Preparation of GIS landslide inventory for the Polog Region

This paper deals with preparation of Geographic Information Systems (GIS) landslide inventoryfor the Polog region. A number of activities were undertaken for this purpose, such as: analysis of own data on landslides, visits of the sites noted in the surveys filled by municipalities, digitizing of landslides from old geological mapsin scale 1:25000, analysis and digitizing of landslides from the archive of the Geological Survey of Macedonia, interviews with employees and retired colleagues from geotechnical companies, analysis of landslides along the channelsof the “Mavrovo” system, visit to the National University in Tetovo and joint site visit, and visits to several geotechnicalcompanies in Macedonia. Since this is the first attempt to create a regional landslide inventory in N. Macedonia, theadopted structure of the inventory is presented in the paper. Moreover, to see what benefits can be gained from theavailability of such inventory some of the most important findings regarding the landslides are presented further. Currently the inventory consists of 136 occurrences, and in time it should be appropriately updated. The main findingsrelated to the distribution and characteristics of the landslides show that future analyses should include preparation oflandslide susceptibility/hazard models both for shallow and deep landslides, as well as for flow-like type of slides. Inthe following stages of investigation, it is planned to analyze a LIDAR (LIght Detection and Ranging) survey that isbeing prepared for the region and incorporate more landslides in the inventory. Also, findings of the InSAR (Interferometric Synthetic Aperture Radar) analysis will be combined with the inventory, which will lead to conclusions on themovement rates of detected sites. The latter two approaches will be presented in future papers

LANDSLIDE EVOLUTION PATTERN REVEALED BY MULTI-TEMPORAL DSMS OBTAINED FROM HISTORICAL AERIAL IMAGES

Abstract. Landslides are a widespread natural hazard that cause damages to people and to the built up environment. Accurate knowledge of landslide distribution is crucial to develop planning strategies, prevention and resilient communities worldwide. One of the most diffuse way of reporting landslides distribution in a territory is by preparing landslide inventory maps. Such a task is mostly accomplished by expert photo-interpretation of historical aerial photographs, which are an invaluable source of information because they portray the landscape when the anthropic pressure was lower than the present day, providing an observation of the landscape closer to the natural conditions. Despite such a common use of aerial photographs, they are poorly exploited to obtain quantitative measures to support landslide mapping activities. In this paper we present a comparison of two photogrammetric approaches to measure elevation changes in a 50-years period for an area densely affected by landslides in Southern Italy. The obtained results allowed to revisit the original expert mapping proving that such a method is a useful tool to support geomorphological mapping and to improve the overall accuracy of landslide inventories

Application of innovative technologies in landslide research in the area of the City of Zagreb (Croatia, Europe)

This paper describes the application of innovative technologies for landslide detection, mapping and monitoring in the City of Zagreb since 2010. Airborne Light Detection and Ranging (LiDAR) data are used to visually identify landslides in the Podsljeme Zone over the area of 180 km2 for the purpose of landslide inventory mapping. The total number of landslides in the analyzed area (approx. 1,600 landslides) is estimated based on the average landslide density (9 landslides per square km) from the most reliable geomorphological historical inventory, which was produced in 1979. Examples of the visual interpretation of very-high-resolution bare-earth DEMs (Digital Elevation Model) are given to show the potential of these innovative techniques to identify the landslide contours of the very small, small and moderately small landslides that are characteristic of the study area, which is composed of engineering soils and/or soft rocks (marls). In the framework of the described landslide research, the biggest landslide in the Podsljeme Zone, the Kostanjek landslide (landslide area of 1 km2), was also equipped with an automated near-real time monitoring system that encompassed approximately 40 sensors to monitor landslide movement and landslide causal factors. Monitoring of this deep and large landslide during multiple extreme hydro-meteorological events from January 2013 to January 2015 enabled collection of data for the analysis of landslide movement on the surface and in the underground and as well as analysis of the relationship between landslide reactivations and its triggers, i.e., changes in groundwater level and precipitation. The final aim of the described scientific research in terms of landslide mapping and monitoring is its practical application in land-use planning and civil protection systems in the City of Zagreb. Namely, the conclusions propose reliable and efficient methods for landslide identification and monitoring, which are necessary to provide data and solutions for hazard and risk reduction to local authorities that are managed by the City

Automated determination of landslide locations after large trigger events: advantages and disadvantages compared to manual mapping

