Other
Scientific paper
May 2001
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2001agusm...u52a07l&link_type=abstract
American Geophysical Union, Spring Meeting 2001, abstract #U52A-07
Other
3299 General Or Miscellaneous, 8040 Remote Sensing, 8429 Lava Rheology And Morphology, 8450 Planetary Volcanism (5480)
Scientific paper
Lava flow surfaces preserve information on flow rheology and emplacement in the form of ridges, crease structures, blocks, folds, etc. These morphologies combine to create complicated structures and topographies. Using a 2-D S-transform analysis, which identifies the frequency and orientation of localized signals (structures), we have developed a technique to identify and separate these complicated topographies back into their different component morphologies. To test this technique we have analyzed a digital elevation model (DEM) with a 1-m pixel spacing of the Medicine Lake Dacite Flow (MLD), Medicine Lake, California. The MLD Flow has an estimated volume of 0.1 km 3 and consists of a single flow lobe with a range of surface morphologies (ridges, creases, diapirs and spines). Preliminary results for the frequency bands corresponding to wavelengths of 20-30 m and 30-60 m include three major observations. 1) The technique identifies structures corresponding to ridges and creases visible in the topographic data. Spines and blocks are characterized by frequencies that are currently outside of our range of analysis. 2) The signals for structures that correspond to ridges and creases are distinct and can be used to distinguish the two. Ridges are characterized by a single low frequency signal (30-60 m range), whereas creases are characterized by high frequency (20-30 m range) and low frequency (30-60 m range) signals with different orientations. These signals correspond to individual creases and en echelon groups of creases, respectively. 3) The technique identifies zones within the flow with sharply defined boundaries and a narrow range of structural orientations. These patches suggest that the flow developed as a group of large plates floating on top of the liquid lava flow and/or in response to underlying topography. The location of these plates and the orientation of structures vary with frequency band, suggesting an overprinting by multiple deformation events. Our results show that the S-transform approach allows the rapid, remote analysis of lava flow surface topography. This should be of value for the analysis of both on going lava flows and lava flows with difficult accessibility, including those on other planets.
Lescinsky David T.
Mansinha Lalu
Mayer G. S.
No associations
LandOfFree
S-transform Analysis of Digital Topography: Automated Characterization of Silicic Lava Flow Morphologies does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with S-transform Analysis of Digital Topography: Automated Characterization of Silicic Lava Flow Morphologies, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and S-transform Analysis of Digital Topography: Automated Characterization of Silicic Lava Flow Morphologies will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-1272524