The study of fast geomorphic changes in mountain channels and hillslopes, driven by intense geomorphic processes, requires frequent and detailed topographic surveys. In the last two decades, high-resolution topography (HRT) has provided new opportunities in the Earth Sciences. These have benefited from important developments in surveying techniques, methods, sensors, and platforms. Between these, the application of structure-from-motion (SfM) photogrammetry has become a widely used method to acquire HRT and high-resolution orthomosaics at multiple temporal and spatial scales. SfM photogrammetry has revolutionized the possibility to collect multi-temporal HRT in rugged or inaccessible environments like that observed in debris-flow catchments. However, appropriate workflows incorporating survey planning, data acquisition, post-processing, and error and uncertainty assessment are required, especially when multi-temporal surveys are compared to study topographic changes through time. In this paper, we present a workflow to acquire and process HRT. The workflow was applied in a debris-flow channel of the Moscardo Torrent (Eastern Italian Alps). Due to the topographic complexity of the study area, the SfM surveys were carried out integrating photos obtained from an unmanned aerial vehicle and from the ground. This integration guarantees high data density and avoids shadows. Eight photogrammetric surveys were collected between December 2015 and August 2017. In this time interval, five debris flows occurred. The surveying and data processing procedure described in the workflow permitted to summarize and integrate all the analysis steps and helped to identify and minimize potential sources of error in the multi-temporal SfM data (what we consider here 4D). Our case study demonstrates how the developed workflow presented here allows studying the geomorphic effects of debris flows and check dams functionality in mountain environments.

Monitoring topographic changes through 4D-structure-from-motion photogrammetry: application to a debris-flow channel

Llena M.;
2018

Abstract

The study of fast geomorphic changes in mountain channels and hillslopes, driven by intense geomorphic processes, requires frequent and detailed topographic surveys. In the last two decades, high-resolution topography (HRT) has provided new opportunities in the Earth Sciences. These have benefited from important developments in surveying techniques, methods, sensors, and platforms. Between these, the application of structure-from-motion (SfM) photogrammetry has become a widely used method to acquire HRT and high-resolution orthomosaics at multiple temporal and spatial scales. SfM photogrammetry has revolutionized the possibility to collect multi-temporal HRT in rugged or inaccessible environments like that observed in debris-flow catchments. However, appropriate workflows incorporating survey planning, data acquisition, post-processing, and error and uncertainty assessment are required, especially when multi-temporal surveys are compared to study topographic changes through time. In this paper, we present a workflow to acquire and process HRT. The workflow was applied in a debris-flow channel of the Moscardo Torrent (Eastern Italian Alps). Due to the topographic complexity of the study area, the SfM surveys were carried out integrating photos obtained from an unmanned aerial vehicle and from the ground. This integration guarantees high data density and avoids shadows. Eight photogrammetric surveys were collected between December 2015 and August 2017. In this time interval, five debris flows occurred. The surveying and data processing procedure described in the workflow permitted to summarize and integrate all the analysis steps and helped to identify and minimize potential sources of error in the multi-temporal SfM data (what we consider here 4D). Our case study demonstrates how the developed workflow presented here allows studying the geomorphic effects of debris flows and check dams functionality in mountain environments.
Cucchiaro S.; Cavalli M.; Vericat D.; Crema S.; Llena M.; Beinat A.; Marchi L.; Cazorzi F.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/737780
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