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Sample records for gis-based landslide susceptibility

  1. GIS-based assessment of landslide susceptibility using certainty ...

    Indian Academy of Sciences (India)

    tion systems (GIS) using different models. Many of these ... as spatial multicriteria decision analysis (MCDA) approach ... 2013), support vec- ... Landslide susceptibility assessment using mathematical methods in GIS, Qianyang China 1401.

  2. Landslide susceptibility mapping using GIS-based statistical models and Remote sensing data in tropical environment.

    Science.gov (United States)

    Shahabi, Himan; Hashim, Mazlan

    2015-04-22

    This research presents the results of the GIS-based statistical models for generation of landslide susceptibility mapping using geographic information system (GIS) and remote-sensing data for Cameron Highlands area in Malaysia. Ten factors including slope, aspect, soil, lithology, NDVI, land cover, distance to drainage, precipitation, distance to fault, and distance to road were extracted from SAR data, SPOT 5 and WorldView-1 images. The relationships between the detected landslide locations and these ten related factors were identified by using GIS-based statistical models including analytical hierarchy process (AHP), weighted linear combination (WLC) and spatial multi-criteria evaluation (SMCE) models. The landslide inventory map which has a total of 92 landslide locations was created based on numerous resources such as digital aerial photographs, AIRSAR data, WorldView-1 images, and field surveys. Then, 80% of the landslide inventory was used for training the statistical models and the remaining 20% was used for validation purpose. The validation results using the Relative landslide density index (R-index) and Receiver operating characteristic (ROC) demonstrated that the SMCE model (accuracy is 96%) is better in prediction than AHP (accuracy is 91%) and WLC (accuracy is 89%) models. These landslide susceptibility maps would be useful for hazard mitigation purpose and regional planning.

  3. A GIS-based extended fuzzy multi-criteria evaluation for landslide susceptibility mapping.

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    Feizizadeh, Bakhtiar; Shadman Roodposhti, Majid; Jankowski, Piotr; Blaschke, Thomas

    2014-12-01

    Landslide susceptibility mapping (LSM) is making increasing use of GIS-based spatial analysis in combination with multi-criteria evaluation (MCE) methods. We have developed a new multi-criteria decision analysis (MCDA) method for LSM and applied it to the Izeh River basin in south-western Iran. Our method is based on fuzzy membership functions (FMFs) derived from GIS analysis. It makes use of nine causal landslide factors identified by local landslide experts. Fuzzy set theory was first integrated with an analytical hierarchy process (AHP) in order to use pairwise comparisons to compare LSM criteria for ranking purposes. FMFs were then applied in order to determine the criteria weights to be used in the development of a landslide susceptibility map. Finally, a landslide inventory database was used to validate the LSM map by comparing it with known landslides within the study area. Results indicated that the integration of fuzzy set theory with AHP produced significantly improved accuracies and a high level of reliability in the resulting landslide susceptibility map. Approximately 53% of known landslides within our study area fell within zones classified as having "very high susceptibility", with the further 31% falling into zones classified as having "high susceptibility".

  4. A GIS-based extended fuzzy multi-criteria evaluation for landslide susceptibility mapping

    Science.gov (United States)

    Feizizadeh, Bakhtiar; Shadman Roodposhti, Majid; Jankowski, Piotr; Blaschke, Thomas

    2014-01-01

    Landslide susceptibility mapping (LSM) is making increasing use of GIS-based spatial analysis in combination with multi-criteria evaluation (MCE) methods. We have developed a new multi-criteria decision analysis (MCDA) method for LSM and applied it to the Izeh River basin in south-western Iran. Our method is based on fuzzy membership functions (FMFs) derived from GIS analysis. It makes use of nine causal landslide factors identified by local landslide experts. Fuzzy set theory was first integrated with an analytical hierarchy process (AHP) in order to use pairwise comparisons to compare LSM criteria for ranking purposes. FMFs were then applied in order to determine the criteria weights to be used in the development of a landslide susceptibility map. Finally, a landslide inventory database was used to validate the LSM map by comparing it with known landslides within the study area. Results indicated that the integration of fuzzy set theory with AHP produced significantly improved accuracies and a high level of reliability in the resulting landslide susceptibility map. Approximately 53% of known landslides within our study area fell within zones classified as having “very high susceptibility”, with the further 31% falling into zones classified as having “high susceptibility”. PMID:26089577

  5. Fuzzy Shannon Entropy: A Hybrid GIS-Based Landslide Susceptibility Mapping Method

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    Majid Shadman Roodposhti

    2016-09-01

    Full Text Available Assessing Landslide Susceptibility Mapping (LSM contributes to reducing the risk of living with landslides. Handling the vagueness associated with LSM is a challenging task. Here we show the application of hybrid GIS-based LSM. The hybrid approach embraces fuzzy membership functions (FMFs in combination with Shannon entropy, a well-known information theory-based method. Nine landslide-related criteria, along with an inventory of landslides containing 108 recent and historic landslide points, are used to prepare a susceptibility map. A random split into training (≈70% and testing (≈30% samples are used for training and validation of the LSM model. The study area—Izeh—is located in the Khuzestan province of Iran, a highly susceptible landslide zone. The performance of the hybrid method is evaluated using receiver operating characteristics (ROC curves in combination with area under the curve (AUC. The performance of the proposed hybrid method with AUC of 0.934 is superior to multi-criteria evaluation approaches using a subjective scheme in this research in comparison with a previous study using the same dataset through extended fuzzy multi-criteria evaluation with AUC value of 0.894, and was built on the basis of decision makers’ evaluation in the same study area.

  6. An uncertainty and sensitivity analysis approach for GIS-based multicriteria landslide susceptibility mapping

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    Feizizadeh, Bakhtiar; Blaschke, Thomas

    2014-01-01

    GIS-based multicriteria decision analysis (MCDA) methods are increasingly being used in landslide susceptibility mapping. However, the uncertainties that are associated with MCDA techniques may significantly impact the results. This may sometimes lead to inaccurate outcomes and undesirable consequences. This article introduces a new GIS-based MCDA approach. We illustrate the consequences of applying different MCDA methods within a decision-making process through uncertainty analysis. Three GIS-MCDA methods in conjunction with Monte Carlo simulation (MCS) and Dempster–Shafer theory are analyzed for landslide susceptibility mapping (LSM) in the Urmia lake basin in Iran, which is highly susceptible to landslide hazards. The methodology comprises three stages. First, the LSM criteria are ranked and a sensitivity analysis is implemented to simulate error propagation based on the MCS. The resulting weights are expressed through probability density functions. Accordingly, within the second stage, three MCDA methods, namely analytical hierarchy process (AHP), weighted linear combination (WLC) and ordered weighted average (OWA), are used to produce the landslide susceptibility maps. In the third stage, accuracy assessments are carried out and the uncertainties of the different results are measured. We compare the accuracies of the three MCDA methods based on (1) the Dempster–Shafer theory and (2) a validation of the results using an inventory of known landslides and their respective coverage based on object-based image analysis of IRS-ID satellite images. The results of this study reveal that through the integration of GIS and MCDA models, it is possible to identify strategies for choosing an appropriate method for LSM. Furthermore, our findings indicate that the integration of MCDA and MCS can significantly improve the accuracy of the results. In LSM, the AHP method performed best, while the OWA reveals better performance in the reliability assessment. The WLC

  7. GIS-based landslide susceptibility mapping for the 2005 Kashmir earthquake region

    Science.gov (United States)

    Kamp, Ulrich; Growley, Benjamin J.; Khattak, Ghazanfar A.; Owen, Lewis A.

    2008-11-01

    The Mw 7.6 October 8, 2005 Kashmir earthquake triggered several thousand landslides throughout the Himalaya of northern Pakistan and India. These were concentrated in six different geomorphic-geologic-anthropogenic settings. A spatial database, which included 2252 landslides, was developed and analyzed using ASTER satellite imagery and geographical information system (GIS) technology. A multi-criterion evaluation was applied to determine the significance of event-controlling parameters in triggering the landslides. The parameters included lithology, faults, slope gradient, slope aspect, elevation, land cover, rivers and roads. The results showed four classes of landslide susceptibility. Furthermore, they indicated that lithology had the strongest influence on landsliding, particularly when the rock is highly fractured, such as in shale, slate, clastic sediments, and limestone and dolomite. Moreover, the proximity of the landslides to faults, rivers, and roads was also an important factor in helping to initiate failures. In addition, landslides occurred particularly in moderate elevations on south facing slopes. Shrub land, grassland, and also agricultural land were highly susceptible to failures, while forested slopes had few landslides. One-third of the study area was highly or very highly susceptible to future landsliding and requires immediate mitigation action. The rest of the region had a low or moderate susceptibility to landsliding and remains relatively stable. This study supports the view that (1) earthquake-triggered landslides are concentrated in specific zones associated with event-controlling parameters; and (2) in the western Himalaya deforestation and road construction contributed significantly to landsliding during and shortly after earthquakes.

  8. GIS-Based Integration of Subjective and Objective Weighting Methods for Regional Landslides Susceptibility Mapping

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    Suhua Zhou

    2016-04-01

    Full Text Available The development of landslide susceptibility maps is of great importance due to rapid urbanization. The purpose of this study is to present a method to integrate the subjective weight with objective weight for regional landslide susceptibility mapping on the geographical information system (GIS platform. The analytical hierarchy process (AHP, which is subjective, was employed to weight predictive factors’ contribution to landslide occurrence. The frequency ratio (FR method, which is objective, was used to derive subclasses’ frequency ratio with respect to landslides that indicate the relative importance of a subclass within each predictive factor. A case study was carried out at Tsushima Island, Japan, using a historical inventory of 534 landslides and seven predictive factors: elevation, slope, aspect, terrain roughness index (TRI, lithology, land cover and mean annual precipitation (MAP. The landslide susceptibility index (LSI was calculated using the weighted linear combination of factors’ weights and subclasses’ weights. The study area was classified into five susceptibility zones according to the LSI. In addition, the produced susceptibility map was compared with maps generated using the conventional FR and AHP method and validated using the relative landslide index (RLI. The validation result showed that the proposed method performed better than the conventional application of the FR method and AHP method. The obtained landslide susceptibility maps could serve as a scientific basis for urban planning and landslide hazard management.

  9. GIS-based landslide susceptibility mapping models applied to natural and urban planning in Trikala, Central Greece

    Energy Technology Data Exchange (ETDEWEB)

    Bathrellos, G. D.; Kalivas, D. P.; Skilodimou, H. D.

    2009-07-01

    Landslide susceptibility mapping is a practical tool in natural and urban planning; it can be applied for determining land use zones, in construction design and planning of a variety of projects. In this study, two different GIS based landslide susceptibility maps were generated in the mountainous part of the Trikala Prefecture in Thessaly, Central Greece. This was accomplished by using different methods for correlating factors, which have an effect on landslide occurrences. The instability factors taken into account were: lithology, tectonic features, slope gradients, road network, drainage network, land use and rainfall. A frequency distribution of the half number of the landslide events of the study area in each class of the instability factors was performed in order to rate the classes. Two models have been used to combine the instability factors and assess the overall landslide susceptibility, namely: the Weight Factor Model (WeF), which is a statistical method, and the Multiple Factor Model (MuF) that is a logical method. The produced maps were classified into four zones: Low, Moderate, High and Very High susceptible zones and validated using the other half number of the landslide events of the area. Evaluation of the results is optimized through a Landslide Models Indicator (La.M.I.). (Author) 36 refs.

  10. A GIS-based susceptibility map for landslides at the Franconian Alb, Germany

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    Jaeger, Daniel; Wilde, Martina; Lorenz, Michael; Terhorst, Birgit; Neuhäuser, Bettina; Damm, Bodo; Bemm, Stefan

    2014-05-01

    In general, slopes of cuesta scarps like the Franconian Alb are highly prone to slide activity due to susceptible geological and geomorphological conditions. The geological setting with alternating permeable and non-permeable bedrock results in the characteristic cuesta landforms of almost flat backslopes and steeper front slopes. Furthermore, this bipartite structure leads to a strong disposition for mass movements. The slopes of the study area near the town of Ebermannstadt are affected by different types of mass movements, such as topples, slides, lateral spreads and flows, either in single or in combined occurrence. In the years 1625, 1957, 1961 and 1979, four large landslides took place in the area of Ebermannstadt, reaching close to the town limits and causing major destructions to traffic facilities. In the study area, slopes are covered by debris and slide masses, thus they are prone to remobilization and further mass movements. In order to assess hazardous areas, a GIS-based susceptibility modelling was generated for the study area. The susceptibtibility modeling was processed with the slope stability model SINMAP (Stability Index Mapping), developed by TARBOTON (1997) and PACK et al. (1999). As SINMAP was particularly designed to model shallow translational slides, it should be well designed for describing the conditions of the study area in a sufficient way. SINMAP is based on the "infinite slope stability model" by HAMMONT et al. (1992) and MONTGOMERY & DIETRICH (1994), which focuses on the relation of stabilizing (cohesiveness, friction angle) and destabilizing (gravitation) factors on a plain surface. By adding a slope gradient, as well as soil mechanical and climatical data, indices of slope stabilities are calculated. For a more detailed modeling of the slope conditions, SINMAP computes different "calibration regions", which merge similar parameters of soil, land-use, vegetation, and geology. Due to the fact that vegetation, land-use, and soils only

  11. Susceptibility assessment of landslides: A comparison of two GIS-based methods in the region of Al Hoceima (Eastern Rif, Morocco.

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    El Fahchouch A. N.

    2018-01-01

    Full Text Available The evaluation of the degree of susceptibility to landslides has become a major concern in mountainous areas, it is a key component of manager policies efforts in disaster prevention, mitigate risk and manage the consequences. The region of Al Hoceima is one of most mountain regions in Morocco, and is highly exposed landslides events. For this reason, the area was selected in order to determine its susceptibility to landslides using two methods. The purpose of this study is to evaluate and to compare the results of multivariate (logical regression and bivariate (landslide susceptibility methods in Geographical Information System (GIS based landslide susceptibility assessment procedures. In order to achieve this goal, the selected methods were compared by the Seed Cell Area Indexes (SCAI and by the spatial locations of the resultant susceptibility pixels. We found that both of the methods converge in 80% of the area; however, the weighting algorithm in the bivariate technique (landslide susceptibility method had some severe deficiencies, as the resultant hazard classes in overweighed areas did not converge with the factual landslide inventory map. The result of the multivariate technique (logical regression was more sensitive to the different local features of the test zone and it resulted in more accurate and homogeneous susceptibility maps. This information may have direct applications in landslides susceptibility research programs and can assist decision-makers in the implementation of preventive management strategies in the most sensitive areas.

  12. GIS-based landslide susceptibility mapping models applied to natural and urban planning in Trikala, Central Greece

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    Skilodimou, H. D.

    2009-06-01

    Full Text Available Landslide susceptibility mapping is a practical tool in natural and urban planning; it can be applied for determining land use zones, in construction design and planning of a variety of projects. In this study, two different GIS based landslide susceptibility maps were generated in the mountainous part of the Trikala Prefecture in Thessaly, Central Greece. This was accomplished by using different methods for correlating factors, which have an effect on landslide occurrences. The instability factors taken into account were: lithology, tectonic features, slope gradients, road network, drainage network, land use and rainfall. A frequency distribution of the half number of the landslide events of the study area in each class of the instability factors was performed in order to rate the classes. Two models have been used to combine the instability factors and assess the overall landslide susceptibility, namely: the Weight Factor Model (WeF, which is a statistical method, and the Multiple Factor Model (MuF that is a logical method. The produced maps were classified into four zones: Low, Moderate, High and Very High susceptible zones and validated using the other half number of the landslide events of the area. Evaluation of the results is optimized through a Landslide Models Indicator (La.M.I..Los mapas de susceptibilidad de deslizamientos representan una práctica herramienta en la planificación urbana y de espacios naturales. Así, puede aplicarse a la determinación de los usos de terrenos, en el diseño de construcción civil y para la planificación de gran variedad de actividades. En este estudio se generaron dos tipos diferentes de mapas de susceptibilidad basados en GIS para la parte montañosa de la prefectura de Trikala en Tesalia (Grecia Central. Estos se llevaron a cabo usando dos métodos de correlación de los factores que pueden tener un efecto en la generación de deslizamientos. Los factores de desestabilización tenidos en cuenta

  13. A GIS-based statistical model for rapid landslide susceptibility mapping in the Beichuan-Pingwu area, Sichuan, China

    International Nuclear Information System (INIS)

    Chen, Y; Wang, Q J

    2014-01-01

    The 2008 Wenchuan earthquake, with a magnitude of Mw 8.0, induced numerous landslides. Remote sensing planes were sent out to take high resolution aerial photographs, from which the geologic hazards could be instantly interpreted. However, aerial images covering all of the study area could not be obtained in a short time because of the limitations of the planes and the influence of weather conditions. This studyestablishes a statistical model based on the landslide interpretation results of one photographic strip inside the Beichuan-Pingwu area. It has strong applicability and can be applied to other places without such data. Finally, we produced a landslide susceptibility map, which providesscientific support for the instant evaluation of disaster information and post-disaster reconstruction

  14. Landslide Susceptibility Mapping Using GIS-based Vector Grid File (VGF Validating with InSAR Techniques: Three Gorges, Yangtze River (China

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    Cem Kıncal

    2017-04-01

    Full Text Available A landslide susceptibility assessment for the Three Gorges (TG region (China was performed in a Geographical Information System (GIS environment and Persistent Scatterer (PS InSAR derived displacements were used for validation purposes. Badong County of TG was chosen as case study field. Landslide parameters were derived from two datasets. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER Global Digital Elevation Map (GDEM was used to calculate slope geometry parameters (slope, aspect, drainage, and lineament, while geology and vegetation cover were obtained from Landsat and ASTER data. The majority of historical landslides occurred in the sandstone-shale-claystone intercalations. It appears that slope gradients are more critical than other parameters such as aspect and drainage. The susceptibility assessment was based on a summation of assigned susceptibility scores (points for each 30×30 m unit in a database of a Vector Grid File (VGF composed of ‘vector pixels’. A landslide susceptibility map (LSM was generated using VGF and classified with low, moderate and high landslide susceptibility zones. The comparison between the LSM and PS InSAR derived displacements suggests that landslides only account for parts of the observed surface movements.

  15. Application of a GIS-Based Slope Unit Method for Landslide Susceptibility Mapping along the Longzi River, Southeastern Tibetan Plateau, China

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    Fei Wang

    2017-06-01

    Full Text Available The Longzi River Basin in Tibet is located along the edge of the Himalaya Mountains and is characterized by complex geological conditions and numerous landslides. To evaluate the susceptibility of landslide disasters in this area, eight basic factors were analyzed comprehensively in order to obtain a final susceptibility map. The eight factors are the slope angle, slope aspect, plan curvature, distance-to-fault, distance-to-river, topographic relief, annual precipitation, and lithology. Except for the rainfall factor, which was extracted from the grid cell, all the factors were extracted and classified by the slope unit, which is the basic unit in geological disaster development. The eight factors were superimposed using the information content method (ICM, and the weight of each factor was acquired through an analytic hierarchy process (AHP. The sensitivities of the landslides were divided into four categories: low, moderate, high, and very high, respectively, accounting for 22.76%, 38.64%, 27.51%, and 11.09% of the study area. The accuracies of the area under AUC using slope units and grid cells are 82.6% and 84.2%, respectively, and it means that the two methods are accurate in predicting landslide occurrence. The results show that the high and very high susceptibility areas are distributed throughout the vicinity of the river, with a large component in the north as well as a small portion in the middle and the south. Therefore, it is necessary to conduct landslide warnings in these areas, where the rivers are vast and the population is dense. The susceptibility map can reflect the comprehensive risk of each slope unit, which provides an important reference for later detailed investigations, including research and warning studies.

  16. Landslides along Highways: GIS-based Inventory and Planning Issues

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    Jaeger, Ann-Kathrin; Klose, Martin; Damm, Bodo

    2015-04-01

    Highways rank as critical transportation infrastructures that are at risk of landslides in many areas worldwide (e.g., Hungr et al., 1999; Bhandary et al., 2013). Safe and affordable operations of traffic routes constitute the two main criteria for transportation planning in landslide-prone terrain. A right balancing of these often conflicting priorities requires profound knowledge of landslide locations across highway networks and the costs caused by landslides in the past (e.g., Saha et al., 2005). Much of the direct costs affecting transportation departments relate to capital investments for landslide repair or mitigation and operational expenditures in connection with maintenance works. A systematic collection and inventory of such data sets combined with an acquisition of hazard information on vulnerable road sections is still rarely the case in engineering practice. This is despite significant cost impacts and budgetary burdens, especially in peripheral mountain areas where financial resources are naturally limited (e.g., Klose et al., 2014). The present contribution introduces a regional inventory of landslides along highways in the Harz Mountains, NW Germany. As subset of a landslide database for the entire country, this focused GIS-based inventory has been compiled in close collaboration with the Lower Saxony Department of Transportation. The inventory includes data sets gathered by archive studies and relies on high-quality information sources such as maintenance protocols, geotechnical reports, and documents from tendering, controlling, and accounting. A mapping tool in ArcGIS format is used to specify and visualize road sections affected by landslides. This spatial information on hazard exposure is complemented by narrative risk profiles for landslide sites showing a long history of damage events. By summarizing the occurrence dates of landslides, the associated damages, and the types and costs of repair or prevention, such risk profiles are useful to

  17. Comparison and validation of shallow landslides susceptibility maps generated by bi-variate and multi-variate linear probabilistic GIS-based techniques. A case study from Ribeira Quente Valley (S. Miguel Island, Azores)

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    Marques, R.; Amaral, P.; Zêzere, J. L.; Queiroz, G.; Goulart, C.

    2009-04-01

    Slope instability research and susceptibility mapping is a fundamental component of hazard assessment and is of extreme importance for risk mitigation, land-use management and emergency planning. Landslide susceptibility zonation has been actively pursued during the last two decades and several methodologies are still being improved. Among all the methods presented in the literature, indirect quantitative probabilistic methods have been extensively used. In this work different linear probabilistic methods, both bi-variate and multi-variate (Informative Value, Fuzzy Logic, Weights of Evidence and Logistic Regression), were used for the computation of the spatial probability of landslide occurrence, using the pixel as mapping unit. The methods used are based on linear relationships between landslides and 9 considered conditioning factors (altimetry, slope angle, exposition, curvature, distance to streams, wetness index, contribution area, lithology and land-use). It was assumed that future landslides will be conditioned by the same factors as past landslides in the study area. The presented work was developed for Ribeira Quente Valley (S. Miguel Island, Azores), a study area of 9,5 km2, mainly composed of volcanic deposits (ash and pumice lapilli) produced by explosive eruptions in Furnas Volcano. This materials associated to the steepness of the slopes (38,9% of the area has slope angles higher than 35°, reaching a maximum of 87,5°), make the area very prone to landslide activity. A total of 1.495 shallow landslides were mapped (at 1:5.000 scale) and included in a GIS database. The total affected area is 401.744 m2 (4,5% of the study area). Most slope movements are translational slides frequently evolving into debris-flows. The landslides are elongated, with maximum length generally equivalent to the slope extent, and their width normally does not exceed 25 m. The failure depth rarely exceeds 1,5 m and the volume is usually smaller than 700 m3. For modelling

  18. A GIS-based numerical simulation of the March 2014 Oso landslide fluidized motion

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    Fukuoka, H.; Ogbonnaya, I.; Wang, C.

    2014-12-01

    Sliding and flowing are the major movement type after slope failures. Landslides occur when slope-froming material moves downhill after failing along a sliding surface. Most debris flows originally occur in the form of rainfall-induced landslides before they move into valley channel. Landslides that mobilize into debris flows usually are characterized by high-speed movement and long run-out distance and may present the greatest risk to human life. The 22 March 2014 Oso landslide is a typical case of landside transformint to debris flow. The landslide was triggered on the edge of a plateau about 200 m high composed of glacial sediments after excessive prolonged rainfall of 348 in March 2014. After its initiation, portions of the landslide materials transitioned into a rapidly moving debris flow which traveled long distances across the downslope floodplain. U.S. Geological Survey estimated the volume of the slide to be about 7 million m3, and it traveled about 1 km from the toe of the slope. The apparent friction angle measured by the energy line drawn from the crown of the head scarp to the toe of the deposits which reached largest distance, was only 5~6 degrees. we performed two numerical modeling to predicting the runout distance and to get insight into the behaviour of the landslide movement. One is GIS-based revised Hovland's 3D limit equilibrium model which is used to simulate the movement and stoppage of a landslide. In this research, sliding is defined by a slip surface which cuts through the slope, causing the mass of earth to move above it. The factor of safety will be calculated step by step during the sliding process simulation. Stoppage is defined by the factor of safety much greater than one and the velocity equal zero. The other is GIS-based depth-averaged 2D numerical model using a coupled viscous and Coulomb type law to simulate a debris flow from initiation to deposition. We compared our simulaiton results with the results of preliminary computer

  19. GIS-Based Terrain Analysis of Balakot Region after Occurred Landslide Disaster in October 2005

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    Abdul Salam Soomro

    2011-10-01

    Full Text Available The landslide susceptibility models require the appropriate and reliable terrain analytical based study of the landslides prone areas using SRTM (Shuttle Radar Topography Mission data, based on certain GIS (Geographical Information Systems and remote sensing techniques. This research paper focuses on the analysis of the terrain conditions of Balakot region. The analytical operations have been used in the different phases: (i Extracting the study area from the large data; (ii preparing it into grid format; (iii developing contour lines with certain contour intervals (iv Re-classification of it into required classes and (v preparation of digital terrain model with its different required various supplementary models for analyzing the terrain conditions of the study area located in Mansehra district, north part of Pakistan where the great earthquake induced landslide disaster occurred in October 2005. This analytical study has notified the different sensitive issues concerning to the critical slope angles, variation in the elevation and the surface of study area. The various distinctions in the terrain phenomenon validate the occurred and probable landslides because the topography of such study area can predict the various probable landslide hazards, vulnerability and risk threats in the region again. This analytical study can be useful for the decisive authorities by becoming pro-active to rebuild the region to mitigate the expected losses from the natural disaster.

  20. Use of Satellite Remote Sensing Data in the Mapping of Global Landslide Susceptibility

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    Hong, Yang; Adler, Robert F.; Huffman, George J.

    2007-01-01

    Satellite remote sensing data has significant potential use in analysis of natural hazards such as landslides. Relying on the recent advances in satellite remote sensing and geographic information system (GIS) techniques, this paper aims to map landslide susceptibility over most of the globe using a GIs-based weighted linear combination method. First , six relevant landslide-controlling factors are derived from geospatial remote sensing data and coded into a GIS system. Next, continuous susceptibility values from low to high are assigned to each of the six factors. Second, a continuous scale of a global landslide susceptibility index is derived using GIS weighted linear combination based on each factor's relative significance to the process of landslide occurrence (e.g., slope is the most important factor, soil types and soil texture are also primary-level parameters, while elevation, land cover types, and drainage density are secondary in importance). Finally, the continuous index map is further classified into six susceptibility categories. Results show the hot spots of landslide-prone regions include the Pacific Rim, the Himalayas and South Asia, Rocky Mountains, Appalachian Mountains, Alps, and parts of the Middle East and Africa. India, China, Nepal, Japan, the USA, and Peru are shown to have landslide-prone areas. This first-cut global landslide susceptibility map forms a starting point to provide a global view of landslide risks and may be used in conjunction with satellite-based precipitation information to potentially detect areas with significant landslide potential due to heavy rainfall. 1

  1. A landslide susceptibility map of Africa

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    Broeckx, Jente; Vanmaercke, Matthias; Duchateau, Rica; Poesen, Jean

    2017-04-01

    Studies on landslide risks and fatalities indicate that landslides are a global threat to humans, infrastructure and the environment, certainly in Africa. Nonetheless our understanding of the spatial patterns of landslides and rockfalls on this continent is very limited. Also in global landslide susceptibility maps, Africa is mostly underrepresented in the inventories used to construct these maps. As a result, predicted landslide susceptibilities remain subject to very large uncertainties. This research aims to produce a first continent-wide landslide susceptibility map for Africa, calibrated with a well-distributed landslide dataset. As a first step, we compiled all available landslide inventories for Africa. This data was supplemented by additional landslide mapping with Google Earth in underrepresented regions. This way, we compiled 60 landslide inventories from the literature (ca. 11000 landslides) and an additional 6500 landslides through mapping in Google Earth (including 1500 rockfalls). Various environmental variables such as slope, lithology, soil characteristics, land use, precipitation and seismic activity, were investigated for their significance in explaining the observed spatial patterns of landslides. To account for potential mapping biases in our dataset, we used Monte Carlo simulations that selected different subsets of mapped landslides, tested the significance of the considered environmental variables and evaluated the performance of the fitted multiple logistic regression model against another subset of mapped landslides. Based on these analyses, we constructed two landslide susceptibility maps for Africa: one for all landslide types and one excluding rockfalls. In both maps, topography, lithology and seismic activity were the most significant variables. The latter factor may be surprising, given the overall limited degree of seismicity in Africa. However, its significance indicates that frequent seismic events may serve as in important

  2. Rainfall and earthquake-induced landslide susceptibility assessment using GIS and Artificial Neural Network

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    Y. Li

    2012-08-01

    Full Text Available A GIS-based method for the assessment of landslide susceptibility in a selected area of Qingchuan County in China is proposed by using the back-propagation Artificial Neural Network model (ANN. Landslide inventory was derived from field investigation and aerial photo interpretation. 473 landslides occurred before the Wenchuan earthquake (which were thought as rainfall-induced landslides (RIL in this study, and 885 earthquake-induced landslides (EIL were recorded into the landslide inventory map. To understand the different impacts of rainfall and earthquake on landslide occurrence, we first compared the variations between landslide spatial distribution and conditioning factors. Then, we compared the weight variation of each conditioning factor derived by adjusting ANN structure and factors combination respectively. Last, the weight of each factor derived from the best prediction model was applied to the entire study area to produce landslide susceptibility maps.

    Results show that slope gradient has the highest weight for landslide susceptibility mapping for both RIL and EIL. The RIL model built with four different factors (slope gradient, elevation, slope height and distance to the stream shows the best success rate of 93%; the EIL model built with five different factors (slope gradient, elevation, slope height, distance to the stream and distance to the fault has the best success rate of 98%. Furthermore, the EIL data was used to verify the RIL model and the success rate is 92%; the RIL data was used to verify the EIL model and the success rate is 53%.

  3. Susceptibility of Shallow Landslide in Fraser Hill Catchment, Pahang Malaysia

    Directory of Open Access Journals (Sweden)

    Wan Nor Azmin Sulaiman

    2010-01-01

    Full Text Available In tropical areas especially during monsoon seasons intense precipitation is the main caused that trigger the natural shallow landslide phenomena. This phenomenon can be disastrous and widespread in occurrence even in undisturbed forested catchment. In this paper, an attempt has been made to evaluate the susceptibility of natural hill slopes to failure for a popular hill resort area, the Fraser Hill Catchment under different rainfall regimes and soil thickness. A Digital Elevation Model (DEM was prepared for the 8.2 km2 catchment. A GIS based deterministic model was then applied to predict the spatial landslide occurrence within catchment. Model input parameters include bulk density, friction angle, cohesion and hydraulic conductivity were gathered through in situ and lab analysis as well as from previous soil analysis records. Landslides locations were recorded using GPS as well as previous air photos and satellite imagery to establish landslide source areas inventory. The landslide susceptibility map was produced under different precipitation event’s simulation to see the effects of precipitation to stability of the hill slopes of the catchment. The results were categorized into naturally unstable (Defended, Upper Threshold, Lower Threshold, marginal instability (Quasi Stable and stable area (Moderately Stable and Stable. Results of the simulation indicated notable change in precipitation effect on Defended area is between 10mm to 40mm range in a single storm event. However, when storm event is exceeded 120mm, the result on Defended area produced by the model tends to be constant further on. For area categorized as naturally unstable (Factor of Safety, SF<1, with 110 mm of precipitation in a single storm event and soil depth at 2 meters and 4 meters could affect 69.51% and 69.88% respectively of the catchment area fall under that class. In addition, the model was able to detect 4% more of the landslide inventory under shallower soil depth of

  4. Modeling Typhoon Event-Induced Landslides Using GIS-Based Logistic Regression: A Case Study of Alishan Forestry Railway, Taiwan

    Directory of Open Access Journals (Sweden)

    Sheng-Chuan Chen

    2013-01-01

    Full Text Available This study develops a model for evaluating the hazard level of landslides at Alishan Forestry Railway, Taiwan, by using logistic regression with the assistance of a geographical information system (GIS. A typhoon event-induced landslide inventory, independent variables, and a triggering factor were used to build the model. The environmental factors such as bedrock lithology from the geology database; topographic aspect, terrain roughness, profile curvature, and distance to river, from the topographic database; and the vegetation index value from SPOT 4 satellite images were used as variables that influence landslide occurrence. The area under curve (AUC of a receiver operator characteristic (ROC curve was used to validate the model. Effects of parameters on landslide occurrence were assessed from the corresponding coefficient that appears in the logistic regression function. Thereafter, the model was applied to predict the probability of landslides for rainfall data of different return periods. Using a predicted map of probability, the study area was classified into four ranks of landslide susceptibility: low, medium, high, and very high. As a result, most high susceptibility areas are located on the western portion of the study area. Several train stations and railways are located on sites with a high susceptibility ranking.

  5. TRIGRS Application for landslide susceptibility mapping

    Science.gov (United States)

    Sugiarti, K.; Sukristiyanti, S.

    2018-02-01

    Research on landslide susceptibility has been carried out using several different methods. TRIGRS is a modeling program for landslide susceptibility by considering pore water pressure changes due to infiltration of rainfall. This paper aims to present a current state-of-the-art science on the development and application of TRIGRS. Some limitations of TRIGRS, some developments of it to improve its modeling capability, and some examples of the applications of some versions of it to model the effect of rainfall variation on landslide susceptibility are reviewed and discussed.

  6. Landslide susceptibility map: from research to application

    Science.gov (United States)

    Fiorucci, Federica; Reichenbach, Paola; Ardizzone, Francesca; Rossi, Mauro; Felicioni, Giulia; Antonini, Guendalina

    2014-05-01

    Susceptibility map is an important and essential tool in environmental planning, to evaluate landslide hazard and risk and for a correct and responsible management of the territory. Landslide susceptibility is the likelihood of a landslide occurring in an area on the basis of local terrain conditions. Can be expressed as the probability that any given region will be affected by landslides, i.e. an estimate of "where" landslides are likely to occur. In this work we present two examples of landslide susceptibility map prepared for the Umbria Region and for the Perugia Municipality. These two maps were realized following official request from the Regional and Municipal government to the Research Institute for the Hydrogeological Protection (CNR-IRPI). The susceptibility map prepared for the Umbria Region represents the development of previous agreements focused to prepare: i) a landslide inventory map that was included in the Urban Territorial Planning (PUT) and ii) a series of maps for the Regional Plan for Multi-risk Prevention. The activities carried out for the Umbria Region were focused to define and apply methods and techniques for landslide susceptibility zonation. Susceptibility maps were prepared exploiting a multivariate statistical model (linear discriminant analysis) for the five Civil Protection Alert Zones defined in the regional territory. The five resulting maps were tested and validated using the spatial distribution of recent landslide events that occurred in the region. The susceptibility map for the Perugia Municipality was prepared to be integrated as one of the cartographic product in the Municipal development plan (PRG - Piano Regolatore Generale) as required by the existing legislation. At strategic level, one of the main objectives of the PRG, is to establish a framework of knowledge and legal aspects for the management of geo-hydrological risk. At national level most of the susceptibility maps prepared for the PRG, were and still are obtained

  7. Evaluation of earthquake-triggered landslides in el Salvador using a Gis based newmark model

    OpenAIRE

    García Rodríguez, María José; Havenith, Hans; Benito Oterino, Belen

    2008-01-01

    In this work, a model for evaluating earthquake-triggered landslides hazard following the Newmark methodology is developed in a Geographical Information System (GIS). It is applied to El Salvador, one of the most seismically active regions in Central America, where the last severe destructive earthquakes occurred in January 13th and February 13th, 2001. The first of these earthquakes triggered more the 500 landslides and killed at least 844 people. This study is centred on the area (10x6km) w...

  8. Evaluating performances of simplified physically based landslide susceptibility models.

    Science.gov (United States)

    Capparelli, Giovanna; Formetta, Giuseppe; Versace, Pasquale

    2015-04-01

    Rainfall induced shallow landslides cause significant damages involving loss of life and properties. Prediction of shallow landslides susceptible locations is a complex task that involves many disciplines: hydrology, geotechnical science, geomorphology, and statistics. Usually to accomplish this task two main approaches are used: statistical or physically based model. This paper presents a package of GIS based models for landslide susceptibility analysis. It was integrated in the NewAge-JGrass hydrological model using the Object Modeling System (OMS) modeling framework. The package includes three simplified physically based models for landslides susceptibility analysis (M1, M2, and M3) and a component for models verifications. It computes eight goodness of fit indices (GOF) by comparing pixel-by-pixel model results and measurements data. Moreover, the package integration in NewAge-JGrass allows the use of other components such as geographic information system tools to manage inputs-output processes, and automatic calibration algorithms to estimate model parameters. The system offers the possibility to investigate and fairly compare the quality and the robustness of models and models parameters, according a procedure that includes: i) model parameters estimation by optimizing each of the GOF index separately, ii) models evaluation in the ROC plane by using each of the optimal parameter set, and iii) GOF robustness evaluation by assessing their sensitivity to the input parameter variation. This procedure was repeated for all three models. The system was applied for a case study in Calabria (Italy) along the Salerno-Reggio Calabria highway, between Cosenza and Altilia municipality. The analysis provided that among all the optimized indices and all the three models, Average Index (AI) optimization coupled with model M3 is the best modeling solution for our test case. This research was funded by PON Project No. 01_01503 "Integrated Systems for Hydrogeological Risk

  9. Landslide susceptibility and risk assessment: specificities for road networks

    Science.gov (United States)

    Pellicani, Roberta; Argentiero, Ilenia; Parisi, Alessandro; Spilotro, Giuseppe

    2017-04-01

    A regional-scale assessment of landslide susceptibility and risk along the main road corridors crossing the provincial territory of Matera (Basilicata Region, Southern Italy) was carried out. The entire provincial road network extends for about 1,320 km through a territory, of which represents the main connection infrastructure among thirty-one municipalities due to the lack of an efficient integrated transportation system through the whole regional territory. For this reason, the strategic importance of these roads consists in their uniqueness in connecting every urban center with the socio-economic surrounding context. These roads and their vehicular traffic are continuously exposed to instability processes (about the 40% of the total length is disrupted by landslides), characterized both by high intensity and low frequency and by low intensity and high frequency. This last typology, consisting in small shallow landslides, is particularly hazardous for the roads since it is widespread along the road network, its occurrence is connected to rainfalls and determines high vulnerability conditions for the road in terms of interruption of vehicular traffic. A GIS-based heuristic-bivariate statistical predictive model was performed to assess and map the landslide susceptibility in the study area, by using a polynomial function of eight predisposing factors, weighted according to their influence on the landslide phenomena, recognized and collected in an inventory. Susceptibility associated to small shallow phenomena was assessed by using a polynomial function of specific factors, such as slope angle and aspect, lithological outcrops, rainfalls, etc. In absence of detailed input data, the spatial distribution of landslide risk along the road corridors was assessed and mapped using a qualitative hazard-consequence matrix approach, by which risk is obtained by combining hazard categories with consequence classes pairwise in a two-dimensional table or matrix. Landslide

  10. Landslide susceptibility zonation in part of Tehri reservoir region

    Indian Academy of Sciences (India)

    Fuzzy logic; landslide susceptibility; frequency ratio. ... zones using landslide frequency ratio and fuzzy logic in GIS environment is presented for Tehri ... Temporal remote sensing data was used to prepare important landslide causative factor ...

  11. GIS based landslide hazard evaluation and zonation – A case from Jeldu District, Central Ethiopia

    Directory of Open Access Journals (Sweden)

    Tilahun Hamza

    2017-04-01

    The results revealed that 12% (5.64 km2 of the study area falls under no hazard, 27% (12.69 km2 as low hazard, 32% (15.04 km2 as moderate hazard, 21% (9.87 km2 as high hazard and the rest 8% (3.76 km2 as very high hazard. The validation of LHZ map shows that, 92% of past landslides fall in high or very high hazard zones, while 6% fall in medium and only 2% in low landslide hazard zones. The validation of LHZ map thus, reasonably showed that the adopted methodology produced satisfactory results and the delineated hazard zones may practically be applied for the regional planning and development of infrastructures in the area.

  12. Fuzzy rule-based landslide susceptibility mapping in Yığılca Forest District (Northwest of Turkey

    Directory of Open Access Journals (Sweden)

    Abdurrahim Aydın

    2016-07-01

    Full Text Available Landslide susceptibility map of Yığılca Forest District was formed based on developed fuzzy rules using GIS-based FuzzyCell software. An inventory of 315 landslides was updated through fieldworks after inventory map previously generated by the authors. Based on the landslide susceptibility mapping study previously made in the same area, for the comparison of two maps, same 8 landslide conditioning parameters were selected and then fuzzified for the landslide susceptibility mapping: land use, lithology, elevation, slope, aspect, distance to streams, distance to roads, and plan curvature. Mamdani model was selected as fuzzy inference system. After fuzzy rules definition, Center of Area (COA was selected as defuzzification method in model. The output of developed model was normalized between 0 and 1, and then divided five classes such as very low, low, moderate, high, and very high. According to developed model based 8 conditioning parameters, landslide susceptibility in Yığılca Forest District varies between 32 and 67 (in range of 0-100 with 0.703 Area Under the Curve (AUC value. According to classified landslide susceptibility map, in Yığılca Forest District, 32.89% of the total area has high and very high susceptibility while 29.59% of the area has low and very low susceptibility and the rest located in moderate susceptibility. The result of developed fuzzy rule based model compared with previously generated landslide map with logistic regression (LR. According to comparison of the results of two studies, higher differences exist in terms of AUC value and dispersion of susceptibility classes. This is because fuzzy rule based model completely depends on how parameters are classified and fuzzified and also depends on how truly the expert composed the rules. Even so, GIS-based fuzzy applications provide very valuable facilities for reasoning, which makes it possible to take into account inaccuracies and uncertainties.

  13. Landslide susceptibility analysis using Probabilistic Certainty Factor ...

    Indian Academy of Sciences (India)

    done using many different methods and techniques. A detailed outline of .... of depressions where water is accumulated, espe- cially when the ..... The two decision rules that must be satisfied for a good landslide .... making the susceptibility zonation relative. This is ..... tional Conference on Imaging Systems and Techniques,.

  14. Integration of landslide susceptibility products in the environmental plans

    Science.gov (United States)

    Fiorucci, Federica; Reichenbach, Paola; Rossi, Mauro; Cardinali, Mauro; Guzzetti, Fausto

    2015-04-01

    Landslides are one of the most destructive natural hazard that causes damages to urban area worldwide. The knowledge of where a landslide could occur is essential for the strategic management of the territory and for a good urban planning . In this contest landslide susceptibility zoning (LSZ) is crucial to provide information on the degree to which an area can be affected by future slope movements. Despite landslide susceptibility maps have been prepared extensively during the last decades, there are few examples of application is in the environmental plans (EP). In this work we present a proposal for the integration of the landslide inventory map with the following landslide susceptibility products: (i) landslide susceptibility zonation , (ii) the associated error map and (iii) the susceptibility uncertainty map. Moreover we proposed to incorporate detailed morphological studies for the evaluation of landslide risk associated to local parceling plan. The integration of all this information is crucial for the management of landslide risk in urban expansions forecasts. Municipality, province and regional administration are often not able to support the costs of landslide risk evaluation for extensive areas but should concentrate their financial resources to specific hazardous and unsafe situations defined by the result of the integration of landslide susceptibility products. Zonation and detail morphological analysis should be performed taking into account the existing laws and regulations, and could become a starting point to discuss new regulations for the landslide risk management.

