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The terrain-surface features of the Appalachian Valley and Ridge province were analyzed using Seasat synthetic aperture radar imagery. Particular attention was given to determining the efficiency and capability of this microwave imaging system for geologic mapping.
Lunar pyroclastic deposits are low albedo deposits present throughout the lunar surface including both maria and highlands, nearside and farside, and high latitudes and equatorial regions [e.g., 1]. There are two main types of pyroclastic deposits based upon size: localized (<2500 km2) and regional pyroclastic deposits (>2500 km2) [1]. In this study, we focus on the smaller localized pyroclastic deposits. The first and most detailed study of localized pyroclastic deposits are the deposits in Alphonsus crater [2]. This study included examining the radar and volumetric properties of these deposits. They found that vulcanian-like eruptions are most consistent with their observations. They imagined that a dike intrudes into the crust and creates a cooled basaltic cap. With increasing pressure under the basaltic cap, the pressure eventually overwhelms the surrounding rocks and results in explosive decompression. Later studies examined several pyroclastic deposits across the lunar surface using radar [2–4], digital terrain models (DTMs) [2,4], visible and near-infrared spectrometers [1,4–7], and a radiometer [4] to determine the mineralogy (e.g., olivine, glass, clinopyroxene, orthopyroxene, and plagioclase), deposit thickness and volume, proportion of juvenile material, radar backscatter, surface rock abundance, and regolith density. These various properties were examined against one another to better group localized pyroclastic deposits and understand how they relate to one another [4]. One of the studies divided pyroclastic deposits into three groups based upon the shape of the 1-μm absorption feature. The three Groups could be interpretated as having highlands and pyroclastic material (Group I), mare and pyroclastic material (Group II), and glass and orthopyroxene material (Group III) [5]. Building on that foundation, another study divided the pyroclastic deposits into four groups based upon their surface rock abundance and glass abundance [4], where deposits are classified based upon low surface rock abundance and high glass abundance (Glassy deposits); high rock abundance, high glass abundance (Blocky deposits); moderate rock abundance and low glass abundance (Crystalline deposits); and high rock abundance and low glass abundance (Indistinct Group). In addition to these studies, we can now look at their water contents using the new Effective Single Particle Absorption Thickness (ESPAT) parameter map [8]. The ESPAT map measures the strength of the 3-μm absorption feature in single scattering albedo space. The strength of this feature and its relationship to water content has been calibrated to returned samples, which allows for water content to be derived from remote spectral data (i.e., Moon Mineralogy Mapper). The goal of this study is to examine how water content in the pyroclastic deposits varies with respect to the geometric, mineralogic, and physical properties of the localized pyroclastic deposits as measured by a previous study [i.e., 4]. A more complete version of this work is found in [9].
Thermal gradients in French coastal zones for the period of one year were mapped in order to enable a coherent study of certain oceanic features detectable by the variations in the sea surface temperature field and their evolution in time. The phenomena examined were mesoscale thermal features in the English Channel, the Bay of Biscay, and the northwestern Mediterranean; thermal gradients generated by French estuary systems; and diurnal heating in the sea surface layer. The investigation was based on Heat Capacity Mapping Mission imagery.
The Multispectral Atmospheric Mapping Sensor (MAMS), a modification of NASA's Airborne Thematic Mapper, is described, and radiances from the MAMS and the VISSR Atmospheric Sounder (VAS) are compared which were collected simultaneously on May 18, 1985. Thermal emission from the earth atmosphere system in eight visible and three infrared spectral bands (12.3, 11.2 and 6.5 microns) are measured by the MAMS at up to 50 m horizontal resolution, and the infrared bands are similar to three of the VAS infrared bands. Similar radiometric performance was found for the two systems, though the MAMS showed somewhat less attenuation from water vapor than VAS because its spectral bands are shifted to shorter wavelengths away from the absorption band center.
