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At least 1,243 records · Page 69

Satellite altimetry applications

In satellite altimetry the highly stable platform provided by a satellite is utilized as a moving reference system from which vertical measurements to the ocean surface are made. Satellite altimetry applications are related to geoid determination, questions concerning the consideration of local topography, geological-structure studies, investigations regarding the distribution of wave heights, current detection, and the mapping of land topography.

Mcgoogan, J. T.↗

Evaluation of existing knowledge of the tectonic history and lithospheric structure of South America

While data is available on the lithospheric and crustal structure of the Andes region of South America, there is limited knowledge of these aspects of the eastern portion of the continent. For this reason, a surface wave dispersion study of the area was initiated. Long period seismograms were obtained for a tripartite analysis of dispersion. A flow chart of the analysis to be conducted is presented along with a preliminary geologic/tectonic map that was prepared. Efforts to characterize the provinces identified in terms of their geological and geophysical parameters continue.

Keller, G. R.↗

Multispectral remote sensing as stratigraphic and structural tool, Wind River Basin and Big Horn Basin areas, Wyoming

The use of Landsat TM, Airborne Imaging Spectrometer, and airborne Thermal IR Multispectral Scanner data in the geological evaluation of two sites in central Wyoming is described and illustrated with diagrams, maps, photographs, sample images, and tables of numerical data. The value of the remotely sensed information on the areal variation of attitude, sequence, thickness, and lithology of exposed strata is demonstrated; details of the data analysis are given; and the specialized software packages employed are briefly characterized.

Lang, Harold R.↗

Regional topographic rises on Venus - Geology of Western Eistla Regio and comparison to Beta Regio and Atla Regio

Magellan images are used to assess regional stratigraphic relationships in an attempt to establish the evolutionary history and characterize the styles of volcanism at Western Eistla Regio. The regional geologic characteristics of Beta Regio and Atla Regio, imaged by Magellan during the latter part of its first mapping cycle, are also assessed and compared to those of Western Eistla Regio so as to determine if all three of these areas evolved in a similar manner. The detailed characteristics of each region show them to be quite variable in the presence and distribution of coronae and tessera, suggesting that the detailed characteristics of the individual highlands are linked to the local geologic environment.

Senske, D. A.↗

Earth imaging results from Galileo's second encounter

The recent flyby of the Galileo spacecraft en route to Jupiter contributes a unique perspective to our view of our home planet. Imaging activities conducted during the second Earth encounter provide an important opportunity to assess new methods and approaches on familiar territory. These include unique multispectral observations, low light-level imaging (searches for aurorae, lightning and artificial lights on the nightside) and experiments with multiple exposure times to extend the effective radiometric resolution and dynamic range of the camera system. Galileo imaging data has the potential to make important contributions to terrestrial remote sensing. This is because the particular set of filters included in the Solid State Imaging system are not presently incorporated in any currently operating Earth-orbiting sensor system. The visible/near-infrared bandpasses of the SSI filters are well suited to remote sensing of geological, glaciological, botanical, and meteorological phenomena. Data from this and the previous Earth encounter may provide an extremely valuable reference point in time for comparison with similar data expected from EOS or other systems in the future, contributing directly to our knowledge of global change. The highest resolution imaging (0.2 km/pixel) during the December, 1992 encounter occurred over the central Andes; a five filter mosaic of visible and near infrared bands displays the remarkable spectral heterogeneity of this geologically diverse region. As Galileo departed the Earth, cooperative imaging with the Near Infrared Mapping Spectrometer (NIMS) instrument targeted Antarctica, Australia, and Indonesia at 1.0 to 2.5 km/pixel resolutions in the early morning local times near the terminator. The Antarctic data are of particular interest, potentially allowing ice grain size mapping using the 889 and 968 nm filters and providing an important means of calibrating the technique for application to the Galilean satellites. As the spacecraft receded further, regional scale imaging provided data which, along with data from the previous encounter, will enable the production of global multispectral mosaics of Earth in each of the SSI filters.

