Mathematics – Logic
Scientific paper
May 2007
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2007agusm.p41a..03f&link_type=abstract
American Geophysical Union, Spring Meeting 2007, abstract #P41A-03
Mathematics
Logic
5464 Remote Sensing, 5470 Surface Materials And Properties, 5494 Instruments And Techniques, 6964 Radio Wave Propagation
Scientific paper
Quantitative factors such as RMS height, correlation lengths and surface slope derived from fine-scale topographic datasets hold the potential for characterizing surface morphology in relation to its underlying geologic processes. In an attempt to better understand the relationships between topographic roughness characteristics and geologic processes responsible for creating a distinct surface morphology, we utilize ground-based terrestrial LiDAR and coincidental orthorectified imagery to quantify the variability in RMS heights and correlation lengths. The purpose of this study is to understand directly how various topographic data collection techniques such as LiDAR and manual field-based measurements compare to one another and which techniques are most appropriate for characterizing topography at various scales. Topographic data from several platforms were acquired over desert surfaces in the Mojave Desert near Palm Springs, California and southwestern Arizona. The desert surfaces imaged in the Mojave contained average rock sizes ranging from decimeters to a maximum size near one meter and revealed wide variations in RMS heights and correlation lengths, in keeping with the highly variable surface. Alternately, the Arizona site exhibits less topographic variability and consistent statistics. The data are useful for characterizing the roughness of surfaces for a variety of disciplines, such as penetration of remote sensing signals, upwelling of radiation and characterizing the genetic origin of surfaces. Furthermore, these data become essential to airborne and ground-based imaging sensors and understanding how topographic irregularities affect data fidelity.
Anderson Stephen W.
Arcone Steven A.
Bulmer Mark H.
Finnegan D. C.
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