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The potential loss expectancy is highest with strategic and operational risks and lowest with hazard and financial risks. The risks in most of the categories can have both upside and downside impacts. In this regard, hazard risks are an exception, since for them only a negative effect is possible. Risk radars are used to map the main risks within the risk categories in the annual risk assessment workshops between the Businesses and the Corporate Risk Management function.

During recent years, a similar risk mapping process has also been adopted by certain main support functions, such as HR and the Group Treasury. Business or function specific risk radars are generated for the use and evaluation of the Business Management teams, and are reviewed and updated by them on a regular basis.

CRAN Packages By Name

The Business specific radars are consolidated into a single Group Risk Radar, which is presented to the Board of Directors and the Audit Committee once a year. The purpose is to facilitate the discussion on risk and to give a quick overview of where priorities should lie in terms of risk management. English suomi svenska. Home Investors Governance Risk management. Implementation The Board of Directors and the Board of Management decide and set the guidelines on strategic matters.

The Businesses are responsible for achieving their set strategic goals, and for mitigating and managing their risks. Such event-based landslide inventory maps should be stored in a landslide database implemented in GIS. Much progress has been made in the development of landslide databases at regional or national level.

One of the first comprehensive projects for landslide and flood inventory mapping has been the AVI project in Italy Guzzetti et al. There are good examples in the literature of the use of landslide inventories for hazard assessment Guzzetti, ; Chau et al. However, the existing landslide databases often present several drawbacks Ardizzone et al.

Section 4. Table 2: Overview of techniques for the collection of landslide information. Table 3 provides more details on the relevance of the most important environmental factors for landslide susceptibility assessment. The selection of the environmental factors that are used in the susceptibility assessment is depending on the type of landslide, the failure mechanism, the type of terrain and the availability of existing data and resources.

Often different combinations of environmental factors should be used, resulting in separate landslide susceptibility maps for each failure mechanism, and landslide type. For the Caribbean island it would be best to make separate maps for soil slides and rock slides.

Radar-Based Heart Sound Detection

As topography is one of the major factors in landslide hazard analysis, the generation of a Digital Elevation Model DEM , plays a major role. More information on Digital Elevation Models is given in section 3. Derivatives from DEMs can be used in heuristic analysis at small scales hillshading images for display as backdrop image, physiographic classification, internal relief, drainage density , in statistical analysis at regional scales e.

The use of slope gradient maps in landslide hazard assessment is greatly affected by the resolution of the DEM.

Introduction

Dominica has a DEM generated from much smoothed contour lines, of which the origin is not clear. Saint Lucia also has a poor quality DEM generated from photogrammetry, but due to limited numbers of measured points, many area have very limited elevation data. Traditionally, geological maps form a standard component in heuristic and statistical landslide hazard assessment methods. Mostly the stratigraphical legends of existing geological maps are converted into an engineering geological classification, which gives more information on the rock composition and rock mass strength.

The subdivision of geological formations into meaningful mapping units of individual rock types often poses a problem, as the intercalations of these units cannot be properly mapped at these scales. In detailed hazard studies specific engineering geological maps are collected and rock types are characterized using field tests and laboratory measurements. For the Caribbean countries geological information is available at a rather general level. In detailed hazard studies specific engineering geological maps should be collected and rock types should be characterized using field tests and laboratory measurements.

Also borehole information should be collected on a scale smaller than , and its use is restricted to a site investigation level e. Xie et al. Apart from lithological information structural information is very important for hazard assessment, however, such information is not available for any of the countries. Table 3 : Overview of environmental factors, and their availability and quality for landslide susceptibility and hazard assessment.

Fault information is also used frequently as one of the environmental factors in a statistical landslide hazard assessment. The use of wide buffer zones around faults, which is now the standard practice should be treated with caution, as this might be only true for active faults. In other cases a very narrow buffer zone should be taken, which is related to the zone where rocks are fractured. None of the islands has good fault maps. In terms of soil information required for landslide hazard assessment, there are basically two different thematic data layers needed: soil types, with associated geotechnical and hydrological properties, and soil sequences, with depth information.

Table 4 gives an overview of the most important geotechnical, hydrological and vegetation characteristics required for modelling slope stability for soilslides, rock slides and reactivated landslides. Pedologic soil maps, normally only classify the soils based on the upper soil horizons, with rather complicated legends and are therefore less relevant in case of landslide deeper than meters. Engineering soil maps describe all loose materials on top of the bedrock, and classify them according to the geotechnical characteristics.

They are based on outcrops, borehole information and geophysical studies. Especially the soil depth is very difficult to map over large areas, as it may vary locally quite significantly. Soil thickness can be modeled using a correlation with topographic factors such as slope, or predicted from a process based model Kuriakose et al. Given the fact that soil thickness is one of the most crucial factors in deterministic slope stability modeling, it is surprising that very limited work has been done on the modeling of soil thicknesses over larger areas.