  15. A Support Vector Machine for Landslide Susceptibility Mapping in Gangwon Province, Korea

    Directory of Open Access Journals (Sweden)

    Saro Lee

    2017-01-01

    Full Text Available In this study, the support vector machine (SVM was applied and validated by using the geographic information system (GIS in order to map landslide susceptibility. In order to test the usefulness and effectiveness of the SVM, two study areas were carefully selected: the PyeongChang and Inje areas of Gangwon Province, Korea. This is because, not only did many landslides (2098 in PyeongChang and 2580 in Inje occur in 2006 as a result of heavy rainfall, but the 2018 Winter Olympics will be held in these areas. A variety of spatial data, including landslides, geology, topography, forest, soil, and land cover, were identified and collected in the study areas. Following this, the spatial data were compiled in a GIS-based database through the use of aerial photographs. Using this database, 18 factors relating to topography, geology, soil, forest and land use, were extracted and applied to the SVM. Next, the detected landslide data were randomly divided into two sets; one for training and the other for validation of the model. Furthermore, a SVM, specifically a type of data-mining classification model, was applied by using radial basis function kernels. Finally, the estimated landslide susceptibility maps were validated. In order to validate the maps, sensitivity analyses were carried out through area-under-the-curve analysis. The achieved accuracies from the SVM were approximately 81.36% and 77.49% in the PyeongChang and Inje areas, respectively. Moreover, a sensitivity assessment of the factors was performed. It was found that all of the factors, except for soil topography, soil drainage, soil material, soil texture, timber diameter, timber age, and timber density for the PyeongChang area, and timber diameter, timber age, and timber density for the Inje area, had relatively positive effects on the landslide susceptibility maps. These results indicate that SVMs can be useful and effective for landslide susceptibility analysis.

  16. Landslide inventory and susceptibility modelling using geospatial tools, in Hunza-Nagar valley, northern Pakistan

    NARCIS (Netherlands)

    Bacha, Alam Sher; Shafique, Muhammad; van der Werff, H.M.A.

    2018-01-01

    A comprehensive landslide inventory and susceptibility maps are prerequisite for developing and implementing landslide mitigation strategies. Landslide susceptibility maps for the landslides prone regions in northern Pakistan are rarely available. The Hunza-Nagar valley in northern Pakistan is known

  17. GIS-based debris flow source and runout susceptibility assessment from DEM data – a case study in NW Nicaragua

    Directory of Open Access Journals (Sweden)

    J. M. Vilaplana

    2007-11-01

    Full Text Available In October 1998, Hurricane Mitch triggered numerous landslides (mainly debris flows in Honduras and Nicaragua, resulting in a high death toll and in considerable damage to property. The potential application of relatively simple and affordable spatial prediction models for landslide hazard mapping in developing countries was studied. Our attention was focused on a region in NW Nicaragua, one of the most severely hit places during the Mitch event. A landslide map was obtained at 1:10 000 scale in a Geographic Information System (GIS environment from the interpretation of aerial photographs and detailed field work. In this map the terrain failure zones were distinguished from the areas within the reach of the mobilized materials. A Digital Elevation Model (DEM with 20 m×20 m of pixel size was also employed in the study area. A comparative analysis of the terrain failures caused by Hurricane Mitch and a selection of 4 terrain factors extracted from the DEM which, contributed to the terrain instability, was carried out. Land propensity to failure was determined with the aid of a bivariate analysis and GIS tools in a terrain failure susceptibility map. In order to estimate the areas that could be affected by the path or deposition of the mobilized materials, we considered the fact that under intense rainfall events debris flows tend to travel long distances following the maximum slope and merging with the drainage network. Using the TauDEM extension for ArcGIS software we generated automatically flow lines following the maximum slope in the DEM starting from the areas prone to failure in the terrain failure susceptibility map. The areas crossed by the flow lines from each terrain failure susceptibility class correspond to the runout susceptibility classes represented in a runout susceptibility map. The study of terrain failure and runout susceptibility enabled us to obtain a spatial prediction for landslides, which could contribute to landslide risk

  18. Landslide Susceptibility Statistical Methods: A Critical and Systematic Literature Review

    Science.gov (United States)

    Mihir, Monika; Malamud, Bruce; Rossi, Mauro; Reichenbach, Paola; Ardizzone, Francesca

    2014-05-01

    Landslide susceptibility assessment, the subject of this systematic review, is aimed at understanding the spatial probability of slope failures under a set of geomorphological and environmental conditions. It is estimated that about 375 landslides that occur globally each year are fatal, with around 4600 people killed per year. Past studies have brought out the increasing cost of landslide damages which primarily can be attributed to human occupation and increased human activities in the vulnerable environments. Many scientists, to evaluate and reduce landslide risk, have made an effort to efficiently map landslide susceptibility using different statistical methods. In this paper, we do a critical and systematic landslide susceptibility literature review, in terms of the different statistical methods used. For each of a broad set of studies reviewed we note: (i) study geography region and areal extent, (ii) landslide types, (iii) inventory type and temporal period covered, (iv) mapping technique (v) thematic variables used (vi) statistical models, (vii) assessment of model skill, (viii) uncertainty assessment methods, (ix) validation methods. We then pulled out broad trends within our review of landslide susceptibility, particularly regarding the statistical methods. We found that the most common statistical methods used in the study of landslide susceptibility include logistic regression, artificial neural network, discriminant analysis and weight of evidence. Although most of the studies we reviewed assessed the model skill, very few assessed model uncertainty. In terms of geographic extent, the largest number of landslide susceptibility zonations were in Turkey, Korea, Spain, Italy and Malaysia. However, there are also many landslides and fatalities in other localities, particularly India, China, Philippines, Nepal and Indonesia, Guatemala, and Pakistan, where there are much fewer landslide susceptibility studies available in the peer-review literature. This

  19. Landslide Susceptibility Index Determination Using Aritificial Neural Network

    Science.gov (United States)

    Kawabata, D.; Bandibas, J.; Urai, M.

    2004-12-01

    The occurrence of landslide is the result of the interaction of complex and diverse environmental factors. The geomorphic features, rock types and geologic structure are especially important base factors of the landslide occurrence. Generating landslide susceptibility index by defining the relationship between landslide occurrence and that base factors using conventional mathematical and statistical methods is very difficult and inaccurate. This study focuses on generating landslide susceptibility index using artificial neural networks in Southern Japanese Alps. The training data are geomorphic (e.g. altitude, slope and aspect) and geologic parameters (e.g. rock type, distance from geologic boundary and geologic dip-strike angle) and landslides. Artificial neural network structure and training scheme are formulated to generate the index. Data from areas with and without landslide occurrences are used to train the network. The network is trained to output 1 when the input data are from areas with landslides and 0 when no landslide occurred. The trained network generates an output ranging from 0 to 1 reflecting the possibility of landslide occurrence based on the inputted data. Output values nearer to 1 means higher possibility of landslide occurrence. The artificial neural network model is incorporated into the GIS software to generate a landslide susceptibility map.

  20. Landslides susceptibility mapping at Gunung Ciremai National Park

    Science.gov (United States)

    Faizin; Nur, Bambang Azis

    2018-02-01

    In addition to agriculture, tourism became one of primary economic income for communities around Mount Ciremai, West, Java. Unfortunately, the landscape of West Java has many potential causes to disasters, mainly landslides. Mapping of disaster susceptibility area is needed as a consideration of tourism planning. The study was conducted in Gunung Ciremai National Park, West Java. This paper propose a methodology to map landslides susceptibilities based on spatial data. Using Geographic Information System tools, several environmental parameters such as slope, land use, elevation, and lithology are scored to build a landslide susceptibility map. Then, susceptibility map is overlaid with Utilization Zone.

  1. Susceptibility analysis of landslide in Chittagong City Corporation Area, Bangladesh

    Directory of Open Access Journals (Sweden)

    Sourav Das

    2015-06-01

    Full Text Available In Chittagong city, landslide phenomena is the most burning issue which causes great problems to the life and properties and it is increasing day by day and becoming one of the main problems of city life. On 11 June 2007, a massive landslide happened in Chittagong City Corporation (CCC area, a large number of foothill settlements and slums were demolished; more than 90 people died and huge resource destruction took place. It is therefore essential to analyze the landslide susceptibility for CCC area to prepare mitigation strategies as well as assessing the impacts of climate change. To assess community susceptibility of landslide hazard, a landslide susceptibility index map has been prepared using analytical hierarchy process (AHP model based on geographic information system (GIS and remote sensing (RS and its susceptibility is analyzed through community vulnerability assessment tool (CVAT. The major findings of the research are 27% of total CCC area which is susceptible to landslide hazard and whereas 6.5 sq.km areas are found very highly susceptible. The landslide susceptible areas of CCC have also been analyzed in respect of physical, social, economic, environmental and critical facilities and it is found that the overall CCC area is highly susceptible to landslide hazard. So the findings of the research can be utilized to prioritize risk mitigation investments, measures to strengthen the emergency preparedness and response mechanisms for reducing the losses and damages due to future landslide events. DOI: http://dx.doi.org/10.3126/ije.v4i2.12635 International Journal of Environment Vol.4(2 2015: 157-181

  2. GIS based Grid overlay method versus modeling approach – A comparative study for landslide hazard zonation (LHZ in Meta Robi District of West Showa Zone in Ethiopia

    Directory of Open Access Journals (Sweden)

    Tarun Kumar Raghuvanshi

    2015-12-01

    Full Text Available The present study area is located in Meta Robi District of West Showa Zone in Oromiya Regional State in Ethiopia. The main objective of the present study was to evaluate landslide hazard zonation (LHZ by utilizing ‘Grid overlay’ and ‘GIS modeling’ approaches. Also, it was attempted to know the effectiveness of the two methods. The methodology followed was based on the analysis of past landslides in the area. For the present study six causative factors namely; slope material, slope, aspect, elevation, land use and land cover and groundwater surface traces were considered. Later, Landslide Susceptibility Index (LSI was computed based on the relative influence of causative factors on past landslides. For the ‘Grid overlay’ method a grid with cells 10 m by 10 m was overlaid over the study area and later it was geo-processed to delineate various sub-classes of each causative factor. LSI values were assigned to each sub-causative factor within each grid cell and a ‘Total Landslide Susceptibility Index’ was calculated to produce the LHZ map. For ‘GIS modeling’ the same causative factors and similar LSI values were utilized. In the case of LHZ map prepared by the ‘Grid overlay’ method about 82% of past landslides fall within ‘very high hazard’ or ‘high hazard’ zones whereas in the case of ‘GIS modeling’ about 95% of past landslides fall within ‘very high hazard’ or ‘high hazard’ zones. Finally, the validation showed that ‘GIS modeling’ produced better LHZ map. Also, ‘Grid overlay’ method is more tedious and time consuming as compared to GIS modeling.

  3. LANDSLIDE SUSCEPTIBILITY ASSESSMENT THROUGH FUZZY LOGIC INFERENCE SYSTEM (FLIS

    Directory of Open Access Journals (Sweden)

    T. Bibi

    2016-09-01

    Full Text Available Landslide is among one of the most important natural hazards that lead to modification of the environment. It is a regular feature of a rapidly growing district Mansehra, Pakistan. This caused extensive loss of life and property in the district located at the foothills of Himalaya. Keeping in view the situation it is concluded that besides structural approaches the non-structural approaches such as hazard and risk assessment maps are effective tools to reduce the intensity of damage. A landslide susceptibility map is base for engineering geologists and geomorphologists. However, it is not easy to produce a reliable susceptibility map due to complex nature of landslides. Since 1980s, several mathematical models have been developed to map landslide susceptibility and hazard. Among various models this paper is discussing the effectiveness of fuzzy logic approach for landslide susceptibility mapping in District Mansehra, Pakistan. The factor maps were modified as landslide susceptibility and fuzzy membership functions were assessed for each class. Likelihood ratios are obtained for each class of contributing factors by considering the expert opinion. The fuzzy operators are applied to generate landslide susceptibility maps. According to this map, 17% of the study area is classified as high susceptibility, 32% as moderate susceptibility, 51% as low susceptibility and areas. From the results it is found that the fuzzy model can integrate effectively with various spatial data for landslide hazard mapping, suggestions in this study are hope to be helpful to improve the applications including interpretation, and integration phases in order to obtain an accurate decision supporting layer.

  4. Landslide temporal analysis and susceptibility assessment as bases for landslide mitigation, Machu Picchu, Peru

    Czech Academy of Sciences Publication Activity Database

    Klimeš, Jan

    2013-01-01

    Roč. 70, č. 2 (2013), s. 913-925 ISSN 1866-6280 Institutional research plan: CEZ:AV0Z30460519 Keywords : landslide inventory * landslide frequency * susceptibility map Subject RIV: DE - Earth Magnetism, Geodesy, Geography Impact factor: 1.572, year: 2013

  5. A comparative study on the landslide susceptibility mapping using ...

    Indian Academy of Sciences (India)

    from faults, lithology, normalized difference vegetation index (NDVI), sediment transport index (STI), stream power ... economic losses and creating high maintenance costs, are ..... evidence method to landslide susceptibility map- ping using ...

  6. Landslide susceptibility zonation in part of Tehri reservoir region ...

    Indian Academy of Sciences (India)

    Validation of the model was performed by using cumulative ..... thrusts, folds and joints of varying shape and size ...... Lee S, Choi J and Min K 2002 Landslide susceptibility analy- ... cross-validation in three test areas using a frequency.

  7. Effects of Inventory Bias on Landslide Susceptibility Calculations

    Science.gov (United States)

    Stanley, T. A.; Kirschbaum, D. B.

    2017-01-01

    Many landslide inventories are known to be biased, especially inventories for large regions such as Oregon's SLIDO or NASA's Global Landslide Catalog. These biases must affect the results of empirically derived susceptibility models to some degree. We evaluated the strength of the susceptibility model distortion from postulated biases by truncating an unbiased inventory. We generated a synthetic inventory from an existing landslide susceptibility map of Oregon, then removed landslides from this inventory to simulate the effects of reporting biases likely to affect inventories in this region, namely population and infrastructure effects. Logistic regression models were fitted to the modified inventories. Then the process of biasing a susceptibility model was repeated with SLIDO data. We evaluated each susceptibility model with qualitative and quantitative methods. Results suggest that the effects of landslide inventory bias on empirical models should not be ignored, even if those models are, in some cases, useful. We suggest fitting models in well-documented areas and extrapolating across the study region as a possible approach to modeling landslide susceptibility with heavily biased inventories.

  8. Landslide susceptibility mapping using a neuro-fuzzy

    Science.gov (United States)

    Lee, S.; Choi, J.; Oh, H.

    2009-12-01

    This paper develops and applied an adaptive neuro-fuzzy inference system (ANFIS) based on a geographic information system (GIS) environment using landslide-related factors and location for landslide susceptibility mapping. A neuro-fuzzy system is based on a fuzzy system that is trained by a learning algorithm derived from the neural network theory. The learning procedure operates on local information, and causes only local modifications in the underlying fuzzy system. The study area, Boun, suffered much damage following heavy rain in 1998 and was selected as a suitable site for the evaluation of the frequency and distribution of landslides. Boun is located in the central part of Korea. Landslide-related factors such as slope, soil texture, wood type, lithology, and density of lineament were extracted from topographic, soil, forest, and lineament maps. Landslide locations were identified from interpretation of aerial photographs and field surveys. Landslide-susceptible areas were analyzed by the ANFIS method and mapped using occurrence factors. In particular, we applied various membership functions (MFs) and analysis results were verified using the landslide location data. The predictive maps using triangular, trapezoidal, and polynomial MFs were the best individual MFs for modeling landslide susceptibility maps (84.96% accuracy), proving that ANFIS could be very effective in modeling landslide susceptibility mapping. Various MFs were used in this study, and after verification, the difference in accuracy according to the MFs was small, between 84.81% and 84.96%. The difference was just 0.15% and therefore the choice of MFs was not important in the study. Also, compared with the likelihood ratio model, which showed 84.94%, the accuracy was similar. Thus, the ANFIS could be applied to other study areas with different data and other study methods such as cross-validation. The developed ANFIS learns the if-then rules between landslide-related factors and landslide

  9. Landslide Susceptibility Mapping Based on Selected Optimal Combination of Landslide Predisposing Factors in a Large Catchment

    Directory of Open Access Journals (Sweden)

    Qianqian Wang

    2015-12-01

    Full Text Available Landslides are usually initiated under complex geological conditions. It is of great significance to find out the optimal combination of predisposing factors and create an accurate landslide susceptibility map based on them. In this paper, the Information Value Model was modified to make the Modified Information Value (MIV Model, and together with GIS (Geographical Information System and AUC (Area Under Receiver Operating Characteristic Curve test, 32 factor combinations were evaluated separately, and factor combination group with members Slope, Lithology, Drainage network, Annual precipitation, Faults, Road and Vegetation was selected as the optimal combination group with an accuracy of 95.0%. Based on this group, a landslide susceptibility zonation map was drawn, where the study area was reclassified into five classes, presenting an accurate description of different levels of landslide susceptibility, with 79.41% and 13.67% of the validating field survey landslides falling in the Very High and High zones, respectively, mainly distributed in the south and southeast of the catchment. It showed that MIV model can tackle the problem of “no data in subclass” well, generate the true information value and show real running trend, which performs well in showing the relationship between predisposing factors and landslide occurrence and can be used for preliminary landslide susceptibility assessment in the study area.

  10. GIS-based soil liquefaction susceptibility map of Mumbai city for earthquake events

    Science.gov (United States)

    Mhaske, Sumedh Yamaji; Choudhury, Deepankar

    2010-03-01

    The problem of liquefaction of soil during seismic event is one of the important topics in the field of Geotechnical Earthquake Engineering. Liquefaction of soil is generally occurs in loose cohesionless saturated soil when pore water pressure increases suddenly due to induced ground motion and shear strength of soil decreases to zero and leading the structure situated above to undergo a large settlement, or failure. The failures took place due to liquefaction induced soil movement spread over few square km area continuously. Hence this is a problem where spatial variation involves and to represent this spatial variation Geographic Information System (GIS) is very useful in decision making about the area subjected to liquefaction. In this paper, GIS software GRAM++ is used to prepare soil liquefaction susceptibility map for entire Mumbai city in India by marking three zones viz. critically liquefiable soil, moderately liquefiable soil and non liquefiable soil. Extensive field borehole test data for groundwater depth, standard penetration test (SPT) blow counts, dry density, wet density and specific gravity, etc. have been collected from different parts of Mumbai. Simplified procedure of Youd et al. (2001) is used for calculation of factor of safety against soil liquefaction potential. Mumbai city and suburban area are formed by reclaiming lands around seven islands since 1865 till current date and still it is progressing in the area such as Navi Mumbai and beyond Borivali to Mira road suburban area. The factors of safety against soil liquefaction were determined for earthquake moment magnitude ranging from Mw = 5.0 to 7.5. It is found that the areas like Borivali, Malad, Dahisar, Bhandup may prone to liquefaction for earthquake moment magnitude ranging from Mw = 5.0 to 7.5. The liquefaction susceptibility maps were created by using GRAM++ by showing the areas where the factor of safety against the soil liquefaction is less than one. Proposed liquefaction

  11. A GIS-Based Procedure for Landslide Intensity Evaluation and Specific risk Analysis Supported by Persistent Scatterers Interferometry (PSI

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    Silvia Bianchini

    2017-10-01

    Full Text Available The evaluation of landslide specific risk, defined as the expected degree of loss due to landslides, requires the parameterization and the combination of a number of socio-economic and geological factors, which often needs the interaction of different skills and expertise (geologists, engineers, planners, administrators, etc.. The specific risk sub-components, i.e., hazard and vulnerability of elements at risk, can be determined with different levels of detail depending on the available auxiliary data and knowledge of the territory. These risk factors are subject to short-term variations and nowadays turn out to be easily mappable and evaluable through remotely sensed data and GIS (Geographic Information System tools. In this work, we propose a qualitative approach at municipal scale for producing a “specific risk” map, supported by recent satellite PSI (Persistent Scatterer Interferometry data derived from SENTINEL-1 C-band images in the spanning time 2014–2017, implemented in a GIS environment. In particular, PSI measurements are useful for the updating of a landslide inventory map of the area of interest and are exploited for the zonation map of the intensity of ground movements, needed for evaluating the vulnerability over the study area. Our procedure is presented throughout the application to the Volterra basin and the output map could be useful to support the local authorities with updated basic information required for environmental knowledge and planning at municipal level. Moreover, the proposed procedure is easily managed and repeatable in other case studies, as well as exploiting different SAR sensors in L- or X-band.

  12. Mapping Landslides Susceptibility in a Traditional Northern Nigerian City

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    Oluwafemi, Olawale A.; Yakubu, Tahir A.; Muhammad, Mahmud U.; Shitta, Nyofo; Akinwumiju, Akinola S.

    2018-05-01

    As a result of dearth of relevant information about Landslides Susceptibility in Nigeria, the monitoring and assessment appears intractable. Hence, the study developed a Remote Sensing approach to mapping landslides susceptibility, landuse and landcover analysis in Jos South LGA, Plateau State, Nigeria. Field Observation, SPOT 5 2009 and 2012, ASTER DEM 2009, Geological Map 2006, Topographical Map 1966 were used to map Landslide Susceptibility and Landuse /Lancover Analysis in the study area. Geospatial Analytical Operations employed using ArcGIS 10.3 and Erdas Imagine 2014 include Spatial Modeling, Vectorization, Pre-lineament Extraction, Image Processing among others. Result showed that 72.38 % of the study area is underlain by granitic rocks. The landuse/cover types delineated for the study area include floodplain (29.27 %), farmland (23.96 %), sparsely vegetated land (15.43 %), built up area (13.65 %), vegetated outcrop (8.48 %), light vegetation (5.37 %), thick vegetation (2.39 %), water body (0.58 %), plantation (0.50 %) and mining pond (0.37 %). Landslide Susceptibility Analysis also revealed that 87 % of the study area is relatively at low to very low risk of landslide event. While only 13 % of the study area is at high to very high risk of landslide event. The study revealed that the susceptibility of landslide event is very low in the study area. However, possible landslide event in the hot spots could be pronounced and could destabilize the natural and man-made environmental systems of the study area.

  13. An overview of a GIS method for mapping landslides and assessing landslide susceptibility in the Río La Carbonera watershed, on the SE flank of Pico de Orizaba Volcano, Mexico.

    Science.gov (United States)

    Legorreta Paulin, G.; Bursik, M. I.; Contreras, T.

    2015-12-01

    This poster provides an overview of the on-going research project (Grant PAPIIT # IN102115) from the Institute of Geography at the National Autonomous University of Mexico (UNAM) that seeks to conduct a multi-temporal landslide inventory, produce a landslide susceptibility map, and estimate sediment production by using Geographic Information Systems (GIS). The Río La Carbonera watershed on the southeastern flank of Pico de Orizaba volcano, the highest mountain in Mexico, is selected as a study area. The catchment covers 71.9 km2 with elevations ranging from 1224 to 3643 m a.s.l. and hillslopes between landslides. The methodology encompasses three main stages of analysis to assess landslide hazards: Stage 1 builds a historic landslide inventory. In the study area, an inventory of more than 200 landslides is created from multi-temporal aerial-photo-interpretation and local field surveys to assess landslide distribution. All landslides were digitized into a geographic information system (GIS), and a spatial geo-database of landslides was constructed from standardized GIS datasets. Stage 2 calculates the susceptibility for the watershed. During this stage, (SINMAP using default values) is evaluated. Stage 3 Estimate the potential total material delivered to the main stream drainage channel by all landslides in the catchment. Detailed geometric measurements of individual landslides visited during the field work will be carried out to obtain the landslide area and volume. These measurements revealed an empirical relationship between area and volume that took the form of a power law. This relationship will be used to estimate the potential volume of material delivered to the catchment. The technique and its implementation of each stage in a GIS-based technology is presented and discussed.

  14. Large-area landslide susceptibility with optimized slope-units

    Science.gov (United States)

    Alvioli, Massimiliano; Marchesini, Ivan; Reichenbach, Paola; Rossi, Mauro; Ardizzone, Francesca; Fiorucci, Federica; Guzzetti, Fausto

    2017-04-01

    A Slope-Unit (SU) is a type of morphological terrain unit bounded by drainage and divide lines that maximize the within-unit homogeneity and the between-unit heterogeneity across distinct physical and geographical boundaries [1]. Compared to other terrain subdivisions, SU are morphological terrain unit well related to the natural (i.e., geological, geomorphological, hydrological) processes that shape and characterize natural slopes. This makes SU easily recognizable in the field or in topographic base maps, and well suited for environmental and geomorphological analysis, in particular for landslide susceptibility (LS) modelling. An optimal subdivision of an area into a set of SU depends on multiple factors: size and complexity of the study area, quality and resolution of the available terrain elevation data, purpose of the terrain subdivision, scale and resolution of the phenomena for which SU are delineated. We use the recently developed r.slopeunits software [2,3] for the automatic, parametric delineation of SU within the open source GRASS GIS based on terrain elevation data and a small number of user-defined parameters. The software provides subdivisions consisting of SU with different shapes and sizes, as a function of the input parameters. In this work, we describe a procedure for the optimal selection of the user parameters through the production of a large number of realizations of the LS model. We tested the software and the optimization procedure in a 2,000 km2 area in Umbria, Central Italy. For LS zonation we adopt a logistic regression model implemented in an well-known software [4,5], using about 50 independent variables. To select the optimal SU partition for LS zonation, we want to define a metric which is able to quantify simultaneously: (i) slope-unit internal homogeneity (ii) slope-unit external heterogeneity (iii) landslide susceptibility model performance. To this end, we define a comprehensive objective function S, as the product of three

  15. Predictive susceptibility analysis of typhoon induced landslides in Central Taiwan

    Science.gov (United States)

    Shou, Keh-Jian; Lin, Zora

    2017-04-01

    Climate change caused by global warming affects Taiwan significantly for the past decade. The increasing frequency of extreme rainfall events, in which concentrated and intensive rainfalls generally cause geohazards including landslides and debris flows. The extraordinary, such as 2004 Mindulle and 2009 Morakot, hit Taiwan and induced serious flooding and landslides. This study employs rainfall frequency analysis together with the atmospheric general circulation model (AGCM) downscaling estimation to understand the temporal rainfall trends, distributions, and intensities in the adopted Wu River watershed in Central Taiwan. To assess the spatial hazard of the landslides, landslide susceptibility analysis was also applied. Different types of rainfall factors were tested in the susceptibility models for a better accuracy. In addition, the routes of typhoons were also considered in the predictive analysis. The results of predictive analysis can be applied for risk prevention and management in the study area.

  16. A multi-annual landslide inventory for the assessment of shallow landslide susceptibility - Two test cases in Vorarlberg, Austria

    Science.gov (United States)

    Zieher, Thomas; Perzl, Frank; Rössel, Monika; Rutzinger, Martin; Meißl, Gertraud; Markart, Gerhard; Geitner, Clemens

    2016-04-01

    Geomorphological landslide inventories provide crucial input data for any study on the assessment of landslide susceptibility, hazard or risk. Several approaches for assessing landslide susceptibility have been proposed to identify areas particularly vulnerable to this natural hazard. What they have in common is the need for data of observed landslides. Therefore the first step of any study on landslide susceptibility is usually the compilation of a geomorphological landslide inventory using a geographical information system. Recent research has proved the feasibility of orthophoto interpretation for the preparation of an inventory aimed at the delineation of landslides with the use of distinctive signs in the imagery data. In this study a multi-annual landslide inventory focusing on shallow landslides (i.e. translational soil slides of 0-2 m in depth) was compiled for two study areas in Vorarlberg (Austria) from the interpretation of nine orthophoto series. In addition, derivatives of two generations of airborne laser scanning data aided the mapping procedure. Landslide scar areas were delineated on the basis of a high-resolution differential digital terrain model. The derivation of landslide volumes, depths and depth-to-length ratios are discussed. Results show that most mapped landslides meet the definition of a shallow landslide. The inventory therefore provides the data basis for the assessment of shallow landslide susceptibility and allows for the application of various modelling techniques.

  17. Rainfall-induced landslide susceptibility zonation of Puerto Rico

    Science.gov (United States)

    Chiara Lepore; Sameer A. Kamal; Peter Shanahan; Rafael L. Bras

    2011-01-01

    Landslides are a major geologic hazard with estimated tens of deaths and $1–2 billion in economic losses per year in the US alone. The island of Puerto Rico experiences one or two large events per year, often triggered in steeply sloped areas by prolonged and heavy rainfall. Identifying areas susceptible to landslides thus has great potential value for Puerto Rico and...

  18. MULTI-CRITERIA ANALYSIS APPLIED TO LANDSLIDE SUSCEPTIBILITY MAPPING

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    Mariana Madruga de Brito

    2017-10-01

    Full Text Available This paper presents the application of a multi-criteria analysis (MCA tool for landslide susceptibility assessment in Porto Alegre municipality, southern Brazil. A knowledge driven approach was used, aiming to ensure an optimal use of the available information. The landslide conditioning factors considered were slope, lithology, flow accumulation and distance from lineaments. Standardization of these factors was done through fuzzy membership functions, and evaluation of their relative importance for landslide predisposition was supported by the analytic hierarchy process (AHP, based on local expert knowledge. Finally, factors were integrated in a GIS environment using the weighted linear combination (WLC method. For validation, an inventory, including 107 landslide points recorded between 2007 and 2013 was used. Results indicated that 8.2% (39.40 km² of the study area are highly and very highly susceptible to landslides. An overall accuracy of 95% was found, with an area under the receiver operating characteristic (ROC curve of 0.960. Therefore, the resulting map can be regarded as useful for monitoring landslide-prone areas. Based on the findings, it is concluded that the proposed method is effective for susceptibility assessment since it yielded meaningful results and does not require extensive input data.

  19. A preliminary regional assessment of earthquake-induced landslide susceptibility for Vrancea Seismic Region

    Science.gov (United States)

    Micu, Mihai; Balteanu, Dan; Ionescu, Constantin; Havenith, Hans; Radulian, Mircea; van Westen, Cees; Damen, Michiel; Jurchescu, Marta

    2015-04-01

    ) with head scarps near mountain tops and close to faults is similar to the one of large mass movements for which a seismic origin is proved (such as in the Tien Shan, Pamir, Longmenshan, etc.). Thus, correlations between landslide occurrence and combined seismotectonic and climatic factors are needed to support a regional multi-hazard risk assessment. The purpose of this paper is to harmonize for the first time at a regional scale the landslide predisposing factors and seismotectonic triggers and to present a first qualitative insight into the earthquake-induced landslide susceptibility for the Vrancea Seismic Region in terms of a GIS-based analysis of Newmark displacement (ND). In this way, it aims at better defining spatial and temporal distribution patterns of earthquake-triggered landslides. Arias Intensity calculation involved in the assessment considers both regional seismic hazard aspects and singular earthquake scenarios (adjusted by topography amplification factors). The known distribution of landslides mapped through digital stereographic interpretation of high-resolution aerial photos is compared with digital active fault maps and the computed ND maps to statistically outline the seismotectonic influence on slope stability in the study area. The importance of this approach resides in two main outputs. The fist one, of a fundamental nature, by providing the first regional insight into the seismic landslides triggering framework, is allowing us to understand if deep-focus earthquakes may trigger massive slope failures in an area with a relatively smooth relief (compared to the high mountain regions in Central Asia, the Himalayas), considering possible geologic and topographic site effects. The second one, more applied, will allow a better accelerometer instrumentation and monitoring of slopes and also will provide a first correlation of different levels of seismic shaking with precipitation recurrences, an important relationship within a multi-hazard risk

  20. Landslide susceptibility estimations in the Gerecse hills (Hungary).

    Science.gov (United States)

    Gerzsenyi, Dávid; Gáspár, Albert

    2017-04-01

    Surface movement processes are constantly posing threat to property in populated and agricultural areas in the Gerecse hills (Hungary). The affected geological formations are mainly unconsolidated sediments. Pleistocene loess and alluvial terrace sediments are overwhelmingly present, but fluvio-lacustrine sediments of the latest Miocene, and consolidated Eocene and Mesozoic limestones and marls can also be found in the area. Landslides and other surface movement processes are being studied for a long time in the area, but a comprehensive GIS-based geostatistical analysis have not yet been made for the whole area. This was the reason for choosing the Gerecse as the focus area of the study. However, the base data of our study are freely accessible from online servers, so the used method can be applied to other regions in Hungary. Qualitative data was acquired from the landslide-inventory map of the Hungarian Surface Movement Survey and from the Geological Map of Hungary (1 : 100 000). Morphometric parameters derived from the SRMT-1 DEM were used as quantitative variables. Using these parameters the distribution of elevation, slope gradient, aspect and categorized geological features were computed, both for areas affected and not affected by slope movements. Then likelihood values were computed for each parameters by comparing their distribution in the two areas. With combining the likelihood values of the four parameters relative hazard values were computed for each cell. This method is known as the "empirical probability estimation" originally published by Chung (2005). The map created this way shows each cell's place in their ranking based on the relative hazard values as a percentage for the whole study area (787 km2). These values provide information about how similar is a certain area to the areas already affected by landslides based on the four predictor variables. This map can also serve as a base for more complex landslide vulnerability studies involving

  1. Spatially explicit shallow landslide susceptibility mapping over large areas

    Science.gov (United States)

    Dino Bellugi; William E. Dietrich; Jonathan Stock; Jim McKean; Brian Kazian; Paul Hargrove

    2011-01-01

    Recent advances in downscaling climate model precipitation predictions now yield spatially explicit patterns of rainfall that could be used to estimate shallow landslide susceptibility over large areas. In California, the United States Geological Survey is exploring community emergency response to the possible effects of a very large simulated storm event and to do so...

  2. Rainfall induced landslide susceptibility mapping using weight-of-evidence, linear and quadratic discriminant and logistic model tree method

    Science.gov (United States)

    Hong, H.; Zhu, A. X.

    2017-12-01

    Climate change is a common phenomenon and it is very serious all over the world. The intensification of rainfall extremes with climate change is of key importance to society and then it may induce a large impact through landslides. This paper presents GIS-based new ensemble data mining techniques that weight-of-evidence, logistic model tree, linear and quadratic discriminant for landslide spatial modelling. This research was applied in Anfu County, which is a landslide-prone area in Jiangxi Province, China. According to a literature review and research the study area, we select the landslide influencing factor and their maps were digitized in a GIS environment. These landslide influencing factors are the altitude, plan curvature, profile curvature, slope degree, slope aspect, topographic wetness index (TWI), Stream Power Index (SPI), Topographic Wetness Index (SPI), distance to faults, distance to rivers, distance to roads, soil, lithology, normalized difference vegetation index and land use. According to historical information of individual landslide events, interpretation of the aerial photographs, and field surveys supported by the government of Jiangxi Meteorological Bureau of China, 367 landslides were identified in the study area. The landslide locations were divided into two subsets, namely, training and validating (70/30), based on a random selection scheme. In this research, Pearson's correlation was used for the evaluation of the relationship between the landslides and influencing factors. In the next step, three data mining techniques combined with the weight-of-evidence, logistic model tree, linear and quadratic discriminant, were used for the landslide spatial modelling and its zonation. Finally, the landslide susceptibility maps produced by the mentioned models were evaluated by the ROC curve. The results showed that the area under the curve (AUC) of all of the models was > 0.80. At the same time, the highest AUC value was for the linear and quadratic

  3. Application of Physically based landslide susceptibility models in Brazil

    Science.gov (United States)

    Carvalho Vieira, Bianca; Martins, Tiago D.

    2017-04-01

    Shallow landslides and floods are the processes responsible for most material and environmental damages in Brazil. In the last decades, some landslides events induce a high number of deaths (e.g. Over 1000 deaths in one event) and incalculable social and economic losses. Therefore, the prediction of those processes is considered an important tool for land use planning tools. Among different methods the physically based landslide susceptibility models having been widely used in many countries, but in Brazil it is still incipient when compared to other ones, like statistical tools and frequency analyses. Thus, the main objective of this research was to assess the application of some Physically based landslide susceptibility models in Brazil, identifying their main results, the efficiency of susceptibility mapping, parameters used and limitations of the tropical humid environment. In order to achieve that, it was evaluated SHALSTAB, SINMAP and TRIGRS models in some studies in Brazil along with the Geotechnical values, scales, DEM grid resolution and the results based on the analysis of the agreement between predicted susceptibility and the landslide scar's map. Most of the studies in Brazil applied SHALSTAB, SINMAP and to a lesser extent the TRIGRS model. The majority researches are concentrated in the Serra do Mar mountain range, that is a system of escarpments and rugged mountains that extends more than 1,500 km along the southern and southeastern Brazilian coast, and regularly affected by heavy rainfall that generates widespread mass movements. Most part of these studies used conventional topographic maps with scales ranging from 1:2000 to 1:50000 and DEM-grid resolution between 2 and 20m. Regarding the Geotechnical and hydrological values, a few studies use field collected data which could produce more efficient results, as indicated by international literature. Therefore, even though they have enormous potential in the susceptibility mapping, even for comparison

  4. Spatially explicit shallow landslide susceptibility mapping over large areas

    Science.gov (United States)

    Bellugi, Dino; Dietrich, William E.; Stock, Jonathan D.; McKean, Jim; Kazian, Brian; Hargrove, Paul

    2011-01-01

    Recent advances in downscaling climate model precipitation predictions now yield spatially explicit patterns of rainfall that could be used to estimate shallow landslide susceptibility over large areas. In California, the United States Geological Survey is exploring community emergency response to the possible effects of a very large simulated storm event and to do so it has generated downscaled precipitation maps for the storm. To predict the corresponding pattern of shallow landslide susceptibility across the state, we have used the model Shalstab (a coupled steady state runoff and infinite slope stability model) which susceptibility spatially explicit estimates of relative potential instability. Such slope stability models that include the effects of subsurface runoff on potentially destabilizing pore pressure evolution require water routing and hence the definition of upslope drainage area to each potential cell. To calculate drainage area efficiently over a large area we developed a parallel framework to scale-up Shalstab and specifically introduce a new efficient parallel drainage area algorithm which produces seamless results. The single seamless shallow landslide susceptibility map for all of California was accomplished in a short run time, and indicates that much larger areas can be efficiently modelled. As landslide maps generally over predict the extent of instability for any given storm. Local empirical data on the fraction of predicted unstable cells that failed for observed rainfall intensity can be used to specify the likely extent of hazard for a given storm. This suggests that campaigns to collect local precipitation data and detailed shallow landslide location maps after major storms could be used to calibrate models and improve their use in hazard assessment for individual storms.

  5. Comparison of the landslide susceptibility models in Taipei Water Source Domain, Taiwan

    Science.gov (United States)

    WU, C. Y.; Yeh, Y. C.; Chou, T. H.

    2017-12-01

    Taipei Water Source Domain, locating at the southeast of Taipei Metropolis, is the main source of water resource in this region. Recently, the downstream turbidity often soared significantly during the typhoon period because of the upstream landslides. The landslide susceptibilities should be analysed to assess the influence zones caused by different rainfall events, and to ensure the abilities of this domain to serve enough and quality water resource. Generally, the landslide susceptibility models can be established based on either a long-term landslide inventory or a specified landslide event. Sometimes, there is no long-term landslide inventory in some areas. Thus, the event-based landslide susceptibility models are established widely. However, the inventory-based and event-based landslide susceptibility models may result in dissimilar susceptibility maps in the same area. So the purposes of this study were to compare the landslide susceptibility maps derived from the inventory-based and event-based models, and to interpret how to select a representative event to be included in the susceptibility model. The landslide inventory from Typhoon Tim in July, 1994 and Typhoon Soudelor in August, 2015 was collected, and used to establish the inventory-based landslide susceptibility model. The landslides caused by Typhoon Nari and rainfall data were used to establish the event-based model. The results indicated the high susceptibility slope-units were located at middle upstream Nan-Shih Stream basin.

  6. GIS Supported Landslide Susceptibility Modeling at Regional Scale: An Expert-Based Fuzzy Weighting Method

    Directory of Open Access Journals (Sweden)

    Christos Chalkias

    2014-04-01

    Full Text Available The main aim of this paper is landslide susceptibility assessment using fuzzy expert-based modeling. Factors that influence landslide occurrence, such as elevation, slope, aspect, lithology, land cover, precipitation and seismicity were considered. Expert-based fuzzy weighting (EFW approach was used to combine these factors for landslide susceptibility mapping (Peloponnese, Greece. This method produced a landslide susceptibility map of the investigated area. The landslides under investigation have more or less same characteristics: lateral based and downslope shallow movement of soils or rocks. The validation of the model reveals, that predicted susceptibility levels are found to be in good agreement with the past landslide occurrences. Hence, the obtained landslide susceptibility map could be acceptable, for landslide hazard prevention and mitigation at regional scale.

  7. Weights of Evidence Method for Landslide Susceptibility Mapping in Takengon, Central Aceh, Indonesia

    Science.gov (United States)

    Pamela; Sadisun, Imam A.; Arifianti, Yukni

    2018-02-01

    Takengon is an area prone to earthquake disaster and landslide. On July 2, 2013, Central Aceh earthquake induced large numbers of landslides in Takengon area, which resulted in casualties of 39 people. This location was chosen to assess the landslide susceptibility of Takengon, using a statistical method, referred to as the weight of evidence (WoE). This WoE model was applied to indicate the main factors influencing the landslide susceptible area and to derive landslide susceptibility map of Takengon. The 251 landslides randomly divided into two groups of modeling/training data (70%) and validation/test data sets (30%). Twelve thematic maps of evidence are slope degree, slope aspect, lithology, land cover, elevation, rainfall, lineament, peak ground acceleration, curvature, flow direction, distance to river and roads used as landslide causative factors. According to the AUC, the significant factor controlling the landslide is the slope, the slope aspect, peak ground acceleration, elevation, lithology, flow direction, lineament, and rainfall respectively. Analytical result verified by using test data of landslide shows AUC prediction rate is 0.819 and AUC success rate with all landslide data included is 0.879. This result showed the selective factors and WoE method as good models for assessing landslide susceptibility. The landslide susceptibility map of Takengon shows the probabilities, which represent relative degrees of susceptibility for landslide proneness in Takengon area.

  8. A proposed cell model for multiple-occurrence regional landslide events: Implications for landslide susceptibility mapping

    Science.gov (United States)

    Crozier, M. J.

    2017-10-01

    Multiple-occurrence regional landslide events (MORLEs) consist of hundreds to thousands of shallow landslides occurring more or less simultaneously within defined areas, ranging from tens to thousands of square kilometres. While MORLEs can be triggered by rainstorms and earthquakes, this paper is confined to those landslide events triggered by rainstorms. Globally, MORLEs occur in a range of geological settings in areas of moderate to steep slopes subject to intense rainstorms. Individual landslides in rainstorm-triggered events are dominantly small, shallow debris and earth flows, and debris and earth slides involving regolith or weathered bedrock. The model used to characterise these events assumes that energy distribution within the event area is represented on the land surface by a cell structure; with maximum energy expenditure within an identifiable core and rapid dissipation concentrically away from the centre. The version of the model presented here has been developed for rainfall-triggered landslide events. It proposes that rainfall intensity can be used to determine different critical landslide response zones within the cell (referred to as core, middle, and periphery zones). These zones are most readily distinguished by two conditions: the proportion of the slope that fails and the particular type of the slope stability factor that assumes dominance in determining specific sites of landslide occurrence. The latter condition means that the power of any slope stability factor to distinguish between stable and unstable sites varies throughout the affected area in accordance with the landslide response zones within the cell; certain factors critical for determining the location of landslide sites in one part of the event area have little influence in other parts of the event area. The implication is that landslide susceptibility maps (and subsequently derived mitigation measures) based on conventional slope stability factors may have only limited validity

  9. Application of a neuro-fuzzy model to landslide-susceptibility mapping for shallow landslides in a tropical hilly area

    Science.gov (United States)

    Oh, Hyun-Joo; Pradhan, Biswajeet

    2011-09-01

    This paper presents landslide-susceptibility mapping using an adaptive neuro-fuzzy inference system (ANFIS) using a geographic information system (GIS) environment. In the first stage, landslide locations from the study area were identified by interpreting aerial photographs and supported by an extensive field survey. In the second stage, landslide-related conditioning factors such as altitude, slope angle, plan curvature, distance to drainage, distance to road, soil texture and stream power index (SPI) were extracted from the topographic and soil maps. Then, landslide-susceptible areas were analyzed by the ANFIS approach and mapped using landslide-conditioning factors. In particular, various membership functions (MFs) were applied for the landslide-susceptibility mapping and their results were compared with the field-verified landslide locations. Additionally, the receiver operating characteristics (ROC) curve for all landslide susceptibility maps were drawn and the areas under curve values were calculated. The ROC curve technique is based on the plotting of model sensitivity — true positive fraction values calculated for different threshold values, versus model specificity — true negative fraction values, on a graph. Landslide test locations that were not used during the ANFIS modeling purpose were used to validate the landslide susceptibility maps. The validation results revealed that the susceptibility maps constructed by the ANFIS predictive models using triangular, trapezoidal, generalized bell and polynomial MFs produced reasonable results (84.39%), which can be used for preliminary land-use planning. Finally, the authors concluded that ANFIS is a very useful and an effective tool in regional landslide susceptibility assessment.