Greenberg, R.↗

Titan's Surface Temperatures from Cassini CIRS

The surface brightness temperature of Titan can be measured from Cassini through a spectral window at 19 microns where the atmosphere is low in opacity. The Composite Infrared Spectrometer (CIRS) on Cassini observes this wavelength in its far-infrared channel. Because the Cassini tour has provided global coverage and a range of viewing geometries, CIRS has been able to go beyond the earlier flyby results of Voyager IRIS Near the equator, CIRS measures the zonally-averaged surface brightness temperature to be 917 K, very close to the temperature found at the surface by Huygens. Latitude maps show that Titan's surface temperatures drop off by about 2 K toward the south and by about 3 K toward the north. This temperature distribution is consistent with Titan's late northern winter when the data were taken. As the seasons progress, CIRS is continuing to search for corresponding changes in the temperatures of the surface and lower atmosphere. CIRS is also extending global mapping to both latitude and longitude to look for correlations between surface temperatures and geological features.

Jennings, Donald E.↗

Interpretation of CHAMP Magnetic Anomaly Data over the Pannonian Basin Region Using Lower Altitude Horizontal Gradient Data

The ESA SWARM mission will have three earth orbiting magnetometer bearing satellites one in a high orbit and two side-by-side in lower orbits. These latter satellites will record a horizontal magnetic gradient. In order to determine how we can use these gradient measurements for interpretation of large geologic units we used ten years of CHAMP data to compute a horizontal gradient map over a section of southeastern Europe with our goal to interpret these data over the Pannonian Basin of Hungary.

CHAMP↗

The Spatial Relationship of Graben and Pit Craters at Rimae Daniell and the Implications of Scarp Formation

A geomorphologically complex and understudied region on the Moon is Rimæ Daniell, situated in Lacus Somniorum. This region is characterized by a set of NNW-SSE-oriented grabens, which have been implied to be underlain by dikes through topographic measurements of ground displacements and faulting processes. The coverage of topographic measurements with the Lunar Orbiter Laser Altimeter (LOLA) aboard the Lunar Reconnaissance Orbiter (LRO) now allows for an indepth morphologic analysis of lunar grabens. Lunar grabens, in general, occur peripheral to some near-side mare units, within floor-fractured craters, and inside larger impact structures. From, LOLA data across Rimæ Daniell indicate that these grabens are located atop broad rises that stand 100–150 m above their surroundings. Although has mapped out the northwestern most grabens at Rimæ Daniell, this area has a complex geologic history, including pit chain craters and the transition of the graben system to a steep scarp, which is disrupted by knobby terrain.

C. J. Ahrens↗

Time-lapse seismic inversion for CO 2 saturation with SeisCO2Net: An application to Frio-II site

Seismic monitoring of geological CO 2 storage (GCS) involves highly nonlinear seismic inversion and petrophysical inversion, making it challenging to estimate CO 2 volume efficiently and detect possible early CO 2 leakages. Deep learning (DL) using convolutional neural networks (CNNs) has shown promise in solving highly nonlinear seismic inversion problems. However, direct estimation of CO 2 plume extent/saturation from time-lapse seismic gathers using DL is still underexplored, with no reported field applications to date. The investigation of field data is primarily hindered by scarcity of field data for neural network training. Other obstacles include highly nonlinear seismic-petrophysics inverse relationship, and presence of noise in field seismic data. We introduce SeisCO2Net, a deep CNN that predicts CO 2 saturation maps directly from time-lapse full waveform shot gathers. For training, we use site-specific geological information, fluid flow physics, rock physics, and seismic modeling to generate synthetic datasets that closely resemble the CO 2 storage site. Synthetic tests show promising results, inspiring us to apply SeisCO2Net's trained weights on field data collected at Frio-II GCS site by leveraging transfer learning principles. As reference, we compare SeisCO2Net's predicted CO 2 saturation maps with results obtained from physics-based inversion. Our analyses show both methods display similar CO 2 plume shapes, reasonable CO 2 plume characteristics, and comparable saturation values. Our results suggest pre-training CNNs on physics-informed synthetic datasets and then applying the learned weights to field data is a viable approach to estimating field CO 2 saturation. This method effectively addresses the scarcity of field training data, thus encouraging the feasibility of long-term GCS monitoring.

