3,459 research outputs found

    Rapid methods of landslide hazard mapping : Fiji case study

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    A landslide hazard probability map can help planners (1) prepare for, and/or mitigate against, the effects of landsliding on communities and infrastructure, and (2) avoid or minimise the risks associated with new developments. The aims of the project were to establish, by means of studies in a few test areas, a generic method by which remote sensing and data analysis using a geographic information system (GIS) could provide a provisional landslide hazard zonation map. The provision of basic hazard information is an underpinning theme of the UN’s International Decade for Natural Disaster Reduction (IDNDR). It is an essential requirement for disaster preparedness and mitigation planning. This report forms part of BGS project 92/7 (R5554) ‘Rapid assessment of landslip hazards’ Carried out under the ODA/BGS Technology Development and Research Programme as part of the British Government’s provision of aid to developing countries. It provides a detailed technical account of work undertaken in a test area in Viti Levu in collaboration with Fiji Mineral Resources Department. The study represents a demonstration of a methodology that is applicable to many developing countries. The underlying principle is that relationships between past landsliding events, interpreted from remote sensing, and factors such as the geology, relief, soils etc provide the basis for modelling where future landslides are most likely to occur. This is achieved using a GIS by ‘weighting’ each class of each variable (e.g. each lithology ‘class’ of the variable ‘geology’) according to the proportion of landslides occurring within it compared to the regional average. Combinations of variables, produced by summing the weights in individual classes, provide ‘models’ of landslide probability. The approach is empirical but has the advantage of potentially being able to provide regional scale hazard maps over large areas quickly and cheaply; this is unlikely to be achieved using conventional ground-based geotechnical methods. In Fiji, landslides are usually triggered by intense rain storms commonly associated with tropical cyclones. However, the regional distribution of landslides has not been mapped nor is it known how far geology and landscape influence the location and severity of landsliding events. The report discusses the remote sensing and GIS methodology, and describes the results of the pilot study over an area of 713 km2 in south east Viti Levu. The landslide model uses geology, elevation, slope angle, slope aspect, soil type, and forest cover as inputs. The resulting provisional landslide hazard zonation map, divided into high, medium and low zones of landslide hazard probability, suggests that whilst rainfall is the immediate cause, others controls do exert a significant influence. It is recommended that consideration be given in Fiji to implementing the techniques as part of a national strategic plan for landslide hazard zonation mapping

    Towards the optimal Pixel size of dem for automatic mapping of landslide areas

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    Determining appropriate spatial resolution of digital elevation model (DEM) is a key step for effective landslide analysis based on remote sensing data. Several studies demonstrated that choosing the finest DEM resolution is not always the best solution. Various DEM resolutions can be applicable for diverse landslide applications. Thus, this study aims to assess the influence of special resolution on automatic landslide mapping. Pixel-based approach using parametric and non-parametric classification methods, namely feed forward neural network (FFNN) and maximum likelihood classification (ML), were applied in this study. Additionally, this allowed to determine the impact of used classification method for selection of DEM resolution. Landslide affected areas were mapped based on four DEMs generated at 1m, 2m, 5m and 10m spatial resolution from airborne laser scanning (ALS) data. The performance of the landslide mapping was then evaluated by applying landslide inventory map and computation of confusion matrix. The results of this study suggests that the finest scale of DEM is not always the best fit, however working at 1m DEM resolution on micro-topography scale, can show different results. The best performance was found at 5m DEM-resolution for FFNN and 1m DEM resolution for results. The best performance was found to be using 5m DEM-resolution for FFNN and 1m DEM resolution for ML classification

    From engineering geosciences mapping towards sustainable urban planning

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    Maps are of key topical importance in urban geoscience and engineering practice, mainly in field data synthesis and communication related to a number of fields, such as geomatic techniques, applied geology and geomorphology, engineering geology, soil and rock geotechnics, slope geotechnics, subsurface site geotechnical investigations, urban hydrology, hydraulics and sanitation, coastal zones management, urban geoarcheology and heritage, planning and land use. The value of preparing engineering geoscience maps and plans specificallyfor urban engineering purposes are still a challenging task, particularly to end-users and planners. Nowadays, the application of Geographic Information Systems to geosciences and engineering has become more common. This paper emphasises the importance of an accurate ground field survey and inventory at several scales, GIS mapping and databases, and integrated multidisciplinary urban studies as useful tools to support a sustainable land use planning. Some selected sites are highlighted to demonstrate the importance of urban mapping for land use planning. Thus, in this study the significance of a smart urban geoscience approach is stressed.info:eu-repo/semantics/publishedVersio

    Real-time earthquake hazard assessment in California; the early post-earthquake damage assessment tool and the Caltech-USGS broadcast of earthquakes