  10. A GIS based spatially-explicit sensitivity and uncertainty analysis approach for multi-criteria decision analysis☆

    Science.gov (United States)

    Feizizadeh, Bakhtiar; Jankowski, Piotr; Blaschke, Thomas

    2014-01-01

    GIS multicriteria decision analysis (MCDA) techniques are increasingly used in landslide susceptibility mapping for the prediction of future hazards, land use planning, as well as for hazard preparedness. However, the uncertainties associated with MCDA techniques are inevitable and model outcomes are open to multiple types of uncertainty. In this paper, we present a systematic approach to uncertainty and sensitivity analysis. We access the uncertainty of landslide susceptibility maps produced with GIS-MCDA techniques. A new spatially-explicit approach and Dempster–Shafer Theory (DST) are employed to assess the uncertainties associated with two MCDA techniques, namely Analytical Hierarchical Process (AHP) and Ordered Weighted Averaging (OWA) implemented in GIS. The methodology is composed of three different phases. First, weights are computed to express the relative importance of factors (criteria) for landslide susceptibility. Next, the uncertainty and sensitivity of landslide susceptibility is analyzed as a function of weights using Monte Carlo Simulation and Global Sensitivity Analysis. Finally, the results are validated using a landslide inventory database and by applying DST. The comparisons of the obtained landslide susceptibility maps of both MCDA techniques with known landslides show that the AHP outperforms OWA. However, the OWA-generated landslide susceptibility map shows lower uncertainty than the AHP-generated map. The results demonstrate that further improvement in the accuracy of GIS-based MCDA can be achieved by employing an integrated uncertainty–sensitivity analysis approach, in which the uncertainty of landslide susceptibility model is decomposed and attributed to model's criteria weights. PMID:25843987

  11. A GIS based spatially-explicit sensitivity and uncertainty analysis approach for multi-criteria decision analysis.

    Science.gov (United States)

    Feizizadeh, Bakhtiar; Jankowski, Piotr; Blaschke, Thomas

    2014-03-01

    GIS multicriteria decision analysis (MCDA) techniques are increasingly used in landslide susceptibility mapping for the prediction of future hazards, land use planning, as well as for hazard preparedness. However, the uncertainties associated with MCDA techniques are inevitable and model outcomes are open to multiple types of uncertainty. In this paper, we present a systematic approach to uncertainty and sensitivity analysis. We access the uncertainty of landslide susceptibility maps produced with GIS-MCDA techniques. A new spatially-explicit approach and Dempster-Shafer Theory (DST) are employed to assess the uncertainties associated with two MCDA techniques, namely Analytical Hierarchical Process (AHP) and Ordered Weighted Averaging (OWA) implemented in GIS. The methodology is composed of three different phases. First, weights are computed to express the relative importance of factors (criteria) for landslide susceptibility. Next, the uncertainty and sensitivity of landslide susceptibility is analyzed as a function of weights using Monte Carlo Simulation and Global Sensitivity Analysis. Finally, the results are validated using a landslide inventory database and by applying DST. The comparisons of the obtained landslide susceptibility maps of both MCDA techniques with known landslides show that the AHP outperforms OWA. However, the OWA-generated landslide susceptibility map shows lower uncertainty than the AHP-generated map. The results demonstrate that further improvement in the accuracy of GIS-based MCDA can be achieved by employing an integrated uncertainty-sensitivity analysis approach, in which the uncertainty of landslide susceptibility model is decomposed and attributed to model's criteria weights.

  12. Shallow Landslide Susceptibility Modeling Using the Data Mining Models Artificial Neural Network and Boosted Tree

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    Hyun-Joo Oh

    2017-09-01

    Full Text Available The main purpose of this paper is to present some potential applications of sophisticated data mining techniques, such as artificial neural network (ANN and boosted tree (BT, for landslide susceptibility modeling in the Yongin area, Korea. Initially, landslide inventory was detected from visual interpretation using digital aerial photographic maps with a high resolution of 50 cm taken before and after the occurrence of landslides. The debris flows were randomly divided into two groups: training and validation sets with a 50:50 proportion. Additionally, 18 environmental factors related to landslide occurrence were derived from the topography, soil, and forest maps. Subsequently, the data mining techniques were applied to identify the influence of environmental factors on landslide occurrence of the training set and assess landslide susceptibility. Finally, the landslide susceptibility indexes from ANN and BT were compared with a validation set using a receiver operating characteristics curve. The slope gradient, topographic wetness index, and timber age appear to be important factors in landslide occurrence from both models. The validation result of ANN and BT showed 82.25% and 90.79%, which had reasonably good performance. The study shows the benefit of selecting optimal data mining techniques in landslide susceptibility modeling. This approach could be used as a guideline for choosing environmental factors on landslide occurrence and add influencing factors into landslide monitoring systems. Furthermore, this method can rank landslide susceptibility in urban areas, thus providing helpful information when selecting a landslide monitoring site and planning land-use.

  13. A Hybrid Physical and Maximum-Entropy Landslide Susceptibility Model

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    Jerry Davis

    2015-06-01

    Full Text Available The clear need for accurate landslide susceptibility mapping has led to multiple approaches. Physical models are easily interpreted and have high predictive capabilities but rely on spatially explicit and accurate parameterization, which is commonly not possible. Statistical methods can include other factors influencing slope stability such as distance to roads, but rely on good landslide inventories. The maximum entropy (MaxEnt model has been widely and successfully used in species distribution mapping, because data on absence are often uncertain. Similarly, knowledge about the absence of landslides is often limited due to mapping scale or methodology. In this paper a hybrid approach is described that combines the physically-based landslide susceptibility model “Stability INdex MAPping” (SINMAP with MaxEnt. This method is tested in a coastal watershed in Pacifica, CA, USA, with a well-documented landslide history including 3 inventories of 154 scars on 1941 imagery, 142 in 1975, and 253 in 1983. Results indicate that SINMAP alone overestimated susceptibility due to insufficient data on root cohesion. Models were compared using SINMAP stability index (SI or slope alone, and SI or slope in combination with other environmental factors: curvature, a 50-m trail buffer, vegetation, and geology. For 1941 and 1975, using slope alone was similar to using SI alone; however in 1983 SI alone creates an Areas Under the receiver operator Curve (AUC of 0.785, compared with 0.749 for slope alone. In maximum-entropy models created using all environmental factors, the stability index (SI from SINMAP represented the greatest contributions in all three years (1941: 48.1%; 1975: 35.3; and 1983: 48%, with AUC of 0.795, 0822, and 0.859, respectively; however; using slope instead of SI created similar overall AUC values, likely due to the combined effect with plan curvature indicating focused hydrologic inputs and vegetation identifying the effect of root cohesion

  14. Application of a hybrid model of neural networks and genetic algorithms to evaluate landslide susceptibility

    Science.gov (United States)

    Wang, H. B.; Li, J. W.; Zhou, B.; Yuan, Z. Q.; Chen, Y. P.

    2013-03-01

    In the last few decades, the development of Geographical Information Systems (GIS) technology has provided a method for the evaluation of landslide susceptibility and hazard. Slope units were found to be appropriate for the fundamental morphological elements in landslide susceptibility evaluation. Following the DEM construction in a loess area susceptible to landslides, the direct-reverse DEM technology was employed to generate 216 slope units in the studied area. After a detailed investigation, the landslide inventory was mapped in which 39 landslides, including paleo-landslides, old landslides and recent landslides, were present. Of the 216 slope units, 123 involved landslides. To analyze the mechanism of these landslides, six environmental factors were selected to evaluate landslide occurrence: slope angle, aspect, the height and shape of the slope, distance to river and human activities. These factors were extracted in terms of the slope unit within the ArcGIS software. The spatial analysis demonstrates that most of the landslides are located on convex slopes at an elevation of 100-150 m with slope angles from 135°-225° and 40°-60°. Landslide occurrence was then checked according to these environmental factors using an artificial neural network with back propagation, optimized by genetic algorithms. A dataset of 120 slope units was chosen for training the neural network model, i.e., 80 units with landslide presence and 40 units without landslide presence. The parameters of genetic algorithms and neural networks were then set: population size of 100, crossover probability of 0.65, mutation probability of 0.01, momentum factor of 0.60, learning rate of 0.7, max learning number of 10 000, and target error of 0.000001. After training on the datasets, the susceptibility of landslides was mapped for the land-use plan and hazard mitigation. Comparing the susceptibility map with landslide inventory, it was noted that the prediction accuracy of landslide occurrence

  15. Assessments on landslide susceptibility in the Tseng-wen reservoir watershed, Taiwan

    Science.gov (United States)

    Chen, Yu-Chin; Chen, Yung-Chau; Chen, Wen-Fu

    2014-05-01

    Typhoon Morakot under the strong influence of southwestern monsoon wind struck Taiwan on 8 August 2009, and dumped record-breaking rains in southern Taiwan. It triggered enormous landslides in mountains and severe flooding in low-lying areas. In addition, it destroyed or damaged houses, agricultural fields, roads, bridges, and other infrastructure facilities, causing massive economic loss and, more tragically, human casualties. In order to evaluate landslide hazard and risk assessment, it is important to understand the potential sites of landslide and their spatial distribution. Multi-temporal satellite images and geo-spatial data are used to build landslide susceptibility map for the post-disaster in the Tseng-wen reservoir watershed in this research. Elevation, slope, aspect, NDVI (normalized differential vegetation index), relief, roughness, distance to river, and distance to road are the considered factors for estimating landslide susceptibility. Maximum hourly rainfall and total rainfall, accompanied with typhoon event, are selected as the trigger factors of landslide events. Logistic regression analysis is adopted as the statistical method to model landslide susceptibility. The assessed susceptibility is represented in 4 levels which are high, high-intermediate, intermediate, and low level, respectively. Landslide spatial distribution can be depicted as a landslide susceptibility map with respect to each considered influence factors for a specified susceptible level. The landslide areas are about 358 ha and 1,485 ha before and after typhoon Morakot. The new landslide area, induced by typhoon Morakot, is as almost 4 times as the landslide area before typhoon Morakot. In addition, there is about 44.56% landslide area elevation ranging from 500m to 1000m and about 57.22% average slope ranging from 30° to 45° of landslide area. Furthermore, the devastating landslides were happened at those sites close to rivers, exposed area, and area with big land cover change

  16. Technical Note: Assessing predictive capacity and conditional independence of landslide predisposing factors for shallow landslide susceptibility models

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    S. Pereira

    2012-04-01

    Full Text Available The aim of this study is to identify the landslide predisposing factors' combination using a bivariate statistical model that best predicts landslide susceptibility. The best model is one that has simultaneously good performance in terms of suitability and predictive power and has been developed using variables that are conditionally independent. The study area is the Santa Marta de Penaguião council (70 km2 located in the Northern Portugal.

    In order to identify the best combination of landslide predisposing factors, all possible combinations using up to seven predisposing factors were performed, which resulted in 120 predictions that were assessed with a landside inventory containing 767 shallow translational slides. The best landslide susceptibility model was selected according to the model degree of fitness and on the basis of a conditional independence criterion. The best model was developed with only three landslide predisposing factors (slope angle, inverse wetness index, and land use and was compared with a model developed using all seven landslide predisposing factors.

    Results showed that it is possible to produce a reliable landslide susceptibility model using fewer landslide predisposing factors, which contributes towards higher conditional independence.

  17. Landslide susceptibility assessment using logistic regression and its comparison with a rock mass classification system, along a road section in the northern Himalayas (India)

    Science.gov (United States)

    Das, Iswar; Sahoo, Sashikant; van Westen, Cees; Stein, Alfred; Hack, Robert

    2010-02-01

    Landslide studies are commonly guided by ground knowledge and field measurements of rock strength and slope failure criteria. With increasing sophistication of GIS-based statistical methods, however, landslide susceptibility studies benefit from the integration of data collected from various sources and methods at different scales. This study presents a logistic regression method for landslide susceptibility mapping and verifies the result by comparing it with the geotechnical-based slope stability probability classification (SSPC) methodology. The study was carried out in a landslide-prone national highway road section in the northern Himalayas, India. Logistic regression model performance was assessed by the receiver operator characteristics (ROC) curve, showing an area under the curve equal to 0.83. Field validation of the SSPC results showed a correspondence of 72% between the high and very high susceptibility classes with present landslide occurrences. A spatial comparison of the two susceptibility maps revealed the significance of the geotechnical-based SSPC method as 90% of the area classified as high and very high susceptible zones by the logistic regression method corresponds to the high and very high class in the SSPC method. On the other hand, only 34% of the area classified as high and very high by the SSPC method falls in the high and very high classes of the logistic regression method. The underestimation by the logistic regression method can be attributed to the generalisation made by the statistical methods, so that a number of slopes existing in critical equilibrium condition might not be classified as high or very high susceptible zones.

  18. An Improved Information Value Model Based on Gray Clustering for Landslide Susceptibility Mapping

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    Qianqian Ba

    2017-01-01

    Full Text Available Landslides, as geological hazards, cause significant casualties and economic losses. Therefore, it is necessary to identify areas prone to landslides for prevention work. This paper proposes an improved information value model based on gray clustering (IVM-GC for landslide susceptibility mapping. This method uses the information value derived from an information value model to achieve susceptibility classification and weight determination of landslide predisposing factors and, hence, obtain the landslide susceptibility of each study unit based on the clustering analysis. Using a landslide inventory of Chongqing, China, which contains 8435 landslides, three landslide susceptibility maps were generated based on the common information value model (IVM, an information value model improved by an analytic hierarchy process (IVM-AHP and our new improved model. Approximately 70% (5905 of the inventory landslides were used to generate the susceptibility maps, while the remaining 30% (2530 were used to validate the results. The training accuracies of the IVM, IVM-AHP and IVM-GC were 81.8%, 78.7% and 85.2%, respectively, and the prediction accuracies were 82.0%, 78.7% and 85.4%, respectively. The results demonstrate that all three methods perform well in evaluating landslide susceptibility. Among them, IVM-GC has the best performance.

  19. Landslide susceptibility assessment of SE Bartin (West Black Sea region, Turkey by artificial neural networks

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    M. Ercanoglu

    2005-01-01

    Full Text Available Landslides are significant natural hazards in Turkey, second only to earthquakes with respect to economic losses and casualties. The West Black Sea region of Turkey is known as one of the most landslide-prone regions in the country. The work presented in this paper is aimed at evaluating landslide susceptibility in a selected area in the West Black Sea region using Artificial Neural Network (ANN method. A total of 317 landslides were identified and mapped in the area by extensive field work and by use of air photo interpretations to build a landslide inventory map. A landslide database was then derived automatically from the landslide inventory map. To evaluate landslide susceptibility, six input parameters (slope angle, slope aspect, topographical elevation, topographical shape, wetness index, and vegetation index were used. To obtain maps of these parameters, Digital Elevation Model (DEM and ASTER satellite imagery of the study area were used. At the first stage, all data were normalized in [0, 1] interval, and parameter effects on landslide occurrence were expressed using Statistical Index values (Wi. Then, landslide susceptibility analyses were performed using an ANN. Finally, performance of the resulting map and the applied methodology is discussed relative to performance indicators, such as predicted areal extent of landslides and the strength of relation (rij value. Much of the areal extents of the landslides (87.2% were classified as susceptible to landsliding, and rij value of 0.85 showed a high degree of similarity. In addition to these, at the final stage, an independent validation strategy was followed by dividing the landslide data set into two parts and 82.5% of the validation data set was found to be correctly classified as landslide susceptible areas. According to these results, it is concluded that the map produced by the ANN is reliable and methodology applied in the study produced high performance, and satisfactory results.

  20. Integrating Expert Knowledge with Statistical Analysis for Landslide Susceptibility Assessment at Regional Scale

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    Christos Chalkias

    2016-03-01

    Full Text Available In this paper, an integration landslide susceptibility model by combining expert-based and bivariate statistical analysis (Landslide Susceptibility Index—LSI approaches is presented. Factors related with the occurrence of landslides—such as elevation, slope angle, slope aspect, lithology, land cover, Mean Annual Precipitation (MAP and Peak Ground Acceleration (PGA—were analyzed within a GIS environment. This integrated model produced a landslide susceptibility map which categorized the study area according to the probability level of landslide occurrence. The accuracy of the final map was evaluated by Receiver Operating Characteristics (ROC analysis depending on an independent (validation dataset of landslide events. The prediction ability was found to be 76% revealing that the integration of statistical analysis with human expertise can provide an acceptable landslide susceptibility assessment at regional scale.

  1. Object-based Classification for Detecting Landslides and Stochastic Procedure to landslide susceptibility maps - A Case at Baolai Village, SW Taiwan

    Science.gov (United States)

    Lin, Ying-Tong; Chang, Kuo-Chen; Yang, Ci-Jian

    2017-04-01

    As the result of global warming in the past decades, Taiwan has experienced more and more extreme typhoons with hazardous massive landslides. In this study, we use object-oriented analysis method to classify landslide area at Baolai village by using Formosat-2 satellite images. We used for multiresolution segmented to generate the blocks, and used hierarchical logic to classified 5 different kinds of features. After that, classification the landslide into different type of landslide. Beside, we use stochastic procedure to integrate landslide susceptibility maps. This study assumed that in the extreme event, 2009 Typhoon Morakot, which precipitation goes to 1991.5mm in 5 days, and the highest landslide susceptible area. The results show that study area's landslide area was greatly changes, most of landslide was erosion by gully and made dip slope slide, or erosion by the stream, especially at undercut bank. From the landslide susceptibility maps, we know that the old landslide area have high potential to occur landslides in the extreme event. This study demonstrates the changing of landslide area and the landslide susceptible area. Keywords: Formosat-2, object-oriented, segmentation, classification, landslide, Baolai Village, SW Taiwan, FS

  2. An application of adaptive neuro-fuzzy inference system to landslide susceptibility mapping (Klang valley, Malaysia)

    Science.gov (United States)

    Sezer, Ebru; Pradhan, Biswajeet; Gokceoglu, Candan

    2010-05-01

    Landslides are one of the recurrent natural hazard problems throughout most of Malaysia. Recently, the Klang Valley area of Selangor state has faced numerous landslide and mudflow events and much damage occurred in these areas. However, only little effort has been made to assess or predict these events which resulted in serious damages. Through scientific analyses of these landslides, one can assess and predict landslide-susceptible areas and even the events as such, and thus reduce landslide damages through proper preparation and/or mitigation. For this reason , the purpose of the present paper is to produce landslide susceptibility maps of a part of the Klang Valley areas in Malaysia by employing the results of the adaptive neuro-fuzzy inference system (ANFIS) analyses. Landslide locations in the study area were identified by interpreting aerial photographs and satellite images, supported by extensive field surveys. Landsat TM satellite imagery was used to map vegetation index. Maps of topography, lineaments and NDVI were constructed from the spatial datasets. Seven landslide conditioning factors such as altitude, slope angle, plan curvature, distance from drainage, soil type, distance from faults and NDVI were extracted from the spatial database. These factors were analyzed using an ANFIS to construct the landslide susceptibility maps. During the model development works, total 5 landslide susceptibility models were obtained by using ANFIS results. For verification, the results of the analyses were then compared with the field-verified landslide locations. Additionally, the ROC curves for all landslide susceptibility models were drawn and the area under curve values was calculated. Landslide locations were used to validate results of the landslide susceptibility map and the verification results showed 98% accuracy for the model 5 employing all parameters produced in the present study as the landslide conditioning factors. The validation results showed sufficient

  3. Landslide Susceptibility Assessment Using Frequency Ratio Technique with Iterative Random Sampling

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    Hyun-Joo Oh

    2017-01-01

    Full Text Available This paper assesses the performance of the landslide susceptibility analysis using frequency ratio (FR with an iterative random sampling. A pair of before-and-after digital aerial photographs with 50 cm spatial resolution was used to detect landslide occurrences in Yongin area, Korea. Iterative random sampling was run ten times in total and each time it was applied to the training and validation datasets. Thirteen landslide causative factors were derived from the topographic, soil, forest, and geological maps. The FR scores were calculated from the causative factors and training occurrences repeatedly ten times. The ten landslide susceptibility maps were obtained from the integration of causative factors that assigned FR scores. The landslide susceptibility maps were validated by using each validation dataset. The FR method achieved susceptibility accuracies from 89.48% to 93.21%. And the landslide susceptibility accuracy of the FR method is higher than 89%. Moreover, the ten times iterative FR modeling may contribute to a better understanding of a regularized relationship between the causative factors and landslide susceptibility. This makes it possible to incorporate knowledge-driven considerations of the causative factors into the landslide susceptibility analysis and also be extensively used to other areas.

  4. Landslide Susceptibility Assessment Using Spatial Multi-Criteria Evaluation Model in Rwanda

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    Jean Baptiste Nsengiyumva

    2018-01-01

    Full Text Available Landslides susceptibility assessment has to be conducted to identify prone areas and guide risk management. Landslides in Rwanda are very deadly disasters. The current research aimed to conduct landslide susceptibility assessment by applying Spatial Multi-Criteria Evaluation Model with eight layers of causal factors including: slope, distance to roads, lithology, precipitation, soil texture, soil depth, altitude and land cover. In total, 980 past landslide locations were mapped. The relationship between landslide factors and inventory map was calculated using the Spatial Multi-Criteria Evaluation. The results revealed that susceptibility is spatially distributed countrywide with 42.3% of the region classified from moderate to very high susceptibility, and this is inhabited by 49.3% of the total population. In addition, Provinces with high to very high susceptibility are West, North and South (40.4%, 22.8% and 21.5%, respectively. Subsequently, the Eastern Province becomes the peak under low susceptibility category (87.8% with no very high susceptibility (0%. Based on these findings, the employed model produced accurate and reliable outcome in terms of susceptibility, since 49.5% of past landslides fell within the very high susceptibility category, which confirms the model’s performance. The outcomes of this study will be useful for future initiatives related to landslide risk reduction and management.

  5. Landslide Susceptibility Assessment Using Spatial Multi-Criteria Evaluation Model in Rwanda

    Science.gov (United States)

    Nsengiyumva, Jean Baptiste; Luo, Geping; Nahayo, Lamek; Huang, Xiaotao; Cai, Peng

    2018-01-01

    Landslides susceptibility assessment has to be conducted to identify prone areas and guide risk management. Landslides in Rwanda are very deadly disasters. The current research aimed to conduct landslide susceptibility assessment by applying Spatial Multi-Criteria Evaluation Model with eight layers of causal factors including: slope, distance to roads, lithology, precipitation, soil texture, soil depth, altitude and land cover. In total, 980 past landslide locations were mapped. The relationship between landslide factors and inventory map was calculated using the Spatial Multi-Criteria Evaluation. The results revealed that susceptibility is spatially distributed countrywide with 42.3% of the region classified from moderate to very high susceptibility, and this is inhabited by 49.3% of the total population. In addition, Provinces with high to very high susceptibility are West, North and South (40.4%, 22.8% and 21.5%, respectively). Subsequently, the Eastern Province becomes the peak under low susceptibility category (87.8%) with no very high susceptibility (0%). Based on these findings, the employed model produced accurate and reliable outcome in terms of susceptibility, since 49.5% of past landslides fell within the very high susceptibility category, which confirms the model’s performance. The outcomes of this study will be useful for future initiatives related to landslide risk reduction and management. PMID:29385096

  6. GIS and statistical analysis for landslide susceptibility mapping in the Daunia area, Italy

    Science.gov (United States)

    Mancini, F.; Ceppi, C.; Ritrovato, G.

    2010-09-01

    This study focuses on landslide susceptibility mapping in the Daunia area (Apulian Apennines, Italy) and achieves this by using a multivariate statistical method and data processing in a Geographical Information System (GIS). The Logistic Regression (hereafter LR) method was chosen to produce a susceptibility map over an area of 130 000 ha where small settlements are historically threatened by landslide phenomena. By means of LR analysis, the tendency to landslide occurrences was, therefore, assessed by relating a landslide inventory (dependent variable) to a series of causal factors (independent variables) which were managed in the GIS, while the statistical analyses were performed by means of the SPSS (Statistical Package for the Social Sciences) software. The LR analysis produced a reliable susceptibility map of the investigated area and the probability level of landslide occurrence was ranked in four classes. The overall performance achieved by the LR analysis was assessed by local comparison between the expected susceptibility and an independent dataset extrapolated from the landslide inventory. Of the samples classified as susceptible to landslide occurrences, 85% correspond to areas where landslide phenomena have actually occurred. In addition, the consideration of the regression coefficients provided by the analysis demonstrated that a major role is played by the "land cover" and "lithology" causal factors in determining the occurrence and distribution of landslide phenomena in the Apulian Apennines.

  7. Remote sensing and GIS-based landslide hazard analysis and cross-validation using multivariate logistic regression model on three test areas in Malaysia

    Science.gov (United States)

    Pradhan, Biswajeet

    2010-05-01

    This paper presents the results of the cross-validation of a multivariate logistic regression model using remote sensing data and GIS for landslide hazard analysis on the Penang, Cameron, and Selangor areas in Malaysia. Landslide locations in the study areas were identified by interpreting aerial photographs and satellite images, supported by field surveys. SPOT 5 and Landsat TM satellite imagery were used to map landcover and vegetation index, respectively. Maps of topography, soil type, lineaments and land cover were constructed from the spatial datasets. Ten factors which influence landslide occurrence, i.e., slope, aspect, curvature, distance from drainage, lithology, distance from lineaments, soil type, landcover, rainfall precipitation, and normalized difference vegetation index (ndvi), were extracted from the spatial database and the logistic regression coefficient of each factor was computed. Then the landslide hazard was analysed using the multivariate logistic regression coefficients derived not only from the data for the respective area but also using the logistic regression coefficients calculated from each of the other two areas (nine hazard maps in all) as a cross-validation of the model. For verification of the model, the results of the analyses were then compared with the field-verified landslide locations. Among the three cases of the application of logistic regression coefficient in the same study area, the case of Selangor based on the Selangor logistic regression coefficients showed the highest accuracy (94%), where as Penang based on the Penang coefficients showed the lowest accuracy (86%). Similarly, among the six cases from the cross application of logistic regression coefficient in other two areas, the case of Selangor based on logistic coefficient of Cameron showed highest (90%) prediction accuracy where as the case of Penang based on the Selangor logistic regression coefficients showed the lowest accuracy (79%). Qualitatively, the cross

  8. Landslide susceptibility mapping using logistic statistical regression in Babaheydar Watershed, Chaharmahal Va Bakhtiari Province, Iran

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    Ebrahim Karimi Sangchini

    2015-01-01

    Full Text Available Landslides are amongst the most damaging natural hazards in mountainous regions. Every year, hundreds of people all over the world lose their lives in landslides; furthermore, there are large impacts on the local and global economy from these events. In this study, landslide hazard zonation in Babaheydar watershed using logistic regression was conducted to determine landslide hazard areas. At first, the landslide inventory map was prepared using aerial photograph interpretations and field surveys. The next step, ten landslide conditioning factors such as altitude, slope percentage, slope aspect, lithology, distance from faults, rivers, settlement and roads, land use, and precipitation were chosen as effective factors on landsliding in the study area. Subsequently, landslide susceptibility map was constructed using the logistic regression model in Geographic Information System (GIS. The ROC and Pseudo-R2 indexes were used for model assessment. Results showed that the logistic regression model provided slightly high prediction accuracy of landslide susceptibility maps in the Babaheydar Watershed with ROC equal to 0.876. Furthermore, the results revealed that about 44% of the watershed areas were located in high and very high hazard classes. The resultant landslide susceptibility maps can be useful in appropriate watershed management practices and for sustainable development in the region.

  9. Spatial agreement of predicted patterns in landslide susceptibility maps

    Czech Academy of Sciences Publication Activity Database

    Sterlacchini, S.; Ballabio, C.; Blahůt, Jan; Masetti, J.; Sorichetta, A.

    2011-01-01

    Roč. 125, č. 1 (2011), s. 51-61 ISSN 0169-555X Institutional research plan: CEZ:AV0Z30460519 Keywords : landslide susceptibility * weights of evidence * success rate Subject RIV: DE - Earth Magnetism, Geodesy, Geography Impact factor: 2.520, year: 2011 http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6V93-511TN6P-3&_user=1407143&_coverDate=01%2F01%2F2011&_rdoc=1&_fmt=high&_orig=search&_origin=search&_sort=d&_docanchor=&view=c&_acct=C000052620&_version=1&_urlVersion=0&_userid=1407143&md5=d4e3ac0e1295373f2203f99a1aa8e905&searchtype=a

  10. GIS-BASED ANALYSIS FOR ASSESSING LANDSLIDE AND DROUGHT HAZARD IN THE CORRIDOR OF MT. MERAPI AND MT. MERBABU NATIONAL PARK, INDONESIA

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    Hero Marhaento

    2016-04-01

    Full Text Available A corridor is an area located between two or more protected areas that are important to support the sustainability of the protected areas. This study is aimed at assessing landslide and drought hazard in the corridor area between Mt. Merapi National Park (MMNP and Mt. Merbabu National Park (MMbNP as a part of the corridor management strategy. The corridor area of MMNP and MMbNP comprises four sub-districts in Central Java Province, namely, Sawangan, Selo, Ampel, and Cepogo. A spatial analysis of ArcGIS 10.1 software was used to assess landslide hazard map and the Thorntwaite-Matter Water Balance approach was used to assess drought hazard map. The results have shown that three villages in Cepogo Sub-district and all villages in Selo Sub-district are highly prone to landslide hazard. Furthermore, two villages in Cepogo Sub-district and four villages in Selo Sub-district are prone to drought hazard. This study suggests that these villages should initiate a program called conservation village model based on disaster mitigation for mitigating future landslide and drought disasters.

  11. State of the art of national landslide databases in Europe and their potential for assessing landslide susceptibility, hazard and risk

    Science.gov (United States)

    Van Den Eeckhaut, Miet; Hervás, Javier

    2012-02-01

    A landslide inventory is the most important information source for quantitative zoning of landslide susceptibility, hazard and risk. It should give insight into the location, date, type, size, activity and causal factors of landslides as well as resultant damage. In Europe, many countries have created or are creating national and/or regional landslide databases (LDBs). Yet little is known on their contents, completeness, format, structure, language use and accessibility, and hence on their ability to perform national or transnational landslide zoning. Therefore, this study presents a detailed analysis of existing national LDBs in the EU member states, EU official candidate and potential candidate countries, and EFTA countries, and their possible use for landslide zoning. These national LDBs were compared with a subset of 22 regional databases. Twenty-two out of 37 contacted European countries currently have national LDBs, and six other countries have only regional LDBs. In total, the national LDBs contain 633,696 landslides, of which 485,004 are located in Italy, while Austria, the Czech Republic, France, Norway, Poland, Slovakia, and the UK also have > 10,000 landslides in their LDBs. National LDBs are generally created in the official language of each country and 58% of them contain other natural hazards (e.g. floods and sinkholes). About 68% of the LDBs contain less than 50% of all landslides in each country, but a positive observation is that 60% of the LDBs are updated at least once a year or after a major event. Most landslide locations are collected with traditional methods such as field surveys, aerial photo interpretation and analysis of historical records. Currently, integration of landslide information from different national LDBs is hampered because of differences in language and classification systems for landslide type and activity. Other problems are that currently only half of the national LDBs have a direct link between spatial and alphanumeric

  12. ANFIS modeling for the assessment of landslide susceptibility for the Cameron Highland (Malaysia)

    Science.gov (United States)

    Pradhan, Biswajeet; Sezer, Ebru; Gokceoglu, Candan; Buchroithner, Manfred F.

    2010-05-01

    Landslides are one of the recurrent natural hazard problems throughout most of Malaysia. In landslide literature, there are several approaches such as probabilistic, bivariate and multivariate statistical models, fuzzy and artificial neural network models etc. However, a neuro-fuzzy application on the landslide susceptibility assessment has not been encountered in the literature. For this reason, this study presents the results of an adaptive neuro-fuzzy inference system (ANFIS) using remote sensing data and GIS for landslide susceptibility analysis in a part of the Cameron Highland areas in Malaysia. Landslide locations in the study area were identified by interpreting aerial photographs and satellite images, supported by extensive field surveys. Landsat TM satellite imagery was used to map vegetation index. Maps of topography, lineaments, NDVI and land cover were constructed from the spatial datasets. Seven landslide conditioning factors such as altitude, slope angle, curvature, distance from drainage, lithology, distance from faults and NDVI were extracted from the spatial database. These factors were analyzed using an ANFIS to produce the landslide susceptibility maps. During the model development works, total 5 landslide susceptibility models were constructed. For verification, the results of the analyses were then compared with the field-verified landslide locations. Additionally, the ROC curves for all landslide susceptibility models were drawn and the area under curve values were calculated. Landslide locations were used to validate results of the landslide susceptibility map and the verification results showed 97% accuracy for the model 5 employing all parameters produced in the present study as the landslide conditioning factors. The validation results showed sufficient agreement between the obtained susceptibility map and the existing data on landslide areas. Qualitatively, the model yields reasonable results which can be used for preliminary land

  13. Landslide Hazard Assessment and Mapping in the Guil Catchment (Queyras, Southern French Alps): From Landslide Inventory to Susceptibility Modelling

    Science.gov (United States)

    Roulleau, Louise; Bétard, François; Carlier, Benoît; Lissak, Candide; Fort, Monique

    2016-04-01

    Landslides are common natural hazards in the Southern French Alps, where they may affect human lives and cause severe damages to infrastructures. As a part of the SAMCO research project dedicated to risk evaluation in mountain areas, this study focuses on the Guil river catchment (317 km2), Queyras, to assess landslide hazard poorly studied until now. In that area, landslides are mainly occasional, low amplitude phenomena, with limited direct impacts when compared to other hazards such as floods or snow avalanches. However, when interacting with floods during extreme rainfall events, landslides may have indirect consequences of greater importance because of strong hillslope-channel connectivity along the Guil River and its tributaries (i.e. positive feedbacks). This specific morphodynamic functioning reinforces the need to have a better understanding of landslide hazards and their spatial distribution at the catchment scale to prevent local population from disasters with multi-hazard origin. The aim of this study is to produce a landslide susceptibility mapping at 1:50 000 scale as a first step towards global estimation of landslide hazard and risk. The three main methodologies used for assessing landslide susceptibility are qualitative (i.e. expert opinion), deterministic (i.e. physics-based models) and statistical methods (i.e. probabilistic models). Due to the rapid development of geographical information systems (GIS) during the last two decades, statistical methods are today widely used because they offer a greater objectivity and reproducibility at large scales. Among them, multivariate analyses are considered as the most robust techniques, especially the logistic regression method commonly used in landslide susceptibility mapping. However, this method like others is strongly dependent on the accuracy of the input data to avoid significant errors in the final results. In particular, a complete and accurate landslide inventory is required before the modelling

  14. Landslide susceptibility mapping & prediction using Support Vector Machine for Mandakini River Basin, Garhwal Himalaya, India

    Science.gov (United States)

    Kumar, Deepak; Thakur, Manoj; Dubey, Chandra S.; Shukla, Dericks P.

    2017-10-01

    In recent years, various machine learning techniques have been applied for landslide susceptibility mapping. In this study, three different variants of support vector machine viz., SVM, Proximal Support Vector Machine (PSVM) and L2-Support Vector Machine - Modified Finite Newton (L2-SVM-MFN) have been applied on the Mandakini River Basin in Uttarakhand, India to carry out the landslide susceptibility mapping. Eight thematic layers such as elevation, slope, aspect, drainages, geology/lithology, buffer of thrusts/faults, buffer of streams and soil along with the past landslide data were mapped in GIS environment and used for landslide susceptibility mapping in MATLAB. The study area covering 1625 km2 has merely 0.11% of area under landslides. There are 2009 pixels for past landslides out of which 50% (1000) landslides were considered as training set while remaining 50% as testing set. The performance of these techniques has been evaluated and the computational results show that L2-SVM-MFN obtains higher prediction values (0.829) of receiver operating characteristic curve (AUC-area under the curve) as compared to 0.807 for PSVM model and 0.79 for SVM. The results obtained from L2-SVM-MFN model are found to be superior than other SVM prediction models and suggest the usefulness of this technique to problem of landslide susceptibility mapping where training data is very less. However, these techniques can be used for satisfactory determination of susceptible zones with these inputs.

  15. Non-susceptible landslide areas in Italy and in the Mediterranean region

    Science.gov (United States)

    Marchesini, I.; Ardizzone, F.; Alvioli, M.; Rossi, M.; Guzzetti, F.

    2014-08-01

    We used landslide information for 13 study areas in Italy and morphometric information obtained from the 3-arcseconds shuttle radar topography mission digital elevation model (SRTM DEM) to determine areas where landslide susceptibility is expected to be negligible in Italy and in the landmasses surrounding the Mediterranean Sea. The morphometric information consisted of the local terrain slope which was computed in a square 3 × 3-cell moving window, and in the regional relative relief computed in a circular 15 × 15-cell moving window. We tested three different models to classify the "non-susceptible" landslide areas, including a linear model (LNR), a quantile linear model (QLR), and a quantile, non-linear model (QNL). We tested the performance of the three models using independent landslide information presented by the Italian Landslide Inventory (Inventario Fenomeni Franosi in Italia - IFFI). Best results were obtained using the QNL model. The corresponding zonation of non-susceptible landslide areas was intersected in a geographic information system (GIS) with geographical census data for Italy. The result determined that 57.5% of the population of Italy (in 2001) was located in areas where landslide susceptibility is expected to be negligible. We applied the QNL model to the landmasses surrounding the Mediterranean Sea, and we tested the synoptic non-susceptibility zonation using independent landslide information for three study areas in Spain. Results showed that the QNL model was capable of determining where landslide susceptibility is expected to be negligible in the validation areas in Spain. We expect our results to be applicable in similar study areas, facilitating the identification of non-susceptible landslide areas, at the synoptic scale.

  16. Manifestation of a neuro-fuzzy model to produce landslide susceptibility map using remote sensing data derived parameters

    Science.gov (United States)

    Pradhan, Biswajeet; Lee, Saro; Buchroithner, Manfred

    Landslides are the most common natural hazards in Malaysia. Preparation of landslide suscep-tibility maps is important for engineering geologists and geomorphologists. However, due to complex nature of landslides, producing a reliable susceptibility map is not easy. In this study, a new attempt is tried to produce landslide susceptibility map of a part of Cameron Valley of Malaysia. This paper develops an adaptive neuro-fuzzy inference system (ANFIS) based on a geographic information system (GIS) environment for landslide susceptibility mapping. To ob-tain the neuro-fuzzy relations for producing the landslide susceptibility map, landslide locations were identified from interpretation of aerial photographs and high resolution satellite images, field surveys and historical inventory reports. Landslide conditioning factors such as slope, plan curvature, distance to drainage lines, soil texture, lithology, and distance to lineament were extracted from topographic, soil, and lineament maps. Landslide susceptible areas were analyzed by the ANFIS model and mapped using the conditioning factors. Furthermore, we applied various membership functions (MFs) and fuzzy relations to produce landslide suscep-tibility maps. The prediction performance of the susceptibility map is checked by considering actual landslides in the study area. Results show that, triangular, trapezoidal, and polynomial MFs were the best individual MFs for modelling landslide susceptibility maps (86

  17. Establish susceptibility and risk assessment models for rainfall-induced landslide: A case in Central Taiwan

    Science.gov (United States)

    Wu, Chunhung; Huang, Jyuntai

    2017-04-01

    Most of the landslide cases in Taiwan were triggered by rainfall or earthquake events. The heavy rainfall in the typhoon seasons, from June to October, causes the landslide hazard more serious. Renai Towhship is of the most large landslide cases after 2009 Typhoon Morakot (from Aug. 5 to Aug. 10, 2009) in Taiwan. Around 2,744 landslides cases with the total landslide area of 21.5 km2 (landslide ratio =1.8%), including 26 large landslide cases, induced after 2009 Typhoon Morakot in Renai Towhship. The area of each large landslides case is more than 0.1 km2, and the area of the largest case is around 0.96 km2. 58% of large landslide cases locate in the area with metamorphosed sandstone. The mean slope of 26 large landslide cases ranges from 15 degree to 56 degree, and the accumulated rainfall during 2009 Typhoon Morakot ranges from 530 mm to 937 mm. Three methods, including frequency ratio method (abbreviated as FR), weights of evidence method (abbreviated as WOE), and logistic regression method (abbreviated as LR), are used in this study to establish the landslides susceptibility in the Renai Township, Nantou County, Taiwan. Eight landslide related-factors, including elevation, slope, aspect, geology, land use, distance to drainage, distance to fault, accumulation rainfall during 2009 Typhoon Morakot, are used to establish the landslide susceptibility models in this study. The landslide inventory after 2009 Typhoon Morakot is also used to test the model performance in this study. The mean accumulated rainfall in Renai Township during 2009 typhoon Morakot was around 735 mm with the maximum 1-hr, 3-hrs, and 6-hrs rainfall intensity of 44 mm/1-hr, 106 mm/3-hrs and 204 mm/6-hrs, respectively. The range of original susceptibility values established by three methods are 4.0 to 20.9 for FR, -33.8 to -16.1 for WOE, and -41.7 to 5.7 for LR, and the mean landslide susceptibility value are 8.0, -24.6 and 0.38, respectively. The AUC values are 0.815 for FR, 0.816 for WOE, and 0

  18. Spatial probabilistic approach on landslide susceptibility assessment from high resolution sensors derived parameters

    International Nuclear Information System (INIS)

    Aman, S N A; Latif, Z Abd; Pradhan, B

    2014-01-01

    Landslide occurrence depends on various interrelating factors which consequently initiate to massive mass of soil and rock debris that move downhill due to the gravity action. LiDAR has come with a progressive approach in mitigating landslide by permitting the formation of more accurate DEM compared to other active space borne and airborne remote sensing techniques. The objective of this research is to assess the susceptibility of landslide in Ulu Klang area by investigating the correlation between past landslide events with geo environmental factors. A high resolution LiDAR DEM was constructed to produce topographic attributes such as slope, curvature and aspect. These data were utilized to derive second deliverables of landslide parameters such as topographic wetness index (TWI), surface area ratio (SAR) and stream power index (SPI) as well as NDVI generated from IKONOS imagery. Subsequently, a probabilistic based frequency ratio model was applied to establish the spatial relationship between the landslide locations and each landslide related factor. Factor ratings were summed up to obtain Landslide Susceptibility Index (LSI) to construct the landslide susceptibility map

  19. Earthquake-induced landslide-susceptibility mapping using an artificial neural network

    Directory of Open Access Journals (Sweden)

    S. Lee

    2006-01-01

    Full Text Available The purpose of this study was to apply and verify landslide-susceptibility analysis techniques using an artificial neural network and a Geographic Information System (GIS applied to Baguio City, Philippines. The 16 July 1990 earthquake-induced landslides were studied. Landslide locations were identified from interpretation of aerial photographs and field survey, and a spatial database was constructed from topographic maps, geology, land cover and terrain mapping units. Factors that influence landslide occurrence, such as slope, aspect, curvature and distance from drainage were calculated from the topographic database. Lithology and distance from faults were derived from the geology database. Land cover was identified from the topographic database. Terrain map units were interpreted from aerial photographs. These factors were used with an artificial neural network to analyze landslide susceptibility. Each factor weight was determined by a back-propagation exercise. Landslide-susceptibility indices were calculated using the back-propagation weights, and susceptibility maps were constructed from GIS data. The susceptibility map was compared with known landslide locations and verified. The demonstrated prediction accuracy was 93.20%.