58 GEOSCIENCES↗

Dark materials in Valles Marineris - Indications of the style of volcanism and magmatism on Mars

Computer mapping of spectral reflectance in Viking Orbiter I multispectral images is combined with photogeological interpretation and used to examine the geological significance of the dark materials in Valles Marineris, a canyon system that provides a unique view of the interior of the Martian crust. Special consideration is given to the relation of the dark materials to the past episodes of tectonism, volcanic activity, and igneous intrusion. Spectral mapping suggests that the dark floor-covering materials in the lower canyon are derived from a thick deposit composed of mafic glass, possibly an ancient Martian analogue of the lunar terra mantling deposits. Application of computer mapping techniques to probable young volcanic materials in the central troughs yields an inferred distribution of volcanic activity consistent with the interpretation of extrusion along faults near the margins of the canyon floors. The results support the hypothesis that Valles Marineris originated through tectonic extension.

Geissler, Paul E.↗

A deep learning-based workflow for fast prediction of 3D state variables in geological carbon storage: A dimension reduction approach

Deep learning (DL) models are extensively used as surrogate models for high-fidelity simulations of multiphase fluid flow in porous media at large scales, enabling fast forecasts of the spatial–temporal evolution of three-dimensional (3D) state variables in geological carbon storage (GCS). However, training these models in high-dimensional space remains computationally demanding and prone to overfitting because of limited training data. This paper presents a novel workflow to address these challenges by integrating dimension reduction (DR) methods. Here, the proposed workflow employed pre-trained DR models to extract the latent variables of geological models and state variables and utilized the multi-layer perceptron (MLP) for constructing mapping functions between the input and output variables in latent spaces. Subsequently, the pre-trained reconstruction models converted the MLP-predicted latent state variables to their original high-dimensional form. Furthermore, we proposed a novel strategy for the DR and reconstruction of 3D saturation fields to account for the unique data characteristics of sparsity, nonuniformity, and discontinuity. The proposed strategy applied PCA and inverse PCA for 2D average saturation fields and developed a DL-based 3D reconstruction model, leveraging three 2D average saturation fields as input to produce a 3D saturation field as output. The pre-training of DR and reconstruction models and training of MLP models were conducted on 84 Gulf of Mexico (GoM) simulations and evaluated on 12 testing simulations. Each simulation contained 720 monthly time steps, with the first 360 months as the injection period and the rest as the post-injection period. The proposed workflow, incorporating DR and DL models, accurately predicts the normalized 3D pressure fields, achieving mean square error (MSE) of 2.92 × 10 -7 compared to the ground truth obtained from a full-physics simulator. Furthermore, the proposed strategy outperformed PCA and convolutional autoencoder (CAE) models on 3D saturation fields, resulting in minor workflow prediction errors with an MSE of 2.93 × 10 -5 . The results suggest the proposed workflow provides sufficient predictive fidelity across temporal and spatial scales, and enables a speedup of 160 times compared to the full-physics simulator, facilitating improved decision-making and risk assessment for large-scale GCS management in real-time scenarios.

3D reconstruction model↗

Oberon - Color photometry from Voyager and its geological implications

The surface of the Uranian satellite Oberon is characterized on the basis of ground-based and Voyager photometric observations. Disk-integrated phase-curve and disk-resolved data are presented in extensive tables, graphs, maps, and black-and-white and false-color images and discussed in terms of fits to the Hapke (1986) parameters, local variations in albedo and color, and their possible geological significance. It is found that most of the leading hemisphere is covered with dark materials like those in the crater floors, while the trailing hemisphere has patches of the dark material on a surface with a higher proportion of icy materials which are spectrally neutral.

Helfenstein, Paul↗

Use of coregistered radar, visible and IR images for geologic remote sensing

The Shuttle Imaging Radar (SIR-A) obtained images over the southern portion of the San Rafael Swell in eastern Utah. SEASAT SAR and LANDSAT MSS images and thermal inertia data from the Heat Capacity Mapping Mission (HCMM) were correlated with the SIR-A data. Radar images obtained with different incidence angles and different illumination directions were compared with images obtained in other portions of the spectrum for geologic remote sensing.