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    A real-time earthquake monitoring system which provides source parameters to user groups through a commercial paging service is now in place in California. A GIS-based system to predict and display near real-time damage and casualty estimates is currently being developed by EQE International under contract with the State of California. These new technologies offer immediate tangible benefits to state and local governments, utilities, lifelines and corporations with facilities or operations at risk. This paper will outline the development of these new technologies, identify the contributions they will make to emergency management and explore some directions these innovative systems may take in the future

    Impact of Geographical Information Systems on Geotechnical Engineering

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    Over the last four decades Geographical Information Systems (GIS) have emerged as the predominant medium for graphic representation of geospatial data, including geotechnical, geologic and hydrologic information routinely used by geotechnical and geoenvironmental engineers. GIS allow unlimited forms of spatial data to be co-mingled, weighted and sorted with any number of physical or environmental factors. These data can also be combined with weighted political and aesthetic values to create hybrid graphic products capable of swaying public perceptions and decision making. The downside of some GIS products is that their apparent efficacy and crispness can also be deceptive, if data of unparalleled reliability is absorbed in the mix. Disparities in data age and quality are common when compiling geotechnical and geoenvironmental data. Despite these inherent shortcomings, GIS will continue to grow and evolve as the principal technical communication medium over the foreseeable future and engineers will be forced to prepare their work products in GIS formats which can be widely disseminated through the world wide web. This paper presents the historical evolution of GIS technologies as it relates to the impact in geotechnical engineering, concluding with four case histories on the application of this emerging technology

    Identification, prediction and mitigation of sinkhole hazards in evaporite karst areas

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    Abstract Sinkholes usually have a higher probability of occurrence and a greater genetic diversity in evaporite terrains than in carbonate karst areas. This is because evaporites have a higher solubility, and commonly a lower mechanical strength. Subsidence damage resulting from evaporite dissolution generates substantial losses throughout the world, but the causes are only well-understood in a few areas. To deal with these hazards, a phased approach is needed for sinkhole identification, investigation, prediction, and mitigation. Identification techniques include field surveys, and geomorphological mapping combined with accounts from local people and historical sources. Detailed sinkhole maps can be constructed from sequential historical maps, recent topographical maps and digital elevation models (DEMs) complemented with building-damage surveying, remote sensing, and high-resolution geodetic surveys. On a more detailed level, information from exposed paleosubsidence features (paleokarst), speleological explorations, geophysical investigations, trenching, dating techniques, and boreholes, may help to recognize dissolution and subsidence features. Information on the hydrogeological pathways including caves, springs and swallow holes, are particularly important especially when corroborated by tracer tests. These diverse data sources make a valuable database - the karst inventory. From this dataset, sinkhole susceptibility zonations (relative probability) may be produced based on the spatial and temporal distribution of the features and good knowledge of the local geology. Sinkhole distribution can be investigated by spatial distribution analysis techniques including studies of preferential elongation, alignment and nearest neighbor analysis. More objective susceptibility models may be obtained by analyzing the statistical relationships between the known sinkholes and the conditioning factors, such as weather conditions. Chronological information on sinkhole formation is required to estimate the probability of occurrence of sinkholes (number of sinkholes/km² year). Such spatial and temporal predictions, derived from limited records and based on the assumption that past sinkhole activity may be extrapolated to the future, are non-corroborated hypotheses. Validation methods allow us to assess the predictive capability of the susceptibility maps and to transform them into probability maps. Avoiding the most hazardous areas by preventive planning is the safest strategy for development in sinkhole-prone areas. Corrective measures could be to reduce the dissolution activity and subsidence processes, but these are difficult. A more practical solution for safe development is to reduce the vulnerability of the structures by using subsidence-proof designs

    Remote landslide mapping using a laser rangefinder binocular and GPS

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    We tested a high-quality laser rangefinder binocular coupled with a GPS receiver connected to a Tablet PC running dedicated software to help recognize and map in the field recent rainfall-induced landslides. The system was tested in the period between March and April 2010, in the Monte Castello di Vibio area, Umbria, Central Italy. To test the equipment, we measured thirteen slope failures that were mapped previously during a visual reconnaissance field campaign conducted in February and March 2010. For reference, four slope failures were also mapped by walking the GPS receiver along the landslide perimeter. Comparison of the different mappings revealed that the geographical information obtained remotely for each landslide by the rangefinder binocular and GPS was comparable to the information obtained by walking the GPS around the landslide perimeter, and was superior to the information obtained through the visual reconnaissance mapping. Although our tests were not exhaustive, we maintain that the system is effective to map recent rainfall induced landslides in the field, and we foresee the possibility of using the same (or similar) system to map landslides, and other geomorphological features, in other areas
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