Remote landslide mapping, field validation and model development – An example from Kravarsko, Croatia

The Kravarsko settlement area, in northern Croatia, has multiple landslides and damage to buildings and infrastructure caused by landslides. However, actual landslide investigation data for the wider Kravarsko area (pilot area PA1) is relatively sparse and no landslide inventory or typical landslide model exists. The aim of this research was to develop such a landslide inventory by integrating new approaches in geohazard research such as remote landslide mapping from high resolution digital elevation models (DEMs) and current and historical aerial images with existing and new geological data related to landslides. The conclusion is that detailed DEMs are more than adequate for the development of reliable landslide inventories but field checks are still necessary to account for the specific set of natural and man-made conditions found in the research area. The landslide inventory developed for Kravarsko has been field validated in a smaller validation area (VA1) and a typical simplified landslide model for PA1/VA1 was developed. Within the model, sliding is interpreted as complex with multiple generations of sliding and multiple sliding surfaces. Based on the analysis undertaken and the available field data, around 10-20% of urban structures are endangered in the Kravarsko area and anthropogenic activity was determined as an important landslide triggering factor for landslide activation or reactivation. Still the question remains of how to quantify the anthropogenic influence? The developed landslide inventory for PA1/VA1 could be used for local urban planning/development and endangerment assessment/evaluation

A multidisciplinary approach to landslide monitoring in the Arctic: Case study of the March 2018 ML 1.9 seismic event near the Karrat 2017 landslide

The landslide of 17 June 2017 at Karrat Fjord, central West Greenland, triggered a tsunami that caused four fatalities. The catastrophe highlighted the need for a better understanding of landslides in Greenland and initiated a recent nation-wide landslide screening project led by the Geological Survey of Denmark and Greenland (GEUS; see also Svennevig (2019) this volume). This paper describes an approach for compiling freely available data to improve GEUS’ capability to monitor active landslides in remote areas of the Arctic in near real time. Data include seismological records, space borne Synthetic Aperture Radar (SAR) data and multispectral optical satellite imagery. The workflow was developed in 2018 as part of a collaboration between GEUS and scientists from the Technical University of Denmark (DTU). This methodology provides a model through which GEUS will be able to monitor active landslides and provide relevant knowledge to the public and authorities in the event of future landslides that pose a risk to human life and infrastructure in Greenland. We use a minor event on 26 March 2018, near the site of the Karrat 2017 landslide, as a case study to demonstrate 1) the value of multidisciplinary approaches and 2) that the area around the landslide has continued to be periodically active since the main landslide in 2017

Preliminary landslide mapping in Greenland

The landslide of 17 June 2017 in Karrat Fjord, central West Greenland, highlighted the need for a better understanding of landslides and landslide-generated tsunamis in Greenland and motivated a landslide screening project in 2018, led by the Geological Survey of Denmark and Greenland (GEUS; see also Svennevig et al. this volume). A central part of this project was to conduct a preliminary mapping of Quaternary and historical landslides in Greenland – the first effort of its kind. The main objective was to establish a landslide inventory database that can be used to identify areas prone to landslides and serve as a tool for gaining a better understanding of where, when and why catastrophic landslides take place in Greenland. This paper describes the workflow used to produce the preliminary landslide inventory of Greenland and discusses some of the initial results. To date (June 2019), I have mapped 564 landslides with the vast majority situated in the Nuussuaq Basin between Sigguup Nunaa (Svartenhuk Halvø), and Qeqertarsuaq (Disko) in West Greenland (Fig. 1). The inventory mapping is mainly based on observations and analyses of remotely sensed imagery and pre-existing geological maps. The mapping coverage was not systematic for all of Greenland, but focused on postglacial, potentially tsunamigenic landslides in inhabited coastal regions, i.e. on relatively large landslides on coastal slopes, mainly in West Greenland and small areas of East Greenland. However, smaller and inland landslides were included when they were encountered. Similarly, the less inhabited parts of Greenland were provisionally screened, but call for more thorough, systematic mapping in the future

From 3D mapping to 3D modelling: a case study from the Skaergaard intrusion, southern East Greenland

The powerful 3D mapping tool at the photogrammetry laboratory of the Geological Survey of Denmark and Greenland (GEUS) is ideal for collecting high-quality 3D geological data in remote and inaccessible areas with a high degree of exposure such as Greenland (Vosgerau et al. 2010). So far this 3D mapping tool has been used to visualise and extract very precise geological data from aerial and oblique photographs. In the study reported on here, the 3D mapping tool was used to generate data for 3D geological modelling. The Skaergaard intrusion (Fig. 1) is a well-known Eocene layered gabbro. The study of the intrusion has had great importance for the understanding of magmatic petrology, magma differentiation and fractional crystallisation since the early studies by Wager & Deer (1939). It was chosen for 3D modelling because it is well studied from a petrological point of view and because the shape of the magma chamber was previously modelled in a network of 2D cross sections (Nielsen 2004). In this paper, it is modelled for the first time in 3D using a detailed 1:20 000 scale geological map (McBirney 1989), 1:27 000 scale aerial photographs from 1973, data from drill holes and geophysical data