Identification and mapping of landforms in geomorphology is based on geological and geomorphological survey and interpretation of topographic maps and aerial photos. The traditionally techniques are affected by a high degree of uncertainty. In order to reduce this type of errors new analysis processes calibrated elaborations on Digital Terrain Models (DTM). To this end, we have used SRTM (Shuttle Radar Topography Mission) digital elevation data for Italy. To investigate the question of model sensitivity to various remote-sensing techniques for scaling or aggregation of landscape attributes, it is necessary to work within the context of a given model's data requirements and sensitivity. Model sensitivity to input data error propagation can be evaluated to specify the form and acceptable limits of accuracy of input data sets describing land surface attributes. For certain geomorphological processes that are strongly dependent on tectonic evolution in a certain areas, much of the process variations at sufficiently large spatial and temporal scales, can be explained with direct observations of geometric system using landscape satellite. Our method of analysis is based on a delineation of surface landscape attribute using a multipixel delineation algorithm. The algorithm is designed to map, on a regional scale, surface drainage patterns that may include diffuse flow, curvature and relief analysis. Some landforms (e.g. alluvial fans) show a close correspondence between their limits (curvature and relief), and the direction and diffusion of hydrological drainage pattern, so this type of analysis can represent an objective method to recognize these landforms and to understand their evolution (e.g. telescopic alluvial fan depending on normal faulting). We present a preliminary analysis of SRTM data from Umbria Region. The algorithm is a significant improvement and images of model surface flow provide an excellent means of using SRTM data to study interactions between faulting and drainage patterns. As an example, we discuss some observations of alluvial fans formations induced by the propagation of the trust fault system.

Mapping Landforms in Geomorphology Using SRTM Data.

TARAMELLI, Andrea;MELELLI, Laura
2004

Abstract

Identification and mapping of landforms in geomorphology is based on geological and geomorphological survey and interpretation of topographic maps and aerial photos. The traditionally techniques are affected by a high degree of uncertainty. In order to reduce this type of errors new analysis processes calibrated elaborations on Digital Terrain Models (DTM). To this end, we have used SRTM (Shuttle Radar Topography Mission) digital elevation data for Italy. To investigate the question of model sensitivity to various remote-sensing techniques for scaling or aggregation of landscape attributes, it is necessary to work within the context of a given model's data requirements and sensitivity. Model sensitivity to input data error propagation can be evaluated to specify the form and acceptable limits of accuracy of input data sets describing land surface attributes. For certain geomorphological processes that are strongly dependent on tectonic evolution in a certain areas, much of the process variations at sufficiently large spatial and temporal scales, can be explained with direct observations of geometric system using landscape satellite. Our method of analysis is based on a delineation of surface landscape attribute using a multipixel delineation algorithm. The algorithm is designed to map, on a regional scale, surface drainage patterns that may include diffuse flow, curvature and relief analysis. Some landforms (e.g. alluvial fans) show a close correspondence between their limits (curvature and relief), and the direction and diffusion of hydrological drainage pattern, so this type of analysis can represent an objective method to recognize these landforms and to understand their evolution (e.g. telescopic alluvial fan depending on normal faulting). We present a preliminary analysis of SRTM data from Umbria Region. The algorithm is a significant improvement and images of model surface flow provide an excellent means of using SRTM data to study interactions between faulting and drainage patterns. As an example, we discuss some observations of alluvial fans formations induced by the propagation of the trust fault system.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11391/21098
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