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Research on surface geothermal evidence has been done extensively using remote sensing techniques. For detailed remote sensing exploration on geothermal areas, UAV and airborne based were preferred over the satellite-based sensor. In this research, anomalies in surface temperature, mineral occurrence, and ammonia emission were studied on a set of airborne hyperspectral imagery from NASA, the Hyperspectral Thermal Emission Spectrometer (HyTES). High-resolution surface temperature and mineral maps were able to identify and describe the mineralogy of the mud pots and gryphons at the Davis-Schrimpf Geothermal Field, Salton Sea, California. From the surface temperature map, the surface temperature of the geothermal features wa s measured at approximately 314°K (40oC) and higher. The purest pixels from MNF transformation of the first four cleanest bands of emissivity map produce endmembers that include the geothermal indicator minerals (barite, anhydrite, quartz, gypsum). Based on the mineralogy deposits, these manifestations are classified as potassic alteration types from a porphyry system that could be an indication of an active geothermal system. This also explains that the surface features are part of the upper reservoir of the Salton Sea Geothermal Field. On the other hand, ammonia detection that was performed in this research failed to get any clear recognition from the simple image processing. It is concluded that the airborne hyperspectral imagery could be a reliable option for remote sensing geothermal exploration, as it was able to characterize the surface geothermal manifestation with quite good detail using this imagery from a wide area of survey. [ABSTRACT FROM AUTHOR]

A method based on machine learning and image processing techniques has been developed to track the surface expression of internal waves in near–real time. X-band radar scans are first preprocessed and averaged to suppress surface wave clutter and enhance the signal-to-noise ratio of persistent backscatter features driven by gradients in surface currents. A machine learning algorithm utilizing a support vector machine (SVM) model is then used to classify whether or not the image contains an internal solitary wave (ISW) or internal tide bore (bore). The use of machine learning is found to allow rapid assessment of the large dataset, and provides insight on characterizing optimal environmental conditions to allow for radar illumination and detection of ISWs and bores. Radon transforms and local maxima detections are used to locate these features within images that are determined to contain an ISW or bore. The resulting time series of locations is used to create a map of propagation speed and direction that captures the spatiotemporal variability of the ISW or bore in the coastal environment. This technique is applied to 2 months of data collected near Point Sal, California, and captures ISW and bore propagation speed and direction information that currently cannot be measured with instruments such as moorings and synthetic aperture radar (SAR). [ABSTRACT FROM AUTHOR]

We present results from complementary geological, topographic, seismic and electrical resistivity surveys at the Sagebrush Flat (SGB) site along the Clark fault (CF) strand of the San Jacinto fault zone trifurcation area southeast of Anza, California. Joint interpretation of these data sets, each with unique spatiotemporal sensitivities, allow us to better characterize the shallow (<100 m) fault zone at this structurally complex site. Geological mapping at the surface shows the CF has three main subparallel strands within a <100 m zone with varying degrees of rock damage. These strands intersect units of banded gneiss and tonalite, and various sedimentary units. Near the surface, the weathered but more intact tonalite and gneiss to the southwest have relatively high VP. The low-lying flat sedimentary basins around the two southwestern-most CF strands and elevated damaged gneiss to the northeast have lowest VP <500 m s–1. The high relief of the northeast gneiss unit may in part be explained by its extensive damage and inferred increased relative rock uplift. Resistivity imaging shows the unconsolidated dry basin sediments (maximum >1300 Ohm.m) contrasted against the compacted fine-grained (potentially wet) materials within the CF core and the Bautista Formation (minimum <40 Ohm.m), which is slightly elevated above the flat basins. The inverse relationship between VP (increases) and resistivity (decreases) in the uppermost ∼15 m can be characterized as log–log linear with slopes of –2.6 to –4. At depths >30 m, the velocity heterogeneity near the surface merges into larger-scale structures that are generally slower on the northeast side of the CF core compared to the southwest side (as much as ∼40 per cent reduction in average VP). A previous study revealed a 20–37 per cent variability in peak ground velocities across the SGB site from local earthquakes. The upper end of that range is associated with the near-surface unconsolidated sedimentary basins and northeast damaged gneiss unit. Preliminary analysis of time-dependent topography mostly shows effects of changing vegetation and anthropogenic activity. [ABSTRACT FROM AUTHOR]

The architectural landscape of high-performance computing stretches from superscalar uniprocessor to explicitly parallel systems to dedicated hardware implementations of algorithms. Single-purpose hardware can achieve the highest performance and uniprocessors can be the most programmable. Between these extremes, programmable and reconfigurable architectures provide a wide range of choice in flexibility, programmability, computational density, and performance. The UCSC Kestrel parallel processor strives to attain single-purpose performance while maintaining user programmability. Kestrel is a single-instruction stream, multiple- data stream (SIMD) parallel processor with a 512-element linear array of 8-bit processing elements. The system design focuses on efficient high-throughput DNA and protein sequence analysis, but its programmability enables high performance on computational chemistry, image processing, machine learning, and other applications. The Kestrel system has had unexpected longevity in its utility due to a careful design and analysis process. Experience with the system leads to the conclusion that programmable SIMD architectures can excel in both programmability and performance. This paper presents the architecture, implementation, applications, and observations of the Kestrel project at the University of California at Santa Cruz. [ABSTRACT FROM AUTHOR]

Focuses on detecting vegetation responses to interannual climate using the airborne visible-infrared imaging spectrometer (AVIRIS) data over a natural savanna in the Central Coast Range in California. Information on the two AVIRIS images chosen for the study; Method used to detect and quantify changes between years; Unmixing results using three endmembers.

Vineyards are sampled on multiple occasions during the growing season for a range of purposes, particularly to assess fruit maturation. The objective of this work was to determine if satellite normalized difference vegetation index (NDVI) vineyard images could be used to compute optimal spatially explicit sampling protocols for determining fruit maturation and quality, and minimize the number of locations physically sampled in a vineyard. An algorithm was designed to process Landsat images to locate three consecutive pixels that best represent the three quantile means representing the left tail, center, and right tail of the NDVI pixel population of a vineyard block. This new method (NDVI3) was compared to a commonly used method (CM8) and random sampling (R20) in 13 and 16 vineyard blocks in 2016 and 2017, respectively, in the Central Valley of California. Both NDVI3 and CM8 were highly correlated with R20 in pairwise comparisons of soluble sugars, pH, titratable acidity, and total anthocyanins. Kolmogorov-Smirnov tests indicated that NDVI pixels sampled via the NDVI3 method generally better represented the block population than pixels selected by CM8 or R20. Analysis of 24 blocks over a 3-year period indicated that sampling solutions were temporally stable. [ABSTRACT FROM AUTHOR]