectively, these results indicate the great potential for bathymetric mapping with ICESat-2, offering a promising new tool to assist in filling the global void in nearshore bathymetry.
The author has identified the following significant results. Scientific results may be summarized as follows: (1) A geodetic (UTM) grid can be fitted to MSS bulk images with a positional accuracy in the order of 50 meters (rms). (2) The MSS imagery as corrected and printed in bulk form is in effect or a defined map projection. This projection, if optimized for cartographic presentation, will have distortions in the order of only 1 part in 10,000. (3) The orbit of ERTS-1 and image delineation of MSS imagery can be held by NASA so that predesignated scenes may be identified and used as a basis for a map series. This concept could reduce the time and cost of ERTS-1 image map production many fold as compared to standard quadrangle format production.
Classification, delineation and evaluation of coastal wetlands can be made on the basis of major vegetative associations. To produce wetland maps, two vegetation-analysis look-up tables were developed for use in the ERTS ANALYSIS System. These look-up tables are based on Earth Resources Technology Satellite (ERTS) digital values in Multispectral Scanner (MSS) bands 4, 5, and 7 and were developed using seasonal spectral reflectance measurements from field observations. Computer-generated maps at an approximate scale of 1:20,000 were produced for the primary test site, Chincoteague Marsh, Virginia. There is a high degree of accuracy in the identification of wetland features and plant associations. The classification was also tested on other Atlantic coast salt marshes and a brackish marsh in the Chesapeake Bay.