  20. Neural Network-Based Model for Landslide Susceptibility and Soil Longitudinal Profile Analyses

    DEFF Research Database (Denmark)

    Farrokhzad, F.; Barari, Amin; Choobbasti, A. J.

    2011-01-01

    The purpose of this study was to create an empirical model for assessing the landslide risk potential at Savadkouh Azad University, which is located in the rural surroundings of Savadkouh, about 5 km from the city of Pol-Sefid in northern Iran. The soil longitudinal profile of the city of Babol......, located 25 km from the Caspian Sea, also was predicted with an artificial neural network (ANN). A multilayer perceptron neural network model was applied to the landslide area and was used to analyze specific elements in the study area that contributed to previous landsliding events. The ANN models were...... studies in landslide susceptibility zonation....

  1. Modeling landslide susceptibility in data-scarce environments using optimized data mining and statistical methods

    Science.gov (United States)

    Lee, Jung-Hyun; Sameen, Maher Ibrahim; Pradhan, Biswajeet; Park, Hyuck-Jin

    2018-02-01

    This study evaluated the generalizability of five models to select a suitable approach for landslide susceptibility modeling in data-scarce environments. In total, 418 landslide inventories and 18 landslide conditioning factors were analyzed. Multicollinearity and factor optimization were investigated before data modeling, and two experiments were then conducted. In each experiment, five susceptibility maps were produced based on support vector machine (SVM), random forest (RF), weight-of-evidence (WoE), ridge regression (Rid_R), and robust regression (RR) models. The highest accuracy (AUC = 0.85) was achieved with the SVM model when either the full or limited landslide inventories were used. Furthermore, the RF and WoE models were severely affected when less landslide samples were used for training. The other models were affected slightly when the training samples were limited.

  2. Application of logistic regression for landslide susceptibility zoning of Cekmece Area, Istanbul, Turkey

    Science.gov (United States)

    Duman, T. Y.; Can, T.; Gokceoglu, C.; Nefeslioglu, H. A.; Sonmez, H.

    2006-11-01

    As a result of industrialization, throughout the world, cities have been growing rapidly for the last century. One typical example of these growing cities is Istanbul, the population of which is over 10 million. Due to rapid urbanization, new areas suitable for settlement and engineering structures are necessary. The Cekmece area located west of the Istanbul metropolitan area is studied, because the landslide activity is extensive in this area. The purpose of this study is to develop a model that can be used to characterize landslide susceptibility in map form using logistic regression analysis of an extensive landslide database. A database of landslide activity was constructed using both aerial-photography and field studies. About 19.2% of the selected study area is covered by deep-seated landslides. The landslides that occur in the area are primarily located in sandstones with interbedded permeable and impermeable layers such as claystone, siltstone and mudstone. About 31.95% of the total landslide area is located at this unit. To apply logistic regression analyses, a data matrix including 37 variables was constructed. The variables used in the forwards stepwise analyses are different measures of slope, aspect, elevation, stream power index (SPI), plan curvature, profile curvature, geology, geomorphology and relative permeability of lithological units. A total of 25 variables were identified as exerting strong influence on landslide occurrence, and included by the logistic regression equation. Wald statistics values indicate that lithology, SPI and slope are more important than the other parameters in the equation. Beta coefficients of the 25 variables included the logistic regression equation provide a model for landslide susceptibility in the Cekmece area. This model is used to generate a landslide susceptibility map that correctly classified 83.8% of the landslide-prone areas.

  3. Combined rock slope stability and shallow landslide susceptibility assessment of the Jasmund cliff area (Rügen Island, Germany

    Directory of Open Access Journals (Sweden)

    A. Günther

    2009-05-01

    Full Text Available In this contribution we evaluated both the structurally-controlled failure susceptibility of the fractured Cretaceous chalk rocks and the topographically-controlled shallow landslide susceptibility of the overlying glacial sediments for the Jasmund cliff area on Rügen Island, Germany. We employed a combined methodology involving spatially distributed kinematical rock slope failure testing with tectonic fabric data, and both physically- and inventory-based shallow landslide susceptibility analysis. The rock slope failure susceptibility model identifies areas of recent cliff collapses, confirming its value in predicting the locations of future failures. The model reveals that toppling is the most important failure type in the Cretaceous chalk rocks of the area. The shallow landslide susceptibility analysis involves a physically-based slope stability evaluation which utilizes material strength and hydraulic conductivity data, and a bivariate landslide susceptibility analysis exploiting landslide inventory data and thematic information on ground conditioning factors. Both models show reasonable success rates when evaluated with the available inventory data, and an attempt was made to combine the individual models to prepare a map displaying both terrain instability and landslide susceptibility. This combination highlights unstable cliff portions lacking discrete landslide areas as well as cliff sections highly affected by past landslide events. Through a spatial integration of the rock slope failure susceptibility model with the combined shallow landslide assessment we produced a comprehensive landslide susceptibility map for the Jasmund cliff area.

  4. Comparative Assessment of Three Nonlinear Approaches for Landslide Susceptibility Mapping in a Coal Mine Area

    Directory of Open Access Journals (Sweden)

    Qiaomei Su

    2017-07-01

    Full Text Available Landslide susceptibility mapping is the first and most important step involved in landslide hazard assessment. The purpose of the present study is to compare three nonlinear approaches for landslide susceptibility mapping and test whether coal mining has a significant impact on landslide occurrence in coal mine areas. Landslide data collected by the Bureau of Land and Resources are represented by the X, Y coordinates of its central point; causative factors were calculated from topographic and geologic maps, as well as satellite imagery. The five-fold cross-validation method was adopted and the landslide/non-landslide datasets were randomly split into a ratio of 80:20. From this, five subsets for 20 times were acquired for training and validating models by GIS Geostatistical analysis methods, and all of the subsets were employed in a spatially balanced sample design. Three landslide models were built using support vector machine (SVM, logistic regression (LR, and artificial neural network (ANN models by selecting the median of the performance measures. Then, the three fitted models were compared using the area under the receiver operating characteristics (ROC curves (AUC and the performance measures. The results show that the prediction accuracies are between 73.43% and 87.45% in the training stage, and 67.16% to 73.13% in the validating stage for the three models. AUCs vary from 0.807 to 0.906 and 0.753 to 0.944 in the two stages, respectively. Additionally, three landslide susceptibility maps were obtained by classifying the range of landslide probabilities into four classes representing low (0–0.02, medium (0.02–0.1, high (0.1–0.85, and very high (0.85–1 probabilities of landslides. For the distributions of landslide and area percentages under different susceptibility standards, the SVM model has more relative balance in the four classes compared to the LR and the ANN models. The result reveals that the SVM model possesses better

  5. Utilizing NASA Earth Observations to Assess Landslide Characteristics and Devlelop Susceptibility and Exposure Maps in Malawi

    Science.gov (United States)

    Klug, M.; Cissell, J.; Grossman, M.

    2017-12-01

    Malawi has become increasingly prone to landslides in the past few decades. This can be attributed to the terrain, types of soil and vegetation, increased human interference, and heavy flooding after long periods of drought. In addition to the floods and droughts, landslides cause extra stress to farmlands, thus exacerbating the current food security crisis in the country. It can be difficult to pinpoint just how many people are affected by landslides in Malawi because landslides often occur in rural areas or are grouped with other disasters, such as floods or earthquakes. This project created a Landslide Susceptibility Map to assess landslide-prone areas in Malawi using variables such as slope, distance to roads, distance to streams, soil type, and precipitation. These variables were derived using imagery from Landsat 8 Operational Land Imager (OLI), Shuttle Radar Topography Mission Version 3 (SRTM-v3), Global Precipitation Measurement (GPM), and Tropical Rainfall Measuring Mission (TRMM) satellites. Furthermore, this project created a Landslide Exposure Map to estimate how much of the local population lives in susceptible areas by intersecting population data with the Landslide Susceptibility Map. Additionally, an assessment of GPM and TRMM precipitation measurements was generated to better understand the reliability of both measurements for landslide monitoring. Finally, this project updated NASA SERVIR's Global Landslide Catalog (GLC) for Malawi by using WorldView data from Google Earth and Landsat 8 OLI. These end products were used by NASA SERVIR and the Regional Centre for Mapping of Resources for Development (RCMRD) for aiding in disaster management throughout Malawi.

  6. Evaluation of landslide susceptibility of Sete Cidades Volcano (S. Miguel Island, Azores

    Directory of Open Access Journals (Sweden)

    A. Gomes

    2005-01-01

    Full Text Available Sete Cidades is an active central volcano with a summit caldera located in the westernmost part of S. Miguel Island (Azores. Since the settlement of the Island, in the 15th century, many landslide events occurred in this volcano, causing extensive damages in buildings and infrastructures. The study of historical records and the observation of new occurrences showed that landslides in the region have been triggered by heavy rainfall periods, earthquakes and erosion. In order to assess landslide susceptibility at Sete Cidades Volcano, landslide scars and associated deposits were mapped through aerial photographs and field surveys. The obtained data were inserted in a GIS to produce a landslide distribution map. It was concluded that the high density landslide areas are related with (1 major scarp faults, (2 the margin of fluvial channels, (3 the sea cliffs and (4 volcanic landforms, namely the caldera wall. About 73% of the mapped events took place in areas where pyroclastic deposits are the dominant lithology and more than 77% occurred where slopes are equal or higher than 20°. These two parameters were integrated and used to generate a preliminary susceptibility map. The incorporation of vulnerability data into the GIS allowed concluding that 30% of dwellings and most of the roads on Sete Cidades Volcano are located in areas where landslide susceptibility is high to very high. Such conclusion should be taken into account for emergency and land use planning.

  7. Application of an advanced fuzzy logic model for landslide susceptibility analysis

    Directory of Open Access Journals (Sweden)

    Biswajeet Pradhan

    2010-09-01

    Full Text Available The aim of this study is to evaluate the susceptibility of landslides at Klang valley area, Malaysia, using a Geographic Information System (GIS and remote sensing. Landslide locations were identified in the study area from interpretation of aerial photographs and from field surveys. Topographical and geological data and satellite images were collected, processed, and constructed into a spatial database using GIS and image processing. A data derived model (frequency ratio and a knowledge-derived model (fuzzy operator were combined for landslide susceptibility analysis. The nine factors that influence landslide occurrence were extracted from the database and the frequency ratio coefficient for each factor was computed. Using the factors and the identified landslide, the fuzzy membership values were calculated. Then fuzzy algebraic operators were applied to the fuzzy membership values for landslide susceptibility mapping. Finally, the produced map was verified by comparing with existing landslide locations for calculating prediction accuracy. Among the fuzzy operators, in the case in which the gamma operator (l = 0.8 showed the best accuracy (91% while the case in which the fuzzy algebraic product was applied showed the worst accuracy (79%.

  8. Reprint of "A proposed cell model for multiple-occurrence regional landslide events: Implications for landslide susceptibility mapping"

    Science.gov (United States)

    Crozier, M. J.

    2018-04-01

    Multiple-occurrence regional landslide events (MORLEs) consist of hundreds to thousands of shallow landslides occurring more or less simultaneously within defined areas, ranging from tens to thousands of square kilometres. While MORLEs can be triggered by rainstorms and earthquakes, this paper is confined to those landslide events triggered by rainstorms. Globally, MORLEs occur in a range of geological settings in areas of moderate to steep slopes subject to intense rainstorms. Individual landslides in rainstorm-triggered events are dominantly small, shallow debris and earth flows, and debris and earth slides involving regolith or weathered bedrock. The model used to characterise these events assumes that energy distribution within the event area is represented on the land surface by a cell structure; with maximum energy expenditure within an identifiable core and rapid dissipation concentrically away from the centre. The version of the model presented here has been developed for rainfall-triggered landslide events. It proposes that rainfall intensity can be used to determine different critical landslide response zones within the cell (referred to as core, middle, and periphery zones). These zones are most readily distinguished by two conditions: the proportion of the slope that fails and the particular type of the slope stability factor that assumes dominance in determining specific sites of landslide occurrence. The latter condition means that the power of any slope stability factor to distinguish between stable and unstable sites varies throughout the affected area in accordance with the landslide response zones within the cell; certain factors critical for determining the location of landslide sites in one part of the event area have little influence in other parts of the event area. The implication is that landslide susceptibility maps (and subsequently derived mitigation measures) based on conventional slope stability factors may have only limited validity

  9. Multidisciplinary approach to evaluate landslide susceptibility along highway in northern Calabria, Italy

    Science.gov (United States)

    Muto, Francesco; Conforti, Massimo; Critelli, Salvatore; Fabbricatore, Davide; Filomena, Luciana; Rago, Valeria; Robustelli, Gaetano; Scarciglia, Fabio; Versace, Pasquale

    2014-05-01

    The interaction of landslides with linear infrastructures is often the cause of disasters. In Italy landslide impact on roads, railways and buildings cause millions of Euro per year in damage and restoration as well. The proposed study is aimed to the landslide susceptibility evaluation using a multidisciplinary approach: geological and geomorphological survey, statistical analysis and GIS technique, along a section of highway "A3 (Salerno-Reggio Calabria)" between Cosenza Sud and Altilia, northern Calabria. This study is included in a wider research project, named: PON01-01503, Landslides Early Warning-Sistemi integrati per il monitoraggio e la mitigazione del rischio idrogeologico lungo le grandi vie di comunicazione - aimed at the hydrogeological risk mitigation and at the early warning along the highways. The work was first based on air-photo interpretations and field investigations, in order to realize the geological map, geomorphological map and landslide inventory map. In the study area the geomorphology is strongly controlled by its bedrock geology and tectonics. The bedrock geology consists of Neogene sedimentary rocks that cover a thick stack of allochthonous nappes. These nappes consist of crystalline rocks mainly gneiss, phyllite and schist. A total of 835 landslides were mapped and the type of movement are represented mainly by slides and complex and subordinately flow. In order to estimate and validate landslide susceptibility the landslides were divided in two group. One group (training set) was used to prepare susceptibility map and the second group (validation set) to validate the map. Then, the selection of predisposing factors was performed, according with the geological and geomorphological settings of the study area: lithology, distance from tectonic elements, land use, slope, aspect, stream power index (SPI) and plan curvature. In order to evaluate landslide susceptibility Conditional Analysis was applied to Unique Conditions Units (UCUs

  10. Landslide susceptibility mapping by comparing weight of evidence, fuzzy logic, and frequency ratio methods

    Directory of Open Access Journals (Sweden)

    V. Vakhshoori

    2016-09-01

    Full Text Available A regional scale basin susceptible to landslide located in Qaemshahr area in northern Iran was chosen for comparing the reliability of weight of evidence (WofE, fuzzy logic, and frequency ratio (FR methods for landslide susceptibility mapping. The locations of 157 landslides were identified using Google Earth® or extracted from archived data, from which, 22 rockslides were eliminated from the data-set due to their different conditions. The 135 remaining landslides were randomly divided into two groups of modelling (70% and validation (30% data-sets. Elevation, slope degree, slope aspect, lithology, land use/cover, normalized difference vegetation index, rainfall, distance to drainage network, roads, and faults were considered as landslide causative factors. The landslide susceptibility maps were prepared using the three mentioned methods. The validation process was measured by the success and prediction rates calculated by area under receiver operating characteristic curve. The ‘OR’, ‘AND’, ‘SUM’, and ‘PRODUCT’ operators of the fuzzy logic method were unacceptable because these operators classify the target area into either very high or very low susceptible zones that are inconsistent with the physical conditions of the study area. The results of fuzzy ‘GAMMA’ operators were relatively reliable while, FR and WofE methods showed results that are more reliable.

  11. Comparative assessment of landslide susceptibility. Case study: the Niraj river basin (Transylvania depression, Romania

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    RoŞca Sanda

    2016-05-01

    Full Text Available This study represents a comparison between two independent models used to evaluate landslide susceptibility in Romania: first, the model derived from the Romanian Governmental Decision no. 447/2003 (H.G. 447 and second, the bivariate statistical analysis. Considering the numerous objections to the first approach, which is also imposed by law, the accuracy of the results was analyzed using an alternative method which takes into consideration the reality from the field to a greater extent (the inventory of the existing landslides. The case study is focused on the Niraj catchment area (658 km2, a representative area for frequent landslide occurrence. The H.G. 447 model implies the estimation of the importance of eight factors involved in landslide occurrence: lithology, geomorphology, structure, hydro-climatic factors, hydrogeology, seismicity, forest cover and the anthropogenic factor. A thematic map was generated and analyzed for each one of the eight factors influencing slope instability and a specific coefficient was assigned. The statistical model, based on the bivariate probability analysis, was applied in order to predict the spatial distribution of the susceptibility classes. The probability of landslide occurrence was estimated based on the assumption that the prediction of the spatial distributions of landslides starts from the existing ones. In order to validate the model, the resulting maps were compared with the existing landslide maps: the relative landslide density index (R and the relative operation curve (ROC value were calculated, which indicate that the statistical model emphasizes a better correlation between the susceptibility classes and the active landslides (ROC value 0.972, the causative factors selected being relevant for the applied models.

  12. Landslide susceptibility mapping for a part of North Anatolian Fault Zone (Northeast Turkey) using logistic regression model

    Science.gov (United States)

    Demir, Gökhan; aytekin, mustafa; banu ikizler, sabriye; angın, zekai

    2013-04-01

    The North Anatolian Fault is know as one of the most active and destructive fault zone which produced many earthquakes with high magnitudes. Along this fault zone, the morphology and the lithological features are prone to landsliding. However, many earthquake induced landslides were recorded by several studies along this fault zone, and these landslides caused both injuiries and live losts. Therefore, a detailed landslide susceptibility assessment for this area is indispancable. In this context, a landslide susceptibility assessment for the 1445 km2 area in the Kelkit River valley a part of North Anatolian Fault zone (Eastern Black Sea region of Turkey) was intended with this study, and the results of this study are summarized here. For this purpose, geographical information system (GIS) and a bivariate statistical model were used. Initially, Landslide inventory maps are prepared by using landslide data determined by field surveys and landslide data taken from General Directorate of Mineral Research and Exploration. The landslide conditioning factors are considered to be lithology, slope gradient, slope aspect, topographical elevation, distance to streams, distance to roads and distance to faults, drainage density and fault density. ArcGIS package was used to manipulate and analyze all the collected data Logistic regression method was applied to create a landslide susceptibility map. Landslide susceptibility maps were divided into five susceptibility regions such as very low, low, moderate, high and very high. The result of the analysis was verified using the inventoried landslide locations and compared with the produced probability model. For this purpose, Area Under Curvature (AUC) approach was applied, and a AUC value was obtained. Based on this AUC value, the obtained landslide susceptibility map was concluded as satisfactory. Keywords: North Anatolian Fault Zone, Landslide susceptibility map, Geographical Information Systems, Logistic Regression Analysis.

  13. Characterization of past landslides and slope susceptibility analysis for Lima and Callao provinces, Peru

    Science.gov (United States)

    Tatard, Lucile; Villacorta, Sandra; Metzger, Pascale

    2013-04-01

    85% of people exposed to earthquakes, hurricanes, floods and drought live in developing countries (IPU, 2010). This population is also exposed to the landslide risk as this phenomenon is mainly triggered by earthquakes and rainfall. There is an urgent need to propose methods to evaluate and mitigate the landslide risk for developing countries, where few studies were undergone and data, and information on data, are scarce. In this study, we characterize a landslide inventory set up for the megalopolis of Lima, Peru, by the local geological bureau (INGEMMET). This inventory was set up using satellite images and includes landslides of all ages. It is composed of two landslide types: rockfalls and debris flows (huaycos) that we investigate together and separately. First, we describe qualitatively the landslide occurrences in terms of geology, slope steepness, altitude, etc. We notably find that debris flows occur at altitudes larger than the ones of the rockfalls, probably due to the climatic conditions. Then we find that the rockfalls and debris flows area distributions follow a power law when investigated separately whereas it does not follow a power law when investigated together. This highlights a logical difference of mechanics between the two landslide types. Then, using the dimension of correlation D (Grassberger and Procaccia, 1983) we show that the event spatial occurrences are not uniformly distributed but clustered. It supports the existence of controlling parameters on the spatial occurrence of landslides and the research to identify them. Last, we investigate the relationships between different landslide parameters (geology, altitude, slope steepness, ...) using the linear correlation coefficient r, and we find that all these parameters are independent to each other. This allows us to investigate each parameter separately in terms of landslide susceptibility and to define values for which the landslide susceptibility is low, medium or high for each

  14. Landslide susceptibility mapping on a global scale using the method of logistic regression

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    L. Lin

    2017-08-01

    Full Text Available This paper proposes a statistical model for mapping global landslide susceptibility based on logistic regression. After investigating explanatory factors for landslides in the existing literature, five factors were selected for model landslide susceptibility: relative relief, extreme precipitation, lithology, ground motion and soil moisture. When building the model, 70 % of landslide and nonlandslide points were randomly selected for logistic regression, and the others were used for model validation. To evaluate the accuracy of predictive models, this paper adopts several criteria including a receiver operating characteristic (ROC curve method. Logistic regression experiments found all five factors to be significant in explaining landslide occurrence on a global scale. During the modeling process, percentage correct in confusion matrix of landslide classification was approximately 80 % and the area under the curve (AUC was nearly 0.87. During the validation process, the above statistics were about 81 % and 0.88, respectively. Such a result indicates that the model has strong robustness and stable performance. This model found that at a global scale, soil moisture can be dominant in the occurrence of landslides and topographic factor may be secondary.

  15. Evaluation of landslide susceptibility mapping techniques using lidar-derived conditioning factors (Oregon case study

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    Rubini Mahalingam

    2016-11-01

    Full Text Available Landslides are a significant geohazard, which frequently result in significant human, infrastructure, and economic losses. Landslide susceptibility mapping using GIS and remote sensing can help communities prepare for these damaging events. Current mapping efforts utilize a wide variety of techniques and consider multiple factors. Unfortunately, each study is relatively independent of others in the applied technique and factors considered, resulting in inconsistencies. Further, input data quality often varies in terms of source, data collection, and generation, leading to uncertainty. This paper investigates if lidar-derived data-sets (slope, slope roughness, terrain roughness, stream power index, and compound topographic index can be used for predictive mapping without other landslide conditioning factors. This paper also assesses the differences in landslide susceptibility mapping using several, widely used statistical techniques. Landslide susceptibility maps were produced from the aforementioned lidar-derived data-sets for a small study area in Oregon using six representative statistical techniques. Most notably, results show that only a few factors were necessary to produce satisfactory maps with high predictive capability (area under the curve >0.7. The sole use of lidar digital elevation models and their derivatives can be used for landslide mapping using most statistical techniques without requiring additional detailed data-sets that are often difficult to obtain or of lower quality.

  16. Combined landslide inventory and susceptibility assessment based on different mapping units: an example from the Flemish Ardennes, Belgium

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    M. Van Den Eeckhaut

    2009-03-01

    Full Text Available For a 277 km2 study area in the Flemish Ardennes, Belgium, a landslide inventory and two landslide susceptibility zonations were combined to obtain an optimal landslide susceptibility assessment, in five classes. For the experiment, a regional landslide inventory, a 10 m × 10 m digital representation of topography, and lithological and soil hydrological information obtained from 1:50 000 scale maps, were exploited. In the study area, the regional inventory shows 192 landslides of the slide type, including 158 slope failures occurred before 1992 (model calibration set, and 34 failures occurred after 1992 (model validation set. The study area was partitioned in 2.78×106 grid cells and in 1927 topographic units. The latter are hydro-morphological units obtained by subdividing slope units based on terrain gradient. Independent models were prepared for the two terrain subdivisions using discriminant analysis. For grid cells, a single pixel was identified as representative of the landslide depletion area, and geo-environmental information for the pixel was obtained from the thematic maps. The landslide and geo-environmental information was used to model the propensity of the terrain to host landslide source areas. For topographic units, morphologic and hydrologic information and the proportion of lithologic and soil hydrological types in each unit, were used to evaluate landslide susceptibility, including the depletion and depositional areas. Uncertainty associated with the two susceptibility models was evaluated, and the model performance was tested using the independent landslide validation set. An heuristic procedure was adopted to combine the landslide inventory and the susceptibility zonations. The procedure makes optimal use of the available landslide and susceptibility information, minimizing the limitations inherent in the inventory and the susceptibility maps. For the established susceptibility classes, regulations to

  17. Combined landslide inventory and susceptibility assessment based on different mapping units: an example from the Flemish Ardennes, Belgium

    Science.gov (United States)

    van den Eeckhaut, M.; Reichenbach, P.; Guzzetti, F.; Rossi, M.; Poesen, J.

    2009-03-01

    For a 277 km2 study area in the Flemish Ardennes, Belgium, a landslide inventory and two landslide susceptibility zonations were combined to obtain an optimal landslide susceptibility assessment, in five classes. For the experiment, a regional landslide inventory, a 10 m × 10 m digital representation of topography, and lithological and soil hydrological information obtained from 1:50 000 scale maps, were exploited. In the study area, the regional inventory shows 192 landslides of the slide type, including 158 slope failures occurred before 1992 (model calibration set), and 34 failures occurred after 1992 (model validation set). The study area was partitioned in 2.78×106 grid cells and in 1927 topographic units. The latter are hydro-morphological units obtained by subdividing slope units based on terrain gradient. Independent models were prepared for the two terrain subdivisions using discriminant analysis. For grid cells, a single pixel was identified as representative of the landslide depletion area, and geo-environmental information for the pixel was obtained from the thematic maps. The landslide and geo-environmental information was used to model the propensity of the terrain to host landslide source areas. For topographic units, morphologic and hydrologic information and the proportion of lithologic and soil hydrological types in each unit, were used to evaluate landslide susceptibility, including the depletion and depositional areas. Uncertainty associated with the two susceptibility models was evaluated, and the model performance was tested using the independent landslide validation set. An heuristic procedure was adopted to combine the landslide inventory and the susceptibility zonations. The procedure makes optimal use of the available landslide and susceptibility information, minimizing the limitations inherent in the inventory and the susceptibility maps. For the established susceptibility classes, regulations to link terrain domains to appropriate land

  18. Landslide susceptibility mapping in Mawat area, Kurdistan Region, NE Iraq: a comparison of different statistical models

    Science.gov (United States)

    Othman, A. A.; Gloaguen, R.; Andreani, L.; Rahnama, M.

    2015-03-01

    During the last decades, expansion of settlements into areas prone to landslides in Iraq has increased the importance of accurate hazard assessment. Susceptibility mapping provides information about hazardous locations and thus helps to potentially prevent infrastructure damage due to mass wasting. The aim of this study is to evaluate and compare frequency ratio (FR), weight of evidence (WOE), logistic regression (LR) and probit regression (PR) approaches in combination with new geomorphological indices to determine the landslide susceptibility index (LSI). We tested these four methods in Mawat area, Kurdistan Region, NE Iraq, where landslides occur frequently. For this purpose, we evaluated 16 geomorphological, geological and environmental predicting factors mainly derived from the advanced spaceborne thermal emission and reflection radiometer (ASTER) satellite. The available reference inventory includes 351 landslides representing a cumulative surface of 3.127 km2. This reference inventory was mapped from QuickBird data by manual delineation and partly verified by field survey. The areas under curve (AUC) of the receiver operating characteristic (ROC), and relative landslide density (R index) show that all models perform similarly and that focus should be put on the careful selection of proxies. The results indicate that the lithology and the slope aspects play major roles for landslide occurrences. Furthermore, this paper demonstrates that using hypsometric integral as a prediction factor instead of slope curvature gives better results and increases the accuracy of the LSI.

  19. A precipitation-induced landslide susceptibility model for natural gas transmission pipelines

    Energy Technology Data Exchange (ETDEWEB)

    Finley, Jason P. [Fugro William Lettis and Associates, Inc., Valencia, California (United States); Slayter, David L.; Hitchcock, Chris S. [Fugro William Lettis and Associates, Inc., Walnut Creek, California (United States); Lee, Chih-Hung [Pacific Gas and Electric Company, Gas Systems Integrity Management, Walnut Creek, California (United States)

    2010-07-01

    Landslides related to heavy rainfall can cause extensive damage to natural gas transmission pipelines. Fugro William Lettis and Associates Inc. have developed and implemented a geographic information system (GIS) model that evaluates near real-time precipitation-induced landslide susceptibility. The model incorporates state-wide precipitation data and geologically-based landslide classifications to produce rapid landslide risk evaluation for Pacific Gas and Electric Company's (PGandE) gas transmission system during winter rain storms in California. The precipitation data include pre-storm event quantitative precipitation forecasts (QPF) and post-storm event quantitative precipitation estimate (QPE) from the United States National Oceanic and Atmospheric Administration (NOAA). The geologic classifications are based on slope, susceptible geologic formations, and the locations of historic or known landslide occurrences. Currently the model is calibrated using qualitative measures. This paper describes the development of the model algorithm and input data, model results, calibration efforts, and the on-going research and landslide collection warranted for continued refinement of the model.

  20. Data Mining Approaches for Landslide Susceptibility Mapping in Umyeonsan, Seoul, South Korea

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    Sunmin Lee

    2017-07-01

    Full Text Available The application of data mining models has become increasingly popular in recent years in assessments of a variety of natural hazards such as landslides and floods. Data mining techniques are useful for understanding the relationships between events and their influencing variables. Because landslides are influenced by a combination of factors including geomorphological and meteorological factors, data mining techniques are helpful in elucidating the mechanisms by which these complex factors affect landslide events. In this study, spatial data mining approaches based on data on landslide locations in the geographic information system environment were investigated. The topographical factors of slope, aspect, curvature, topographic wetness index, stream power index, slope length factor, standardized height, valley depth, and downslope distance gradient were determined using topographical maps. Additional soil and forest variables using information obtained from national soil and forest maps were also investigated. A total of 17 variables affecting the frequency of landslide occurrence were selected to construct a spatial database, and support vector machine (SVM and artificial neural network (ANN models were applied to predict landslide susceptibility from the selected factors. In the SVM model, linear, polynomial, radial base function, and sigmoid kernels were applied in sequence; the model yielded 72.41%, 72.83%, 77.17% and 72.79% accuracy, respectively. The ANN model yielded a validity accuracy of 78.41%. The results of this study are useful in guiding effective strategies for the prevention and management of landslides in urban areas.

  1. Weights of evidence method for landslide susceptibility mapping in Tangier, Morocco

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    Bousta Mahfoud

    2018-01-01

    Full Text Available Tangier region is known by a high density of mass movements which cause several human and economic losses. The goal of this paper is to assess the landslide susceptibility of Tangier using the Weight of Evidence method (WofE. The method is founded on the principle that an event (landslide is more likely to occur based on the relationship between the presence or absence of a predictive variable (predisposing factors and the occurrence of this event. The inventory, description and analysis of mass movements were prepared. Then the main factors governing their occurrence (lithology, fault, slope, elevation, exposure, drainage and land use were mapped before applying WofE. Finally, the ROC curves were established and the areas under curves (AUC were calculated to evaluate the degree of fit of the model and to choose the best landslide susceptibility zonation. The prediction accuracy was found to be 70%. Obtained susceptibility map shows that 60% of inventoried landslides are in the high to very high susceptibility zones, which is very satisfactory for the validation of the adopted model and the obtained results. These zones are mainly located in the N-E and E part of the Tangier region in the soft and fragile facies of the marls and clays of the Tangier unit, where landuse is characterized by dominance of arable and agricultural land (lack of forest cover. From a purely spatial point of view, the localization of these two classes of susceptibility is completely corresponding to the ground truth data, that is to say that all the environmental and anthropogenic conditions are in place for making this area prone to landslide hazards. The obtained map is a decision-making tool for presenting, comparing and discussing development and urban scenarios in Tangier. These results fall within the context of sustainable development and will help to mitigate the socio-economic impacts usually observed when landslides are triggered.

  2. Evaluating performance of simplified physically based models for shallow landslide susceptibility

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    G. Formetta

    2016-11-01

    Full Text Available Rainfall-induced shallow landslides can lead to loss of life and significant damage to private and public properties, transportation systems, etc. Predicting locations that might be susceptible to shallow landslides is a complex task and involves many disciplines: hydrology, geotechnical science, geology, hydrogeology, geomorphology, and statistics. Two main approaches are commonly used: statistical or physically based models. Reliable model applications involve automatic parameter calibration, objective quantification of the quality of susceptibility maps, and model sensitivity analyses. This paper presents a methodology to systemically and objectively calibrate, verify, and compare different models and model performance indicators in order to identify and select the models whose behavior is the most reliable for particular case studies.The procedure was implemented in a package of models for landslide susceptibility analysis and integrated in the NewAge-JGrass hydrological model. The package includes three simplified physically based models for landslide susceptibility analysis (M1, M2, and M3 and a component for model verification. It computes eight goodness-of-fit indices by comparing pixel-by-pixel model results and measurement data. The integration of the package in NewAge-JGrass uses other components, such as geographic information system tools, to manage input–output processes, and automatic calibration algorithms to estimate model parameters. The system was applied for a case study in Calabria (Italy along the Salerno–Reggio Calabria highway, between Cosenza and Altilia. The area is extensively subject to rainfall-induced shallow landslides mainly because of its complex geology and climatology. The analysis was carried out considering all the combinations of the eight optimized indices and the three models. Parameter calibration, verification, and model performance assessment were performed by a comparison with a detailed landslide

  3. Rainfall thresholds and susceptibility mapping for shallow landslides and debris flows in Scotland

    Science.gov (United States)

    Postance, Benjamin; Hillier, John; Dijkstra, Tom; Dixon, Neil

    2017-04-01

    Shallow translational slides and debris flows (hereafter 'landslides') pose a significant threat to life and cause significant annual economic impacts (e.g. by damage and disruption of infrastructure). The focus of this research is on the definition of objective rainfall thresholds using a weather radar system and landslide susceptibility mapping. In the study area Scotland, an inventory of 75 known landslides was used for the period 2003 to 2016. First, the effect of using different rain records (i.e. time series length) on two threshold selection techniques in receiver operating characteristic (ROC) analysis was evaluated. The results show that thresholds selected by 'Threat Score' (minimising false alarms) are sensitive to rain record length and which is not routinely considered, whereas thresholds selected using 'Optimal Point' (minimising failed alarms) are not; therefore these may be suited to establishing lower limit thresholds and be of interest to those developing early warning systems. Robust thresholds are found for combinations of normalised rain duration and accumulation at 1 and 12 day's antecedence respectively; these are normalised using the rainy-day normal and an equivalent measure for rain intensity. This research indicates that, in Scotland, rain accumulation provides a better indicator than rain intensity and that landslides may be generated by threshold conditions lower than previously thought. Second, a landslide susceptibility map is constructed using a cross-validated logistic regression model. A novel element of the approach is that landslide susceptibility is calculated for individual hillslope sections. The developed thresholds and susceptibility map are combined to assess potential hazards and impacts posed to the national highway network in Scotland.

  4. Optimizing landslide susceptibility zonation: Effects of DEM spatial resolution and slope unit delineation on logistic regression models

    Science.gov (United States)

    Schlögel, R.; Marchesini, I.; Alvioli, M.; Reichenbach, P.; Rossi, M.; Malet, J.-P.

    2018-01-01

    We perform landslide susceptibility zonation with slope units using three digital elevation models (DEMs) of varying spatial resolution of the Ubaye Valley (South French Alps). In so doing, we applied a recently developed algorithm automating slope unit delineation, given a number of parameters, in order to optimize simultaneously the partitioning of the terrain and the performance of a logistic regression susceptibility model. The method allowed us to obtain optimal slope units for each available DEM spatial resolution. For each resolution, we studied the susceptibility model performance by analyzing in detail the relevance of the conditioning variables. The analysis is based on landslide morphology data, considering either the whole landslide or only the source area outline as inputs. The procedure allowed us to select the most useful information, in terms of DEM spatial resolution, thematic variables and landslide inventory, in order to obtain the most reliable slope unit-based landslide susceptibility assessment.

  5. Susceptibility and triggering scenarios at a regional scale for shallow landslides

    Science.gov (United States)

    Gullà, G.; Antronico, L.; Iaquinta, P.; Terranova, O.

    2008-07-01

    The work aims at identifying susceptible areas and pluviometric triggering scenarios at a regional scale in Calabria (Italy), with reference to shallow landsliding events. The proposed methodology follows a statistical approach and uses a database linked to a GIS that has been created to support the various steps of spatial data management and manipulation. The shallow landslide predisposing factors taken into account are derived from (i) the 40-m digital terrain model of the region, an ˜ 15,075 km 2 extension; (ii) outcropping lithology; (iii) soils; and (iv) land use. More precisely, a map of the slopes has been drawn from the digital terrain model. Two kinds of covers [prevalently coarse-grained (CG cover) or fine-grained (FG cover)] were identified, referring to the geotechnical characteristics of geomaterial covers and to the lithology map; soilscapes were drawn from soil maps; and finally, the land use map was employed without any prior processing. Subsequently, the inventory maps of some shallow landsliding events, totaling more than 30,000 instabilities of the past and detected by field surveys and photo aerial restitution, were employed to calibrate the relative importance of these predisposing factors. The use of single factors (first level analysis) therefore provides three different susceptibility maps. Second level analysis, however, enables better location of areas susceptible to shallow landsliding events by crossing the single susceptibility maps. On the basis of the susceptibility map obtained by the second level analysis, five different classes of susceptibility to shallow landsliding events have been outlined over the regional territory: 8.9% of the regional territory shows very high susceptibility, 14.3% high susceptibility, 15% moderate susceptibility, 3.6% low susceptibility, and finally, about 58% very low susceptibility. Finally, the maps of two significant shallow landsliding events of the past and their related rainfalls have been

  6. Landslide susceptibility mapping by combining the three methods Fuzzy Logic, Frequency Ratio and Analytical Hierarchy Process in Dozain basin

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    E. Tazik

    2014-10-01

    Full Text Available Landslides are among the most important natural hazards that lead to modification of the environment. Therefore, studying of this phenomenon is so important in many areas. Because of the climate conditions, geologic, and geomorphologic characteristics of the region, the purpose of this study was landslide hazard assessment using Fuzzy Logic, frequency ratio and Analytical Hierarchy Process method in Dozein basin, Iran. At first, landslides occurred in Dozein basin were identified using aerial photos and field studies. The influenced landslide parameters that were used in this study including slope, aspect, elevation, lithology, precipitation, land cover, distance from fault, distance from road and distance from river were obtained from different sources and maps. Using these factors and the identified landslide, the fuzzy membership values were calculated by frequency ratio. Then to account for the importance of each of the factors in the landslide susceptibility, weights of each factor were determined based on questionnaire and AHP method. Finally, fuzzy map of each factor was multiplied to its weight that obtained using AHP method. At the end, for computing prediction accuracy, the produced map was verified by comparing to existing landslide locations. These results indicate that the combining the three methods Fuzzy Logic, Frequency Ratio and Analytical Hierarchy Process method are relatively good estimators of landslide susceptibility in the study area. According to landslide susceptibility map about 51% of the occurred landslide fall into the high and very high susceptibility zones of the landslide susceptibility map, but approximately 26 % of them indeed located in the low and very low susceptibility zones.

  7. Root reinforcement and its implications in shallow landsliding susceptibility on a small alpine catchment

    Science.gov (United States)

    Morandi, M. C.; Farabegoli, E.; Onorevoli, G.

    2012-04-01

    Roots shear resistance offers a considerable contribution to hill-slope stability on vegetated terrains. Through the pseudo-cohesion of shrubs, trees and turf's roots, the geomechanical properties of soils can be drastically increased, exerting a positive influence on the hillslope stability. We analysed the shallow landsliding susceptibility of a small alpine catchment (Duron valley, Central Dolomites, Italy) that we consider representative of a wide altitude belt of the Dolomites (1800 - 2400 m a.s.l). The catchment is mostly mantled by grass (Nardetum strictae s.l.), with clustered shrubs (Rhododendron hirsutum and Juniperus nana), and trees (Pinus cembra, Larix decidua and Picea abies). The soil depth, investigated with direct and indirect methods, ranges from 0 to 180 cm, with its peak at the hollow axes. Locally, the bedrock, made of Triassic volcanic rocks, is deeply incised by the Holocene drainage network. Intensive grazing of cows and horses pervades the catchment area and cattle-trails occupy ca 20% of the grass cover. We used laboratory and field tests to characterize the geotechnical properties of these alpine soils; moreover we designed and tested an experimental device that measures, in situ, the shear strengths of the grass mantle. In the study area we mapped 18 shallow landslides, mostly related to road cuts and periodically reactivated as retrogressive landslides. The triggering mechanisms of these shallow landslides were qualitatively analysed at large scale and modelled at smaller scale. We used SHALSTAB to model the shallow landsliding susceptibility of the catchment at the basin scale and SLIDE (RocScience) to compute the Safety Factor at the versant scale. Qualitative management solutions are provided, in order to reduce the shallow landsliding susceptibility risk in this alpine context.

  8. Landslide susceptibility modeling applying machine learning methods: A case study from Longju in the Three Gorges Reservoir area, China

    Science.gov (United States)

    Zhou, Chao; Yin, Kunlong; Cao, Ying; Ahmed, Bayes; Li, Yuanyao; Catani, Filippo; Pourghasemi, Hamid Reza

    2018-03-01

    Landslide is a common natural hazard and responsible for extensive damage and losses in mountainous areas. In this study, Longju in the Three Gorges Reservoir area in China was taken as a case study for landslide susceptibility assessment in order to develop effective risk prevention and mitigation strategies. To begin, 202 landslides were identified, including 95 colluvial landslides and 107 rockfalls. Twelve landslide causal factor maps were prepared initially, and the relationship between these factors and each landslide type was analyzed using the information value model. Later, the unimportant factors were selected and eliminated using the information gain ratio technique. The landslide locations were randomly divided into two groups: 70% for training and 30% for verifying. Two machine learning models: the support vector machine (SVM) and artificial neural network (ANN), and a multivariate statistical model: the logistic regression (LR), were applied for landslide susceptibility modeling (LSM) for each type. The LSM index maps, obtained from combining the assessment results of the two landslide types, were classified into five levels. The performance of the LSMs was evaluated using the receiver operating characteristics curve and Friedman test. Results show that the elimination of noise-generating factors and the separated modeling of each landslide type have significantly increased the prediction accuracy. The machine learning models outperformed the multivariate statistical model and SVM model was found ideal for the case study area.

  9. Landslide susceptibility mapping using frequency ratio, logistic regression, artificial neural networks and their comparison: A case study from Kat landslides (Tokat—Turkey)

    Science.gov (United States)

    Yilmaz, Işık

    2009-06-01

    The purpose of this study is to compare the landslide susceptibility mapping methods of frequency ratio (FR), logistic regression and artificial neural networks (ANN) applied in the Kat County (Tokat—Turkey). Digital elevation model (DEM) was first constructed using GIS software. Landslide-related factors such as geology, faults, drainage system, topographical elevation, slope angle, slope aspect, topographic wetness index (TWI) and stream power index (SPI) were used in the landslide susceptibility analyses. Landslide susceptibility maps were produced from the frequency ratio, logistic regression and neural networks models, and they were then compared by means of their validations. The higher accuracies of the susceptibility maps for all three models were obtained from the comparison of the landslide susceptibility maps with the known landslide locations. However, respective area under curve (AUC) values of 0.826, 0.842 and 0.852 for frequency ratio, logistic regression and artificial neural networks showed that the map obtained from ANN model is more accurate than the other models, accuracies of all models can be evaluated relatively similar. The results obtained in this study also showed that the frequency ratio model can be used as a simple tool in assessment of landslide susceptibility when a sufficient number of data were obtained. Input process, calculations and output process are very simple and can be readily understood in the frequency ratio model, however logistic regression and neural networks require the conversion of data to ASCII or other formats. Moreover, it is also very hard to process the large amount of data in the statistical package.