Maps of the brightness distribution of Jupiter at 1.3 cm wavelength are reported for the two orthogonal linear polarizations; one approximately parallel to the equator and one approximately parallel to the pole. The synthesized beam is 6.0 arc sec by 12.0 arc sec, which provides about 55 picture elements over the visible disk. The two maps do not differ significantly. There are no small real features of the size of one resolution element with brightness greater than 6 K. The disk brightness is approximately uniform, which is consistent with saturated ammonia vapor as the source of opacity in the atmosphere. Uniformly mixed ammonia, molecular hydrogen, and methane are strongly excluded as major sources of the opacity. Forcing the maps to have symmetry about the pole, as expected for the rapidly rotating planet, reduces the residual noise level in the maps so that there appears to be a small amount of limb darkening along the equator and a small amount of brightening at the poles.
We use archival COBE/DIRBE data to construct a map of polycyclic aromatic hydrocarbon (PAH) emission in the λ-Orionis region. The presence of the 3.3 μm PAH feature within the DIRBE 3.5 μm band and the corresponding lack of significant PAH spectral features in the adjacent DIRBE bands (1.25, 2.2, and 4.9 μm) enable estimation of the PAH contribution to the 3.5 μm data. Having the shortest wavelength of known PAH features, the 3.3 μm feature probes the smallest PAHs, which are also the leading candidates for carriers of anomalous microwave emission (AME). We use this map to investigate the association between the AME and the emission from PAH molecules. We find that the spatial correlation in λ-Orionis is higher between AME and far-infrared dust emission (as represented by the DIRBE 240 μm map) than it is between our PAH map and AME. This finding, in agreement with previous studies using PAH features at longer wavelengths, is in tension with the hypothesis that AME is due to spinning PAHs. However, the expected correlation between mid-infrared and microwave emission could potentially be degraded by different sensitivities of each emission mechanism to local environmental conditions even if PAHs are the carriers of both.
The author has identified the following significant results. Photographic prints made from negatives of day-visible and day-IR cover of selected areas were compared with enhanced color composites generated from LANDSAT computer compatible tapes and films. For geological mapping purposes, HCMM imagery is of limited value. While large scale features like the Mikadoodi anticlinorium, contrasting lithological units, and major structures may be distinguished on day-visible and day-IR cover, the spectral bands are too broad and the resolution too coarse even for regional mapping purposes. The imagery appears to be most useful for drainage studies. Where drainage is seasonal, sequential imagery permits monitoring of broad scale water movement while the day-IR imagery yields valuable information on former channels. In plains areas subject to periodic change of stream courses, comparable IR cover at a larger scale would offer considerable potential for reconstruction of former drainage patterns essential for the correct interpretation of geochemical data relative to mineral exploration.
Earth-based albedo maps of Mars were compared with Mariner 9 television data and ground-based radar profiles to investigate the nature of the bright and dark albedo features. Little correlation was found except at the boundaries of classical albedo features, where some topographic control is indicated. Wind-blown dust models for seasonal and secular albedo variations are supported, but it is not clear whether the fines are derived from bright or dark parent rock. Mars, like the Earth and Moon, has probably generated two distinct types of crustal material.
Earth-based albedo maps of Mars were compared with Mariner 9 television data and ground-based radar profiles to investigate the nature of the bright and dark albedo features. Little correlation was found except at the boundaries of classical albedo features, where some topographic control is indicated. Windblown dust models for seasonal and secular albedo variations are supported, but it is not clear whether the fines are derived from bright or dark parent rock. Mars, like the earth and moon, has probably generated two distinct types of crustal material.
The bright swirling features on the lunar surface in areas around the Moon but most prominently at Reiner Gamma, have intrigued scientists for many years. After Apollo and later Lunar Prospector (LP} mapped the Lunar magnetic fields from orbit, it was observed that these features are generally associated with crustal magnetic anomalies. This led researchers to propose a number of explanations for the swirls that invoke these fields. Prominent among these include magnetic shielding in the form of a mini-magnetosphere which impedes space weathering by the solar wind, magnetically controlled dust transport, and cometary or asteroidal impacts that would result in shock magnetization with concomitant formation ofthe swirls. In this presentation, we will consider another possibility, that the ambient magnetic and electric fields can transport and channel secondary ions produced by micrometeorite or solar wind ion impacts. In this scenario, ions that are created in these impacts are under the influence of these fields and can drift for significant distances before encountering the magnetic anomalies when their trajectories are disrupted and concentrated onto nearby areas. These ions may then be responsible for chemical alteration of the surface leading either to a brightening effect or a disruption of space weathering processes. To test this hypothesis we have run ion trajectory simulations that show ions from regions about the magnetic anomalies can be channeled into very small areas near the anomalies and although questions remain as to nature of the mechanisms that could lead to brightening of the surface it appears that the channeling effect is consistent with the existence of the swirls.
