Regional early warning systems for landslides rely on historic data to forecast future events and to verify and improve alarms. However, databases of landslide events are often spatially biased towards roads or other infrastructure, with few reported in remote areas. In this study, we demonstrate how Google Earth Engine can be used to create multi-temporal change detection image composites with freely available Sentinel-1 and -2 satellite images, in order to improve landslide visibility and facilitate landslide detection. First, multispectral Sentinel-2 images were used to map landslides triggered by a summer rainstorm in Jølster (Norway), based on changes in the normalised difference vegetation index (NDVI) between pre- and post-event images. Pre- and post-event multi-temporal images were then created by reducing across all available images within one month before and after the landslide events, from which final change detection image composites were produced. We used the mean of backscatter intensity in co- (VV) and cross-polarisations (VH) for Sentinel-1 synthetic aperture radar (SAR) data and maximum NDVI for Sentinel-2. The NDVI-based mapping increased the number of registered events from 14 to 120, while spatial bias was decreased, from 100% of events located within 500 m of a road to 30% close to roads in the new inventory. Of the 120 landslides, 43% were also detectable in the multi-temporal SAR image composite in VV polarisation, while only the east-facing landslides were clearly visible in VH. Noise, from clouds and agriculture in Sentinel-2, and speckle in Sentinel-1, was reduced using the multi-temporal composite approaches, improving landslide visibility without compromising spatial resolution. Our results indicate that manual or automated landslide detection could be significantly improved with multi-temporal image composites using freely available earth observation images and Google Earth Engine, with valuable potential for improving spatial bias in landslide inventories. Using the multi-temporal satellite image composites, we observed significant improvements in landslide visibility in Jølster, compared with conventional bi-temporal change detection methods, and applied this for the first time using VV-polarised SAR data. The GEE scripts allow this procedure to be quickly repeated in new areas, which can be helpful for reducing spatial bias in landslide databases.

Strong cultural heritage management relies on a thorough evaluation of the threats faced by heritage sites, both in the present and in the future. In this study, we analysed the changes in the position of Hiorthhamn shoreline (Svalbard), which is affecting coastal cultural heritage sites, for a period of 93 years (1927–2020). Shoreline changes were mapped by using maps, ortophotos, drone images, terrestrial laser scanning (TLS), and topographic surveys. Also, TLS was used to 3D document the endangered coastal cultural heritage sites. Detailed sedimentological and morphological mapping was made in the field and from the newly acquired drone images in order to understand shoreline-landscape interaction and to depict changes occurring from 2019 to 2020. Short-term (2019–2020) and long-term (1927–2020) shoreline erosion/accretion was made with the help of the Digital Shoreline Analysis System (DSAS) and prompted a subdivision of three sectors, based on change pattern. Compared to a previous long-term analysis (1927–2019), this year’s average erosion rate analysis (expressed by the EPR parameter) for the 93-year period is −0.14 m/yr. This shift in mean development is due to a newly formed spit-bar in Sector 2. Referring strictly to Sector 1, where the protected cultural heritage objects are located, the erosion rate increased from the previous analysis of –0.76 m/yr to −0.77 m/yr. The shoreline forecast analysis highlights that half of the protected cultural heritage objects will likely disappear over the next decade and almost all the cultural heritage objects analysed in this study will disappear in roughly two decades. This shows the great danger the Arctic’s cultural heritage sites is in if no mitigation measures are undertaken by the local authorities.

Hiorthhamn is an abandoned Norwegian coal mining settlement with a loading dock and a lot of industrial infrastructure left in the coastal zone. In this study, changes in the position of 1.3 km of the Hiorthhamn shoreline, which affect cultural heritage, is described for a time-period spanning 92 years (1927–2019). The shoreline positions were established based on a map (1927), orthophotos (2009) and a topographic survey with differential Global Positioning System (GPS) (summer 2019). Detailed geomorphological and surface sediment mapping was conducted to form a framework for understanding shoreline-landscape interaction. The shoreline was divided into three sectors to calculate the erosion/stability/accretion rates by using the DSAS (Digital Shoreline Analysis System) extension of ArcGIS. The DSAS analysis showed very high erosion in Sector 1, while Sectors 2 and 3 showed moderate accretion and moderate erosion, respectively. Sector 1 is geologically composed of easily erodible sorted beach sediments and protected remains from the mining industry such as wrecks of heavy machines, loading carts, wagons and rusty tracks that are directly exposed to coastal erosion. The all-sector average shoreline erosion rate (EPR parameter) for the 92 years period was −0.21 m/year. The high shoreline erosion rates in Sector 1, together with the high potential damage to cultural heritage, supports the urgent need of continued coastal monitoring and sustainable management of cultural heritage in Hiorthhamn.