Glaciares de Chile
- Glaciares del Volcán Melimoyu
- Glaciares del Nevado de Queulat
- Glaciares del Volcán Mentolat
- Glaciares del Volcán Cay
- Glaciares del Volcán Macá
- Glaciares del Volcán Hudson
- Glaciar Erasmo
- Glaciar San Rafael
- Glaciar San Quintín
- Campo de Hielo Norte
- Glaciar Nef
- Glaciar Colonia
- Lago Cachet II
- Glaciar Steffen
- Glaciares del Monte San Lorenzo
- Glaciar Jorge Montt
- Glaciar Lucía
- Glaciar Los Moscos
- Glaciar Bernardo
- Glaciar O’Higgins
- Glaciar Chico
- Campo de Hielo Sur
- Campo de Hielo Sur
- Glaciar Témpanos
- Glaciar Pío XI
- Glaciar Viedma
- Glaciar Perito Moreno
- Glaciar Dickson
- Glaciar Olvidado
- Glaciar Grey
- Glaciar Amalia
- Glaciar Pingo
- Glaciar Tyndall
- Glaciar Balmaceda
- Isla Desolación
- Glaciares de la Isla Santa Inés
- Seno Gabriel
- Glaciar Schiaparelli
- Glaciar Marinelli
- Fiordo Parry
- Cordillera Darwin
- Glaciar Garibaldi
- Glaciar Roncagli
- Glaciares Isla Hoste
Antártica
"Optical Flow Applied to time-lapse image series to estimate glacier motion in the Southern Patagonia ice field"
Lannutti, E.; M.G. Lenzano; C. Toth; L. Lenzano & A. Rivera (2016) : “Optical Flow Applied to time-lapse image series to estimate glacier motion in the Southern Patagonia ice field” Remote Sensing and Spatial Information Sciences, XLI-B8.
Resumen / Abstract.
In this work, we assessed the feasibility of using optical flow to obtain the motion estimation of a glacier. In general, former investigations used to detect glacier changes involve solutions that require repeated observations which are many times based on extensive field work. Taking into account glaciers are usually located in geographically complex and hard to access areas, deploying time-lapse imaging sensors, optical flow may provide an efficient solution at good spatial and temporal resolution to describe mass motion. Several studies in computer vision and image processing community have used this method to detect large displacements. Therefore, we carried out a test of the proposed Large Displacement Optical Flow method at the Viedma Glacier, located at South Patagonia Icefield, Argentina. We collected monoscopic terrestrial time-lapse imagery, acquired by a calibrated camera at every 24 hour from April 2014 until April 2015. A filter based on temporal correlation and RGB color discretization between the images was applied to minimize errors related to changes in lighting, shadows, clouds and snow. This selection allowed discarding images that do not follow a sequence of similarity. Our results show a flow field in the direction of the glacier movement with acceleration in the terminus. We analyzed the errors between image pairs, and the matching generally appears to be adequate, although some areas show random gross errors related to the presence of changes in lighting. The proposed technique allowed the determination of glacier motion during one year, providing accurate and reliable motion data for subsequent analysis.