  10. Susceptibility assessment of earthquake-triggered landslides in El Salvador using logistic regression

    Science.gov (United States)

    García-Rodríguez, M. J.; Malpica, J. A.; Benito, B.; Díaz, M.

    2008-03-01

    This work has evaluated the probability of earthquake-triggered landslide occurrence in the whole of El Salvador, with a Geographic Information System (GIS) and a logistic regression model. Slope gradient, elevation, aspect, mean annual precipitation, lithology, land use, and terrain roughness are the predictor variables used to determine the dependent variable of occurrence or non-occurrence of landslides within an individual grid cell. The results illustrate the importance of terrain roughness and soil type as key factors within the model — using only these two variables the analysis returned a significance level of 89.4%. The results obtained from the model within the GIS were then used to produce a map of relative landslide susceptibility.

  11. The comparison of landslide ratio-based and general logistic regression landslide susceptibility models in the Chishan watershed after 2009 Typhoon Morakot

    Science.gov (United States)

    WU, Chunhung

    2015-04-01

    The research built the original logistic regression landslide susceptibility model (abbreviated as or-LRLSM) and landslide ratio-based ogistic regression landslide susceptibility model (abbreviated as lr-LRLSM), compared the performance and explained the error source of two models. The research assumes that the performance of the logistic regression model can be better if the distribution of landslide ratio and weighted value of each variable is similar. Landslide ratio is the ratio of landslide area to total area in the specific area and an useful index to evaluate the seriousness of landslide disaster in Taiwan. The research adopted the landside inventory induced by 2009 Typhoon Morakot in the Chishan watershed, which was the most serious disaster event in the last decade, in Taiwan. The research adopted the 20 m grid as the basic unit in building the LRLSM, and six variables, including elevation, slope, aspect, geological formation, accumulated rainfall, and bank erosion, were included in the two models. The six variables were divided as continuous variables, including elevation, slope, and accumulated rainfall, and categorical variables, including aspect, geological formation and bank erosion in building the or-LRLSM, while all variables, which were classified based on landslide ratio, were categorical variables in building the lr-LRLSM. Because the count of whole basic unit in the Chishan watershed was too much to calculate by using commercial software, the research took random sampling instead of the whole basic units. The research adopted equal proportions of landslide unit and not landslide unit in logistic regression analysis. The research took 10 times random sampling and selected the group with the best Cox & Snell R2 value and Nagelkerker R2 value as the database for the following analysis. Based on the best result from 10 random sampling groups, the or-LRLSM (lr-LRLSM) is significant at the 1% level with Cox & Snell R2 = 0.190 (0.196) and Nagelkerke R2

  12. Implementation of landslide susceptibility maps in Lower Austria as part of risk governance

    Science.gov (United States)

    Bell, Rainer; Petschko, Helene; Bauer, Christian; Glade, Thomas; Granica, Klaus; Heiss, Gerhard; Leopold, Philip; Pomaroli, Gilbert; Proske, Herwig; Schweigl, Joachim

    2013-04-01

    Landslides frequently cause damage to agricultural land and infrastructure in Lower Austria - a province of Austria. Also settlements and people are threatened by landslides. To reduce landslide risks and to prevent the establishment of new settlements in highly landslide prone areas, the project "MoNOE" (Method development for landslide susceptibility modeling in Lower Austria) was set up by the provincial government. The main aim of the project is the development of methods to model rock fall and slide susceptibility for an area of approx. 15,900 km2 and to implement the resulting susceptibility maps into the spatial planning strategies of the state. Right from the beginning of the project a close cooperation between the involved scientists and the stakeholders from the Geological Survey of Lower Austria and the Department of Spatial Planning and Regional Policy of Lower Austria was established to ensure that method development and final susceptibility maps meet exactly the needs and demands of the stakeholders. This posed huge challenges, together with its realization in the large study area and a (heterogeneous) complex geological situation,. Limitations were given by restricted data availability (e.g. for geology or landslide inventories) in such a large study area. Rock fall susceptibility was modeled by a combined approach of determining rock fall release areas by empirical slope thresholds (dependent on geology) followed by empirical run-out modeling. Slide susceptibility was modeled based on the statistical approaches of weights of evidence (WofE) and generalized additive models (GAM) by two different research groups. Huge efforts were spent on the validation of all susceptibility models. In a later stage of the project we found that the best scientific maps are not necessarily the best maps to be implemented in spatial planning strategies. Thus, in close cooperation with the stakeholders, decisions had to be taken to find the best resolution of the maps

  13. The spatial prediction of landslide susceptibility applying artificial neural network and logistic regression models: A case study of Inje, Korea

    Science.gov (United States)

    Saro, Lee; Woo, Jeon Seong; Kwan-Young, Oh; Moung-Jin, Lee

    2016-02-01

    The aim of this study is to predict landslide susceptibility caused using the spatial analysis by the application of a statistical methodology based on the GIS. Logistic regression models along with artificial neutral network were applied and validated to analyze landslide susceptibility in Inje, Korea. Landslide occurrence area in the study were identified based on interpretations of optical remote sensing data (Aerial photographs) followed by field surveys. A spatial database considering forest, geophysical, soil and topographic data, was built on the study area using the Geographical Information System (GIS). These factors were analysed using artificial neural network (ANN) and logistic regression models to generate a landslide susceptibility map. The study validates the landslide susceptibility map by comparing them with landslide occurrence areas. The locations of landslide occurrence were divided randomly into a training set (50%) and a test set (50%). A training set analyse the landslide susceptibility map using the artificial network along with logistic regression models, and a test set was retained to validate the prediction map. The validation results revealed that the artificial neural network model (with an accuracy of 80.10%) was better at predicting landslides than the logistic regression model (with an accuracy of 77.05%). Of the weights used in the artificial neural network model, `slope' yielded the highest weight value (1.330), and `aspect' yielded the lowest value (1.000). This research applied two statistical analysis methods in a GIS and compared their results. Based on the findings, we were able to derive a more effective method for analyzing landslide susceptibility.

  14. The spatial prediction of landslide susceptibility applying artificial neural network and logistic regression models: A case study of Inje, Korea

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    Saro Lee

    2016-02-01

    Full Text Available The aim of this study is to predict landslide susceptibility caused using the spatial analysis by the application of a statistical methodology based on the GIS. Logistic regression models along with artificial neutral network were applied and validated to analyze landslide susceptibility in Inje, Korea. Landslide occurrence area in the study were identified based on interpretations of optical remote sensing data (Aerial photographs followed by field surveys. A spatial database considering forest, geophysical, soil and topographic data, was built on the study area using the Geographical Information System (GIS. These factors were analysed using artificial neural network (ANN and logistic regression models to generate a landslide susceptibility map. The study validates the landslide susceptibility map by comparing them with landslide occurrence areas. The locations of landslide occurrence were divided randomly into a training set (50% and a test set (50%. A training set analyse the landslide susceptibility map using the artificial network along with logistic regression models, and a test set was retained to validate the prediction map. The validation results revealed that the artificial neural network model (with an accuracy of 80.10% was better at predicting landslides than the logistic regression model (with an accuracy of 77.05%. Of the weights used in the artificial neural network model, ‘slope’ yielded the highest weight value (1.330, and ‘aspect’ yielded the lowest value (1.000. This research applied two statistical analysis methods in a GIS and compared their results. Based on the findings, we were able to derive a more effective method for analyzing landslide susceptibility.

  15. Analysis of significance of environmental factors in landslide susceptibility modeling: Case study Jemma drainage network, Ethiopia

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    Vít Maca

    2017-06-01

    Full Text Available Aim of the paper is to describe methodology for calculating significance of environmental factors in landslide susceptibility modeling and present result of selected one. As a study area part of a Jemma basin in Ethiopian Highland is used. This locality is highly affected by mass movement processes. In the first part all major factors and their influence are described briefly. Majority of the work focuses on research of other methodologies used in susceptibility models and design of own methodology. This method is unlike most of the methods used completely objective, therefore it is not possible to intervene in the results. In article all inputs and outputs of the method are described as well as all stages of calculations. Results are illustrated on specific examples. In study area most important factor for landslide susceptibility is slope, on the other hand least important is land cover. At the end of article landslide susceptibility map is created. Part of the article is discussion of results and possible improvements of the methodology.

  16. An Ensemble Model for Co-Seismic Landslide Susceptibility Using GIS and Random Forest Method

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    Suchita Shrestha

    2017-11-01

    Full Text Available The Mw 7.8 Gorkha earthquake of 25 April 2015 triggered thousands of landslides in the central part of the Nepal Himalayas. The main goal of this study was to generate an ensemble-based map of co-seismic landslide susceptibility in Sindhupalchowk District using model comparison and combination strands. A total of 2194 co-seismic landslides were identified and were randomly split into 1536 (~70%, to train data for establishing the model, and the remaining 658 (~30% for the validation of the model. Frequency ratio, evidential belief function, and weight of evidence methods were applied and compared using 11 different causative factors (peak ground acceleration, epicenter proximity, fault proximity, geology, elevation, slope, plan curvature, internal relief, drainage proximity, stream power index, and topographic wetness index to prepare the landslide susceptibility map. An ensemble of random forest was then used to overcome the various prediction limitations of the individual models. The success rates and prediction capabilities were critically compared using the area under the curve (AUC of the receiver operating characteristic curve (ROC. By synthesizing the results of the various models into a single score, the ensemble model improved accuracy and provided considerably more realistic prediction capacities (91% than the frequency ratio (81.2%, evidential belief function (83.5% methods, and weight of evidence (80.1%.

  17. Landslide susceptibility mapping at Hoa Binh province (Vietnam) using an adaptive neuro-fuzzy inference system and GIS

    Science.gov (United States)

    Tien Bui, Dieu; Pradhan, Biswajeet; Lofman, Owe; Revhaug, Inge; Dick, Oystein B.

    2012-08-01

    The objective of this study is to investigate a potential application of the Adaptive Neuro-Fuzzy Inference System (ANFIS) and the Geographic Information System (GIS) as a relatively new approach for landslide susceptibility mapping in the Hoa Binh province of Vietnam. Firstly, a landslide inventory map with a total of 118 landslide locations was constructed from various sources. Then the landslide inventory was randomly split into a testing dataset 70% (82 landslide locations) for training the models and the remaining 30% (36 landslides locations) was used for validation purpose. Ten landslide conditioning factors such as slope, aspect, curvature, lithology, land use, soil type, rainfall, distance to roads, distance to rivers, and distance to faults were considered in the analysis. The hybrid learning algorithm and six different membership functions (Gaussmf, Gauss2mf, Gbellmf, Sigmf, Dsigmf, Psigmf) were applied to generate the landslide susceptibility maps. The validation dataset, which was not considered in the ANFIS modeling process, was used to validate the landslide susceptibility maps using the prediction rate method. The validation results showed that the area under the curve (AUC) for six ANFIS models vary from 0.739 to 0.848. It indicates that the prediction capability depends on the membership functions used in the ANFIS. The models with Sigmf (0.848) and Gaussmf (0.825) have shown the highest prediction capability. The results of this study show that landslide susceptibility mapping in the Hoa Binh province of Vietnam using the ANFIS approach is viable. As far as the performance of the ANFIS approach is concerned, the results appeared to be quite satisfactory, the zones determined on the map being zones of relative susceptibility.

  18. Assessment of earthquake-triggered landslide susceptibility in El Salvador based on an Artificial Neural Network model

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    M. J. García-Rodríguez

    2010-06-01

    Full Text Available This paper presents an approach for assessing earthquake-triggered landslide susceptibility using artificial neural networks (ANNs. The computational method used for the training process is a back-propagation learning algorithm. It is applied to El Salvador, one of the most seismically active regions in Central America, where the last severe destructive earthquakes occurred on 13 January 2001 (Mw 7.7 and 13 February 2001 (Mw 6.6. The first one triggered more than 600 landslides (including the most tragic, Las Colinas landslide and killed at least 844 people.

    The ANN is designed and programmed to develop landslide susceptibility analysis techniques at a regional scale. This approach uses an inventory of landslides and different parameters of slope instability: slope gradient, elevation, aspect, mean annual precipitation, lithology, land use, and terrain roughness. The information obtained from ANN is then used by a Geographic Information System (GIS to map the landslide susceptibility. In a previous work, a Logistic Regression (LR was analysed with the same parameters considered in the ANN as independent variables and the occurrence or non-occurrence of landslides as dependent variables. As a result, the logistic approach determined the importance of terrain roughness and soil type as key factors within the model. The results of the landslide susceptibility analysis with ANN are checked using landslide location data. These results show a high concordance between the landslide inventory and the high susceptibility estimated zone. Finally, a comparative analysis of the ANN and LR models are made. The advantages and disadvantages of both approaches are discussed using Receiver Operating Characteristic (ROC curves.

  19. Assessment of earthquake-triggered landslide susceptibility in El Salvador based on an Artificial Neural Network model

    Science.gov (United States)

    García-Rodríguez, M. J.; Malpica, J. A.

    2010-06-01

    This paper presents an approach for assessing earthquake-triggered landslide susceptibility using artificial neural networks (ANNs). The computational method used for the training process is a back-propagation learning algorithm. It is applied to El Salvador, one of the most seismically active regions in Central America, where the last severe destructive earthquakes occurred on 13 January 2001 (Mw 7.7) and 13 February 2001 (Mw 6.6). The first one triggered more than 600 landslides (including the most tragic, Las Colinas landslide) and killed at least 844 people. The ANN is designed and programmed to develop landslide susceptibility analysis techniques at a regional scale. This approach uses an inventory of landslides and different parameters of slope instability: slope gradient, elevation, aspect, mean annual precipitation, lithology, land use, and terrain roughness. The information obtained from ANN is then used by a Geographic Information System (GIS) to map the landslide susceptibility. In a previous work, a Logistic Regression (LR) was analysed with the same parameters considered in the ANN as independent variables and the occurrence or non-occurrence of landslides as dependent variables. As a result, the logistic approach determined the importance of terrain roughness and soil type as key factors within the model. The results of the landslide susceptibility analysis with ANN are checked using landslide location data. These results show a high concordance between the landslide inventory and the high susceptibility estimated zone. Finally, a comparative analysis of the ANN and LR models are made. The advantages and disadvantages of both approaches are discussed using Receiver Operating Characteristic (ROC) curves.

  20. Landslide Susceptibility Mapping of Tegucigalpa, Honduras Using Artificial Neural Network, Bayesian Network and Decision Trees

    Science.gov (United States)

    Garcia Urquia, E. L.; Braun, A.; Yamagishi, H.

    2016-12-01

    Tegucigalpa, the capital city of Honduras, experiences rainfall-induced landslides on a yearly basis. The high precipitation regime and the rugged topography the city has been built in couple with the lack of a proper urban expansion plan to contribute to the occurrence of landslides during the rainy season. Thousands of inhabitants live at risk of losing their belongings due to the construction of precarious shelters in landslide-prone areas on mountainous terrains and next to the riverbanks. Therefore, the city is in the need for landslide susceptibility and hazard maps to aid in the regulation of future development. Major challenges in the context of highly dynamic urbanizing areas are the overlap of natural and anthropogenic slope destabilizing factors, as well as the availability and accuracy of data. Data-driven multivariate techniques have proven to be powerful in discovering interrelations between factors, identifying important factors in large datasets, capturing non-linear problems and coping with noisy and incomplete data. This analysis focuses on the creation of a landslide susceptibility map using different methods from the field of data mining, Artificial Neural Networks (ANN), Bayesian Networks (BN) and Decision Trees (DT). The input dataset of the study contains geomorphological and hydrological factors derived from a digital elevation model with a 10 m resolution, lithological factors derived from a geological map, and anthropogenic factors, such as information on the development stage of the neighborhoods in Tegucigalpa and road density. Moreover, a landslide inventory map that was developed in 2014 through aerial photo interpretation was used as target variable in the analysis. The analysis covers an area of roughly 100 km2, while 8.95 km2 are occupied by landslides. In a first step, the dataset was explored by assessing and improving the data quality, identifying unimportant variables and finding interrelations. Then, based on a training

  1. IDENTIFICATION OF LANDSLIDES SUSCEPTIBILITY IN THE DOBRIC CATCHMENT AREA USING THE FREQUENCY RATE MODEL

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    ROXANA VĂIDEAN

    2013-11-01

    Full Text Available The landslides susceptibility of the Dobric catchment area (Ilişua river. The territorial geomorfological investigation focuses mainly on the analysis of the present situation, as context of future events occurrence. The previous evolutionary context is secondary in place due also to the particular attention it has received so far. The significance of the knowledge regarding the present events and their evolution is explicit in the attempt to mitigate their impact on the built area and on the resources. The identification of areas characterized by maximum susceptibility in the landslides occurrence is absolutely necessary. The method which makes the identification of these areas possible is none other than the method considering the conditional factors, as well as the spatial distribution of the events that have already occurred. In this regard, the use of the frequency rate model is considered to be ideal.

  2. Landslide susceptibility modeling in a landslide prone area in Mazandarn Province, north of Iran: a comparison between GLM, GAM, MARS, and M-AHP methods

    Science.gov (United States)

    Pourghasemi, Hamid Reza; Rossi, Mauro

    2017-10-01

    Landslides are identified as one of the most important natural hazards in many areas throughout the world. The essential purpose of this study is to compare general linear model (GLM), general additive model (GAM), multivariate adaptive regression spline (MARS), and modified analytical hierarchy process (M-AHP) models and assessment of their performances for landslide susceptibility modeling in the west of Mazandaran Province, Iran. First, landslides were identified by interpreting aerial photographs, and extensive field works. In total, 153 landslides were identified in the study area. Among these, 105 landslides were randomly selected as training data (i.e. used in the models training) and the remaining 48 (30 %) cases were used for the validation (i.e. used in the models validation). Afterward, based on a deep literature review on 220 scientific papers (period between 2005 and 2012), eleven conditioning factors including lithology, land use, distance from rivers, distance from roads, distance from faults, slope angle, slope aspect, altitude, topographic wetness index (TWI), plan curvature, and profile curvature were selected. The Certainty Factor (CF) model was used for managing uncertainty in rule-based systems and evaluation of the correlation between the dependent (landslides) and independent variables. Finally, the landslide susceptibility zonation was produced using GLM, GAM, MARS, and M-AHP models. For evaluation of the models, the area under the curve (AUC) method was used and both success and prediction rate curves were calculated. The evaluation of models for GLM, GAM, and MARS showed 90.50, 88.90, and 82.10 % for training data and 77.52, 70.49, and 78.17 % for validation data, respectively. Furthermore, The AUC value of the produced landslide susceptibility map using M-AHP showed a training value of 77.82 % and validation value of 82.77 % accuracy. Based on the overall assessments, the proposed approaches showed reasonable results for landslide

  3. Using online databases for landslide susceptibility assessment: an example from the Veneto Region (northeastern Italy

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    M. Floris

    2011-07-01

    Full Text Available In this paper, spatial data available in the Italian portals was used to evaluate the landslide susceptibility of the Euganean Hills Regional Park, located SW of Padua (northeastern Italy. Quality, applicability and possible analysis scales of the online data were investigated.

    After a brief overview on the WebGIS portals around the world, their contents and tools for natural risk analyses, a susceptibility analysis of the study area was carried out using a simple probabilistic approach that compared landslide distribution and influencing factors. The input factors used in the analysis depended on available data and included landslides, morphometric data (elevation, slope, curvature, profile and plan Curvature and non-morphometric data (land use, distance to roads and distance to rivers. Great attention was paid to the pre-processing step, in particular the re-classification of continuous data that was performed following objective, geologic and geomorphologic criteria.

    The results of the study show that the simple probabilistic approach used for the susceptibility evaluation showed quite good accuracy and precision (repeatability. However, heuristic, statistical or deterministic methods could be applied to the online data to improve the prediction.

    The data available online for the Italian territory allows susceptibility assessment at medium and large scales. Morphometric factors, such as elevation and slope angle, are important because they implicitly include information that is not available, such as lithologic and structural data. The main drawback of the Italian online databases is the lack of information on the frequency of landslides; thus, a complete hazard analysis is not possible.

    Despite the good results achieved to date, collection and sharing of data on natural risks must be improved in Italy and around the world. The creation of spatial data infrastructure and more WebGIS portals is desirable.

  4. Assessing landslide susceptibility by applying fuzzy sets, possibility evidence-based theories

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    Ibsen Chivatá Cárdenas

    2008-01-01

    Full Text Available A landslide susceptibility model was developed for the city of Manizales, Colombia; landslides have been the city’s main environmental problem. Fuzzy sets and possibility and evidence-based theories were used to construct the mo-del due to the set of circumstances and uncertainty involved in the modelling; uncertainty particularly concerned the lack of representative data and the need for systematically coordinating subjective information. Susceptibility and the uncertainty were estimated via data processing; the model contained data concerning mass vulnerability and uncer-tainty. Output data was expressed on a map defined by linguistic categories or uncertain labels as having low, me-dium, high and very high susceptibility; this was considered appropriate for representing susceptibility. A fuzzy spec-trum was developed for classifying susceptibility levels according to perception and expert opinion. The model sho-wed levels of susceptibility in the study area, ranging from low to high susceptibility (medium susceptibility being mo-re frequent. This article shows the details concerning systematic data processing by presenting theories and tools regarding uncertainty. The concept of fuzzy parameters is introduced; this is useful in modelling phenomena regar-ding uncertainty, complexity and nonlinear performance, showing that susceptibility modelling can be feasible. The paper also shows the great convenience of incorporating uncertainty into modelling and decision-making. However, quantifying susceptibility is not suitable when modelling identified uncertainty because incorporating model output information cannot be reduced into exact or real numerical quantities when the nature of the variables is particularly uncertain. The latter concept is applicable to risk assessment.

  5. Slope stability susceptibility evaluation parameter (SSEP) rating scheme - An approach for landslide hazard zonation

    Science.gov (United States)

    Raghuvanshi, Tarun Kumar; Ibrahim, Jemal; Ayalew, Dereje

    2014-11-01

    In this paper a new slope susceptibility evaluation parameter (SSEP) rating scheme is presented which is developed as an expert evaluation approach for landslide hazard zonation. The SSEP rating scheme is developed by considering intrinsic and external triggering parameters that are responsible for slope instability. The intrinsic parameters which are considered are; slope geometry, slope material (rock or soil type), structural discontinuities, landuse and landcover and groundwater. Besides, external triggering parameters such as, seismicity, rainfall and manmade activities are also considered. For SSEP empirical technique numerical ratings are assigned to each of the intrinsic and triggering parameters on the basis of logical judgments acquired from experience of studies of intrinsic and external triggering factors and their relative impact in inducing instability to the slope. Further, the distribution of maximum SSEP ratings is based on their relative order of importance in contributing instability to the slope. Finally, summation of all ratings for intrinsic and triggering parameter based on actual observation will provide the expected degree of landslide in a given land unit. This information may be utilized to develop a landslide hazard zonation map. The SSEP technique was applied in the area around Wurgessa Kebelle of North Wollo Zonal Administration, Amhara National Regional State in northern Ethiopia, some 490 km from Addis Ababa. The results obtained indicates that 8.33% of the area fall under Moderately hazard and 83.33% fall within High hazard whereas 8.34% of the area fall under Very high hazard. Further, in order to validate the LHZ map prepared during the study, active landslide activities and potential instability areas, delineated through inventory mapping was overlain on it. All active landslide activities and potential instability areas fall within very high and high hazard zone. Thus, the satisfactory agreement confirms the rationality of

  6. Field-based landslide susceptibility assessment in a data-scarce environment: the populated areas of the Rwenzori Mountains

    Science.gov (United States)

    Jacobs, Liesbet; Dewitte, Olivier; Poesen, Jean; Sekajugo, John; Nobile, Adriano; Rossi, Mauro; Thiery, Wim; Kervyn, Matthieu

    2018-01-01

    The inhabited zone of the Ugandan Rwenzori Mountains is affected by landslides, frequently causing loss of life, damage to infrastructure and loss of livelihood. This area of ca. 1230 km2 is characterized by contrasting geomorphologic, climatic and lithological patterns, resulting in different landslide types. In this study, the spatial pattern of landslide susceptibility is investigated based on an extensive field inventory constructed for five representative areas within the region (153 km2) and containing over 450 landslides. To achieve a reliable susceptibility assessment, the effects of (1) using different topographic data sources and spatial resolutions and (2) changing the scale of assessment by comparing local and regional susceptibility models on the susceptibility model performances are investigated using a pixel-based logistic regression approach. Topographic data are extracted from different digital elevation models (DEMs) based on radar interferometry (SRTM and TanDEM-X) and optical stereophotogrammetry (ASTER DEM). Susceptibility models using the radar-based DEMs tend to outperform the ones using the ASTER DEM. The model spatial resolution is varied between 10, 20, 30 and 90 m. The optimal resolution depends on the location of the investigated area within the region but the lowest model resolution (90 m) rarely yields the best model performances while the highest model resolution (10 m) never results in significant increases in performance compared to the 20 m resolution. Models built for the local case studies generally have similar or better performances than the regional model and better reflect site-specific controlling factors. At the regional level the effect of distinguishing landslide types between shallow and deep-seated landslides is investigated. The separation of landslide types allows us to improve model performances for the prediction of deep-seated landslides and to better understand factors influencing the occurrence of shallow

  7. Field-based landslide susceptibility assessment in a data-scarce environment: the populated areas of the Rwenzori Mountains

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    L. Jacobs

    2018-01-01

    Full Text Available The inhabited zone of the Ugandan Rwenzori Mountains is affected by landslides, frequently causing loss of life, damage to infrastructure and loss of livelihood. This area of ca. 1230 km2 is characterized by contrasting geomorphologic, climatic and lithological patterns, resulting in different landslide types. In this study, the spatial pattern of landslide susceptibility is investigated based on an extensive field inventory constructed for five representative areas within the region (153 km2 and containing over 450 landslides. To achieve a reliable susceptibility assessment, the effects of (1 using different topographic data sources and spatial resolutions and (2 changing the scale of assessment by comparing local and regional susceptibility models on the susceptibility model performances are investigated using a pixel-based logistic regression approach. Topographic data are extracted from different digital elevation models (DEMs based on radar interferometry (SRTM and TanDEM-X and optical stereophotogrammetry (ASTER DEM. Susceptibility models using the radar-based DEMs tend to outperform the ones using the ASTER DEM. The model spatial resolution is varied between 10, 20, 30 and 90 m. The optimal resolution depends on the location of the investigated area within the region but the lowest model resolution (90 m rarely yields the best model performances while the highest model resolution (10 m never results in significant increases in performance compared to the 20 m resolution. Models built for the local case studies generally have similar or better performances than the regional model and better reflect site-specific controlling factors. At the regional level the effect of distinguishing landslide types between shallow and deep-seated landslides is investigated. The separation of landslide types allows us to improve model performances for the prediction of deep-seated landslides and to better understand factors influencing the

  8. Optimization of Causative Factors for Landslide Susceptibility Evaluation Using Remote Sensing and GIS Data in Parts of Niigata, Japan.

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    Jie Dou

    Full Text Available This paper assesses the potentiality of certainty factor models (CF for the best suitable causative factors extraction for landslide susceptibility mapping in the Sado Island, Niigata Prefecture, Japan. To test the applicability of CF, a landslide inventory map provided by National Research Institute for Earth Science and Disaster Prevention (NIED was split into two subsets: (i 70% of the landslides in the inventory to be used for building the CF based model; (ii 30% of the landslides to be used for the validation purpose. A spatial database with fifteen landslide causative factors was then constructed by processing ALOS satellite images, aerial photos, topographical and geological maps. CF model was then applied to select the best subset from the fifteen factors. Using all fifteen factors and the best subset factors, landslide susceptibility maps were produced using statistical index (SI and logistic regression (LR models. The susceptibility maps were validated and compared using landslide locations in the validation data. The prediction performance of two susceptibility maps was estimated using the Receiver Operating Characteristics (ROC. The result shows that the area under the ROC curve (AUC for the LR model (AUC = 0.817 is slightly higher than those obtained from the SI model (AUC = 0.801. Further, it is noted that the SI and LR models using the best subset outperform the models using the fifteen original factors. Therefore, we conclude that the optimized factor model using CF is more accurate in predicting landslide susceptibility and obtaining a more homogeneous classification map. Our findings acknowledge that in the mountainous regions suffering from data scarcity, it is possible to select key factors related to landslide occurrence based on the CF models in a GIS platform. Hence, the development of a scenario for future planning of risk mitigation is achieved in an efficient manner.

  9. Optimization of Causative Factors for Landslide Susceptibility Evaluation Using Remote Sensing and GIS Data in Parts of Niigata, Japan.

    Science.gov (United States)

    Dou, Jie; Tien Bui, Dieu; Yunus, Ali P; Jia, Kun; Song, Xuan; Revhaug, Inge; Xia, Huan; Zhu, Zhongfan

    2015-01-01

    This paper assesses the potentiality of certainty factor models (CF) for the best suitable causative factors extraction for landslide susceptibility mapping in the Sado Island, Niigata Prefecture, Japan. To test the applicability of CF, a landslide inventory map provided by National Research Institute for Earth Science and Disaster Prevention (NIED) was split into two subsets: (i) 70% of the landslides in the inventory to be used for building the CF based model; (ii) 30% of the landslides to be used for the validation purpose. A spatial database with fifteen landslide causative factors was then constructed by processing ALOS satellite images, aerial photos, topographical and geological maps. CF model was then applied to select the best subset from the fifteen factors. Using all fifteen factors and the best subset factors, landslide susceptibility maps were produced using statistical index (SI) and logistic regression (LR) models. The susceptibility maps were validated and compared using landslide locations in the validation data. The prediction performance of two susceptibility maps was estimated using the Receiver Operating Characteristics (ROC). The result shows that the area under the ROC curve (AUC) for the LR model (AUC = 0.817) is slightly higher than those obtained from the SI model (AUC = 0.801). Further, it is noted that the SI and LR models using the best subset outperform the models using the fifteen original factors. Therefore, we conclude that the optimized factor model using CF is more accurate in predicting landslide susceptibility and obtaining a more homogeneous classification map. Our findings acknowledge that in the mountainous regions suffering from data scarcity, it is possible to select key factors related to landslide occurrence based on the CF models in a GIS platform. Hence, the development of a scenario for future planning of risk mitigation is achieved in an efficient manner.

  10. Landslide susceptibility mapping using AHP method and GIS in the peninsula of Tangier (Rif-northern morocco

    Directory of Open Access Journals (Sweden)

    Ait Brahim L

    2018-01-01

    Full Text Available The peninsula of Tangier (Northern Morocco is submitted to a significant number of landslides each year due to its lithological, structural and morphological complexity; which cause a lot of damage to the road network and other related infrastructure. The main objective of this study is to create a landslide indexed susceptibility map of Tangier peninsula, by using AHP (Analytical Hierarchical Processes model to calculate each factor’s weight. The work is made via GIS by using an ArcGIS AHP extension. In the current research, First of all, the four main types of landslides were identified and mapped from existing documents, works and new data which came from either remote sensing or fieldwork. Lithology, land use, slope, hypsometry, exposure, fault density and drainage network density were used as main parameters controlling the occurrence of the selected landslides. Then, afterward, each parameter is classified into a number of significant classes based on their relative influence on gravitational movement genesis. The validity of the susceptibility zoning map which is obtained through linear summation of indexed maps was tested and cross-checked by inventoried and studied landslides. The obtained landslide susceptibility map constitutes a powerful decision-making tool in land-use planning, i.e. New highways, secondary highways, railways, etc. within the national development program in the Northern provinces. It is a necessary step for the landslides hazard assessment in the Tangier peninsula in northern Morocco.

  11. Landslide susceptibility mapping along PLUS expressways in Malaysia using probabilistic based model in GIS

    Science.gov (United States)

    Yusof, Norbazlan M.; Pradhan, Biswajeet

    2014-06-01

    PLUS Berhad holds the concession for a total of 987 km of toll expressways in Malaysia, the longest of which is the North-South Expressway or NSE. Acting as the backbone' of the west coast of the peninsula, the NSE stretches from the Malaysian-Thai border in the north to the border with neighbouring Singapore in the south, linking several major cities and towns along the way. North-South Expressway in Malaysia contributes to the country economic development through trade, social and tourism sector. Presently, the highway is good in terms of its condition and connection to every state but some locations need urgent attention. Stability of slopes at these locations is of most concern as any instability can cause danger to the motorist. In this paper, two study locations have been analysed; they are Gua Tempurung (soil slope) and Jelapang (rock slope) which are obviously having two different characteristics. These locations passed through undulating terrain with steep slopes where landslides are common and the probability of slope instability due to human activities in surrounding areas is high. A combination of twelve (12) landslide conditioning factors database on slope stability such as slope degree and slope aspect were extracted from IFSAR (interoferometric synthetic aperture radar) while landuse, lithology and structural geology were constructed from interpretation of high resolution satellite data from World View II, Quickbird and Ikonos. All this information was analysed in geographic information system (GIS) environment for landslide susceptibility mapping using probabilistic based frequency ratio model. Consequently, information on the slopes such as inventories, condition assessments and maintenance records were assessed through total expressway maintenance management system or better known as TEMAN. The above mentioned system is used by PLUS as an asset management and decision support tools for maintenance activities along the highways as well as for data

  12. Landslide susceptibility mapping along PLUS expressways in Malaysia using probabilistic based model in GIS

    International Nuclear Information System (INIS)

    Yusof, Norbazlan M; Pradhan, Biswajeet

    2014-01-01

    PLUS Berhad holds the concession for a total of 987 km of toll expressways in Malaysia, the longest of which is the North-South Expressway or NSE. Acting as the backbone' of the west coast of the peninsula, the NSE stretches from the Malaysian-Thai border in the north to the border with neighbouring Singapore in the south, linking several major cities and towns along the way. North-South Expressway in Malaysia contributes to the country economic development through trade, social and tourism sector. Presently, the highway is good in terms of its condition and connection to every state but some locations need urgent attention. Stability of slopes at these locations is of most concern as any instability can cause danger to the motorist. In this paper, two study locations have been analysed; they are Gua Tempurung (soil slope) and Jelapang (rock slope) which are obviously having two different characteristics. These locations passed through undulating terrain with steep slopes where landslides are common and the probability of slope instability due to human activities in surrounding areas is high. A combination of twelve (12) landslide conditioning factors database on slope stability such as slope degree and slope aspect were extracted from IFSAR (interoferometric synthetic aperture radar) while landuse, lithology and structural geology were constructed from interpretation of high resolution satellite data from World View II, Quickbird and Ikonos. All this information was analysed in geographic information system (GIS) environment for landslide susceptibility mapping using probabilistic based frequency ratio model. Consequently, information on the slopes such as inventories, condition assessments and maintenance records were assessed through total expressway maintenance management system or better known as TEMAN. The above mentioned system is used by PLUS as an asset management and decision support tools for maintenance activities along the highways as well as for

  13. Landslide Susceptibility Evaluation on agricultural terraces of DOURO VALLEY (PORTUGAL), using physically based mathematical models.

    Science.gov (United States)

    Faria, Ana; Bateira, Carlos; Laura, Soares; Fernandes, Joana; Gonçalves, José; Marques, Fernando

    2016-04-01

    The work focuses the evaluation of landslide susceptibility in Douro Region agricultural terraces, supported by dry stone walls and earth embankments, using two physically based models. The applied models, SHALSTAB (Montgomery et al.,1994; Dietrich et al., 1995) and SINMAP (PACK et al., 2005), combine an infinite slope stability model with a steady state hydrological model, and both use the following geophysical parameters: cohesion, friction angle, specific weight and soil thickness. The definition of the contributing areas is different in both models. The D∞ methodology used by SINMAP model suggests a great influence of the terraces morphology, providing a much more diffuse flow on the internal flow modelling. The MD8 used in SHALSTAB promotes an important degree of flow concentration, representing an internal flow based on preferential paths of the runoff as the areas more susceptible to saturation processes. The model validation is made through the contingency matrix method (Fawcett, 2006; Raia et al., 2014) and implies the confrontation with the inventory of past landslides. The True Positive Rate shows that SHALSTAB classifies 77% of the landslides on the high susceptibility areas, while SINMAP reaches 90%. The SINMAP has a False Positive Rate (represents the percentage of the slipped area that is classified as unstable but without landslides) of 83% and the SHALSTAB has 67%. The reliability (analyzes the areas that were correctly classified on the total area) of SHALSTAB is better (33% against 18% of SINMAP). Relative to Precision (refers to the ratio of the slipped area correctly classified over the whole area classified as unstable) SHALSTAB has better results (0.00298 against 0.00283 of SINMAP). It was elaborate the index TPR/FPR and better results obtained by SHALSTAB (1.14 against 1.09 of SINMAP). SHALSTAB shows a better performance in the definition of susceptibility most prone areas to instability processes. One of the reasons for the difference of

  14. Tropical Forest Fire Susceptibility Mapping at the Cat Ba National Park Area, Hai Phong City, Vietnam, Using GIS-Based Kernel Logistic Regression

    Directory of Open Access Journals (Sweden)

    Dieu Tien Bui

    2016-04-01

    Full Text Available The Cat Ba National Park area (Vietnam with its tropical forest is recognized as being part of the world biodiversity conservation by the United Nations Educational, Scientific and Cultural Organization (UNESCO and is a well-known destination for tourists, with around 500,000 travelers per year. This area has been the site for many research projects; however, no project has been carried out for forest fire susceptibility assessment. Thus, protection of the forest including fire prevention is one of the main concerns of the local authorities. This work aims to produce a tropical forest fire susceptibility map for the Cat Ba National Park area, which may be helpful for the local authorities in forest fire protection management. To obtain this purpose, first, historical forest fires and related factors were collected from various sources to construct a GIS database. Then, a forest fire susceptibility model was developed using Kernel logistic regression. The quality of the model was assessed using the Receiver Operating Characteristic (ROC curve, area under the ROC curve (AUC, and five statistical evaluation measures. The usability of the resulting model is further compared with a benchmark model, the support vector machine (SVM. The results show that the Kernel logistic regression model has a high level of performance in both the training and validation dataset, with a prediction capability of 92.2%. Since the Kernel logistic regression model outperforms the benchmark model, we conclude that the proposed model is a promising alternative tool that should also be considered for forest fire susceptibility mapping in other areas. The results of this study are useful for the local authorities in forest planning and management.

  15. Regional landslide susceptibility assessment using multi-stage remote sensing data along the coastal range highway in northeastern Taiwan

    Science.gov (United States)

    Lee, Ching-Fang; Huang, Wei-Kai; Chang, Yu-Lin; Chi, Shu-Yeong; Liao, Wu-Chang

    2018-01-01

    Typhoons Megi (2010) and Saola (2012) brought torrential rainfall which triggered regional landslides and flooding hazards along Provincial Highway No. 9 in northeastern Taiwan. To reduce property loss and saving lives, this study combines multi-hazard susceptibility assessment with environmental geology map a rock mass rating system (RMR), remote sensing analysis, and micro-topography interpretation to develop an integrated landslide hazard assessment approach and reflect the intrinsic state of slopeland from the past toward the future. First, the degree of hazard as indicated by historical landslides was used to determine many landslide regions in the past. Secondly, geo-mechanical classification of rock outcroppings was performed by in-situ investigation along the vulnerable road sections. Finally, a high-resolution digital elevation model was extracted from airborne LiDAR and multi-temporal remote sensing images which was analyzed to discover possible catastrophic landslide hotspot shortly. The results of the analysis showed that 37% of the road sections in the study area were highly susceptible to landslide hazards. The spatial distribution of the road sections revealed that those characterized by high susceptibility were located near the boundaries of fault zones and in areas of lithologic dissimilarity. Headward erosion of gullies and concave-shaped topographic features had an adverse effect and was the dominant factor triggering landslides. Regional landslide reactivation on this coastal highway are almost related to the past landslide region based on hazard statistics. The final results of field validation demonstrated that an accuracy of 91% could be achieved for forecasting geohazard followed by intense rainfall events and typhoons.

  16. Landslide susceptibility mapping using decision-tree based CHi-squared automatic interaction detection (CHAID) and Logistic regression (LR) integration

    International Nuclear Information System (INIS)

    Althuwaynee, Omar F; Pradhan, Biswajeet; Ahmad, Noordin

    2014-01-01

    This article uses methodology based on chi-squared automatic interaction detection (CHAID), as a multivariate method that has an automatic classification capacity to analyse large numbers of landslide conditioning factors. This new algorithm was developed to overcome the subjectivity of the manual categorization of scale data of landslide conditioning factors, and to predict rainfall-induced susceptibility map in Kuala Lumpur city and surrounding areas using geographic information system (GIS). The main objective of this article is to use CHi-squared automatic interaction detection (CHAID) method to perform the best classification fit for each conditioning factor, then, combining it with logistic regression (LR). LR model was used to find the corresponding coefficients of best fitting function that assess the optimal terminal nodes. A cluster pattern of landslide locations was extracted in previous study using nearest neighbor index (NNI), which were then used to identify the clustered landslide locations range. Clustered locations were used as model training data with 14 landslide conditioning factors such as; topographic derived parameters, lithology, NDVI, land use and land cover maps. Pearson chi-squared value was used to find the best classification fit between the dependent variable and conditioning factors. Finally the relationship between conditioning factors were assessed and the landslide susceptibility map (LSM) was produced. An area under the curve (AUC) was used to test the model reliability and prediction capability with the training and validation landslide locations respectively. This study proved the efficiency and reliability of decision tree (DT) model in landslide susceptibility mapping. Also it provided a valuable scientific basis for spatial decision making in planning and urban management studies

  17. Landslide susceptibility mapping using decision-tree based CHi-squared automatic interaction detection (CHAID) and Logistic regression (LR) integration

    Science.gov (United States)

    Althuwaynee, Omar F.; Pradhan, Biswajeet; Ahmad, Noordin

    2014-06-01

    This article uses methodology based on chi-squared automatic interaction detection (CHAID), as a multivariate method that has an automatic classification capacity to analyse large numbers of landslide conditioning factors. This new algorithm was developed to overcome the subjectivity of the manual categorization of scale data of landslide conditioning factors, and to predict rainfall-induced susceptibility map in Kuala Lumpur city and surrounding areas using geographic information system (GIS). The main objective of this article is to use CHi-squared automatic interaction detection (CHAID) method to perform the best classification fit for each conditioning factor, then, combining it with logistic regression (LR). LR model was used to find the corresponding coefficients of best fitting function that assess the optimal terminal nodes. A cluster pattern of landslide locations was extracted in previous study using nearest neighbor index (NNI), which were then used to identify the clustered landslide locations range. Clustered locations were used as model training data with 14 landslide conditioning factors such as; topographic derived parameters, lithology, NDVI, land use and land cover maps. Pearson chi-squared value was used to find the best classification fit between the dependent variable and conditioning factors. Finally the relationship between conditioning factors were assessed and the landslide susceptibility map (LSM) was produced. An area under the curve (AUC) was used to test the model reliability and prediction capability with the training and validation landslide locations respectively. This study proved the efficiency and reliability of decision tree (DT) model in landslide susceptibility mapping. Also it provided a valuable scientific basis for spatial decision making in planning and urban management studies.

  18. Landslide susceptibility mapping in the coastal region in the State of São Paulo, Brazil

    Science.gov (United States)

    Alvala, R. C.; Camarinha, P. I.; Canavesi, V.

