Holocene flows of the Cima volcanic field, Mojave Desert (California), Part 1: Remote sensing and multi-scale morphometry

Abstract:

Lava flow morphology and texture can provide insight into rheological and other physical properties of the flow. Studies of terrestrial and extra-terrestrial lava flows rely heavily on remotely sensed observations. This research aims to quantify micromorphology and texture of a Holocene lava flow in the Cima volcanic field (eastern California) using digital elevation models and radar backscatter imagery. We are testing the hypothesis that spatial patterns in morphometry and backscatter roughness correspond with varying rheological conditions during emplacement. The site is ideally suited for morphological study owing to the youthfulness of the flow, as well as the lack of vegetation and minimal surface erosion resulting from the high desert climate. The studied lava flow spans approximately 2.5 km and exhibits well defined lobate forms and lava ropes with clear A’a’ to Pahoehoe transitions. This study assesses lava flow micromorphology using a very high resolution (5 cm pixel) digital elevation model (DEM). The DEM was constructed from low-altitude aerial photos acquired using a remotely-controlled model aircraft. In addition to the DEM, the resulting orthoimagery provided a basis for distinguishing pristine lava flow surfaces from areas covered by vegetation and/or eolian deposits. Longer-wavelength morphology (spatial scales greater than 1 meter) is analyzed using a 50 cm pixel DEM produced using stereoscopic NAPP aerial photographs. Roughness estimates are compared with radar backscatter images including steeply incident C-band (5.6 cm wavelength) and L-band (24 cm wavelength) satellite data, as well as shallow incidence Ku-band data (1.7 cm wavelength) acquired using a ground-based imaging radar from an adjacent cinder cone. Photogrammetry and radar provide complementary information on lava flow morphology and micromorphological roughness, which are assessed at different spatial scales using general statistics, as well as the local hypsometric integral.