ABSTRACT This chapter demonstrates a nondestructive, multispectral approach to evaluating chemical and spatial heterogeneities within mudstone fabrics. A combination of laser scanning confocal microscopy (LSCM) and scanning electron microscopy (SEM) was used to document nanometer- to millimeter-scale microtextures in mudstones. Additionally, micro-Fourier transform infrared (micro-FTIR) spectroscopy was used to identify both clay minerals and compositional structures, such as aromatic and aliphatic components in kerogen. A set of organic-rich mudstones with thermal maturities ranging from immature to oil prone were analyzed and used as examples to document the multispectral, multiscale approach. This work demonstrates the different spectral approaches and their applicability to the analysis of organic-rich mudstones. Single-channel fluorescence images collected with various excitation/emission wavelengths were used to access microtextural details in mudstones, whereas multichannel composite fluorescence images were used to evaluate relative thermal maturity among samples. In addition, SEM backscatter and energy dispersive X-ray microscopy were used to calibrate fluorescence signals to mineralogy and provide submicron information on grain boundaries and microfabrics. Micro-FTIR chemical maps represent the spatial distribution of chemical information related to properties of interest such as the presence and character of hydrocarbons and clay minerals. The infrared (IR) spectra associated with organic matter were also analyzed for quantitative indicators of thermal maturity. Opportunities for image processing and analysis that have the capability to integrate these multiscale, multispectral approaches are discussed for a more robust understanding of mudstone microfabrics, heterogeneity, and their impact on mudstone reservoir quality.

Abstract Many volcanoes around the world are poorly monitored and new eruptions increase the need for rapid ground-based monitoring, which is not always available in a timely manner. Initial observations therefore are commonly provided by orbital remote sensing instruments at different temporal, spatial and wavelength scales. Even at well-monitored volcanoes, satellite data still play an important role. The ASTER (Advanced Spaceborne Thermal Emission Radiometer) orbital sensor provides moderately high spatial resolution images in multiple wavelength regions; however, because ASTER is a scheduled instrument, the data are not acquired over specific targets every orbit. Therefore, in an attempt to improve the temporal frequency of ASTER specifically for volcano observations and to have the images integrate synergistically with high temporal resolution data, the Urgent Request Protocol (URP) system was developed in 2004. Now integrated with both the AVHRR (Advanced Very High Resolution Radiometer) and MODIS (Moderate Resolution Imaging Spectroradiometer) hotspot monitoring programmes, the URP acquires an average of 24 volcanic datasets every month and planned improvements will allow this number to increase in the future. New URP data are sent directly to investigators responding to the ongoing eruption, and the large archive is also being used for retrospective science and operational studies for future instruments. The URP Program has been very successful over the past decade and will continue until at least 2017 or as long as the ASTER sensor is operational. Several volcanic science examples are given here that highlight the various stages of the URP development. However, not all are strictly focused on effusive eruptions. Rather, these examples were chosen to demonstrate the wide range of applications, as well as the general usefulness of the higher resolution, multispectral data of ASTER.

Abstract The Volcano Sensor Web (VSW) is a globe-spanning net of sensors and applications for detecting volcanic activity. Alerts from the VSW are used to trigger observations from space using the Earth Observing-1 ( EO-1 ) spacecraft. Onboard EO-1 is the Autonomous Sciencecraft Experiment (ASE) advanced autonomy software. Using ASE has streamlined spacecraft operations and has enabled the rapid delivery of high-level products to end-users. The entire process, from initial alert to product delivery, is autonomous. This facility is of great value as a rapid response is vital during a volcanic crisis. ASE consists of three parts: (1) Science Data Classifiers, which process EO-1 Hyperion data to identify anomalous thermal signals; (2) a Spacecraft Command Language; and (3) the Continuous Activity Scheduling Planning Execution and Replanning (CASPER) software that plans and replans activities, including downlinks, based on available resources and operational constraints. For each eruption detected, thermal emission maps and estimates of eruption parameters are posted to a website at the Jet Propulsion Laboratory, California Institute of Technology, in Pasadena, CA. Selected products are emailed to end-users. The VSW uses software agents to detect volcanic activity alerts generated from a wide variety of sources on the ground and in space, and can also be easily triggered manually.

Abstract Developments in spaceborne Earth Observation (EO) sensor technology over the last decade, combined with well-tested physical models and multispectral data-processing techniques developed from the early 1980s, have paved the way to the global monitoring of volcanoes by sensors of metric, decametric, kilometric and multi-kilometric spatial resolution. Such variable geometries provide for revisit intervals ranging from about monthly – at high-spatial resolution in Low-Earth Orbit – to less than 5 min – at low-spatial resolution, from geostationary platforms. There are currently about 20 spacecrafts available for carrying out 24/7 quantitative observations of volcanic unrest, at all resolutions and as close as possible to real-time. We show some successful examples of synergetic EO on volcanoes on three continents from 10 different payloads, automatically processed with three, end-to-end unsupervised procedures, on eight major eruptions and a lava lake between 2006 and 2014.