    2013-05-01

    The exposure of populations in risk areas is a matter of global concern, because it is a determining factor for the natural disasters occurrences. Furthermore, it has also been observed an intensification of extreme hydrometeorological events that has triggered disasters in various parts of the globe, further increasing the need for monitoring and alerting for natural disasters, aiming the safeguarding of life and minimize economic losses. Accordingly, different methodologies for risk assessment have been proposed, focusing on the specific natural hazards. Particularly for Brazil, which has economic axis of development in the regions near the coast, it is common to observe the process of urbanization advancing on steep slopes of the mountain regions. This characteristic causes the population exposure to the natural hazards related to the mass movements, which the landslides stood out as the cause of many deaths and economic losses every year. Thus, prior to risk analysis (when human occupation intersect with natural hazard), it is essential to analyze the susceptibility, which reflects the physical and environmental conditions that trigger for such phenomena. However, this task becomes a major challenge due to the difficulty of finding databases with good quality. In this context, this paper presents a methodology based only on spatial information in the public domain, integrated into a Geographic Information System free, in order to analyze the landslides susceptibility. In a first effort, we evaluated four counties of Southeastern Brazil - Santos, Cubatão, Caraguatatuba and Ubatuba - located in a region that includes the rugged reliefs of Serra do Mar and the transition to the coastal region, that have historic of disasters related. It is noteworthy that the methodology takes into account many variables that was weighted and crossed by Fuzzy Gamma technique, such as: topography (horizontal and vertical curvature of the slopes), geology, geomorphology, slope

  19. Variable-Weighted Linear Combination Model for Landslide Susceptibility Mapping: Case Study in the Shennongjia Forestry District, China

    Directory of Open Access Journals (Sweden)

    Wei Chen

    2017-11-01

    Full Text Available A landslide susceptibility map plays an essential role in urban and rural planning. The main purpose of this study is to establish a variable-weighted linear combination model (VWLC and assess its potential for landslide susceptibility mapping. Firstly, different objective methods are employed for data processing rather than the frequently-used subjective judgments: K-means clustering is used for classification; binarization is introduced to determine buffer length thresholds for locational elements (road, river, and fault; landslide area density is adopted as the contribution index; and a correlation analysis is conducted for suitable factor selection. Secondly, considering the dimension changes of the preference matrix varying with the different locations of the mapping cells, the variable weights of each optimal factor are determined based on the improved analytic hierarchy process (AHP. On this basis, the VWLC model is established and applied to regional landslide susceptibility mapping for the Shennongjia Forestry District, China, where shallow landslides frequently occur. The obtained map is then compared with a map using the traditional WLC, and the results of the comparison show that VWLC is more reasonable, with a higher accuracy, and can be used anywhere that has the same or similar geological and topographical conditions.

  20. Landslide susceptibility assessment in the Peloritani Mts. (Sicily, Italy and clues for tectonic control of relief processes

    Directory of Open Access Journals (Sweden)

    G. De Guidi

    2013-04-01

    Full Text Available Many destructive shallow landslides hit villages in the Peloritani Mountains area (Sicily, Italy on 1 October 2009 after heavy rainfall. The collection of several types of spatial data, together with a landslide inventory, allows the assessment of the landslide susceptibility by applying a statistical technique. The susceptibility model was validated by performing an analysis in a test area using independent landslide information, the results being able to correctly predict more than 70% of the landslides. Furthermore, the susceptibility analysis allowed the identification of which combinations of classes, within the different factors, have greater relevance in slope instability, and afterwards associating the most unstable combinations (with a short–medium term incidence with the endogenic processes acting in the area (huge regional uplift, fault activity. Geological and tectonic history are believed to be key to interpreting morphological processes and landscape evolution. Recent tectonic activity was found to be a very important controlling factor in landscape evolution. A geomorphological model of cyclical relief evolution is proposed in which endogenic processes are directly linked to superficial processes. The results are relevant both to risk reduction and the understanding of active geological dynamics.

  1. Expert opinion on landslide susceptibility elicted by probabilistic inversion from scenario rankings

    Science.gov (United States)

    Lee, Katy; Dashwood, Claire; Lark, Murray

    2016-04-01

    For many natural hazards the opinion of experts, with experience in assessing susceptibility under different circumstances, is a valuable source of information on which to base risk assessments. This is particularly important where incomplete process understanding, and limited data, limit the scope to predict susceptibility by mechanistic or statistical modelling. The expert has a tacit model of a system, based on their understanding of processes and their field experience. This model may vary in quality, depending on the experience of the expert. There is considerable interest in how one may elicit expert understanding by a process which is transparent and robust, to provide a basis for decision support. One approach is to provide experts with a set of scenarios, and then to ask them to rank small overlapping subsets of these with respect to susceptibility. Methods of probabilistic inversion have been used to compute susceptibility scores for each scenario, implicit in the expert ranking. It is also possible to model these scores as functions of measurable properties of the scenarios. This approach has been used to assess susceptibility of animal populations to invasive diseases, to assess risk to vulnerable marine environments and to assess the risk in hypothetical novel technologies for food production. We will present the results of a study in which a group of geologists with varying degrees of expertise in assessing landslide hazards were asked to rank sets of hypothetical simplified scenarios with respect to land slide susceptibility. We examine the consistency of their rankings and the importance of different properties of the scenarios in the tacit susceptibility model that their rankings implied. Our results suggest that this is a promising approach to the problem of how experts can communicate their tacit model of uncertain systems to those who want to make use of their expertise.

  2. Progress in national-scale landslide susceptibility mapping in Romania using a combined statistical-heuristical approach

    Science.gov (United States)

    Bălteanu, Dan; Micu, Mihai; Malet, Jean-Philippe; Jurchescu, Marta; Sima, Mihaela; Kucsicsa, Gheorghe; Dumitrică, Cristina; Petrea, Dănuţ; Mărgărint, Ciprian; Bilaşco, Ştefan; Văcăreanu, Radu; Georgescu, Sever; Senzaconi, Francisc

    2017-04-01

    Landslide processes represent a very widespread geohazard in Romania, affecting mainly the hilly and plateau regions as well as the mountain sectors developed on flysch formations. Two main projects provided the framework for improving the existing national landslide susceptibility map (Bălteanu et al. 2010): the ELSUS (Pan-European and nation-wide landslide susceptibility assessment, EC-CERG) and the RO-RISK (Disaster Risk Evaluation at National Level, ESF-POCA) projects. The latter one, a flagship project aiming at strengthening risk prevention and management in Romania, focused on a national-level evaluation of the main risks in the country including landslides. The strategy for modeling landslide susceptibility was designed based on the experience gained from continental and national level assessments conducted in the frame of the International Programme on Landslides (IPL) project IPL-162, the European Landslides Expert Group - JRC and the ELSUS project. The newly proposed landslide susceptibility model used as input a reduced set of landslide conditioning factor maps available at scales of 1:100,000 - 1:200,000 and consisting of lithology, slope angle and land cover. The input data was further differentiated for specific natural environments, defined here as morpho-structural units in order to incorporate differences induced by elevation (vertical climatic zonation), morpho-structure as well as neotectonic features. In order to best discern the specific landslide conditioning elements, the analysis has been carried out for one single process category, namely slides. The existence of a landslide inventory covering the whole country's territory ( 30,000 records, Micu et al. 2014), although affected by incompleteness and lack of homogeneity, allowed for the application of a semi-quantitative, mixed statistical-heuristical approach having the advantage of combining the objectivity of statistics with expert-knowledge in calibrating class and factor weights. The

  3. Producing landslide susceptibility maps by utilizing machine learning methods. The case of Finikas catchment basin, North Peloponnese, Greece.

    Science.gov (United States)

    Tsangaratos, Paraskevas; Ilia, Ioanna; Loupasakis, Constantinos; Papadakis, Michalis; Karimalis, Antonios

    2017-04-01

    The main objective of the present study was to apply two machine learning methods for the production of a landslide susceptibility map in the Finikas catchment basin, located in North Peloponnese, Greece and to compare their results. Specifically, Logistic Regression and Random Forest were utilized, based on a database of 40 sites classified into two categories, non-landslide and landslide areas that were separated into a training dataset (70% of the total data) and a validation dataset (remaining 30%). The identification of the areas was established by analyzing airborne imagery, extensive field investigation and the examination of previous research studies. Six landslide related variables were analyzed, namely: lithology, elevation, slope, aspect, distance to rivers and distance to faults. Within the Finikas catchment basin most of the reported landslides were located along the road network and within the residential complexes, classified as rotational and translational slides, and rockfalls, mainly caused due to the physical conditions and the general geotechnical behavior of the geological formation that cover the area. Each landslide susceptibility map was reclassified by applying the Geometric Interval classification technique into five classes, namely: very low susceptibility, low susceptibility, moderate susceptibility, high susceptibility, and very high susceptibility. The comparison and validation of the outcomes of each model were achieved using statistical evaluation measures, the receiving operating characteristic and the area under the success and predictive rate curves. The computation process was carried out using RStudio an integrated development environment for R language and ArcGIS 10.1 for compiling the data and producing the landslide susceptibility maps. From the outcomes of the Logistic Regression analysis it was induced that the highest b coefficient is allocated to lithology and slope, which was 2.8423 and 1.5841, respectively. From the

  4. Spatial prediction of landslide susceptibility in parts of Garhwal Himalaya, India, using the weight of evidence modelling.

    Science.gov (United States)

    Guri, Pardeep Kumar; Ray, P K Champati; Patel, Ramesh Chandra

    2015-06-01

    Garhwal Himalaya in northern India has emerged as one of the most prominent hot spots of landslide occurrences in the Himalaya mainly due to geological causes related to mountain building processes, steep topography and frequent occurrences of extreme precipitation events. As this region has many pilgrimage and tourist centres, it is visited by hundreds of thousands of people every year, and in the recent past, there has been rapid development to provide adequate roads and building infrastructure. Additionally, attempts are also made to harness hydropower by constructing tunnels, dams and reservoirs and thus altering vulnerable slopes at many places. As a result, the overall risk due to landslide hazards has increased many folds and, therefore, an attempt was made to assess landslide susceptibility using 'Weights of Evidence (WofE)', a well-known bivariate statistical modelling technique implemented in a much improved way using remote sensing and Geographic Information System. This methodology has dual advantage as it demonstrates how to derive critical parameters related to geology, geomorphology, slope, land use and most importantly temporal landslide distribution in one of the data scarce region of the world. Secondly, it allows to experiment with various combination of parameters to assess their cumulative effect on landslides. In total, 15 parameters related to geology, geomorphology, terrain, hydrology and anthropogenic factors and 2 different landslide inventories (prior to 2007 and 2008-2011) were prepared from high-resolution Indian remote sensing satellite data (Cartosat-1 and Resourcesat-1) and were validated by field investigation. Several combinations of parameters were carried out using WofE modelling, and finally using best combination of eight parameters, 76.5 % of overall landslides were predicted in 24 % of the total area susceptible to landslide occurrences. The study has highlighted that using such methodology landslide susceptibility assessment

  5. The inner structure of landslides and landslide-prone slopes in south German cuesta landscapes assessed by geophysical, geomorphological and sedimentological approaches

    Science.gov (United States)

    Schwindt, Daniel; Sandmeier, Christine; Büdel, Christian; Jäger, Daniel; Wilde, Martina; Terhorst, Birgit

    2016-04-01

    Investigations on landslide activity in the cuesta landscape of Germany, usually characterized by an interbedding of morphologically hard (e.g. sand-/limestones) and soft (clay) sedimentary rocks are relatively sparse. However, spring 2013 has once again revealed a high susceptibility of the slopes in the Franconian and Swabian Alb to mass movements, when enduring rainfalls initiated numerous landslides causing considerable damage to settlements and infrastructure. Many aspects like the spatial distribution of landslides, triggering factors, and process dynamics - especially with view on the reactivation of landslides - require intensive investigations to allow for assessment of the landslide vulnerability and the development of reliable early-warning systems. Aim of the study is to achieve a deeper insight into the triggering factors and the process dynamics of landslides in the cuesta landscape with special regard on landslide proneness of slopes and the potential reactivation of old landslides. A multi-methodological approach was conducted based on geophysical investigations (seismic refraction tomography - SRT, electrical resistivity tomography - ERT), geomorphological mapping, morphometric GIS-based analysis, core soundings and substrate mapping. Study sites are located in the Swabian Alb (southwestern Germany) in the Jurassic escarpment where where Oxfordian marls and limestones superimpose Callovian clays, as well as in the northeastern Franconian Alb, within the escarpment of the so called Rhätolias with with red claystones of the late Norian (Feuerletten formation) below interbedding layers of sand- and claystones of the Rhaetian (Upper Triassic) and Hettangian ( Lower Jurassic). The investigated landslides strongly differ with respect to their age, from young landslides originated in spring 2013 to ancient landslides. Investigations reveal a distinct diversity of landslide types composed of a complex combination of processes. The applied methods allow

  6. Landslide susceptibility near highways is increased by 1 order of magnitude in the Andes of southern Ecuador, Loja province

    Science.gov (United States)

    Brenning, A.; Schwinn, M.; Ruiz-Páez, A. P.; Muenchow, J.

    2015-01-01

    Mountain roads in developing countries are known to increase landslide occurrence due to often inadequate drainage systems and mechanical destabilization of hillslopes by undercutting and overloading. This study empirically investigates landslide initiation frequency along two paved interurban highways in the tropical Andes of southern Ecuador across different climatic regimes. Generalized additive models (GAM) and generalized linear models (GLM) were used to analyze the relationship between mapped landslide initiation points and distance to highway while accounting for topographic, climatic, and geological predictors as possible confounders. A spatial block bootstrap was used to obtain nonparametric confidence intervals for the odds ratio of landslide occurrence near the highways (25 m distance) compared to a 200 m distance. The estimated odds ratio was 18-21, with lower 95% confidence bounds >13 in all analyses. Spatial bootstrap estimation using the GAM supports the higher odds ratio estimate of 21.2 (95% confidence interval: 15.5-25.3). The highway-related effects were observed to fade at about 150 m distance. Road effects appear to be enhanced in geological units characterized by Holocene gravels and Laramide andesite/basalt. Overall, landslide susceptibility was found to be more than 1 order of magnitude higher in close proximity to paved interurban highways in the Andes of southern Ecuador.

  7. Landslide susceptibility near highways is increased by one order of magnitude in the Andes of southern Ecuador, Loja province

    Science.gov (United States)

    Brenning, A.; Schwinn, M.; Ruiz-Páez, A. P.; Muenchow, J.

    2014-03-01

    Mountain roads in developing countries are known to increase landslide occurrence due to often inadequate drainage systems and mechanical destabilization of hillslopes by undercutting and overloading. This study empirically investigates landslide initiation frequency along two paved interurban highways in the tropical Andes of southern Ecuador across different climatic regimes. Generalized additive models (GAM) and generalized linear models (GLM) were used to analyze the relationship between mapped landslide initiation points and distance to highway while accounting for topographic, climatic and geological predictors as possible confounders. A spatial block bootstrap was used to obtain non-parametric confidence intervals for the odds ratio of landslide occurrence near the highways (25 m distance) compared to a 200 m distance. The estimated odds ratio was 18-21 with lower 95% confidence bounds > 13 in all analyses. Spatial bootstrap estimation using the GAM supports the higher odds ratio estimate of 21.2 (95% confidence interval: 15.5-25.3). The highway-related effects were observed to fade at about 150 m distance. Road effects appear to be enhanced in geological units characterized by Holocene gravels and Laramide andesite/basalt. Overall, landslide susceptibility was found to be more than one order of magnitude higher in close proximity to paved interurban highways in the Andes of southern Ecuador.

  8. Handling high predictor dimensionality in slope-unit-based landslide susceptibility models through LASSO-penalized Generalized Linear Model

    KAUST Repository

    Camilo, Daniela Castro

    2017-08-30

    Grid-based landslide susceptibility models at regional scales are computationally demanding when using a fine grid resolution. Conversely, Slope-Unit (SU) based susceptibility models allows to investigate the same areas offering two main advantages: 1) a smaller computational burden and 2) a more geomorphologically-oriented interpretation. In this contribution, we generate SU-based landslide susceptibility for the Sado Island in Japan. This island is characterized by deep-seated landslides which we assume can only limitedly be explained by the first two statistical moments (mean and variance) of a set of predictors within each slope unit. As a consequence, in a nested experiment, we first analyse the distributions of a set of continuous predictors within each slope unit computing the standard deviation and quantiles from 0.05 to 0.95 with a step of 0.05. These are then used as predictors for landslide susceptibility. In addition, we combine shape indices for polygon features and the normalized extent of each class belonging to the outcropping lithology in a given SU. This procedure significantly enlarges the size of the predictor hyperspace, thus producing a high level of slope-unit characterization. In a second step, we adopt a LASSO-penalized Generalized Linear Model to shrink back the predictor set to a sensible and interpretable number, carrying only the most significant covariates in the models. As a result, we are able to document the geomorphic features (e.g., 95% quantile of Elevation and 5% quantile of Plan Curvature) that primarily control the SU-based susceptibility within the test area while producing high predictive performances. The implementation of the statistical analyses are included in a parallelized R script (LUDARA) which is here made available for the community to replicate analogous experiments.

  9. Handling high predictor dimensionality in slope-unit-based landslide susceptibility models through LASSO-penalized Generalized Linear Model

    KAUST Repository

    Camilo, Daniela Castro; Lombardo, Luigi; Mai, Paul Martin; Dou, Jie; Huser, Raphaë l

    2017-01-01

    Grid-based landslide susceptibility models at regional scales are computationally demanding when using a fine grid resolution. Conversely, Slope-Unit (SU) based susceptibility models allows to investigate the same areas offering two main advantages: 1) a smaller computational burden and 2) a more geomorphologically-oriented interpretation. In this contribution, we generate SU-based landslide susceptibility for the Sado Island in Japan. This island is characterized by deep-seated landslides which we assume can only limitedly be explained by the first two statistical moments (mean and variance) of a set of predictors within each slope unit. As a consequence, in a nested experiment, we first analyse the distributions of a set of continuous predictors within each slope unit computing the standard deviation and quantiles from 0.05 to 0.95 with a step of 0.05. These are then used as predictors for landslide susceptibility. In addition, we combine shape indices for polygon features and the normalized extent of each class belonging to the outcropping lithology in a given SU. This procedure significantly enlarges the size of the predictor hyperspace, thus producing a high level of slope-unit characterization. In a second step, we adopt a LASSO-penalized Generalized Linear Model to shrink back the predictor set to a sensible and interpretable number, carrying only the most significant covariates in the models. As a result, we are able to document the geomorphic features (e.g., 95% quantile of Elevation and 5% quantile of Plan Curvature) that primarily control the SU-based susceptibility within the test area while producing high predictive performances. The implementation of the statistical analyses are included in a parallelized R script (LUDARA) which is here made available for the community to replicate analogous experiments.

  10. Presence-only approach to assess landslide triggering-thickness susceptibility: a test for the Mili catchment (north-eastern Sicily, Italy)

    KAUST Repository

    Lombardo, Luigi; Fubelli, G.; Amato, G.; Bonasera, M.

    2016-01-01

    This study evaluates the performances of the presence-only approach, Maximum Entropy, in assessing landslide triggering-thickness susceptibility within the Mili catchment (Sicily, Italy). This catchment underwent several meteorological stresses

  11. Landslide-susceptibility analysis using light detection and ranging-derived digital elevation models and logistic regression models: a case study in Mizunami City, Japan

    Science.gov (United States)

    Wang, Liang-Jie; Sawada, Kazuhide; Moriguchi, Shuji

    2013-01-01

    To mitigate the damage caused by landslide disasters, different mathematical models have been applied to predict landslide spatial distribution characteristics. Although some researchers have achieved excellent results around the world, few studies take the spatial resolution of the database into account. Four types of digital elevation model (DEM) ranging from 2 to 20 m derived from light detection and ranging technology to analyze landslide susceptibility in Mizunami City, Gifu Prefecture, Japan, are presented. Fifteen landslide-causative factors are considered using a logistic-regression approach to create models for landslide potential analysis. Pre-existing landslide bodies are used to evaluate the performance of the four models. The results revealed that the 20-m model had the highest classification accuracy (71.9%), whereas the 2-m model had the lowest value (68.7%). In the 2-m model, 89.4% of the landslide bodies fit in the medium to very high categories. For the 20-m model, only 83.3% of the landslide bodies were concentrated in the medium to very high classes. When the cell size decreases from 20 to 2 m, the area under the relative operative characteristic increases from 0.68 to 0.77. Therefore, higher-resolution DEMs would provide better results for landslide-susceptibility mapping.

  12. Landslide susceptibility mapping based on Support Vector Machine: A case study on natural slopes of Hong Kong, China

    Science.gov (United States)

    Yao, X.; Tham, L. G.; Dai, F. C.

    2008-11-01

    The Support Vector Machine (SVM) is an increasingly popular learning procedure based on statistical learning theory, and involves a training phase in which the model is trained by a training dataset of associated input and target output values. The trained model is then used to evaluate a separate set of testing data. There are two main ideas underlying the SVM for discriminant-type problems. The first is an optimum linear separating hyperplane that separates the data patterns. The second is the use of kernel functions to convert the original non-linear data patterns into the format that is linearly separable in a high-dimensional feature space. In this paper, an overview of the SVM, both one-class and two-class SVM methods, is first presented followed by its use in landslide susceptibility mapping. A study area was selected from the natural terrain of Hong Kong, and slope angle, slope aspect, elevation, profile curvature of slope, lithology, vegetation cover and topographic wetness index (TWI) were used as environmental parameters which influence the occurrence of landslides. One-class and two-class SVM models were trained and then used to map landslide susceptibility respectively. The resulting susceptibility maps obtained by the methods were compared to that obtained by the logistic regression (LR) method. It is concluded that two-class SVM possesses better prediction efficiency than logistic regression and one-class SVM. However, one-class SVM, which only requires failed cases, has an advantage over the other two methods as only "failed" case information is usually available in landslide susceptibility mapping.

  13. Spatial prediction of landslide susceptibility using an adaptive neuro-fuzzy inference system combined with frequency ratio, generalized additive model, and support vector machine techniques

    Science.gov (United States)

    Chen, Wei; Pourghasemi, Hamid Reza; Panahi, Mahdi; Kornejady, Aiding; Wang, Jiale; Xie, Xiaoshen; Cao, Shubo

    2017-11-01

    The spatial prediction of landslide susceptibility is an important prerequisite for the analysis of landslide hazards and risks in any area. This research uses three data mining techniques, such as an adaptive neuro-fuzzy inference system combined with frequency ratio (ANFIS-FR), a generalized additive model (GAM), and a support vector machine (SVM), for landslide susceptibility mapping in Hanyuan County, China. In the first step, in accordance with a review of the previous literature, twelve conditioning factors, including slope aspect, altitude, slope angle, topographic wetness index (TWI), plan curvature, profile curvature, distance to rivers, distance to faults, distance to roads, land use, normalized difference vegetation index (NDVI), and lithology, were selected. In the second step, a collinearity test and correlation analysis between the conditioning factors and landslides were applied. In the third step, we used three advanced methods, namely, ANFIS-FR, GAM, and SVM, for landslide susceptibility modeling. Subsequently, the results of their accuracy were validated using a receiver operating characteristic curve. The results showed that all three models have good prediction capabilities, while the SVM model has the highest prediction rate of 0.875, followed by the ANFIS-FR and GAM models with prediction rates of 0.851 and 0.846, respectively. Thus, the landslide susceptibility maps produced in the study area can be applied for management of hazards and risks in landslide-prone Hanyuan County.

  14. Cloud GIS Based Watershed Management

    Science.gov (United States)

    Bediroğlu, G.; Colak, H. E.

    2017-11-01

    In this study, we generated a Cloud GIS based watershed management system with using Cloud Computing architecture. Cloud GIS is used as SAAS (Software as a Service) and DAAS (Data as a Service). We applied GIS analysis on cloud in terms of testing SAAS and deployed GIS datasets on cloud in terms of DAAS. We used Hybrid cloud computing model in manner of using ready web based mapping services hosted on cloud (World Topology, Satellite Imageries). We uploaded to system after creating geodatabases including Hydrology (Rivers, Lakes), Soil Maps, Climate Maps, Rain Maps, Geology and Land Use. Watershed of study area has been determined on cloud using ready-hosted topology maps. After uploading all the datasets to systems, we have applied various GIS analysis and queries. Results shown that Cloud GIS technology brings velocity and efficiency for watershed management studies. Besides this, system can be easily implemented for similar land analysis and management studies.

  15. Automatic delineation of geomorphological slope units with r.slopeunits v1.0 and their optimization for landslide susceptibility modeling

    Directory of Open Access Journals (Sweden)

    M. Alvioli

    2016-11-01

    Full Text Available Automatic subdivision of landscapes into terrain units remains a challenge. Slope units are terrain units bounded by drainage and divide lines, but their use in hydrological and geomorphological studies is limited because of the lack of reliable software for their automatic delineation. We present the r.slopeunits software for the automatic delineation of slope units, given a digital elevation model and a few input parameters. We further propose an approach for the selection of optimal parameters controlling the terrain subdivision for landslide susceptibility modeling. We tested the software and the optimization approach in central Italy, where terrain, landslide, and geo-environmental information was available. The software was capable of capturing the variability of the landscape and partitioning the study area into slope units suited for landslide susceptibility modeling and zonation. We expect r.slopeunits to be used in different physiographical settings for the production of reliable and reproducible landslide susceptibility zonations.

  16. The variability of root cohesion as an influence on shallow landslide susceptibility in the Oregon Coast Range

    Science.gov (United States)

    Schmidt, K.M.; Roering, J.J.; Stock, J.D.; Dietrich, W.E.; Montgomery, D.R.; Schaub, T.

    2001-01-01

    Decades of quantitative measurement indicate that roots can mechanically reinforce shallow soils in forested landscapes. Forests, however, have variations in vegetation species and age which can dominate the local stability of landslide-initiation sites. To assess the influence of this variability on root cohesion we examined scarps of landslides triggered during large storms in February and November of 1996 in the Oregon Coast Range and hand-dug soil pits on stable ground. At 41 sites we estimated the cohesive reinforcement to soil due to roots by determining the tensile strength, species, depth, orientation, relative health, and the density of roots ???1 mm in diameter within a measured soil area. We found that median lateral root cohesion ranges from 6.8-23.2 kPa in industrial forests with significant understory and deciduous vegetation to 25.6-94.3 kPa in natural forests dominated by coniferous vegetation. Lateral root cohesion in clearcuts is uniformly ???10 kPa. Some 100-year-old industrial forests have species compositions, lateral root cohesion, and root diameters that more closely resemble 10-year-old clearcuts than natural forests. As such, the influence of root cohesion variability on landslide susceptibility cannot be determined solely from broad age classifications or extrapolated from the presence of one species of vegetation. Furthermore, the anthropogenic disturbance legacy modifies root cohesion for at least a century and should be considered when comparing contemporary landslide rates from industrial forests with geologic background rates.

  17. A new-old approach for shallow landslide analysis and susceptibility zoning in fine-grained weathered soils of southern Italy

    Science.gov (United States)

    Cascini, Leonardo; Ciurleo, Mariantonietta; Di Nocera, Silvio; Gullà, Giovanni

    2015-07-01

    Rainfall-induced shallow landslides involve several geo-environmental contexts and different types of soils. In clayey soils, they affect the most superficial layer, which is generally constituted by physically weathered soils characterised by a diffuse pattern of cracks. This type of landslide most commonly occurs in the form of multiple-occurrence landslide phenomena simultaneously involving large areas and thus has several consequences in terms of environmental and economic damage. Indeed, landslide susceptibility zoning is a relevant issue for land use planning and/or design purposes. This study proposes a multi-scale approach to reach this goal. The proposed approach is tested and validated over an area in southern Italy affected by widespread shallow landslides that can be classified as earth slides and earth slide-flows. Specifically, by moving from a small (1:100,000) to a medium scale (1:25,000), with the aid of heuristic and statistical methods, the approach identifies the main factors leading to landslide occurrence and effectively detects the areas potentially affected by these phenomena. Finally, at a larger scale (1:5000), deterministic methods, i.e., physically based models (TRIGRS and TRIGRS-unsaturated), allow quantitative landslide susceptibility assessment, starting from sample areas representative of those that can be affected by shallow landslides. Considering the reliability of the obtained results, the proposed approach seems useful for analysing other case studies in similar geological contexts.

  18. A comparative study on the predictive ability of the decision tree, support vector machine and neuro-fuzzy models in landslide susceptibility mapping using GIS

    Science.gov (United States)

    Pradhan, Biswajeet

    2013-02-01

    The purpose of the present study is to compare the prediction performances of three different approaches such as decision tree (DT), support vector machine (SVM) and adaptive neuro-fuzzy inference system (ANFIS) for landslide susceptibility mapping at Penang Hill area, Malaysia. The necessary input parameters for the landslide susceptibility assessments were obtained from various sources. At first, landslide locations were identified by aerial photographs and field surveys and a total of 113 landslide locations were constructed. The study area contains 340,608 pixels while total 8403 pixels include landslides. The landslide inventory was randomly partitioned into two subsets: (1) part 1 that contains 50% (4000 landslide grid cells) was used in the training phase of the models; (2) part 2 is a validation dataset 50% (4000 landslide grid cells) for validation of three models and to confirm its accuracy. The digitally processed images of input parameters were combined in GIS. Finally, landslide susceptibility maps were produced, and the performances were assessed and discussed. Total fifteen landslide susceptibility maps were produced using DT, SVM and ANFIS based models, and the resultant maps were validated using the landslide locations. Prediction performances of these maps were checked by receiver operating characteristics (ROC) by using both success rate curve and prediction rate curve. The validation results showed that, area under the ROC curve for the fifteen models produced using DT, SVM and ANFIS varied from 0.8204 to 0.9421 for success rate curve and 0.7580 to 0.8307 for prediction rate curves, respectively. Moreover, the prediction curves revealed that model 5 of DT has slightly higher prediction performance (83.07), whereas the success rate showed that model 5 of ANFIS has better prediction (94.21) capability among all models. The results of this study showed that landslide susceptibility mapping in the Penang Hill area using the three approaches (e

  19. Geographic Information Systems and geomorphological mapping applied to landslide inventory and susceptibility mapping in El Estado river, Pico de Orizaba, Mexico

    Directory of Open Access Journals (Sweden)

    José Fernando Aceves Quesada

    2016-11-01

    Full Text Available With the aim of raising awareness on the prevention of landslide disasters, this work develops a methodology that incorporates geomorphological mapping into the mapping of landslide susceptibility using Geographic Information Systems (GIS and Multiple Logistic Regression (MLR. In Mexico, some studies have evaluated the stability of hillsides using GIS. However, these studies set a general framework and guidance (that includes basic concepts and explanations of landslide classification, triggering mechanisms, criteria, considerations, and analysis for landslide hazard reconnaissance, etc. for preparing a landslide atlas at state and city levels. So far, these have not developed a practical and standardized approach incorporating geomorphological maps into the landslide inventory using GIS. This paper describes the analysis conducted to develop an analytical technique and morphometric analysis for a multi-temporal landslide inventory. Three data management levels are used to create GIS thematic layers. For the first level, analogue topographic, geological, land-use, and climate paper are converted to raster format, georeferenced, and incorporated as GIS thematic layers. For the second level, five layers are derived from topographic elevation data: slope angles, slope curvature, contributing area, flow direction, and saturation. For the third level, thematic maps are derived from the previous two levels of data: a hypsometric map (heuristically classified to highlight altimetric levels, a reclassified slope map (allowing to highlight differences in relief , and a morphographic map (derived from a heuristic reclassification of the slope map to highlight volcanic landforms. The theoretical aspects of geomorphological mapping contribute to set the conceptual basis to support landslide mapping. The GIS thematic layers provide context and establish an overall characterization of landslide processes within the watershed. Through the retrieval and on

  20. Using online database for landslide susceptibility assessment with an example from the Veneto Region (north-eastern Italy).

    Science.gov (United States)

    Floris, Mario; Squarzoni, Cristina; Zorzi, Luca; D'Alpaos, Andrea; Iafelice, Maria

    2010-05-01

    Landslide susceptibility maps describe landslide-prone areas by the spatial correlation between landslides and related factors, derived from different kinds of datasets: geological, geotechnical and geomechanical maps, hydrogeological maps, landslides maps, vector and raster terrain data, real-time inclinometer and pore pressure data. In the last decade, thanks to the increasing use of web-based tools for management, sharing and communication of territorial information, many Web-based Geographical Information Systems (WebGIS) were created by local governments or nations, University and Research Centres. Nowadays there is a strong proliferation of geological WebGIS or GeoBrowser, allowing free download of spatial information. There are global Cartographical Portals that provide a free download of DTM and other vector data related to the whole planet (http://www.webgis.com). At major scale, there are WebGIS regarding entire nation (http://www.agiweb.org), or specific region of a country (http://www.mrt.tas.gov.au), or single municipality (http://sitn.ne.ch/). Moreover, portals managed by local government and academic government (http://turtle.ags.gov.ab.ca/Peace_River/Site/) or by a private agency (http://www.bbt-se.com) are noteworthy. In Italy, the first national projects for the creation of WebGIS and web-based databases begun during the 1980s, and evolved, through years, to the present number of different WebGIS, which have different territorial extensions: national (Italian National Cartographical Portal, http://www.pcn.minambiente.it; E-GEO Project, http://www.egeo.unisi.it), interregional (River Tiber Basin Authority, www.abtevere.it ), and regional (Veneto Region, www.regione.veneto.it). In this way we investigated most of the Italian WebGIS in order to verify their geographic range and the availability and quality of data useful for landslide hazard analyses. We noticed a large variability of the accessing information among the different browsers. In

  1. Impacts of Landuse Management and Climate Change on Landslides Susceptibility over the Olympic Peninsula of Washington State

    Science.gov (United States)

    Barik, M. G.; Adam, J. C.

    2009-12-01

    The commercial forests on the western side of the Olympic Mountains in Washington State are a region of steep slopes and high annual rainfall (2500-6000 mm/year) and are therefore highly susceptible to landslides. Potential climatic change (more intense and frequent winter storms) may exacerbate landslide susceptibility unless forest management practices are changed. As this area is a critical habitat for numerous organisms, including salmon, this may result in potentially severe consequences to riparian habitat due to increased sediment loads. Therefore, there is a need to investigate potential forest management plans to promote the economic viability of timber extraction while protecting the natural habitat, particularly in riparian areas. The objective of this study is to predict the long term effects of forest management decisions under projected climate change on slope stability. We applied the physically-based Distributed Hydrology Soil Vegetation Model (DHSVM) with its sediment module to simulate mass wasting and sediment delivery under different vegetation and climate scenarios. Sub-basins were selected and classified according to elevation, slope, land cover and soil type. Various land management practices (such as clear-cutting in riparian areas, logging under short rotations, varying amount of timbers left intact in riparian areas) were applied to each of the selected sub-basins. DHSVM was used to simulate landslide volume, frequency, and sediment loads for each of the land cover applications under various future climate scenarios. We comment on the suitability of various harvesting techniques for different parts of the forest to minimize landslide-induced sediment loading to streams in an altered climate. This approach can be developed as a decision making tool that can be used by forest managers to make long-term planning decisions.

  2. Estimation of the susceptibility of a road network to shallow landslides with the integration of the sediment connectivity

    Directory of Open Access Journals (Sweden)

    M. Bordoni

    2018-06-01

    Full Text Available Landslides cause severe damage to the road network of the hit zone, in terms of both direct (partial or complete destruction of a road or blockages and indirect (traffic restriction or the cut-off of a certain area costs. Thus, the identification of the parts of the road network that are more susceptible to landslides is fundamental to reduce the risk to the population potentially exposed and the financial expense caused by the damage. For these reasons, this paper aimed to develop and test a data-driven model for the identification of road sectors that are susceptible to being hit by shallow landslides triggered in slopes upstream from the infrastructure. This model was based on the Generalized Additive Method, where the function relating predictors and response variable is an empirically fitted smooth function that allows fitting the data in the more likely functional form, considering also non-linear relations. This work also analyzed the importance, on the estimation of the susceptibility, of considering or not the sediment connectivity, which influences the path and the travel distance of the materials mobilized by a slope failure until hitting a potential barrier such as a road. The study was carried out in a catchment of northeastern Oltrepò Pavese (northern Italy, where several shallow landslides affected roads in the last 8 years. The most significant explanatory variables were selected by a random partition of the available dataset in two parts (training and test subsets, 100 times according to a bootstrap procedure. These variables (selected 80 times by the bootstrap procedure were used to build the final susceptibility model, the accuracy of which was estimated through a 100-fold repetition of the holdout method for regression, based on the training and test sets created through the 100 bootstrap model selection. The presented methodology allows the identification, in a robust and reliable way, of the most susceptible road

  3. Landslide Catastrophes and Disaster Risk Reduction: A GIS Framework for Landslide Prevention and Management

    Directory of Open Access Journals (Sweden)

    Xin Wang

    2010-09-01

    Full Text Available As catastrophic phenomena, landslides often cause large-scale socio-economic destruction including loss of life, economic collapse, and human injury. In addition, landslides can impair the functioning of critical infrastructure and destroy cultural heritage and ecological systems. In order to build a more landslide resistant and resilient society, an original GIS-based decision support system is put forth in order to help emergency managers better prepare for and respond to landslide disasters. The GIS-based landslide monitoring and management system includes a Central Repository System (CRS, Disaster Data Processing Modules (DDPM, a Command and Control System (CCS and a Portal Management System (PMS. This architecture provides valuable insights into landslide early warning, landslide risk and vulnerability analyses, and critical infrastructure damage assessments. Finally, internet-based communications are used to support landslide disaster modelling, monitoring and management.

  4. Determination of Areas Susceptible to Landsliding Using Spatial Patterns of Rainfall from Tropical Rainfall Measuring Mission Data, Rio de Janeiro, Brazil

    Directory of Open Access Journals (Sweden)

    Renato Fontes Guimarães

    2017-10-01

    Full Text Available Spatial patterns of shallow landslide initiation reflect both spatial patterns of heavy rainfall and areas susceptible to mass movements. We determine the areas most susceptible to shallow landslide occurrence through the calculation of critical soil cohesion and spatial patterns of rainfall derived from TRMM (Tropical Rainfall Measuring Mission data for Paraty County, State of Rio de Janeiro, Brazil. Our methodology involved: (a creating the digital elevation model (DEM and deriving attributes such as slope and contributing area; (b incorporating spatial patterns of rainfall derived from TRMM into the shallow slope stability model SHALSTAB; and (c quantitative assessment of the correspondence of mapped landslide scars to areas predicted to be most prone to shallow landsliding. We found that around 70% of the landslide scars occurred in less than 10% of the study area identified as potentially unstable. The greatest concentration of landslides occurred in areas where the root strength of vegetation is an important contribution to slope stability in regions of orographically-enhanced rainfall on the coastal topographic flank. This approach helps quantify landslide hazards in areas with similar geomorphological characteristics, but different spatial patterns of rainfall.

  5. A Combination of Geographically Weighted Regression, Particle Swarm Optimization and Support Vector Machine for Landslide Susceptibility Mapping: A Case Study at Wanzhou in the Three Gorges Area, China

    Directory of Open Access Journals (Sweden)

    Xianyu Yu

    2016-05-01

    Full Text Available In this study, a novel coupling model for landslide susceptibility mapping is presented. In practice, environmental factors may have different impacts at a local scale in study areas. To provide better predictions, a geographically weighted regression (GWR technique is firstly used in our method to segment study areas into a series of prediction regions with appropriate sizes. Meanwhile, a support vector machine (SVM classifier is exploited in each prediction region for landslide susceptibility mapping. To further improve the prediction performance, the particle swarm optimization (PSO algorithm is used in the prediction regions to obtain optimal parameters for the SVM classifier. To evaluate the prediction performance of our model, several SVM-based prediction models are utilized for comparison on a study area of the Wanzhou district in the Three Gorges Reservoir. Experimental results, based on three objective quantitative measures and visual qualitative evaluation, indicate that our model can achieve better prediction accuracies and is more effective for landslide susceptibility mapping. For instance, our model can achieve an overall prediction accuracy of 91.10%, which is 7.8%–19.1% higher than the traditional SVM-based models. In addition, the obtained landslide susceptibility map by our model can demonstrate an intensive correlation between the classified very high-susceptibility zone and the previously investigated landslides.

  6. A Combination of Geographically Weighted Regression, Particle Swarm Optimization and Support Vector Machine for Landslide Susceptibility Mapping: A Case Study at Wanzhou in the Three Gorges Area, China.

    Science.gov (United States)

    Yu, Xianyu; Wang, Yi; Niu, Ruiqing; Hu, Youjian

    2016-05-11

    In this study, a novel coupling model for landslide susceptibility mapping is presented. In practice, environmental factors may have different impacts at a local scale in study areas. To provide better predictions, a geographically weighted regression (GWR) technique is firstly used in our method to segment study areas into a series of prediction regions with appropriate sizes. Meanwhile, a support vector machine (SVM) classifier is exploited in each prediction region for landslide susceptibility mapping. To further improve the prediction performance, the particle swarm optimization (PSO) algorithm is used in the prediction regions to obtain optimal parameters for the SVM classifier. To evaluate the prediction performance of our model, several SVM-based prediction models are utilized for comparison on a study area of the Wanzhou district in the Three Gorges Reservoir. Experimental results, based on three objective quantitative measures and visual qualitative evaluation, indicate that our model can achieve better prediction accuracies and is more effective for landslide susceptibility mapping. For instance, our model can achieve an overall prediction accuracy of 91.10%, which is 7.8%-19.1% higher than the traditional SVM-based models. In addition, the obtained landslide susceptibility map by our model can demonstrate an intensive correlation between the classified very high-susceptibility zone and the previously investigated landslides.

  7. The Pliocene Horcón Formation, Central Chile: a case study of earthquake-induced landslide susceptibility

    Science.gov (United States)

    Valdivia, D.; Elgueta, S.; Hodgkin, A.; Marquardt, C.; del Valle, F.; Yáñez Morroni, G.

    2017-12-01

    Stability slope analysis is typically focused on modeling using cohesion and friction angle parameters but in earthquake-induced landslides, susceptibility is correlated more to lithological and stratigraphic parameters. In sedimentary deposits whose cohesion and diagenesis are very low, the risk of landslides increases. The Horcón Formation, which crops out continuously along cliffs in Central Chile between 32.5° and 33°S, is a Miocene-Pliocene well preserved, horizontally stratified unit composed of marine strata which overlies Paleozoic-Mesozoic igneous basement. During the Quaternary, the sequence was tectonically uplifted 80 meters and covered by unconsolidated eolian deposits. Given that Seismotectonic and Barrier-Asperity models suggest the occurrence of a forthcoming megathrust earthquake in a segment which includes this area, the Horcón Formation constitutes a good case study to characterize the susceptibility of this type of sediment for mass movements triggered by earthquakes. Field mapping, stratigraphic and sedimentological studies, including petrographic analyses to determine lithological composition and paragenesis of diagenetic events, have been carried out along with limited gravimetric profiling and CPTU drill tests. High resolution digital elevation modeling has also been applied. This work has led to the recognition of a shallow marine lithofacies association composed of weakly lithified fossiliferous and bioturbated medium to fine grained litharenite, mudstone, and fine conglomerate. The low grade of diagenesis in the sedimentary deposits was in response to a short period of burial and a subsequent accelerated uplift evidenced along the coast of Chile during the Quaternary. We have generated a predictive model of landslide susceptibility for the Horcón Formation and for the overlying Quaternary eolian deposits incorporating variables such as composition and diagenesis of lithofacies, slope, structures, weathering and landcover. The model

  8. Multi-Collinearity Based Model Selection for Landslide Susceptibility Mapping: A Case Study from Ulus District of Karabuk, Turkey

    Science.gov (United States)

    Sahin, E. K.; Colkesen, I., , Dr; Kavzoglu, T.