There are no engineering soil maps available for the four countries and the available pedologic soil maps are old around 40 years and generated within use of GIS or remote sensing, and therefore do not fit well with the rest of the data. Geomorphological maps are made at various scales to show land units based on their shape, material, processes and genesis. There is no generally accepted legend for geomorphological maps, and there may be a large variation in contents based on the experience of the geomorphologist.

An important field within geomorphology is the quantitative analysis of terrain forms from DEMs, called geomorphometry or digital terrain analysis, which combines elements from earth sciences, engineering, mathematics, statistics and computer science Pike, Part of the work focuses on the automatic classification of geomorphological land units based on morphometric characteristics at small scales Asselen and Seijmonsbergen, or on the extraction of slope facets at medium scales which can be used as the basic mapping units in statistical analysis.

In most of the statistical methods the analysis is carried out for a number of basic mapping units, that can be either grid cells, slope facets that are derived from DEMs or unique conditions units which are made by overlaying a number of landslide preparatory factors, such as lithology, land cover, slope gradient, slope curvature and upslope contributing area Cardinali et al.

Landuse is too often considered as a static factor in landslide hazard studies, and few researches involve constantly changing land use as a factor in the analysis Van Beek and Van Asch, Changes in land cover and land use resulting from human activities, such as deforestation, forest logging, road construction, fire and cultivation on steep slopes can have an important impact on landslide activity. Although change detection techniques such as post-classification comparison, temporal image differencing, temporal image ratioing, or Bayesian probabilistic methods have been widely applied in land use applications, fairly limited work has been done on the inclusion of multi- temporal land use change maps in landslide hazard studies.

The landuse maps for the four countries are all derived from image classification using high resolution images. See also use section 3. Information related to triggering factors generally has both temporal and spatial importance. The availability of historical rainfall information is crucial for analysing frequency of rainfall characteristics. But also the spatial rainfall distribution is very important as the Windward Island display clear relations between altitude, exposure and rainfall amounts See methodology chapter 2 on analysing triggers.

Case 2: How Safe are our Safeguards?

Data related to rainfall, temperature and earthquake records over sufficiently large time periods are essential for the assessment of magnitude-frequency relations. Rainfall and temperature data are measured in individual meteorological stations, and earthquake data is normally available as earthquake catalogs. The spatial variation over the study area can be represented by interpolating the point data, provided that enough measurement data is available. For example a map of the maximum expected rainfall in 24 hours for different return periods can be generated as the input in dynamic slope stability modeling.

In the case of earthquake triggered landslides a map of the peak ground acceleration PGA could be used as input in subsequent infinite slope modeling. The use of weather radar for rainfall prediction in landslide studies is a field which is very promising e. Crosta and Frattini, As will be explained more in detail in section 4. The occurrence of landslides is governed by complex interrelationships between factors, some of which cannot be determined in detail and others only with a large degree of uncertainty.

Some important aspects in this respect are: the error, accuracy, uncertainty and precision of the input data and the objectivity and reproducibility of the input maps. The accuracy of input data refers to the degree of closeness of the measured or mapped values or classes of a map to its actual true value or class in the field.

An error is defined as the difference between the mapped values or classes and the ones. The precision of a measurement is the degree to which repeated measurements under unchanged conditions show the same results. Uncertainty refers to the degree with which the actual characteristics of the terrain can be represented spatially in a map.

The sources of errors, which may occur in the generaton of input data for landslide hazard and risk analysis are schematically represented in table 5. The error in a map can be assessed only if another map, or field information is available which is error-free, and with which it can be verified.

Slope angles, for example, can be measured at several points in the terrain, and these point values can be compared with a slope map derived from a DEM to assess the degree of error.

Separating Storage Performance from Data Durability

This evaluation is different for maps which are not based on factual, measured data, but on interpretation, such as the genetic elements of a geomorphological map. Such a map can also be checked in the field, but it is still possible that different geomorphologists will not agree on the specific origin of a certain landform.

For maps based on interpretation, only the uncertainty of the map can be assessed, by comparison of different maps by different observers. This method will only render reliable result if the field experience of the observers, and the mapping method is identically. Therefore, the actual uncertainty of such maps is difficult to determine in an absolute manner.

Table 5 : Main sources of uncertainty of input data for landslide hazard and risk assessment. We have identified multiple issues related to geospatial information in the region present a considerable challenge to detailed hazard and risk assessments.


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The following points have been outlined:. Through several operations, countries are working together with International partners to address these issues and improve data availability and management. The products generated through this project will become good practice examples of data management for the beneficiary countries. Akcay, H. Automatic detection of geospatial objects using multiple hierarchical segmentations.

Ardizzone, F. Impact of mapping errors on the reliability of landslide hazard maps. Natural Hazards and Earth System Sciences 2, Cardinali, M. Reichenbach Identification and mapping of recent rainfall-induced landslides using elevation data collected by airborne Lidar.