Abstract. Accurate and timely information on avalanche occurrence is key for avalanche warning, crisis management and avalanche documentation. Today such information is mainly available at isolated locations provided by observers in the field. The achieved reliability, considering accuracy, completeness and reliability of the reported avalanche events, is limited. In this study we present the spatially continuous mapping of a large avalanche period in January 2018 covering the majority of the Swiss Alps (12 500 km2). We tested different satellite sensors available for rapid mapping during the first avalanche period. Based on these experiences, we tasked SPOT6 and SPOT7 for data acquisition to cover the second, much larger avalanche period. We manually mapped the outlines of 18 737 individual avalanche events, applying image enhancement techniques to analyze regions in the shade as well as in brightly illuminated ones. The resulting dataset of mapped avalanche outlines, having unique completeness and reliability, is evaluated to produce maps of avalanche occurrence and avalanche size. We validated the mapping of the avalanche outlines using photographs acquired from helicopters just after the avalanche period. This study demonstrates the applicability of optical, very high spatial resolution satellite data to map an exceptional avalanche period with very high completeness, accuracy and reliability over a large region. The generated avalanche data are of great value in validating avalanche bulletins, in completing existing avalanche databases and for research applications by enabling meaningful statistics on important avalanche parameters.

Accurate and timely information on avalanche occurrence are key for avalanche warning, crisis 10 management and avalanche documentation. Today such information is mainly available at isolated locations provided by observers in the field. The achieved reliability considering accuracy, completeness and reliability of the reported avalanche events is limited. In this study we present the spatial continuous mapping of a large avalanche period in January 2018 covering the majority of the Swiss Alps (12'500 km 2 ). 15We tested different satellite sensors available for rapid mapping during a first avalanche period. Based on these experiences, we tasked SPOT6/7 data for data acquisition to cover the second, much larger avalanche period. We manually mapped the outlines of 18'737 individual avalanche events, applying image enhancement techniques to analyze regions in cast shadow as well as brightly illuminated ones. 20The resulting dataset of mapped avalanche outlines, having a unique completeness and reliability, is evaluated to produce maps of avalanche occurrence and avalanche size. We validated the mapping of the avalanche outlines using photographs acquired from helicopters just after the avalanche period.This study demonstrates the applicability of optical, very high spatial resolution satellite data to map an 25 exceptional avalanche period with very high completeness, accuracy and reliability over a large region.

Archival aerial imagery (AAI) represents a unique and relatively unexploited resource for assessing long-term environmental changes at a very high spatial resolution. A major constraint for the wider use of AAI often lies in the difficulties of establishing precise geo-referencing, namely in the difficult and time-consuming task of assigning ground reference through manual digitization of Ground control points (GCPs). We present a highly automated photogrammetric workflow for orientation of AAI. The workflow substitutes manual GCP measurements by generating image matches to a digital reference. The resulting abundant observations are algorithmically filtered and used in a bundle block adjustment (BBA) to obtain final image orientations. The proposed workflow has successfully been employed to process a complete coverage of AAI over the territory of Switzerland based on images acquired between 1985 and 1991. The accuracies obtained from the orientation process are very satisfying and allow for generating meaningful 2D and 3D products. The absolute accuracy for derived orthophotos and their mosaics is about 1 m. The relative accuracies are in the subpixel range and allow for generation of country-wide Digital surface models (DSMs) through dense-image matching. The obtained accuracies are comparable to those obtained at the authors’ affiliation using classical workflows that involve manual GCP identification from digital reference data. With regard to human working time, the workflow has, in our case, proven to be at least five times more efficient than classical workflows whilst the required computational resources are very moderate.