    2017-12-01

    Identification of localities prone to landslide areas plays an important role for emergency planning, disaster management and recovery planning. Due to its great importance for disaster management, producing accurate and up-to-date landslide susceptibility maps is essential for hazard mitigation purpose and regional planning. The main objective of the present study was to apply multi-collinearity based model selection approach for the production of a landslide susceptibility map of Ulus district of Karabuk, Turkey. It is a fact that data do not contain enough information to describe the problem under consideration when the factors are highly correlated with each other. In such cases, choosing a subset of the original features will often lead to better performance. This paper presents multi-collinearity based model selection approach to deal with the high correlation within the dataset. Two collinearity diagnostic factors (Tolerance (TOL) and the Variance Inflation Factor (VIF)) are commonly used to identify multi-collinearity. Values of VIF that exceed 10.0 and TOL values less than 1.0 are often regarded as indicating multi-collinearity. Five causative factors (slope length, curvature, plan curvature, profile curvature and topographical roughness index) were found highly correlated with each other among 15 factors available for the study area. As a result, the five correlated factors were removed from the model estimation, and performances of the models including the remaining 10 factors (aspect, drainage density, elevation, lithology, land use/land cover, NDVI, slope, sediment transport index, topographical position index and topographical wetness index) were evaluated using logistic regression. The performance of prediction model constructed with 10 factors was compared to that of 15-factor model. The prediction performance of two susceptibility maps was evaluated by overall accuracy and the area under the ROC curve (AUC) values. Results showed that overall

  9. Landslide Susceptibility Assessment in the Central Part of Republic of Moldova

    Science.gov (United States)

    Ercanoglu, Murat; Boboc, Nicolae; Sirodoev, Igor; Ahmet Temiz, F.; Sirodoev, Ghenadi

    2010-05-01

    There has been an increasing interest in natural hazard assessments within the scientific community, particularly in the last two decades. In other respect, there is also a dramatically rising trend in the number of natural hazards. Growing population and expansion of settlements and lifelines over hazardous areas have largely increased the impact of natural disasters both in industrialized and developing countries. Furthermore, natural disasters such as earthquakes, landslides, floods have dramatic effects on human life, infrastructures, environment, and so on. Landslides, one of the most destructive natural hazards, constitute a major geological hazard throughout the world, like in Turkey and Moldova. There are a lot of regions affected by landslides in Turkey (particularly the West, Middle and East Black Sea Region) and Moldova (e.g.: area between Nisporeni, Calarasi, Balti, Western Rezina District, Codri Hills in Central Moldova etc.), and consequences of landslides are of great importance in the two countries. In the last 50 years' period, only the economic loss due to landslides in Turkey is estimated about 5 billion , and 12.5 % of the whole settlement areas, including big and populated cities, are facing landslide threat. Similar to Turkey, there are about 16000 areas affected by landslides in Moldova. In February-March, 1998 the intensity of landslides in the central part of Moldova, including Chisinau, considerably increased. In total, 357 private households involving 1400 people were affected, 214 houses were destroyed, and 137 were damaged. The total national damage accounted for 44.3 million Lei. At present on Moldavian territory, there are more than 17000 landslides of various types. These landslides are mostly located within Central Moldavian heights, one of the most complicated geomorphologic structure and territory's fragmentation. Among major landslide triggering factors, in addition to natural ones, one should also consider the anthropogenic

  10. Landslide susceptibility assessment by using a neuro-fuzzy model: a case study in the Rupestrian heritage rich area of Matera

    Science.gov (United States)

    Sdao, F.; Lioi, D. S.; Pascale, S.; Caniani, D.; Mancini, I. M.

    2013-02-01

    The complete assessment of landslide susceptibility needs uniformly distributed detailed information on the territory. This information, which is related to the temporal occurrence of landslide phenomena and their causes, is often fragmented and heterogeneous. The present study evaluates the landslide susceptibility map of the Natural Archaeological Park of Matera (Southern Italy) (Sassi and area Rupestrian Churches sites). The assessment of the degree of "spatial hazard" or "susceptibility" was carried out by the spatial prediction regardless of the return time of the events. The evaluation model for the susceptibility presented in this paper is very focused on the use of innovative techniques of artificial intelligence such as Neural Network, Fuzzy Logic and Neuro-fuzzy Network. The method described in this paper is a novel technique based on a neuro-fuzzy system. It is able to train data like neural network and it is able to shape and control uncertain and complex systems like a fuzzy system. This methodology allows us to derive susceptibility maps of the study area. These data are obtained from thematic maps representing the parameters responsible for the instability of the slopes. The parameters used in the analysis are: plan curvature, elevation (DEM), angle and aspect of the slope, lithology, fracture density, kinematic hazard index of planar and wedge sliding and toppling. Moreover, this method is characterized by the network training which uses a training matrix, consisting of input and output training data, which determine the landslide susceptibility. The neuro-fuzzy method was integrated to a sensitivity analysis in order to overcome the uncertainty linked to the used membership functions. The method was compared to the landslide inventory map and was validated by applying three methods: a ROC (Receiver Operating Characteristic) analysis, a confusion matrix and a SCAI method. The developed neuro-fuzzy method showed a good performance in the

  11. A comparative study of frequency ratio, weights of evidence and logistic regression methods for landslide susceptibility mapping: Sultan Mountains, SW Turkey

    Science.gov (United States)

    Ozdemir, Adnan; Altural, Tolga

    2013-03-01

    This study evaluated and compared landslide susceptibility maps produced with three different methods, frequency ratio, weights of evidence, and logistic regression, by using validation datasets. The field surveys performed as part of this investigation mapped the locations of 90 landslides that had been identified in the Sultan Mountains of south-western Turkey. The landslide influence parameters used for this study are geology, relative permeability, land use/land cover, precipitation, elevation, slope, aspect, total curvature, plan curvature, profile curvature, wetness index, stream power index, sediment transportation capacity index, distance to drainage, distance to fault, drainage density, fault density, and spring density maps. The relationships between landslide distributions and these parameters were analysed using the three methods, and the results of these methods were then used to calculate the landslide susceptibility of the entire study area. The accuracy of the final landslide susceptibility maps was evaluated based on the landslides observed during the fieldwork, and the accuracy of the models was evaluated by calculating each model's relative operating characteristic curve. The predictive capability of each model was determined from the area under the relative operating characteristic curve and the areas under the curves obtained using the frequency ratio, logistic regression, and weights of evidence methods are 0.976, 0.952, and 0.937, respectively. These results indicate that the frequency ratio and weights of evidence models are relatively good estimators of landslide susceptibility in the study area. Specifically, the results of the correlation analysis show a high correlation between the frequency ratio and weights of evidence results, and the frequency ratio and logistic regression methods exhibit correlation coefficients of 0.771 and 0.727, respectively. The frequency ratio model is simple, and its input, calculation and output processes are

  12. Comparison and applicability of landslide susceptibility models based on landslide ratio-based logistic regression, frequency ratio, weight of evidence, and instability index methods in an extreme rainfall event

    Science.gov (United States)

    Wu, Chunhung

    2016-04-01

    Few researches have discussed about the applicability of applying the statistical landslide susceptibility (LS) model for extreme rainfall-induced landslide events. The researches focuses on the comparison and applicability of LS models based on four methods, including landslide ratio-based logistic regression (LRBLR), frequency ratio (FR), weight of evidence (WOE), and instability index (II) methods, in an extreme rainfall-induced landslide cases. The landslide inventory in the Chishan river watershed, Southwestern Taiwan, after 2009 Typhoon Morakot is the main materials in this research. The Chishan river watershed is a tributary watershed of Kaoping river watershed, which is a landslide- and erosion-prone watershed with the annual average suspended load of 3.6×107 MT/yr (ranks 11th in the world). Typhoon Morakot struck Southern Taiwan from Aug. 6-10 in 2009 and dumped nearly 2,000 mm of rainfall in the Chishan river watershed. The 24-hour, 48-hour, and 72-hours accumulated rainfall in the Chishan river watershed exceeded the 200-year return period accumulated rainfall. 2,389 landslide polygons in the Chishan river watershed were extracted from SPOT 5 images after 2009 Typhoon Morakot. The total landslide area is around 33.5 km2, equals to the landslide ratio of 4.1%. The main landslide types based on Varnes' (1978) classification are rotational and translational slides. The two characteristics of extreme rainfall-induced landslide event are dense landslide distribution and large occupation of downslope landslide areas owing to headward erosion and bank erosion in the flooding processes. The area of downslope landslide in the Chishan river watershed after 2009 Typhoon Morakot is 3.2 times higher than that of upslope landslide areas. The prediction accuracy of LS models based on LRBLR, FR, WOE, and II methods have been proven over 70%. The model performance and applicability of four models in a landslide-prone watershed with dense distribution of rainfall

  13. Comparison between monitored and modeled pore water pressure and safety factor in a slope susceptible to shallow landslides

    Science.gov (United States)

    Bordoni, Massimiliano; Meisina, Claudia; Zizioli, Davide; Valentino, Roberto; Bittelli, Marco; Chersich, Silvia

    2014-05-01

    Shallow landslides can be defined as slope movements affecting superficial deposits of small thicknesses which are usually triggered due to extreme rainfall events, also very concentrated in time. Shallow landslides are hazardous phenomena: in particular, if they happen close to urbanized areas they could cause significant damages to cultivations, structures, infrastructures and, sometimes, human losses. The triggering mechanism of rainfall-induced shallow landslides is strictly linked with the hydrological and mechanical responses of usually unsaturated soils to rainfall events. For this reason, it is fundamental knowing the intrinsic hydro-mechanical properties of the soils in order to assess both susceptibility and hazard of shallow landslide and to develop early-warning systems at large scale. The hydrological data collected by a 20 months monitoring on a slope susceptible to shallow landslides in an area of the North -Eastern Oltrepo Pavese (Northern Apennines, Italy) were used to identify the hydrological behaviors of the investigated soils towards rainfall events. Field conditions under different rainfall trends have also been modeled by using both hydrological and physically-based stability models for the evaluation of the slope safety factor . The main objectives of this research are: (a) to compare the field measured pore water pressures at different depths with results of hydrological models, in order to evaluate the efficiency of the tested models and to determine how precipitations affect pore pressure development; (b) to compare the time trends of the safety factor that have been obtained by applying different stability models; (c) to evaluate, through a sensitivity analysis, the effects of soil hydrological properties on modeling pore water pressure and safety factor. The test site slope where field measurements were acquired is representative of other sites in Northern Apennines affected by shallow landslides and is characterized by medium

  14. Landslide susceptibility assessment using Spatial Analysis and GIS modeling in Cluj-Napoca Metropolitan Area, Romania

    Directory of Open Access Journals (Sweden)

    Bogdan Eugen Dolean

    2017-06-01

    Full Text Available In Romania, landslides together with the multitude geomorphological processes linked to them are some of the most common hazards which manifested in vulnerable areas with important human activities can induce many negative effects. From this perspective, identifying the areas affected by landslides, based on GIS spatial analysis models and statistical methods, is a subject frequently discussed in the national and international literature. This research was focused on the methods and practices of GIS spatial analysis, with a target of creating a complex model and a viable methodology of assessment the probability of occurrence of landslides, applicable within any territory. The study was based on the identification and analysis in a bivariate systemic manner of the numerous factors involved in the production of landslides, such as topography, morphology, hydrography, geological, lithology, weather, land use. The area in which the analysis has been conducted, The Metropolitan Area of Cluj-Napoca, was chosen due to the exacerbated urbanization of the recent years, coupled with a massive increase in the number of inhabitants, thus being a space of socioeconomic importance and a real challenge regarding spatial planning. Applying the model in this area has generated relatively good results, with a power of predictability of over 80%, measured in landslides sample areas used for the validation of the results, fact which attest the viability of the model and the fact that the model can be used in different areas with related morphometric and environmental characteristics.

  15. Landslide disaster avoidance: learning from Leyte

    Science.gov (United States)

    Davies, T. R.

    2006-12-01

    On 17 February 2006 a gigantic rockslide triggered a debris avalanche that overran the barangay Guinsaugon, St. Bernard in Southern Leyte Province, Philippines, burying 154 victims, with 990 missing including 246 school children. Even with satellite imagery, GIS-based landslide susceptibility modelling and real-time meteorological and seismic data analysis, scientific prediction of every potentially fatal landslide is not possible in most parts of the world. This is particular the case in steep, unstable, densely-populated country in which heavy rain is common. So how can further events of this type be prevented from turning into disasters? A number of precursory phenomena were noted by local inhabitants at Guinsaugon: a crack around the slope that failed was noticed in May 2005; coconut trees near the northern foot of the landslide scarp began to lean increasingly in the down-slope direction in December 2005; a slope around the northern edge of the 17 February 2006 landslide scarp failed on December 17, 2005; in the 9 days prior to the rockslide, 640 mm of rain fell; 450 mm in a 3-day period. Such phenomena are commonly reported by local inhabitants before large landslides (e.g. Elm, Mayunmarca, and many others). In many cases, therefore, it is in principle possible for local people to avoid the consequences of the landslide if they know enough to act appropriately in response to the precursory phenomena. For this possibility to be realized, appropriate information must be provided to and assimilated by the local population. Useful ways of achieving this include pamphlets, video, TV and radio programs and visits from civil defence personnel. The information must be properly presented; scientific language will be ineffective. A communication pyramid, leading from government agencies to local leaders, can facilitate the rapid availability of the information to all potentially susceptible communities. If science can determine those areas not vulnerable to landslide

  16. Factors selection in landslide susceptibility modelling on large scale following the gis matrix method: application to the river Beiro basin (Spain

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    D. Costanzo

    2012-02-01

    Full Text Available A procedure to select the controlling factors connected to the slope instability has been defined. It allowed us to assess the landslide susceptibility in the Rio Beiro basin (about 10 km2 over the northeastern area of the city of Granada (Spain. Field and remote (Google EarthTM recognition techniques allowed us to generate a landslide inventory consisting in 127 phenomena. To discriminate between stable and unstable conditions, a diagnostic area had been chosen as the one limited to the crown and the toe of the scarp of the landslide. 15 controlling or determining factors have been defined considering topographic, geologic, geomorphologic and pedologic available data. Univariate tests, using both association coefficients and validation results of single-variable susceptibility models, allowed us to select the best predictors, which were combined for the unique conditions analysis. For each of the five recognised landslide typologies, susceptibility maps for the best models were prepared. In order to verify both the goodness of fit and the prediction skill of the susceptibility models, two different validation procedures were applied and compared. Both procedures are based on a random partition of the landslide archive for producing a test and a training subset. The first method is based on the analysis of the shape of the success and prediction rate curves, which are quantitatively analysed exploiting two morphometric indexes. The second method is based on the analysis of the degree of fit, by considering the relative error between the intersected target landslides by each of the different susceptibility classes in which the study area was partitioned. Both the validation procedures confirmed a very good predictive performance of the susceptibility models and of the actual procedure followed to select the controlling factors.

  17. Integrating the effects of forest cover on slope stability in a deterministic landslide susceptibility model (TRIGRS 2.0)

    Science.gov (United States)

    Zieher, T.; Rutzinger, M.; Bremer, M.; Meissl, G.; Geitner, C.

    2014-12-01

    The potentially stabilizing effects of forest cover in respect of slope stability have been the subject of many studies in the recent past. Hence, the effects of trees are also considered in many deterministic landslide susceptibility models. TRIGRS 2.0 (Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability; USGS) is a dynamic, physically-based model designed to estimate shallow landslide susceptibility in space and time. In the original version the effects of forest cover are not considered. As for further studies in Vorarlberg (Austria) TRIGRS 2.0 is intended to be applied in selected catchments that are densely forested, the effects of trees on slope stability were implemented in the model. Besides hydrological impacts such as interception or transpiration by tree canopies and stems, root cohesion directly influences the stability of slopes especially in case of shallow landslides while the additional weight superimposed by trees is of minor relevance. Detailed data on tree positions and further attributes such as tree height and diameter at breast height were derived throughout the study area (52 km²) from high-resolution airborne laser scanning data. Different scenarios were computed for spruce (Picea abies) in the study area. Root cohesion was estimated area-wide based on published correlations between root reinforcement and distance to tree stems depending on the stem diameter at breast height. In order to account for decreasing root cohesion with depth an exponential distribution was assumed and implemented in the model. Preliminary modelling results show that forest cover can have positive effects on slope stability yet strongly depending on tree age and stand structure. This work has been conducted within C3S-ISLS, which is funded by the Austrian Climate and Energy Fund, 5th ACRP Program.

  18. Evaluation of prediction capability, robustness, and sensitivity in non-linear landslide susceptibility models, Guantánamo, Cuba

    Science.gov (United States)

    Melchiorre, C.; Castellanos Abella, E. A.; van Westen, C. J.; Matteucci, M.

    2011-04-01

    This paper describes a procedure for landslide susceptibility assessment based on artificial neural networks, and focuses on the estimation of the prediction capability, robustness, and sensitivity of susceptibility models. The study is carried out in the Guantanamo Province of Cuba, where 186 landslides were mapped using photo-interpretation. Twelve conditioning factors were mapped including geomorphology, geology, soils, landuse, slope angle, slope direction, internal relief, drainage density, distance from roads and faults, rainfall intensity, and ground peak acceleration. A methodology was used that subdivided the database in 3 subsets. A training set was used for updating the weights. A validation set was used to stop the training procedure when the network started losing generalization capability, and a test set was used to calculate the performance of the network. A 10-fold cross-validation was performed in order to show that the results are repeatable. The prediction capability, the robustness analysis, and the sensitivity analysis were tested on 10 mutually exclusive datasets. The results show that by means of artificial neural networks it is possible to obtain models with high prediction capability and high robustness, and that an exploration of the effect of the individual variables is possible, even if they are considered as a black-box model.

  19. APPLICATION OF LiDAR DATE TO ASSESS THE LANDSLIDE SUSCEPTIBILITY MAP USING WEIGHTS OF EVIDENCE METHOD – AN EXAMPLE FROM PODHALE REGION (SOUTHERN POLAND

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    M. Kamiński

    2016-06-01

    Full Text Available Podhale is a region in southern Poland, which is the northernmost part of the Central Carpathian Mountains. It is characterized by the presence of a large number of landslides that threaten the local infrastructure. In an article presents application of LiDAR data and geostatistical methods to assess landslides susceptibility map. Landslide inventory map were performed using LiDAR data and field work. The Weights of Evidence method was applied to assess landslides susceptibility map. Used factors for modeling: slope gradient, slope aspect, elevation, drainage density, faults density, lithology and curvature. All maps were subdivided into different classes. Then were converted to grid format in the ArcGIS 10.0. The conditional independence test was carried out to determine factors that are conditionally independent of each other with landslides. As a result, chi-square test for further GIS analysis used only five factors: slope gradient, slope aspect, elevation, drainage density and lithology. The final prediction results, it is concluded that the susceptibility map gives useful information both on present instability of the area and its possible future evolution in agreement with the morphological evolution of the area.

  20. The Rock Engineering System (RES) applied to landslide susceptibility zonation of the northeastern flank of Etna: methodological approach and results

    Science.gov (United States)

    Apuani, Tiziana; Corazzato, Claudia

    2015-04-01

    Ground deformations in the northeastern flank of Etna are well known. Despite only a few landslide events have been documented, these have significantly involved and damaged lifelines and buildings. These events are mainly related to the activity of the volcano-tectonic structures and associated seismicity, as in the case of the 2002 reactivation of the Presa landslide during an increased activity of the Pernicana fault system. In order to highlight the areal distribution of potentially unstable slopes based on a detailed, site-specific study of the factors responsible for landslide, and to ultimately contribute to risk management, a landslide susceptibility analysis of the northeastern flank of Etna in the Pernicana area was carried out, and a susceptibility map at 1:10.000 scale was produced, extending over an area of 168 km2. Different methods are proposed in the literature to obtain the regional distribution of potentially unstable slopes, depending on the problem scale, the slope dynamic evolution in the geological context, and the availability of data. Among semi-quantitative approaches, the present research combines the Rock Engineering System (RES) methodology with parameter zonation mapping in a GIS environment. The RES method represents a structured approach to manage a high number of interacting factors involved in the instability problem. A numerically coded, site-specific interaction matrix (IM) analyzes the cause-effect relationship in these factors, and calculates the degree of interactivity of each parameter, normalized by the overall interactivity of the system (weight factor). In the specific Etna case, the considered parameters are: slope attitude, lithotechnical properties (lithology, structural complexity, soil and rock mass quality), land use, tectonic structures, seismic activity (horizontal acceleration) and hydrogeological conditions (groundwater and drainage). Thematic maps are prepared at 1:10.000 scale for each of these parameters, and

  1. Presence-only approach to assess landslide triggering-thickness susceptibility. A test for the Mili catchment (North-Eastern Sicily, Italy)

    Science.gov (United States)

    Lombardo, Luigi; Fubelli, Giandomenico; Amato, Gabriele; Bonasera, Mauro; Hochschild, Volker; Rotigliano, Edoardo

    2015-04-01

    This study aims at comparing the performances of a presence only approach, namely Maximum Entropy, in assessing landslide triggering-thickness susceptibility within the Mili catchment, located in the north-eastern Sicily, Italy. This catchment has been recently exposed to three main meteorological extreme events, resulting in the activation of multiple fast landslides, which occurred on the 1st October 2009, 10th March 2010 and 1st March 2011. Differently from the 2009 event, which only marginally hit the catchment, the 2010 and 2011 storms fully involved the area of the Mili catchment. Detailed field data was collected to associate the thickness of mobilised materials at the triggering zone to each mass movement within the catchment. This information has been used to model the landslide susceptibility for two classes of processes clustered into shallow failures for maximum depths of 0.5m and deep ones in case of values equal or greater than 0.5m. As the authors believed that the peculiar geomorphometry of this narrow and steep catchment played a fundamental role in generating two distinct patterns of landslide thicknesses during the initiation phase, a HRDEM was used to extract topographic attributes to express near-triggering geomorphological conditions. On the other hand, medium resolution vegetation indexes derived from ASTER scenes were used as explanatory variables pertaining to a wider spatial neighbourhood, whilst a revised geological map, the land use from CORINE and a tectonic map were used to convey an even wider area connected to the slope instability. The choice of a presence-only approach allowed to effectively discriminate between the two types of landslide thicknesses at the triggering zone, producing outstanding prediction skills associated with relatively low variances across a set of 20 randomly generated replicates. The validation phase produced indeed average AUC values of 0.91 with a standard deviation of 0.03 for both the modelled landslide

  2. Shallow landslide stability computation using a distributed transient response model for susceptibility assessment and validation. A case study from Ribeira Quente valley (S. Miguel island, Azores)

    Science.gov (United States)

    Amaral, P.; Marques, R.; Zêzere, J. L.; Marques, F.; Queiroz, G.

    2009-04-01

    In the last 15 years, several heavy rainstorms have occurred in Povoação County (S. Miguel Island, Azores), namely in the Ribeira Quente Valley. These rainfall events have triggered hundreds of shallow landslides that killed tens of people and have been responsible for direct and indirect damages amounting to tens of millions of Euros. On the 6th March 2005 an intense rainfall episode, up to 160 mm of rain in less than 24 h, triggered several shallow landslides that caused 3 victims and damaged/blocked roads. The Ribeira Quente Valley has an area of about 9.5 km2 and is mainly constituted by pyroclastic materials (pumice ash and lapilli), that were produced by the Furnas Volcano explosive eruptions. To provide an assessment of slope-failure conditions for the 6th March 2005 rainfall event, it was applied a distributed transient response model for slope stability analysis. The adopted methodology is a modified version of Iversońs (2000) transient response model, which couple an infinite slope stability analysis with an analytic solution of the Richard's equation for vertical water infiltration in quasi-saturated soil. The validation was made on two different scales: (1) at a slope scale, using two distinct test sites where landslides were triggered; and (2) at the basin scale, using the entire landslide database and generalizing the modeling input parameters for the regional spatialization of results. At the slope scale, the obtained results were very accurate, and it was possible to predict the precise time of the slope failures. At the basin scale, the obtained results were very conservative, even though the model predicted all the observed landslide locations, in the 23.7% of the area classified as untable at the time of the slope failures. This methodology revealed to be a reasonable tool for landslide forecast for both temporal and spatial distributions, on both slope and regional scales. In the future, the model components will be integrated into a GIS

  3. Comparative study of landslides susceptibility mapping methods: Multi-Criteria Decision Making (MCDM) and Artificial Neural Network (ANN)

    Science.gov (United States)

    Salleh, S. A.; Rahman, A. S. A. Abd; Othman, A. N.; Mohd, W. M. N. Wan

    2018-02-01

    As different approach produces different results, it is crucial to determine the methods that are accurate in order to perform analysis towards the event. This research aim is to compare the Rank Reciprocal (MCDM) and Artificial Neural Network (ANN) analysis techniques in determining susceptible zones of landslide hazard. The study is based on data obtained from various sources such as local authority; Dewan Bandaraya Kuala Lumpur (DBKL), Jabatan Kerja Raya (JKR) and other agencies. The data were analysed and processed using Arc GIS. The results were compared by quantifying the risk ranking and area differential. It was also compared with the zonation map classified by DBKL. The results suggested that ANN method gives better accuracy compared to MCDM with 18.18% higher accuracy assessment of the MCDM approach. This indicated that ANN provides more reliable results and it is probably due to its ability to learn from the environment thus portraying realistic and accurate result.

  4. Impact of geo-environmental factors on landslide susceptibility using an AHP method: A case study of Fruška Gora Mt., Serbia

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    Marjanović Miloš

    2013-01-01

    Full Text Available The paper considers the outcome of multi-criteria analysis of landslide susceptibility on the NW outskirts of Fruška Gora Mountain, Serbia. The area of the interest is known for landslide occurrences, and to focus on the most affected areas, it was necessary to consider some principal factors (lithology, slope inclination, rainfall, erosion, vegetation, altitude and slope aspect and sort them by their importance to the phenomena. Prior to any criteria assessment, available data records had been assembled and refashioned as raster datasets. Thereafter, the criteria arising from an analytical hierarchy process (AHP provided their weights of preference in the final model. In addition, the model was analyzed for the information gain and classified in accordance to the optimal informativeness. Being tailored in the context of raster modelling, aided by the GIS spatial tools, our result gained substantial correlation to the control reference map (a digital photo-geological interpretation map of active and potential landslides.

  5. A comparison between univariate probabilistic and multivariate (logistic regression) methods for landslide susceptibility analysis: the example of the Febbraro valley (Northern Alps, Italy)

    Science.gov (United States)

    Rossi, M.; Apuani, T.; Felletti, F.

    2009-04-01

    The aim of this paper is to compare the results of two statistical methods for landslide susceptibility analysis: 1) univariate probabilistic method based on landslide susceptibility index, 2) multivariate method (logistic regression). The study area is the Febbraro valley, located in the central Italian Alps, where different types of metamorphic rocks croup out. On the eastern part of the studied basin a quaternary cover represented by colluvial and secondarily, by glacial deposits, is dominant. In this study 110 earth flows, mainly located toward NE portion of the catchment, were analyzed. They involve only the colluvial deposits and their extension mainly ranges from 36 to 3173 m2. Both statistical methods require to establish a spatial database, in which each landslide is described by several parameters that can be assigned using a main scarp central point of landslide. The spatial database is constructed using a Geographical Information System (GIS). Each landslide is described by several parameters corresponding to the value of main scarp central point of the landslide. Based on bibliographic review a total of 15 predisposing factors were utilized. The width of the intervals, in which the maps of the predisposing factors have to be reclassified, has been defined assuming constant intervals to: elevation (100 m), slope (5 °), solar radiation (0.1 MJ/cm2/year), profile curvature (1.2 1/m), tangential curvature (2.2 1/m), drainage density (0.5), lineament density (0.00126). For the other parameters have been used the results of the probability-probability plots analysis and the statistical indexes of landslides site. In particular slope length (0 ÷ 2, 2 ÷ 5, 5 ÷ 10, 10 ÷ 20, 20 ÷ 35, 35 ÷ 260), accumulation flow (0 ÷ 1, 1 ÷ 2, 2 ÷ 5, 5 ÷ 12, 12 ÷ 60, 60 ÷27265), Topographic Wetness Index 0 ÷ 0.74, 0.74 ÷ 1.94, 1.94 ÷ 2.62, 2.62 ÷ 3.48, 3.48 ÷ 6,00, 6.00 ÷ 9.44), Stream Power Index (0 ÷ 0.64, 0.64 ÷ 1.28, 1.28 ÷ 1.81, 1.81 ÷ 4.20, 4.20 ÷ 9

  6. Landslide susceptibility assessment in the Upper Orcia Valley (Southern Tuscany, Italy through conditional analysis: a contribution to the unbiased selection of causal factors

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    F. Vergari

    2011-05-01

    Full Text Available In this work the conditional multivariate analysis was applied to evaluate landslide susceptibility in the Upper Orcia River Basin (Tuscany, Italy, where widespread denudation processes and agricultural practices have a mutual impact. We introduced an unbiased procedure for causal factor selection based on some intuitive statistical indices. This procedure is aimed at detecting among different potential factors the most discriminant ones in a given study area. Moreover, this step avoids generating too small and statistically insignificant spatial units by intersecting the factor maps. Finally, a validation procedure was applied based on the partition of the landslide inventory from multi-temporal aerial photo interpretation.

    Although encompassing some sources of uncertainties, the applied susceptibility assessment method provided a satisfactory and unbiased prediction for the Upper Orcia Valley. The results confirmed the efficiency of the selection procedure, as an unbiased step of the landslide susceptibility evaluation. Furthermore, we achieved the purpose of presenting a conceptually simple but, at the same time, effective statistical procedure for susceptibility analysis to be used as well by decision makers in land management.

  7. Presence-only approach to assess landslide triggering-thickness susceptibility: a test for the Mili catchment (north-eastern Sicily, Italy)

    KAUST Repository

    Lombardo, Luigi

    2016-06-29

    This study evaluates the performances of the presence-only approach, Maximum Entropy, in assessing landslide triggering-thickness susceptibility within the Mili catchment (Sicily, Italy). This catchment underwent several meteorological stresses, resulting in hundreds of shallow rapid mass movements between 2007 and 2011. In particular, the area has become known for two disasters, which occurred in 2009 and 2010; the first weather system did not pass directly over the catchment; however, peak rainfall was registered over the basin during the second meteorological event. Field data were collected to associate the depth from the slope surface that material was mobilised at the triggering zone to each mass movement within the catchment. This information has been used to model the landslide susceptibility for two classes of processes, divided into shallow failures for maximum depths of 1 m and deep ones in case of values equal or greater than 1 m. Topographic attributes from a 2-m DEM were used as predictors, together with medium resolution vegetation indexes derived from ASTER scenes and geological, land use and tectonic maps. The presence-only approach discriminated between the two depth classes at the landslide trigger zone, producing excellent prediction skills associated with relatively low variances across a set of 50 randomly generated replicates. The role of each predictor was assessed to ascertain the significance to the final model output. This work uses simple field measurements to produce triggering-thickness susceptibility, which is a novel approach and may perform better as a proxy for landslide hazard assessments with respect to more common susceptibility practises. © 2016, Springer Science+Business Media Dordrecht.

  8. A landslide susceptibility assessment in urban areas based on existing data: an example from the Iguaná Valley, Medellín City, Colombia

    Czech Academy of Sciences Publication Activity Database

    Klimeš, Jan; Rios Escobar, V.

    2010-01-01

    Roč. 10, č. 10 (2010), s. 2067-2079 ISSN 1561-8633 R&D Projects: GA ČR GP205/09/P383 Institutional research plan: CEZ:AV0Z30460519 Keywords : landslide susceptibility assessment * Colombia * Medellín Subject RIV: DE - Earth Magnetism, Geodesy, Geography Impact factor: 1.792, year: 2010 http://www.nat-hazards-earth-syst-sci.net/10/2067/2010/nhess-10-2067-2010.html

  9. A Spatially Explicit Approach for Sensitivity and Uncertainty Analysis of GIS-Multicriteria Landslide Susceptibility Mapping. GI_Forum 2013 – Creating the GISociety|

    OpenAIRE

    Feizizadeh, Bakhtiar; Jankowski, Piotr; Blaschke, Thomas

    2016-01-01

    GIS multicriteria decision analysis (MCDA) methods are increasingly being used in landslide susceptibility mapping for the prediction of future hazards, decision making, as well as hazard mitigation plans. However, the uncertainties associated with MCDA techniques are inevitable and model outcomes are prone to multiple types of uncertainty. In this paper, the spatiality explicitly method is employed to assess the uncertainty associated with two methods of GIS-MCDA namely, Analytical Hierarchi...

  10. Landslide Susceptibility Mapping Based on Particle Swarm Optimization of Multiple Kernel Relevance Vector Machines: Case of a Low Hill Area in Sichuan Province, China

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    Yongliang Lin

    2016-10-01

    Full Text Available In this paper, we propose a multiple kernel relevance vector machine (RVM method based on the adaptive cloud particle swarm optimization (PSO algorithm to map landslide susceptibility in the low hill area of Sichuan Province, China. In the multi-kernel structure, the kernel selection problem can be solved by adjusting the kernel weight, which determines the single kernel contribution of the final kernel mapping. The weights and parameters of the multi-kernel function were optimized using the PSO algorithm. In addition, the convergence speed of the PSO algorithm was increased using cloud theory. To ensure the stability of the prediction model, the result of a five-fold cross-validation method was used as the fitness of the PSO algorithm. To verify the results, receiver operating characteristic curves (ROC and landslide dot density (LDD were used. The results show that the model that used a heterogeneous kernel (a combination of two different kernel functions had a larger area under the ROC curve (0.7616 and a lower prediction error ratio (0.28% than did the other types of kernel models employed in this study. In addition, both the sum of two high susceptibility zone LDDs (6.71/100 km2 and the sum of two low susceptibility zone LDDs (0.82/100 km2 demonstrated that the landslide susceptibility map based on the heterogeneous kernel model was closest to the historical landslide distribution. In conclusion, the results obtained in this study can provide very useful information for disaster prevention and land-use planning in the study area.

  11. A simplified GIS-based model for large wood recruitment and connectivity in mountain basins

    Science.gov (United States)

    Lucía, Ana; Antonello, Andrea; Campana, Daniela; Cavalli, Marco; Crema, Stefano; Franceschi, Silvia; Marchese, Enrico; Niedrist, Martin; Schneiderbauer, Stefan; Comiti, Francesco

    2014-05-01

    The mobilization of large wood (LW) elements in mountain rivers channels during floods may increase their hazard potential, especially by clogging narrow sections such as bridges. However, the prediction of LW transport magnitude during flood events is a challenging topic. Although some models on LW transport have been recently developed, the objective of this work was to generate a simplified GIS-based model to identify along the channel network the most likely LW-related critical sections during high-magnitude flood events in forested mountain basins. Potential LW contribution generated by landsliding occurring on hillslopes is assessed using SHALSTAB stability model coupled to a GIS-based connectivity index, developed as a modification of the index proposed by Cavalli et al (2013). Connected slope-derived LW volumes are then summed at each raster cell to LW volumes generated by bank erosion along the erodibile part of river corridors, where bank erosion processes are estimated based on user-defined channel widening ratios stemming from observations following recent extreme events in mountain basins. LW volume in the channel is then routed through the stream network applying simple Boolean rules meant to capture the most important limiting transport condition in these high-energy systems at flood stage, i.e. flow width relative to log length. In addition, the role of bridges and retention check-dams in blocking floating logs is accounted for in the model, in particular bridge length and height are used to characterize their clogging susceptibility for different levels of expected LW volumes and size. The model has been tested in the Rienz and Ahr basins (about 630 km2 each), located in the Eastern Italian Alps. Sixty percent of the basin area is forested, and elevations range from 811 m a.s.l. to 3488 m a.s.l.. We used a 2.5 m resolution DTM and DSM, and their difference was used to calculate the canopy height. Data from 35 plots of the National Forest Inventory

  12. The role of multicollinearity in landslide susceptibility assessment by means of Binary Logistic Regression: comparison between VIF and AIC stepwise selection

    Science.gov (United States)

    Cama, Mariaelena; Cristi Nicu, Ionut; Conoscenti, Christian; Quénéhervé, Geraldine; Maerker, Michael

    2016-04-01

    Landslide susceptibility can be defined as the likelihood of a landslide occurring in a given area on the basis of local terrain conditions. In the last decades many research focused on its evaluation by means of stochastic approaches under the assumption that 'the past is the key to the future' which means that if a model is able to reproduce a known landslide spatial distribution, it will be able to predict the future locations of new (i.e. unknown) slope failures. Among the various stochastic approaches, Binary Logistic Regression (BLR) is one of the most used because it calculates the susceptibility in probabilistic terms and its results are easily interpretable from a geomorphological point of view. However, very often not much importance is given to multicollinearity assessment whose effect is that the coefficient estimates are unstable, with opposite sign and therefore difficult to interpret. Therefore, it should be evaluated every time in order to make a model whose results are geomorphologically correct. In this study the effects of multicollinearity in the predictive performance and robustness of landslide susceptibility models are analyzed. In particular, the multicollinearity is estimated by means of Variation Inflation Index (VIF) which is also used as selection criterion for the independent variables (VIF Stepwise Selection) and compared to the more commonly used AIC Stepwise Selection. The robustness of the results is evaluated through 100 replicates of the dataset. The study area selected to perform this analysis is the Moldavian Plateau where landslides are among the most frequent geomorphological processes. This area has an increasing trend of urbanization and a very high potential regarding the cultural heritage, being the place of discovery of the largest settlement belonging to the Cucuteni Culture from Eastern Europe (that led to the development of the great complex Cucuteni-Tripyllia). Therefore, identifying the areas susceptible to

  13. Spatiotemporal Change Detection in Forest Cover Dynamics Along Landslide Susceptible Region of Karakoram Highway, Pakistan

    Science.gov (United States)

    Rashid, Barira; Iqbal, Javed

    2018-04-01

    Forest Cover dynamics and its understanding is essential for a country's social, environmental, and political engagements. This research provides a methodical approach for the assessment of forest cover along Karakoram Highway. It has great ecological and economic significance because it's a part of China-Pakistan Economic Corridor. Landsat 4, 5 TM, Landsat 7 ETM and Landsat 8 OLI imagery for the years 1990, 2000, 2010 and 2016 respectively were subjected to supervised classification in ArcMap 10.5 to identify forest change. The study area was categorized into five major land use land cover classes i.e., Forest, vegetation, urban, open land and snow cover. Results from post classification forest cover change maps illustrated notable decrease of almost 26 % forest cover over the time period of 26 years. The accuracy assessment revealed the kappa coefficients 083, 0.78, 0.77 and 0.85, respectively. Major reason for this change is an observed replacement of native forest cover with urban areas (12.5 %) and vegetation (18.6 %) However, there is no significant change in the reserved forests along the study area that contributes only 2.97 % of the total forest cover. The extensive forest degradation and risk prone topography of the region has increased the environmental risk of landslides. Hence, effective policies and forest management is needed to protect not only the environmental and aesthetic benefits of the forest cover but also to manage the disaster risks. Apart from the forest assessment, this research gives an insight of land cover dynamics, along with causes and consequences, thereby showing the forest degradation hotspots.

  14. Binary Logistic Regression Versus Boosted Regression Trees in Assessing Landslide Susceptibility for Multiple-Occurring Regional Landslide Events: Application to the 2009 Storm Event in Messina (Sicily, southern Italy).

    Science.gov (United States)

    Lombardo, L.; Cama, M.; Maerker, M.; Parisi, L.; Rotigliano, E.

    2014-12-01

    This study aims at comparing the performances of Binary Logistic Regression (BLR) and Boosted Regression Trees (BRT) methods in assessing landslide susceptibility for multiple-occurrence regional landslide events within the Mediterranean region. A test area was selected in the north-eastern sector of Sicily (southern Italy), corresponding to the catchments of the Briga and the Giampilieri streams both stretching for few kilometres from the Peloritan ridge (eastern Sicily, Italy) to the Ionian sea. This area was struck on the 1st October 2009 by an extreme climatic event resulting in thousands of rapid shallow landslides, mainly of debris flows and debris avalanches types involving the weathered layer of a low to high grade metamorphic bedrock. Exploiting the same set of predictors and the 2009 landslide archive, BLR- and BRT-based susceptibility models were obtained for the two catchments separately, adopting a random partition (RP) technique for validation; besides, the models trained in one of the two catchments (Briga) were tested in predicting the landslide distribution in the other (Giampilieri), adopting a spatial partition (SP) based validation procedure. All the validation procedures were based on multi-folds tests so to evaluate and compare the reliability of the fitting, the prediction skill, the coherence in the predictor selection and the precision of the susceptibility estimates. All the obtained models for the two methods produced very high predictive performances, with a general congruence between BLR and BRT in the predictor importance. In particular, the research highlighted that BRT-models reached a higher prediction performance with respect to BLR-models, for RP based modelling, whilst for the SP-based models the difference in predictive skills between the two methods dropped drastically, converging to an analogous excellent performance. However, when looking at the precision of the probability estimates, BLR demonstrated to produce more robust

  15. An integrated approach coupling physically based models and probabilistic method to assess quantitatively landslide susceptibility at different scale: application to different geomorphological environments

    Science.gov (United States)

    Vandromme, Rosalie; Thiéry, Yannick; Sedan, Olivier; Bernardie, Séverine

    2016-04-01

    Landslide hazard assessment is the estimation of a target area where landslides of a particular type, volume, runout and intensity may occur within a given period. The first step to analyze landslide hazard consists in assessing the spatial and temporal failure probability (when the information is available, i.e. susceptibility assessment). Two types of approach are generally recommended to achieve this goal: (i) qualitative approach (i.e. inventory based methods and knowledge data driven methods) and (ii) quantitative approach (i.e. data-driven methods or deterministic physically based methods). Among quantitative approaches, deterministic physically based methods (PBM) are generally used at local and/or site-specific scales (1:5,000-1:25,000 and >1:5,000, respectively). The main advantage of these methods is the calculation of probability of failure (safety factor) following some specific environmental conditions. For some models it is possible to integrate the land-uses and climatic change. At the opposite, major drawbacks are the large amounts of reliable and detailed data (especially materials type, their thickness and the geotechnical parameters heterogeneity over a large area) and the fact that only shallow landslides are taking into account. This is why they are often used at site-specific scales (> 1:5,000). Thus, to take into account (i) materials' heterogeneity , (ii) spatial variation of physical parameters, (iii) different landslide types, the French Geological Survey (i.e. BRGM) has developed a physically based model (PBM) implemented in a GIS environment. This PBM couples a global hydrological model (GARDENIA®) including a transient unsaturated/saturated hydrological component with a physically based model computing the stability of slopes (ALICE®, Assessment of Landslides Induced by Climatic Events) based on the Morgenstern-Price method for any slip surface. The variability of mechanical parameters is handled by Monte Carlo approach. The

  16. Assessment of susceptibility to earth-flow landslide using logistic regression and multivariate adaptive regression splines: A case of the Belice River basin (western Sicily, Italy)

    Science.gov (United States)

    Conoscenti, Christian; Ciaccio, Marilena; Caraballo-Arias, Nathalie Almaru; Gómez-Gutiérrez, Álvaro; Rotigliano, Edoardo; Agnesi, Valerio

    2015-08-01

    In this paper, terrain susceptibility to earth-flow occurrence was evaluated by using geographic information systems (GIS) and two statistical methods: Logistic regression (LR) and multivariate adaptive regression splines (MARS). LR has been already demonstrated to provide reliable predictions of earth-flow occurrence, whereas MARS, as far as we know, has never been used to generate earth-flow susceptibility models. The experiment was carried out in a basin of western Sicily (Italy), which extends for 51 km2 and is severely affected by earth-flows. In total, we mapped 1376 earth-flows, covering an area of 4.59 km2. To explore the effect of pre-failure topography on earth-flow spatial distribution, we performed a reconstruction of topography before the landslide occurrence. This was achieved by preparing a digital terrain model (DTM) where altitude of areas hosting landslides was interpolated from the adjacent undisturbed land surface by using the algorithm topo-to-raster. This DTM was exploited to extract 15 morphological and hydrological variables that, in addition to outcropping lithology, were employed as explanatory variables of earth-flow spatial distribution. The predictive skill of the earth-flow susceptibility models and the robustness of the procedure were tested by preparing five datasets, each including a different subset of landslides and stable areas. The accuracy of the predictive models was evaluated by drawing receiver operating characteristic (ROC) curves and by calculating the area under the ROC curve (AUC). The results demonstrate that the overall accuracy of LR and MARS earth-flow susceptibility models is from excellent to outstanding. However, AUC values of the validation datasets attest to a higher predictive power of MARS-models (AUC between 0.881 and 0.912) with respect to LR-models (AUC between 0.823 and 0.870). The adopted procedure proved to be resistant to overfitting and stable when changes of the learning and validation samples are

  17. Landslides in Nicaragua - Mapping, Inventory, Hazard Assessment, Vulnerability Reduction, and Forecasting Attempts

    Science.gov (United States)

    Dévoli, G.; Strauch, W.; Álvarez, A.; Muñoz, A.; Kjekstad, O.