Abstract We present a novel method for interpreting time series of multispectral observations of volcanic eruptions. We show how existing models relating to radiance and area emplacement can be generalized into an integration-convolution of a Net Area Emplacement (NAE) function and a cooling function, assuming all surfaces follow the same cooling curve. The NAE describes the variation in the rate of emplacement of hot material with time and temperature, while the cooling function describes the cooling of a hot surface with time. Discretizing the integration-convolution equation yields an underdetermined matrix equation that we solve using second-order Tikhonov regularization to stabilize the solution. We test the inversion by modelling plausible NAE surfaces, calculating the radiances, adding noise and inverting for the original surface. Three or more spectral bands are required to capture the overall shape of the NAE, and recovering specific quantities is difficult. Single wavebands that yield flat kernels recover the total area emplacement curve (rate of increase of hot area – the integral of the NAE with respect to temperature) surprisingly well due to their property of conserving NAE, suggesting novel methods for calculating area emplacement rates (and effusion rates) from time series of satellite images and radiometer measurements.

Warford Ranch is a small “drive-in” shield volcano covering an area of ~2 by 3 km west of Phoenix, and it is accessible from Interstate Highway 8 near Gila Bend, Arizona. The basaltic shield is superposed on silicic lavas, granodiorites, and alluvial deposits and is part of the Sentinel-Arlington volcanic field. Dated at 3.19 Ma, the shield volcano is sufficiently young to preserve the original morphology, but it also shows the effects of moderate weathering, development of desert varnish, and the formation of caliche deposits. Imaged in both color near-infrared (IR) and in thermal infrared multispectral scanner (TIMS) data, these various units afford the opportunity to conduct simple remote-sensing mapping, which can then be field tested. In addition to the lava flows comprising the shield, pyroclastic deposits and dikes are also present. The compact size of the volcano enables the entire feature to be examined in the field in one day. With short introductory discussion, participants of nearly any background can be introduced to the fundamentals of remote sensing, igneous rocks, field methods, and evaluation of the volcanic history of a small volcano.

The Gruithuisen region in northern Oceanus Procellarum on the Moon contains three distinctive domes interpreted as nonmare volcanic features of Imbrian age. A 4 d extravehicular activity (EVA), four-astronaut sortie mission to explore these enigmatic features and the surrounding terrain provides the opportunity to address key outstanding lunar science questions. The landing site is on the mare south of Gruithuisen 3 (36.22°N, 40.60°W). From this site, diverse geologic terrains and features are accessible, including highlands, dome material, mare basalts, multiple craters, small rilles, and a negative topographic feature of unknown origin. Preliminary mission planning is based on Clementine multispectral data, Lunar Prospector geochemical estimates, and high-resolution (0.5 m/pixel) stereo images from the Lunar Reconnaissance Orbiter Narrow Angle Camera. Science objectives for the mission include: (1) determining the nature of the domes, (2) identifying and measuring the distribution of any potassium, rare earth elements, and phosphorus (KREEP)- and thorium-rich materials, (3) collecting samples for age dating of key units to investigate the evolution of the region, and (4) deploying a passive seismic grid as part of a global lunar network. Satisfying the science objectives requires 7 h, ~20 km round-trip EVAs, and significant time driving on slopes up to ~15°.

Abstract Two recent papers, “Utility of high-altitude infrared spectral data in mineral exploration: Application to northern Patagonia Mountains, Arizona,” by Berger et al. (2003), and “Mapping hydrothermally altered rocks at Cuprite, Nevada, using the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), a new satellite-imaging system,” by Rowan et al. (2003), make a distinctive mark on the use of airborne and satellite hyperspectral imaging as an exploration tool. These two papers deal with imaging of the Earth’s surface using the visible (0.4 μ m) to near infrared (2.5 μ m) part of the electromagnetic spectrum to map various mineral species. Depending on their structure and molecular bonding, minerals reflect and absorb the electromagnetic spectrum in unique ways. A large group of minerals have distinct electromagnetic signatures that make it possible to identify them from imaging systems that map the range of the electromagnetic spectrum between 0.5 and 2.5 μ m. These papers represent two distinct approaches. The first paper, by Berger et al., discusses the use of the AVIRIS (Airborne Visible Infrared Imaging Spectrometer) scanner, which provides high-resolution reflectance measurements in the spectral domain (224 channels between 0.4 and 2.45 μ m) and variable spatial resolution (20 m), dependent on aircraft altitude. The second paper, by Rowan et al., discusses the use of the ASTER satellite scanner, which offers a limited range of spectra at three spatial resolutions (15, 30, and 90 m). ASTER measures reflectance radiation in 3 bands within the 0.52- to 0.86- μ m range (visible-near-infrared) at 15-m spatial resolution, and 6 bands between 1.00 and 2.43 μ m (short wave infrared) at 30-m spatial resolution. Emitted radiation is measured in 5 bands between 8.125 and 11.650 μ m (thermal infrared) with a 90-m spatial resolution. The main advantage of the AVIRIS sensor is the level of spectral detail, which provides accurate measurements of reflectance and absorption features of minerals that enables detailed mineral mapping. Its main disadvantages, however, are the extensive processing required to make the reflectance spectra useful, and its limited spatial coverage and acquisition cost based on programmed flights. In contrast, the main advantage of the ASTER sensor is that it measures key portions of the visible, near-infrared, and thermal infrared spectra of minerals for large-scale mapping projects, whereas its main disadvantage is that the data represent only portions of the electromagnetic spectrum and some minerals cannot be distinctively mapped. In addition, the lower spatial resolution in the near-and thermal infrared portions of the spectrum makes it more difficult to map at detailed scales.