The closed quiet magnetosphere model of Beard (1979) and Beard et al. (1982) is used to identify those features of commonly observed dayside auroras that can be explained by either of two processes: mapping distortions or distortions caused by nearby Birkeland currents. It is shown that single and multiple linear and hooked auroral forms can be easily explained in terms of mapping distortions in a quiet magnetosphere. On the other hand, the shapes of bright twisted or folded auroral forms can be more easily explained as distortions produced by localized Birkeland currents.
The Pet6n region of northern Guatemala contains some of the most significant Mayan archeological sites in Latin America. It was in this region that the Maya civilization began, flourished, and abruptly disappeared. Remote sensing technology is helping to locate and map ancient Maya sites that are threatened today by accelerating deforestation and looting. Thematic Mapper, IKONOS, and QuickBird satellite, and airborne STAR-3i and AIRSAR radar data, combined with Global Positioning System (GPS) technology, are successfully detecting ancient Maya features such as sites, roadways, canals, and water reservoirs. Satellite imagery is also being used to map the bajos, which are seasonally flooded swamps that cover over 40% of the land surface. Through the use of various airborne and satellite sensor systems we have been able to detect and map ancient causeways, temples, reservoirs, and land forms, and locate these features on the ground through GPS technology. Recently, we have discovered that there is a strong relationship between a tropical forest vegetation signature in satellite imagery and the location of archeological sites. We believe that the use of limestone and lime plasters in ancient Maya construction affects the moisture, nutrition, and plant species of the surface vegetation. We have mapped these vegetation signatures in the imagery and verified through field survey that they are indicative of archeological sites. Through the use of remote sensing and GIS technology it is possible to identify unrecorded archeological features in a dense tropical forest environment and monitor these cultural features for their protection.
The Peten region of northern Guatemala contains some of the most significant Mayan archeological sites in Latin America. It was in this region that the Maya civilization began, flourished, and abruptly disappeared. Remote sensing technology is helping to locate and map ancient Maya sites that are threatened today by accelerating deforestation and looting. Thematic Mapper, IKONOS, and QuickBird satellite, and airborne STAR-3i and AIRSAR radar data, combined with Global Positioning System (GPS) technology, are successfully detecting ancient Maya features such as sites, roadways, canals, and water reservoirs. Satellite imagery is also being used to map the bajos, which are seasonally flooded swamps that cover over 40% of the land surface. Through the use of various airborne and satellite sensor systems we have been able to detect and map ancient causeways, temples, reservoirs, and land forms, and locate these features on the ground through GPS technology. Recently, we have discovered that there is a strong relationship between a tropical forest vegetation signature in satellite imagery and the location of archeological sites. We believe that the use o f limestone and lime plasters in ancient Maya construction affects the moisture, nutrition, and plant species of the surface vegetation. We have mapped these vegetation signatures in the imagery and verified through field survey that they are indicative of archeological sites. Through the use of remote sensing and GIS technology it is possible to identify unrecorded archeological features in a dense tropical forest environment and monitor these cultural features for their protection.
The author has identified the following significant results. Photographic and digital imagery obtained by ERTS-1 was analyzed and assigned to land features related to agricultural and forest resources. Land use and forest site evaluation maps were prepared by comparing remote sensing and ground truth data. Relationships found in this investigation between spectral signatures recorded by ERTS-1 and land features can be used for the assessment and development of agricultural and forest resources. The results are applicable to areas with ecological and geological conditions similar to those of Greece.