Evans, D. L.↗

Topsoil bulk geochemical compositions - An updated harmonized global dataset

Mineral weathering is a key biogeochemical process because of the capacity of minerals to stabilize organic matter. However, predicting soil weathering status across large spatial areas still isn’t possible due to a lack of global data and theoretical frameworks. To address this knowledge gap, multiple global datasets of bulk topsoil geochemical compositions have been harmonized using R. These datasets document topsoil bulk geochemical compositions across five continents (n = ~16,000 observations). Source data for these observations include the EuroGEOSurveys Geochemical Baseline Database (FOREGS), the US Geological Survey National Geochemical Database (NASGLP), the Geochemical Atlas of Australia (GAA), the US Geological Survey Alaska Geochemical Database (AGD84), the National Cooperative Soil Survey (NCSS), the European Geochemical Mapping of Agricultural Soil (GEMAS), Ecorespira-Amazon (ERA), the New Zealand Geochemical Baseline Survey (NZ_GBS), and the African Soil Information Service (AFSIS). Major elements observed include Aluminum (Al), Calcium (Ca), Iron (Fe), Potassium (K), Magnesium (Mg), Sodium (Na), Titanium (Ti), Manganese (Mn), Phosphorus (P), Carbon (C), and Sulfur (S). This data package includes the harmonized dataset itself, and the R scripts necessary to harmonize these datasets, in addition to metadata that describes all columns, files, and databases used in this project. Methods & Sampling Step 1 – Databases of geochemical data identified This study aimed to leverage existing measurements of topsoil geochemical data. Databases were first identified and deemed appropriate for inclusion if they were measuring soils and performed these measurements on the <2mm soil fraction. Databases such as NCSS and AGD84 needed more post processing to include in the database and this was done using the NCSS_datamerge_031626 R file and Alaska_USGSmerge_031626 R file, respectively. Step 2 – Database harmonization Once appropriate databases were identified, they were harmonized for ease of analysis using the R script Database_Harmonization_031826. This included removing columns from original datasets that would not be used in analysis (removed columns are noted in the code). Then, data cleaning procedures specific to each dataset were undertaken. This includes standardizing columns to include units and adding metadata columns regarding procedures for analyzing specific elements. Functions for standardizing measurements and units are outline in R files: calculate element_mg_kg_031626, calculate_oxide_wt_perc_031626, change_oxide_caps_031626, and conv_2_numeric_031626. This also included adding a unique identifier for each sample to identify it with its respective database (see CD_ID in data dictionary). Geographic information: Data reflect a compilation of datasets collected globally. Geographic areas covered by each of the datasets include: - EuroGEOSurveys Geochemical Baseline Database (FOREGS) - European continent - North American Soil Geochemical Landscapes (NASGLP) - continental United States and limited parts of Canada (see database key for more details) - National Geochemical Survey of Australia (GAA) - Australia - Alaska geochemical database (AGDB4) - Alaska - National Cooperative Soil Survey (NCSS) - Global measurements, but concentrated in the continental United States - Geochemical data for arable land and land under permanent grass cover in continental Europe (GEMAS) - continental Europe - Ecorespira-Amazon (ERA) - Geochemical data from the Amazon basin - Geochemical baseline data for New Zealand (NZGBS) - New Zealand - Geochemical data collected across continental Africa (AfSIS) - Measurements across Africa

EARTH SCIENCE > LAND SURFACE > SOILS↗

To assess the value of satellite imagery in resource inventorization on a national scale

The author has identified the following significant results. Production of 1:500,000 scale false color photolithoprints proved to be very valuable. Significant results were obtained in geomorphological mapping, mapping of disturbed and undisturbed natural vegetation as well as in the discovery of major geologic lineaments, some of which may be associated with mineralization. The cartographic quality of system corrected MSS imagery was also evaluated.

Malan, O. G.↗

Amazonas project: Application of remote sensing techniques for the integrated survey of natural resources in Amazonas

The use of LANDSAT multispectral scanner and return beam vidicon imagery for surveying the natural resources of the Brazilian Amazonas is described. Purposes of the Amazonas development project are summarized. The application of LANDSAT imagery to identification of vegetation coverage and soil use, identification of soil types, geomorphology, and geology and highway planning is discussed. An evaluation of the worth of LANDSAT imagery in mapping the region is presented. Maps generated by the project are included.

Dejesusparada, N.↗

Structure, composition and thermal state of the crust in Brazil

Efforts in support of a geomagnetic survey of the Brazilian area are described. Software to convert MAGSAT data tapes to the Burroughs/B-6700 binary format was developed and tested. A preliminary analysis of the first total intensity anomaly map was performed and methodologies for more intensive analysis were defined. The sources for correlative geological, aeromagnetic, and gravimetric data are described.

Pacca, I. I. G.↗