Earthquakes in mountainous areas can trigger thousands of co-seismic landslides, causing significant damage, hampering relief efforts, and rapidly redistributing sediment across the landscape. Efforts to understand the controls on these landslides rely heavily on manually mapped landslide inventories, but these are costly and time-consuming to collect, and their reproducibility is not typically well constrained. Here we develop a new automated landslide detection algorithm (ALDI) based on pixel-wise NDVI differencing of Landsat time series within Google Earth Engine accounting for seasonality. We compare classified inventories to manually mapped inventories from five recent earthquakes: 2005 Kashmir, 2007 Aisen, 2008 Wenchuan, 2010 Haiti, and 2015 Gorkha. We test the ability of ALDI to recover landslide locations (using ROC curves) and landslide sizes (in terms of landslide area-frequency statistics). We find that ALDI more skilfully identifies landslides than published inventories in 10 of 14 cases when ALDI is locally optimised, and in 8 of 14 cases both when ALDI is globally optimised and in holdback testing. These results reflect both good performance of the automated approach but also surprisingly poor performance of manual mapping, which has implications not only for how future classifiers are tested but also for the interpretations that are based on these inventories. We conclude that ALDI already represents a viable alternative to manual mapping in terms of its ability to identify landslide-affected image pixels. Its fast run-time, cost-free image requirements and near-global coverage make it an attractive alternative with the potential to significantly improve the coverage and quantity of landslide inventories. Its simplicity (pixel-wise analysis only) and parsimony of inputs (optical imagery only) suggests that considerable further improvement should be possible

Impacts of anthropogenic and environmental factors on the occurrence of shallow landslides in an alpine catchment (Urseren Valley, Switzerland)

Changes in climate and land use pose a risk to stability of alpine soils, but the direction and magnitude of the impact is still discussed controversially with respect to the various alpine regions. In this study, we explicitly consider the influence of dynamic human-induced changes on the occurrence of landslides in addition to natural factors. Our hypothesis was that if changes in land use and climate have a significant influence on the occurrence of landslides we would see a trend in the incidence of landslides over time. We chose the Urseren Valley in the Central Swiss Alps as investigation site because the valley is dramatically affected by landslides and the land use history is well documented. Maps of several environmental factors were used to analyse the spatial landslide pattern. In order to explain the causation of the temporal variation, time-series (45 years) of precipitation characteristics, cattle stocking and pasture maps were compared to a series of seven landslide investigation maps between 1959 and 2004. We found that the area affected by landslides increased by 92% from 1959 to 2004. Even though catchment characteristics like geology and slope largely explain the spatial variation in landslide susceptibility (68%), this cannot explain the temporal trend in landslide activity. The increase in stocking numbers and the increased intensity of torrential rain events had most likely an influence on landslide incidence. In addition, our data and interviews with farmers pointed to the importance of management practice

Recommendations for the quantitative analysis of landslide risk

This paper presents recommended methodologies for the quantitative analysis of landslide hazard, vulnerability and risk at different spatial scales (site-specific, local, regional and national), as well as for the verification and validation of the results. The methodologies described focus on the evaluation of the probabilities of occurrence of different landslide types with certain characteristics. Methods used to determine the spatial distribution of landslide intensity, the characterisation of the elements at risk, the assessment of the potential degree of damage and the quantification of the vulnerability of the elements at risk, and those used to perform the quantitative risk analysis are also described. The paper is intended for use by scientists and practising engineers, geologists and other landslide experts.JRC.H.5-Land Resources Managemen

LANDSLIDE HAZARD MAPPING NEAR THE ADMIRAL ÁLVARO ALBERTO NUCLEAR COMPLEX, RIO DE JANEIRO, BRAZIL.

Technological accidents can be vast in scope and require a rapid response to evacuate the affected region. Access routes to nuclear power stations are essential for the preparation of emergency plans in the event of technological disasters. The Admiral Álvaro Alberto Nuclear Power Plant (Central Nuclear Almirante Álvaro Alberto - CNAAA) in Angra dos Reis, Brazil, is located in a region with high rainfall and rugged terrain. This article presents digital image processing and geoprocessing procedures for mapping landslide-susceptible areas and landslide scars associated with the CNAAA access routes. Digital Elevation Models and their derivations were used to identify landslide-susceptible areas, and LANDSAT images were used to map the land cover. The information was superimposed, and the hazard areas and potential landslide scars were mapped. Most of the study area is medium or high risk for landslide events. Landslides scars mapping achieved over 50% of accuracy representing a potential methodology for the risk assessment and landslides monitoring in the study area. The results demonstrate that further and detailed studies must be performed in the areas in order to maintain the access roads available for eventual evacuations in a technological disaster event