Oppia Quadrangle Av-10 (288-360 deg E, +/- 22 deg) is a junction of key geologic features that preserve a rough history of Asteroid (4) Vesta and serves as a case study of using geologic mapping to define a relative geologic timescale. Clear filter images, stereo-derived topography, slope maps, and multispectral color-ratio images from the Framing Camera on NASA's Dawn spacecraft served as basemaps to create a geologic map and investigate the spatial and temporal relationships of the local stratigraphy. Geologic mapping reveals the oldest map unit within Av-10 is the cratered highlands terrain which possibly represents original crustal material on Vesta that was then excavated by one or more impacts to form the basin Feralia Planitia. Saturnalia Fossae and Divalia Fossae ridge and trough terrains intersect the wall of Feralia Planitia indicating that this impact basin is older than both the Veneneia and Rheasilvia impact structures, representing Pre-Veneneian crustal material. Two of the youngest geologic features in Av-10 are Lepida (approximately 45 km diameter) and Oppia (approximately 40 km diameter) impact craters that formed on the northern and southern wall of Feralia Planitia and each cross-cuts a trough terrain. The ejecta blanket of Oppia is mapped as 'dark mantle' material because it appears dark orange in the Framing Camera 'Clementine-type' colorratio image and has a diffuse, gradational contact distributed to the south across the rim of Rheasilvia. Mapping of surface material that appears light orange in color in the Framing Camera 'Clementine-type' color-ratio image as 'light mantle material' supports previous interpretations of an impact ejecta origin. Some light mantle deposits are easily traced to nearby source craters, but other deposits may represent distal ejecta deposits (emplaced greater than 5 crater radii away) in a microgravity environment.
The author has identified the following significant results. A method for mapping snow over large areas was developed combining the possibilities of a Quantimet (QTM 72) to evaluate the exact density level of the snow cover for each individual image (or a selected section of the photo) with the higher resolution of photographic techniques. The density level established on the monitor by visual control is used as reference for the exposure time of a lithographic film, producing a clear tonal separation of all snow- and ice-covered areas from uncovered land in black and white. The data is projected onto special maps 1:500,000 or 1:100,000 showing the contour lines and the hydrographic features only. The areal extent of the snow cover may be calculated directly with the QTM 720 or on the map. Bands 4 and 5 provide the most accurate results for mapping snow. Using all four bands a separation of an old melting snow cover from a new one is possible. Regional meteorological studies combining ERTS-1 imagery and conventional sources describe synoptical evolution of meteorological systems over the Alps.
The author has identified the following significant results. Skylab photographs may be successfully utilized for preparing a reconnaissance geological map in the areas where no maps or semi-detailed maps exist. Large coverage of area and regional perspective from Skylab photographs can help better coordination in regional mapping. It is possible to delineate major structural trends and other features like mega-lineaments, geofractures, and faults, which have evaded their detection by conventional methods. The photointerpretability is better in areas dominated by sedimentary rocks. Rock units of smaller extent and having poor geomorphic expressions are difficult to map. Demarcation of quaternary river alluvium can be made with better precision and ease with the Skylab photographs. Stereoscopic viewing greatly helps in interpretation of area structures. Skylab photographs are not good for preparing geological maps larger than 1:270,000 scale.
This study presents a comprehensive framework for flood susceptibility mapping by integrating geospatial factors with both statistical and machine learning models. Thirteen Flood-related factors, including DEM, slope, TWI, NDVI, etc., are extracted as features of models, and historical flood data derived from Sentinel-1 SAR from 2018 to 2023 are used as the target variables of the models. These datasets are analyzed using a frequency-based statistical model and three machine learning models, including Random Forest, XGBoost, and CNN, to generate flood susceptibility maps. The performance of each model is evaluated through AUC; and SHAP scores are separately generated for Machine learning (ML) models to explain each feature contribution in the ML model. The generated susceptibility maps are validated by high-flood-risk locations monitored by flood sensors, BLE inundation models, and flood-prone areas suggested by the Local Community Task Force. The results indicate that the XGBoost model outperforms all other models, with an AUC of 0.92 and demonstrates the highest alignment with recommended high-flood-risk locations, while the frequency-based statistical model showed the weakest performance with an AUC of 0.65. SHAP value graphs highlight the elevation, slope, and TWI as the most influential features across all models. The susceptibility maps generated by the machine learning model show strong agreement with the BLE map and high-flood-risk areas identified by the local Community Task Force.