ALBERT

Description: The aim of this project was to study the propagation of star formation (SF) with a self-consistent deterministic model for the interstellar gas. The questions of under what conditions does star formation propagate in this model and what are the mechanisms of the propagation are explored. Here, researchers used the deterministic Oort-type cloud fluid model of Scalo and Struck-Marcell (1984, also see the review of Struck-Marcell, Scalo and Appleton 1987). This cloud fluid approach includes simple models for the effects of cloud collisional coalescence or disruption, collisional energy dissipation, and cloud disruption and acceleration as the result of young star winds, HII regions and supernovae. An extensive one-zone parameter study is presented in Struck-Marcell and Scalo (1987). To answer the questions above, researchers carried out one-dimensional calculations for an annulus within a galactic disk, like the so-called solar neighborhood of the galactic chemical evolution. In the calculations the left-hand boundary is set equal to the right hand boundary. The calculation is obviously idealized; however, it is computationally convenient to study the first order effects of propagating star formation. The annulus was treated as if it were at rest, i.e., in the local rotating frame. This assumption may remove some interesting effects of a supersonic gas flow, but was necessary to maintain a numerical stability in the annulus. The results on the one-dimensional propagation of SF in the Oort cloud fluid model follow: (1) SF is propagated by means of hydrodynamic waves, which can be generated by external forces or by the pressure generated by local bursts. SF is not effectively propagated via diffusion or variation in cloud interaction rates without corresponding density and velocity changes. (2) The propagation and long-range effects of SF depend on how close the gas density is to the critical threshold value, i.e., on the susceptibility of the medium.

Description: Since the initial experiments nearly 50 years ago, techniques for detecting caves using airborne and spacecraft acquired thermal imagery have improved markedly. These advances are largely due to a combination of higher instrument sensitivity, modern computing systems, and processor-intensive analytical techniques. Through applying these advancements, our goals were to: (1) Determine the efficacy of methods designed for terrain analysis and applied to thermal imagery; (2) evaluate the usefulness of predawn and midday imagery for detecting caves; and (3) ascertain which imagery type (predawn, midday, or the difference between those two times) was most informative. Using forward stepwise logistic (FSL) and Least Absolute Shrinkage and Selection Operator (LASSO) regression analyses for model selection, and a thermal imagery dataset acquired from the Mojave Desert, California, we examined the efficacy of three well-known terrain descriptors (i.e., slope, topographic position index (TPI), and curvature) on thermal imagery for cave detection. We also included the actual, untransformed thermal DN values (hereafter “unenhanced thermal”) as a fourth dataset. Thereafter, we compared the thermal signatures of known cave entrances to all non-cave surface locations. We determined these terrain-based analytical methods, which described the “shape” of the thermal landscape, hold significant promise for cave detection. All imagery types produced similar results. Down-selected covariates per imagery type, based upon the FSL models, were: Predawn— slope, TPI, curvature at 0 m from cave entrance, as well as slope at 1 m from cave entrance; midday— slope, TPI, and unenhanced thermal at 0 m from cave entrance; and difference— TPI and slope at 0 m from cave entrance, as well as unenhanced thermal and TPI at 3.5 m from cave entrance. We provide recommendations for future research directions in terrestrial and planetary cave detection using thermal imagery.