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Eruptions of active volcanoes in the presence of snow and ice can cause dangerous floods, avalanches and lahars,threatening millions of people living close to such volcanoes. Colombia’s deadliest volcanic hazard in recordedhistory was caused by Nevado del Ruiz Volcano. On November 13, 1985, a relatively small eruption triggeredenormous lahars, killing over 23,000 people in the city of Armero and 2,000 people in the town of Chinchina.Meltwater from a glacier capping the summit of the volcano was the main contributor to the lahars. From 2010 topresent, increased seismicity, surface deformation, ash plumes and gas emissions have been observed at Nevadodel Ruiz. The DEM is a key parameter for accurate prediction of the pathways of lava flows, pyroclastic flows, andlahars. While satellite coverage has greatly improved the quality of DEMs around the world, volcanoes remain achallenging target because of extremely rugged terrain with steep slopes and deeply cut valleys. In this study, threetypes of remote sensing data sources with different spatial scales (satellite radar interferometry, terrestrial radarinterferometry (TRI), and structure from motion (SfM)) were combined to generate a high resolution DEM (10 m)of Nevado del Ruiz. 1) Synthetic aperture radar (SAR) images acquired by TSX/TDX satellites were applied togenerate DEM covering most of the study area. To reduce the effect of geometric distortion inherited from SARimages, TSX/TDX DEMs from ascending and descending orbits were merged to generate a 10×10 m DEM. 2) TRIis a technique that uses a scanning radar to measure the amplitude and phase of a backscattered microwave signal.It provides a more flexible and reliable way to generate DEMs in steep-slope terrain compared with TSX/TDXsatellites. The TRI was mounted at four different locations to image the upper slopes of the volcano. A DEM with5×5 m resolution was generated by TRI. 3) SfM provides an alternative for shadow zones in both TSX/TDX andTRI images. It is a low-cost and effective method to generate high-quality DEMs in relatively small spatial scales.More than 2000 photos were combined to create a DEM of the deep valley in the shadow zones. DEMs from theabove three remote sensing data sources were merged into a final DEM with 10×10 m resolution. The effect ofthis improved DEM on hazard assessment can be evaluated using numerical flow models.

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Presented at the 19th EGU General Assembly on April 26th, 2017 in Vienna, Austria