    2009-04-01

    access, manage, update and distribute in a short time to all sectors and users; and finally, the need of a comprehensive understanding of landslide processes. Many efforts have been made in the last 10 years to gain a more comprehensive and predictive understanding of landslide processes in Nicaragua. Since 1998, landslide inventory GIS based maps have been produced in different areas of the country, as part of international and multidisciplinary development projects. Landslide susceptibility and hazard maps are available now at INETEŔs Website for all municipalities of the country. The insights on landslide hazard have been transmitted to governmental agencies, local authorities, NGÓs, international agencies to be used in measures for risk reduction. A massive application example was the integration of hazard assessment studies in a large house building program in Nicaragua. Hazards of landslides, and other dangerous phenomena, were evaluated in more than 90 house building projects, each with 50 - 200 houses to be build, sited mainly in rural areas of the country. For more than 7000 families, this program could finally assure that their new houses were build in safe areas. Attempts have been made to develop a strategy for early warning of landslides in Nicaragua. First approaches relied on precipitation gauges with satellite based telemetry which were installed in some Nicaraguan volcanoes where lahars occur frequently. The occurrence of lahars in certain gullies could be detected by seismic stations. A software system gave acoustic alarm at INETEŔs Monitoring Centre when certain trigger levels of the accumulated precipitation were reached. The monitoring and early warning for all areas under risk would have required many rain gauges. A new concept is tested which uses near real time precipitation estimates from NOAA meteorological satellite data. A software system sends out alarm messages if strong or long lasting rains are observed over certain landslide "hot spots

  18. Directions of the US Geological Survey Landslide Hazards Reduction Program

    Science.gov (United States)

    Wieczorek, G.F.

    1993-01-01

    The US Geological Survey (USGS) Landslide Hazards Reduction Program includes studies of landslide process and prediction, landslide susceptibility and risk mapping, landslide recurrence and slope evolution, and research application and technology transfer. Studies of landslide processes have been recently conducted in Virginia, Utah, California, Alaska, and Hawaii, Landslide susceptibility maps provide a very important tool for landslide hazard reduction. The effects of engineering-geologic characteristics of rocks, seismic activity, short and long-term climatic change on landslide recurrence are under study. Detailed measurement of movement and deformation has begun on some active landslides. -from Author

  19. Susceptibility mapping in the Río El Estado watershed, Pico de Orizaba volcano, Mexico

    Science.gov (United States)

    Legorreta Paulin, G.; Bursik, M. I.; Lugo Hubp, J.; Paredes Mejía, L.; Aceves Quesada, F.

    2013-12-01

    ) to create the susceptibility map. Finally, the model was compared with the reality expressed by the inventory map. The technique and its implementation of each level in a GIS-based technology is presented and discussed.

  20. An overview of a GIS method for mapping landslides and assessing landslide hazards at Río El Estado watershed, on the SW flank of Pico de Orizaba Volcano, Mexico

    Science.gov (United States)

    Legorreta Paulin, G.; Bursik, M. I.; Contreras, T.; Polenz, M.; Ramírez Herrera, M.; Paredes Mejía, L.; Arana Salinas, L.

    2012-12-01

    This poster provides an overview of the on-going research project (Grant SEP-CONACYT no 167495) from the Institute of Geography at the National Autonomous University of Mexico (UNAM) that seeks to conduct a multi-temporal landslide inventory, produce a landslide susceptibility map, and estimate sediment production by using Geographic Information Systems (GIS). The Río El Estado watershed on the southwestern flank of Pico de Orizaba volcano, the highest mountain in Mexico, is selected as a study area. The catchment covers 5.2 km2 with elevations ranging from 2676.79 to 4248.2 m a.s.l. and hillslopes between 0° and 56°. The stream system of Río El Estado catchment erodes Tertiary and Quaternary lavas, pyroclastic flows, and fall deposits. The geologic and geomorphologic factors in combination with high seasonal precipitation, high degree of weathering, and steep slopes predispose the study area to landslides. The methodology encompasses three main stages of analysis to assess landslide hazards: Stage 1 builds a historic landslide inventory. In the study area, an inventory of more than 170 landslides is created from multi-temporal aerial-photo-interpretation and local field surveys to assess landslide distribution. All landslides were digitized into a geographic information system (GIS), and a spatial geo-database of landslides was constructed from standardized GIS datasets. Stage 2 Calculates the susceptibility for the watershed. During this stage, Multiple Logistic Regression and SINMAP) will be evaluated to select the one that provides scientific accuracy, technical accessibility, and applicability. Stage 3 Estimate the potential total material delivered to the main stream drainage channel by all landslides in the catchment. Detailed geometric measurements of individual landslides visited during the field work will be carried out to obtain the landslide area and volume. These measurements revealed an empirical relationship between area and volume that took the

  1. Towards a real-time susceptibility assessment of rainfall-induced shallow landslides on a regional scale

    Directory of Open Access Journals (Sweden)

    L. Montrasio

    2011-07-01

    Full Text Available In the framework of landslide risk management, it appears relevant to assess, both in space and in time, the triggering of rainfall-induced shallow landslides, in order to prevent damages due to these kind of disasters. In this context, the use of real-time landslide early warning systems has been attracting more and more attention from the scientific community. This paper deals with the application, on a regional scale, of two physically-based stability models: SLIP (Shallow Landslides Instability Prediction and TRIGRS (Transient Rainfall Infiltration and Grid-based Regional Slope-stability analysis. A back analysis of some recent case-histories of soil slips which occurred in the territory of the central Emilian Apennine, Emilia Romagna Region (Northern Italy is carried out and the main results are shown. The study area is described from geological and climatic viewpoints. The acquisition of geospatial information regarding the topography, the soil properties and the local landslide inventory is also explained.

    The paper outlines the main features of the SLIP model and the basic assumptions of TRIGRS. Particular attention is devoted to the discussion of the input data, which have been stored and managed through a Geographic Information System (GIS platform. Results of the SLIP model on a regional scale, over a one year time interval, are finally presented. The results predicted by the SLIP model are analysed both in terms of safety factor (Fs maps, corresponding to particular rainfall events, and in terms of time-varying percentage of unstable areas over the considered time interval. The paper compares observed landslide localizations with those predicted by the SLIP model. A further quantitative comparison between SLIP and TRIGRS, both applied to the most important event occurred during the analysed period, is presented. The limits of the SLIP model, mainly due to some restrictions of simplifying the physically

  2. The role of windstorm exposure and yellow cedar decline on landslide susceptibility in southeast Alaskan temperate rainforests

    Science.gov (United States)

    Brian Buma; Adelaide C. Johnson

    2015-01-01

    Interactions between ecological disturbances have the potential to alter other disturbances and their associated regimes, such as the likelihood, severity, and extent of events. The influence of exposure to wind and yellow cedar decline on the landslide regime of Alaskan temperate rainforests was explored using presence-only modeling techniques. The wind regime was...

  3. Open Source GIS based integrated watershed management

    Science.gov (United States)

    Byrne, J. M.; Lindsay, J.; Berg, A. A.

    2013-12-01

    challenging resource management issues in industry, government and nongovernmental agencies. Current research and analysis tools were developed to manage meteorological, climatological, and land and water resource data efficiently at high resolution in space and time. The deliverable for this work is a Whitebox-GENESYS open-source resource management capacity with routines for GIS based watershed management including water in agriculture and food production. We are adding urban water management routines through GENESYS in 2013-15 with an engineering PhD candidate. Both Whitebox-GAT and GENESYS are already well-established tools. The proposed research will combine these products to create an open-source geomatics based water resource management tool that is revolutionary in both capacity and availability to a wide array of Canadian and global users

  4. Landslide prediction system for rainfall induced landslides in Slovenia (Masprem

    Directory of Open Access Journals (Sweden)

    Mateja Jemec Auflič

    2016-12-01

    Full Text Available In this paper we introduce a landslide prediction system for modelling the probabilities of landslides through time in Slovenia (Masprem. The system to forecast rainfall induced landslides is based on the landslide susceptibility map, landslide triggering rainfall threshold values and the precipitation forecasting model. Through the integrated parameters a detailed framework of the system, from conceptual to operational phases, is shown. Using fuzzy logic the landslide prediction is calculated. Potential landslide areas are forecasted on a national scale (1: 250,000 and on a local scale (1: 25,000 for fie selected municipalities where the exposure of inhabitants, buildings and different type of infrastructure is displayed, twice daily. Due to different rainfall patterns that govern landslide occurrences, the system for landslide prediction considers two different rainfall scenarios (M1 and M2. The landslides predicted by the two models are compared with a landslide inventory to validate the outputs. In this study we highlight the rainfall event that lasted from the 9th to the 14th of September 2014 when abundant precipitation triggered over 800 slope failures around Slovenia and caused large material damage. Results show that antecedent rainfall plays an important role, according to the comparisons of the model (M1 where antecedent rainfall is not considered. Although in general the landslides areas are over-predicted and largely do not correspond to the landslide inventory, the overall performance indicates that the system is able to capture the crucial factors in determining the landslide location. Additional calibration of input parameters and the landslide inventory as well as improved spatially distributed rainfall forecast data can further enhance the model's prediction.

  5. Modelling shallow landslide susceptibility by means of a subsurface flow path connectivity index and estimates of soil depth spatial distribution

    Directory of Open Access Journals (Sweden)

    C. Lanni

    2012-11-01

    Full Text Available Topographic index-based hydrological models have gained wide use to describe the hydrological control on the triggering of rainfall-induced shallow landslides at the catchment scale. A common assumption in these models is that a spatially continuous water table occurs simultaneously across the catchment. However, during a rainfall event isolated patches of subsurface saturation form above an impeding layer and their hydrological connectivity is a necessary condition for lateral flow initiation at a point on the hillslope.

    Here, a new hydrological model is presented, which allows us to account for the concept of hydrological connectivity while keeping the simplicity of the topographic index approach. A dynamic topographic index is used to describe the transient lateral flow that is established at a hillslope element when the rainfall amount exceeds a threshold value allowing for (a development of a perched water table above an impeding layer, and (b hydrological connectivity between the hillslope element and its own upslope contributing area. A spatially variable soil depth is the main control of hydrological connectivity in the model. The hydrological model is coupled with the infinite slope stability model and with a scaling model for the rainfall frequency–duration relationship to determine the return period of the critical rainfall needed to cause instability on three catchments located in the Italian Alps, where a survey of soil depth spatial distribution is available. The model is compared with a quasi-dynamic model in which the dynamic nature of the hydrological connectivity is neglected. The results show a better performance of the new model in predicting observed shallow landslides, implying that soil depth spatial variability and connectivity bear a significant control on shallow landsliding.

  6. Assessing deep-seated landslide susceptibility using 3-D groundwater and slope-stability analyses, southwestern Seattle, Washington

    Science.gov (United States)

    Brien, Dianne L.; Reid, Mark E.

    2008-01-01

    In Seattle, Washington, deep-seated landslides on bluffs along Puget Sound have historically caused extensive damage to land and structures. These large failures are controlled by three-dimensional (3-D) variations in strength and pore-water pressures. We assess the slope stability of part of southwestern Seattle using a 3-D limit-equilibrium analysis coupled with a 3-D groundwater flow model. Our analyses use a high-resolution digital elevation model (DEM) combined with assignment of strength and hydraulic properties based on geologic units. The hydrogeology of the Seattle area consists of a layer of permeable glacial outwash sand that overlies less permeable glacial lacustrine silty clay. Using a 3-D groundwater model, MODFLOW-2000, we simulate a water table above the less permeable units and calibrate the model to observed conditions. The simulated pore-pressure distribution is then used in a 3-D slope-stability analysis, SCOOPS, to quantify the stability of the coastal bluffs. For wet winter conditions, our analyses predict that the least stable areas are steep hillslopes above Puget Sound, where pore pressures are elevated in the outwash sand. Groundwater flow converges in coastal reentrants, resulting in elevated pore pressures and destabilization of slopes. Regions predicted to be least stable include the areas in or adjacent to three mapped historically active deep-seated landslides. The results of our 3-D analyses differ significantly from a slope map or results from one-dimensional (1-D) analyses.

  7. Global terrain classification using Multiple-Error-Removed Improved-Terrain (MERIT) to address susceptibility of landslides and other geohazards

    Science.gov (United States)

    Iwahashi, J.; Yamazaki, D.; Matsuoka, M.; Thamarux, P.; Herrick, J.; Yong, A.; Mital, U.

    2017-12-01

    A seamless model of landform classifications with regional accuracy will be a powerful platform for geophysical studies that forecast geologic hazards. Spatial variability as a function of landform on a global scale was captured in the automated classifications of Iwahashi and Pike (2007) and additional developments are presented here that incorporate more accurate depictions using higher-resolution elevation data than the original 1-km scale Shuttle Radar Topography Mission digital elevation model (DEM). We create polygon-based terrain classifications globally by using the 280-m DEM interpolated from the Multi-Error-Removed Improved-Terrain DEM (MERIT; Yamazaki et al., 2017). The multi-scale pixel-image analysis method, known as Multi-resolution Segmentation (Baatz and Schäpe, 2000), is first used to classify the terrains based on geometric signatures (slope and local convexity) calculated from the 280-m DEM. Next, we apply the machine learning method of "k-means clustering" to prepare the polygon-based classification at the globe-scale using slope, local convexity and surface texture. We then group the divisions with similar properties by hierarchical clustering and other statistical analyses using geological and geomorphological data of the area where landslides and earthquakes are frequent (e.g. Japan and California). We find the 280-m DEM resolution is only partially sufficient for classifying plains. We nevertheless observe that the categories correspond to reported landslide and liquefaction features at the global scale, suggesting that our model is an appropriate platform to forecast ground failure. To predict seismic amplification, we estimate site conditions using the time-averaged shear-wave velocity in the upper 30-m (VS30) measurements compiled by Yong et al. (2016) and the terrain model developed by Yong (2016; Y16). We plan to test our method on finer resolution DEMs and report our findings to obtain a more globally consistent terrain model as there

  8. GIS-based bivariate statistical techniques for groundwater potential ...

    Indian Academy of Sciences (India)

    Ali Haghizadeh

    2017-11-23

    Nov 23, 2017 ... regions. This study shows the potency of two GIS-based data driven ... growth of these tools has also prepared another ..... Urban. 30467. 3. 0.06. 0.20. 0.74. 0.80. −0.64. Distance from road ..... and artificial neural networks for potential groundwater .... ping: A case study at Mehran region, Iran; Catena 137.

  9. GIS-Based bivariate statistical techniques for groundwater potential ...

    Indian Academy of Sciences (India)

    24

    This study shows the potency of two GIS-based data driven bivariate techniques namely ... In the view of these weaknesses , there is a strong requirement for reassessment of .... Font color: Text 1, Not Expanded by / Condensed by , ...... West Bengal (India) using remote sensing, geographical information system and multi-.

  10. A GIS based hydrogeomorphic approach for identification of site ...

    Indian Academy of Sciences (India)

    a Geographical Information System (GIS) based hydrogeomorphic approach in the Bhatsa and. Kalu river basins of Thane district, in western DVP. The criteria adopted for the GIS analysis were based .... segments of the rivers. The majority of the lineaments correspond to either dyke ridges or stream channels which are of ...

  11. Landslide hazard and risk assessment using semi-automatically created landslide inventories

    NARCIS (Netherlands)

    Martinez, J.A.; van Westen, C.J.; Kerle, N.; Jetten, V.G.; Kumar, K.V.

    2013-01-01

    Landslide inventories prepared manually from remote sensing data or through field surveys have shown to be useful for preparation of landslide susceptibility and hazard maps. Recent literatures show several studies have been carried out to prepare landslide inventories from satellite data by

  12. From Physical Process to Economic Cost - Integrated Approaches of Landslide Risk Assessment

    Science.gov (United States)

    Klose, M.; Damm, B.

    2014-12-01

    The nature of landslides is complex in many respects, with landslide hazard and impact being dependent on a variety of factors. This obviously requires an integrated assessment for fundamental understanding of landslide risk. Integrated risk assessment, according to the approach presented in this contribution, implies combining prediction of future landslide occurrence with analysis of landslide impact in the past. A critical step for assessing landslide risk in integrated perspective is to analyze what types of landslide damage affected people and property in which way and how people contributed and responded to these damage types. In integrated risk assessment, the focus is on systematic identification and monetization of landslide damage, and analytical tools that allow deriving economic costs from physical landslide processes are at the heart of this approach. The broad spectrum of landslide types and process mechanisms as well as nonlinearity between landslide magnitude, damage intensity, and direct costs are some main factors explaining recent challenges in risk assessment. The two prevailing approaches for assessing the impact of landslides in economic terms are cost survey (ex-post) and risk analysis (ex-ante). Both approaches are able to complement each other, but yet a combination of them has not been realized so far. It is common practice today to derive landslide risk without considering landslide process-based cause-effect relationships, since integrated concepts or new modeling tools expanding conventional methods are still widely missing. The approach introduced in this contribution is based on a systematic framework that combines cost survey and GIS-based tools for hazard or cost modeling with methods to assess interactions between land use practices and landslides in historical perspective. Fundamental understanding of landslide risk also requires knowledge about the economic and fiscal relevance of landslide losses, wherefore analysis of their

  13. GIS-BASED PREDICTION OF HURRICANE FLOOD INUNDATION

    Energy Technology Data Exchange (ETDEWEB)

    JUDI, DAVID [Los Alamos National Laboratory; KALYANAPU, ALFRED [Los Alamos National Laboratory; MCPHERSON, TIMOTHY [Los Alamos National Laboratory; BERSCHEID, ALAN [Los Alamos National Laboratory

    2007-01-17

    A simulation environment is being developed for the prediction and analysis of the inundation consequences for infrastructure systems from extreme flood events. This decision support architecture includes a GIS-based environment for model input development, simulation integration tools for meteorological, hydrologic, and infrastructure system models and damage assessment tools for infrastructure systems. The GIS-based environment processes digital elevation models (30-m from the USGS), land use/cover (30-m NLCD), stream networks from the National Hydrography Dataset (NHD) and soils data from the NRCS (STATSGO) to create stream network, subbasins, and cross-section shapefiles for drainage basins selected for analysis. Rainfall predictions are made by a numerical weather model and ingested in gridded format into the simulation environment. Runoff hydrographs are estimated using Green-Ampt infiltration excess runoff prediction and a 1D diffusive wave overland flow routing approach. The hydrographs are fed into the stream network and integrated in a dynamic wave routing module using the EPA's Storm Water Management Model (SWMM) to predict flood depth. The flood depths are then transformed into inundation maps and exported for damage assessment. Hydrologic/hydraulic results are presented for Tropical Storm Allison.

  14. Landslide Regions

    Data.gov (United States)

    Department of Homeland Security — These data are a digital version of U.S. Geological Survey Professional Paper 1183, Landslide Overview Map of the Conterminous United States. The map and digital...

  15. An integrated methodology to develop a standard for landslide early warning systems

    OpenAIRE

    Fathani, Teuku Faisal; Karnawati, Dwikorita; Wilopo, Wahyu

    2016-01-01

    Landslides are one of the most widespread and commonly occurring natural hazards. In regions of high vulnerability, these complex hazards can cause significant negative social and economic impacts. Considering the worldwide susceptibility to landslides, it is necessary to establish a standard for early warning systems specific to landslide disaster risk reduction. This standard would provide guidance in conducting landslide detection, prediction, interpretation, and response...

  16. A GIS-BASED ENVIRONMENTAL HEALTH INFORMATION SOURCE FOR MALAYSIAN CONTEXT

    OpenAIRE

    Lau Tiu Chung; Lau Bee Theng; Henry Lee Seldon

    2013-01-01

    In this paper, we propose a GIS-based system for collection and targeted distribution of latest alerts and real-time environmental factors to the Malaysian population. We call it the Environmental Health Management System (EHMS). This GIS-based system is designed to facilitate and encourage research into environmental health quality issues by providing a comprehensive tracking and monitoring tool. This GIS-based system is embedded with Google Maps API and Geocoding API services to visualize t...

  17. GIS-based poverty and population distribution analysis in China

    Science.gov (United States)

    Cui, Jing; Wang, Yingjie; Yan, Hong

    2009-07-01

    Geographically, poverty status is not only related with social-economic factors but also strongly affected by geographical environment. In the paper, GIS-based poverty and population distribution analysis method is introduced for revealing their regional differences. More than 100000 poor villages and 592 national key poor counties are chosen for the analysis. The results show that poverty distribution tends to concentrate in most of west China and mountainous rural areas of mid China. Furthermore, the fifth census data are overlaid to those poor areas in order to gain its internal diversity of social-economic characteristics. By overlaying poverty related social-economic parameters, such as sex ratio, illiteracy, education level, percentage of ethnic minorities, family composition, finding shows that poverty distribution is strongly correlated with high illiteracy rate, high percentage minorities, and larger family member.

  18. Assessing Landslide Characteristics and Developing a Landslide Potential Hazard Map in Rwanda and Uganda Using NASA Earth Observations

    Science.gov (United States)

    Sinclair, L.; Conner, P.; le Roux, J.; Finley, T.

    2015-12-01

    The International Emergency Disasters Database indicates that a total of 482 people have been killed and another 27,530 have been affected by landslides in Rwanda and Uganda, although the actual numbers are thought to be much higher. Data for individual countries are poorly tracked, but hotspots for devastating landslides occur throughout Rwanda and Uganda due to the local topography and soil type, intense rainfall events, and deforestation. In spite of this, there has been little research in this region that utilizes satellite imagery to estimate areas susceptible to landslides. This project utilized Landsat 8 Operational Land Imager (OLI) data and Google Earth to identify landslides that occurred within the study area. These landslides were then added to SERVIR's Global Landslide Catalog (GLC). Next, Landsat 8 OLI, the Tropical Rainfall Measuring Mission (TRMM), the Global Precipitation Measurement (GPM), and Shuttle Radar Topography Mission Version 2 (SRTM V2) data were used to create a Landslide Susceptibility Map. This was combined with population data from the Socioeconomic Data and Applications Center (SEDAC) to create a Landslide Hazard map. A preliminary assessment of the relative performance of GPM and TRMM in identifying landslide conditions was also performed. The additions to the GLC, the Landslide Susceptibility Map, the Landslide Hazard Map, and the preliminary assessment of satellite rainfall performance will be used by SERVIR and the Regional Centre for Mapping of Resources for Development (RCMRD) for disaster risk management, land use planning, and determining landslide conditions and moisture thresholds.

  19. Landslides in Flanders (Belgium): Where science meets public policy

    Science.gov (United States)

    van den Eeckhaut, M.; Poesen, J.; Vandekerckhove, L.

    2009-04-01

    Although scientific research on landslides in the Flemish Ardennes (710 km²; Belgium), has been conducted over the last decades, the Flemish Government only took account of slope failure as a soil degradation process after the occurrence of several damaging landslides in the beginning of the 21st century. Here we aim to present the successful collaboration between the Physical and Regional Geography Research Group (FRG; Dept. Earth and Environmental Sciences K.U.Leuven) and the Environment, Nature and Energy Department (LNE; Flemish Government) in landslide management. We will demonstrate how geomorphologists produced practical tools for landslide management which can be directly applied by LNE as well as other local and regional authorities and planners. Since 2004 three projects on landslide inventory mapping and susceptibility assessment in the Flemish Ardennes have been funded by LNE, and a fourth one on landslide susceptibility assessment in remaining hilly regions in Flanders west of Brussels recently started. Together with a steering committee composed of stakeholders, persons from LNE supervise the research carried out by geomorphologists experienced in landslide studies. For the establishment of the landslide inventory map of the Flemish Ardennes we combined the analysis of LIDAR-derived hillshade and contour line maps with detailed field controls. Additional information was collected through interviews with local authorities and inhabitants and from analysis of newspaper articles and technical reports. Then, a statistical model, logistic regression, was applied to produce a high quality classified landslide susceptibility map. The unique part of this collaboration is that all end products are online available at user-friendly websites designed by LNE. The scientific report containing (1) general information on landslides, (2) a description of the study area, (3) an explanation of the materials and methods used, (4) a presentation of the resulting

  20. Assessing internal biophysical vulnerability to landslide hazards - a nested catchment approach: Xiangxi Watershed / Three Gorges Reservoir

    Science.gov (United States)

    Wiegand, Matthias; Seeber, Christoph; Hartmann, Heike; Xiang, Wei; King, Lorenz

    2010-05-01

    . Dwellings and road infrastructure, chosen as high priorities, are captured based on various data like: high resolution satellite imagery, topographic information and field investigation. Currently demographic data is available only at administrative county level - therefore buildings will serve as spatial proxy for population density. Elements at risk will be classified into categories and susceptibility factors will be identified for sampled groups. The envisaged model defines the susceptibility of a certain element at risk not only by the element itself - it assumes that the specific susceptibility is also strongly influenced by the particular surroundings. The susceptibility of a certain building, as for instance, will be defined by the structure type and condition, and in addition or as proxy, specific site characteristics like: slope angle and aspect, soil type and erodibility, lithology, proximity to streams, proximity to the Three Gorges reservoir, depth to groundwater, land use change and dissect intensity, if feasible. Each factor with potential influence on susceptibility will go through a GIS based factor weighting procedure as part of the quantitative vulnerability model. Holistic, "cross scale integrated" vulnerability assessment models need to integrate environmental, social/ cultural and economic aspects. Therefore the proposed vulnerability assessment model must be seen as a starting point for a conceptual framework, and might serve as stimulus to local disaster- and resources management systems. Furthermore the GIS based model enables the opportunity to be linked and refined within the local spatial data infrastructure initiatives.

  1. Gis-based procedures for hydropower potential spotting

    Energy Technology Data Exchange (ETDEWEB)

    Larentis, Dante G.; Collischonn, Walter; Tucci, Carlos E.M. [Instituto de Pesquisas Hidraulicas da UFRGS, Av. Bento Goncalves, 9500, CEP 91501-970, Caixa Postal 15029, Porto Alegre, RS (Brazil); Olivera, Francisco (Texas A and M University, Zachry Department of Civil Engineering 3136 TAMU, College Station, TX 77843-3136, US)

    2010-10-15

    The increasing demand for energy, especially from renewable and sustainable sources, spurs the development of small hydropower plants and encourages investment in new survey studies. Preliminary hydropower survey studies usually carry huge uncertainties about the technical, economic and environmental feasibility of the undeveloped potential. This paper presents a methodology for large-scale survey of hydropower potential sites to be applied in the inception phase of hydroelectric development planning. The sequence of procedures to identify hydropower sites is based on remote sensing and regional streamflow data and was automated within a GIS-based computational program: Hydrospot. The program allows spotting more potential sites along the drainage network than it would be possible in a traditional survey study, providing different types of dam-powerhouse layouts and two types (operating modes) of projects: run-of-the-river and storage projects. Preliminary results from its applications in a hydropower-developed basin in Brazil have shown Hydrospot's limitations and potentialities in giving support to the mid-to-long-term planning of the electricity sector. (author)

  2. Camili (Macahel Havzasının (Artvin, KD Türkiye Heyelan Duyarlılık Analizi Landslide Susceptibility Analysis of Camili (Macahel Basin (Artvin, NE Turkey

    Directory of Open Access Journals (Sweden)

    Emre ÖZŞAHİN

    2013-03-01

    Full Text Available One of the most common natural disasters in Turkey and in theworld is landslides. Investigation of Turkey’s profile of the last 50 yearsshows that the landslides are the most commonly occurring naturaldisasters with a ratio of 45%.The current study investigated the landslide susceptibility analysisof Camili (Macahel which is one of the unique places on earth with itsspecific fauna and flora and which is the first Biosphere Reserve Area ofTurkey. The landslides which are among the most common naturaldisaster risks in the basin with international recognizance present crucialthreats both in terms of settlement and planning. In this context, thestudy examined the factors that cause landslides in the basin area, theirimpact levels, ratios of potential landslide zones and their geographicaldistributions.The study employed factor maps of various scales obtained fromdifferent resources. 17 parameter factors obtained with the help of thesemaps were evaluated separately and in connection with conditiondependent overlay method to identify landslide risk zones. The studybased on a topography plate with scaled 1/25.000 made use of maps ofvarious scales about different parameters as well as Landsat satelliteimages. Mapping and analysis phases of the study were based onGeographical Information Systems (GIS and Remote Sensing (RStechnology. In this context, ArcGIS/ArcMap 10 GIS and ERDAS 2012 RSsoftware was utilized.It was identified at the end of the landslide susceptibility study ofthe basin that medium level susceptible zones display the highestdistribution with 56 % ratio (14284 ha followed by high (6972 ha - 28 %and very high (611 ha – 2 % level susceptible zones with 30 % and low3288 ha – 13 % and very low (67 ha – 1 % level susceptible zones with14 %. It was determined that potential risk zones are concentratedaround slopes overlooking north where relief and precipitation values arehigh, mountain and slope morphology is dominant and vegetation

  3. GIS Based Measurement and Regulatory Zoning of Urban Ecological Vulnerability

    Directory of Open Access Journals (Sweden)

    Xiaorui Zhang

    2015-07-01

    Full Text Available Urban ecological vulnerability is measured on the basis of ecological sensitivity and resilience based on the concept analysis of vulnerability. GIS-based multicriteria decision analysis (GIS-MCDA methods are used, supported by the spatial analysis tools of GIS, to define different levels of vulnerability for areas of the urban ecology. These areas are further classified into different types of regulatory zones. Taking the city of Hefei in China as the empirical research site, this study uses GIS-MCDA, including the index system, index weights and overlay rules, to measure the degree of its ecological vulnerability on the GIS platform. There are eight indices in the system. Raking and analytical hierarchy process (AHP methods are used to calculate index weights according to the characteristics of the index system. The integrated overlay rule, including selection of the maximum value, and weighted linear combination (WLC are applied as the overlay rules. In this way, five types of vulnerability areas have been classified as follows: very low vulnerability, low vulnerability, medium vulnerability, high vulnerability and very high vulnerability. They can be further grouped into three types of regulatory zone of ecological green line, ecological grey line and ecological red line. The study demonstrates that ecological green line areas are the largest (53.61% of the total study area and can be intensively developed; ecological grey line areas (19.59% of the total area can serve as the ecological buffer zone, and ecological red line areas (26.80% cannot be developed and must be protected. The results indicate that ecological green line areas may provide sufficient room for future urban development in Hefei city. Finally, the respective regulatory countermeasures are put forward. This research provides a scientific basis for decision-making around urban ecological protection, construction and sustainable development. It also provides theoretical method

  4. A logical framework for ranking landslide inventory maps

    Science.gov (United States)

    Santangelo, Michele; Fiorucci, Federica; Bucci, Francesco; Cardinali, Mauro; Ardizzone, Francesca; Marchesini, Ivan; Cesare Mondini, Alessandro; Reichenbach, Paola; Rossi, Mauro; Guzzetti, Fausto

    2014-05-01

    Landslides inventory maps are essential for quantitative landslide hazard and risk assessments, and for geomorphological and ecological studies. Landslide maps, including geomorphological, event based, multi-temporal, and seasonal inventory maps, are most commonly prepared through the visual interpretation of (i) monoscopic and stereoscopic aerial photographs, (ii) satellite images, (iii) LiDAR derived images, aided by more or less extensive field surveys. Landslide inventory maps are the basic information for a number of different scientific, technical and civil protection purposes, such as: (i) quantitative geomorphic analyses, (ii) erosion studies, (iii) deriving landslide statistics, (iv) urban development planning (v) landslide susceptibility, hazard and risk evaluation, and (vi) landslide monitoring systems. Despite several decades of activity in landslide inventory making, still no worldwide-accepted standards, best practices and protocols exist for the ranking and the production of landslide inventory maps. Standards for the preparation (and/or ranking) of landslide inventories should indicate the minimum amount of information for a landslide inventory map, given the scale, the type of images, the instrumentation available, and the available ancillary data. We recently attempted at a systematic description and evaluation of a total of 22 geomorphological inventories, 6 multi-temporal inventories, 10 event inventories, and 3 seasonal inventories, in the scale range between 1:10,000 and 1:500,000, prepared for areas in different geological and geomorphological settings. All of the analysed inventories were carried out by using image interpretation techniques, or field surveys. Firstly, a detailed characterisation was performed for each landslide inventory, mainly collecting metadata related (i) to the amount of information used for preparing the landslide inventory (i.e. images used, instrumentation, ancillary data, digitalisation method, legend, validation

  5. An open source GIS-based tool to integrate the fragmentation mechanism in rockfall propagation

    Science.gov (United States)

    Matas, Gerard; Lantada, Nieves; Gili, Josep A.; Corominas, Jordi

    2015-04-01

    Rockfalls are frequent instability processes in road cuts, open pit mines and quarries, steep slopes and cliffs. Even though the stability of rock slopes can be determined using analytical approaches, the assessment of large rock cliffs require simplifying assumptions due to the difficulty of working with a large amount of joints, the scattering of both the orientations and strength parameters. The attitude and persistency of joints within the rock mass define the size of kinematically unstable rock volumes. Furthermore the rock block will eventually split in several fragments during its propagation downhill due its impact with the ground surface. Knowledge of the size, energy, trajectory… of each block resulting from fragmentation is critical in determining the vulnerability of buildings and protection structures. The objective of this contribution is to present a simple and open source tool to simulate the fragmentation mechanism in rockfall propagation models and in the calculation of impact energies. This tool includes common modes of motion for falling boulders based on the previous literature. The final tool is being implemented in a GIS (Geographic Information Systems) using open source Python programming. The tool under development will be simple, modular, compatible with any GIS environment, open source, able to model rockfalls phenomena correctly. It could be used in any area susceptible to rockfalls with a previous adjustment of the parameters. After the adjustment of the model parameters to a given area, a simulation could be performed to obtain maps of kinetic energy, frequency, stopping density and passing heights. This GIS-based tool and the analysis of the fragmentation laws using data collected from recent rockfall have being developed within the RockRisk Project (2014-2016). This project is funded by the Spanish Ministerio de Economía y Competitividad and entitled "Rockfalls in cliffs: risk quantification and its prevention"(BIA2013-42582-P).

  6. A GIS-BASED ENVIRONMENTAL HEALTH INFORMATION SOURCE FOR MALAYSIAN CONTEXT

    Directory of Open Access Journals (Sweden)

    Lau Tiu Chung

    2013-04-01

    Full Text Available In this paper, we propose a GIS-based system for collection and targeted distribution of latest alerts and real-time environmental factors to the Malaysian population. We call it the Environmental Health Management System (EHMS. This GIS-based system is designed to facilitate and encourage research into environmental health quality issues by providing a comprehensive tracking and monitoring tool. This GIS-based system is embedded with Google Maps API and Geocoding API services to visualize the location and environmental health reports from the aggregated online newspaper and social media news feeds. We introduce the design and implementation of EHMS, including the web frontend, backend, ontology, database, data acquisition, classification engine, and the standard news feeds.

  7. The use of GIS-based support of recreational trail planning by local governments

    DEFF Research Database (Denmark)

    Olafsson, Anton Stahl; Skov-Petersen, Hans

    2014-01-01

    In the last decade, multiple GIS-based planning support systems have been developed in order to improve the basis for spatial planning. Recent research has focused on problems regarding a lack of utilisation or barriers to the use of advanced GIS and GIS-based planning support systems in planning...... applications. This paper discusses these research findings in the context of outdoor recreational planning by local governments in Denmark. According to a national survey of municipal planners, GIS-based planning support is widely used in Denmark, but more GIS is needed and is being requested for local outdoor...... recreation planning. However, considerable differences exist between the ways municipalities assess their need for and use of GIS planning support. These differences are explored in more detail using a factor analysis of planning variables and uses of GIS. Three situations are described: 1) extensive network...

  8. Global Landslide Catalog Export

    Data.gov (United States)

    National Aeronautics and Space Administration — The Global Landslide Catalog (GLC) was developed with the goal of identifying rainfall-triggered landslide events around the world, regardless of size, impacts or...

  9. Global Landslide Hazard Distribution

    Data.gov (United States)

    National Aeronautics and Space Administration — Global Landslide Hazard Distribution is a 2.5 minute grid of global landslide and snow avalanche hazards based upon work of the Norwegian Geotechnical Institute...

  10. Experience in landslide control

    Energy Technology Data Exchange (ETDEWEB)

    Koz' min, L S

    1983-06-01

    The problems of slope stability in the Krasnoyarskugol' surface mines are discussed. Methods used for slide prevention and slide control from 1977 to 1982 are analyzed. Landslides were caused by weathering of the argillite layer in the coal seam roof. Sliding plane was parallel to the coal seam roof. At a later stage of landslide prevention sliding planes were in the coal seam floor (which consisted of weak rock layers). Range of landslides was evaluated. Losses caused by landslides were discussed: working time losses, losses of coal, damaged equipment. Landslide hazards were controlled by reducing slope angle and by changing cut geometry. Cross section of the cut with a spoil bank prone to landslides is shown in a scheme. Reducing angle of slope inclination, using strong rock layers as the spoil bank base and changing cut geometry eliminated landslides in 1982. Recommendations on landslide control in coal surface mines with layers of weak rocks influenced by weathering are made.

  11. LANDSLIDES IN SUCEAVA COUNTY

    Directory of Open Access Journals (Sweden)

    Dan Zarojanu

    2017-07-01

    Full Text Available In the county of Suceava, the landslides are a real and permanent problem. This paper presents the observations of landslides over the last 30 years in Suceava County, especially their morphology, theirs causes and the landslide stopping measures. It presents also several details regarding the lanslides from the town of Suceava, of Frasin and the village of Brodina.

  12. A GIS-based framework for evaluating investments in fire management: Spatial allocation of recreation values

    Science.gov (United States)

    Kenneth A. Baerenklau; Armando González-Cabán; Catrina I. Páez; Edgard Chávez

    2009-01-01

    The U.S. Forest Service is responsible for developing tools to facilitate effective and efficient fire management on wildlands and urban-wildland interfaces. Existing GIS-based fire modeling software only permits estimation of the costs of fire prevention and mitigation efforts as well as the effects of those efforts on fire behavior. This research demonstrates how the...

  13. Major risk from rapid, large-volume landslides in Europe (EU Project RUNOUT)

    Science.gov (United States)

    Kilburn, Christopher R. J.; Pasuto, Alessandro

    2003-08-01

    Project RUNOUT has investigated methods for reducing the risk from large-volume landslides in Europe, especially those involving rapid rates of emplacement. Using field data from five test sites (Bad Goisern and Köfels in Austria, Tessina and Vajont in Italy, and the Barranco de Tirajana in Gran Canaria, Spain), the studies have developed (1) techniques for applying geomorphological investigations and optical remote sensing to map landslides and their evolution; (2) analytical, numerical, and cellular automata models for the emplacement of sturzstroms and debris flows; (3) a brittle-failure model for forecasting catastrophic slope failure; (4) new strategies for integrating large-area Global Positioning System (GPS) arrays with local geodetic monitoring networks; (5) methods for raising public awareness of landslide hazards; and (6) Geographic Information System (GIS)-based databases for the test areas. The results highlight the importance of multidisciplinary studies of landslide hazards, combining subjects as diverse as geology and geomorphology, remote sensing, geodesy, fluid dynamics, and social profiling. They have also identified key goals for an improved understanding of the physical processes that govern landslide collapse and runout, as well as for designing strategies for raising public awareness of landslide hazards and for implementing appropriate land management policies for reducing landslide risk.

  14. Defining Primary Care Shortage Areas: Do GIS-based Measures Yield Different Results?

    Science.gov (United States)

    Daly, Michael R; Mellor, Jennifer M; Millones, Marco

    2018-02-12

    To examine whether geographic information systems (GIS)-based physician-to-population ratios (PPRs) yield determinations of geographic primary care shortage areas that differ from those based on bounded-area PPRs like those used in the Health Professional Shortage Area (HPSA) designation process. We used geocoded data on primary care physician (PCP) locations and census block population counts from 1 US state to construct 2 shortage area indicators. The first is a bounded-area shortage indicator defined without GIS methods; the second is a GIS-based measure that measures the populations' spatial proximity to PCP locations. We examined agreement and disagreement between bounded shortage areas and GIS-based shortage areas. Bounded shortage area indicators and GIS-based shortage area indicators agree for the census blocks where the vast majority of our study populations reside. Specifically, 95% and 98% of the populations in our full and urban samples, respectively, reside in census blocks where the 2 indicators agree. Although agreement is generally high in rural areas (ie, 87% of the rural population reside in census blocks where the 2 indicators agree), agreement is significantly lower compared to urban areas. One source of disagreement suggests that bounded-area measures may "overlook" some shortages in rural areas; however, other aspects of the HPSA designation process likely mitigate this concern. Another source of disagreement arises from the border-crossing problem, and it is more prevalent. The GIS-based PPRs we employed would yield shortage area determinations that are similar to those based on bounded-area PPRs defined for Primary Care Service Areas. Disagreement rates were lower than previous studies have found. © 2018 National Rural Health Association.

  15. A GIS-based disaggregate spatial watershed analysis using RADAR data

    International Nuclear Information System (INIS)

    Al-Hamdan, M.

    2002-01-01

    Hydrology is the study of water in all its forms, origins, and destinations on the earth.This paper develops a novel modeling technique using a geographic information system (GIS) to facilitate watershed hydrological routing using RADAR data. The RADAR rainfall data, segmented to 4 km by 4 km blocks, divides the watershed into several sub basins which are modeled independently. A case study for the GIS-based disaggregate spatial watershed analysis using RADAR data is provided for South Fork Cowikee Creek near Batesville, Alabama. All the data necessary to complete the analysis is maintained in the ArcView GIS software. This paper concludes that the GIS-Based disaggregate spatial watershed analysis using RADAR data is a viable method to calculate hydrological routing for large watersheds. (author)

  16. GIS-based Approaches to Catchment Area Analyses of Mass Transit

    DEFF Research Database (Denmark)

    Andersen, Jonas Lohmann Elkjær; Landex, Alex

    2009-01-01

    Catchment area analyses of stops or stations are used to investigate potential number of travelers to public transportation. These analyses are considered a strong decision tool in the planning process of mass transit especially railroads. Catchment area analyses are GIS-based buffer and overlay...... analyses with different approaches depending on the desired level of detail. A simple but straightforward approach to implement is the Circular Buffer Approach where catchment areas are circular. A more detailed approach is the Service Area Approach where catchment areas are determined by a street network...... search to simulate the actual walking distances. A refinement of the Service Area Approach is to implement additional time resistance in the network search to simulate obstacles in the walking environment. This paper reviews and compares the different GIS-based catchment area approaches, their level...

  17. Technical Potential Assessment for the Renewable Energy Zone (REZ) Process: A GIS-Based Approach

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Nathan [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Roberts, Billy J [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2018-04-05

    Geographic Information Systems (GIS)-based energy resource and technical potential assessments identify areas capable of supporting high levels of renewable energy (RE) development as part of a Renewable Energy Zone (REZ) Transmission Planning process. This document expands on the REZ Process to aid practitioners in conducting GIS-based RE resource and technical potential assessments. The REZ process is an approach to plan, approve, and build transmission infrastructure that connects REZs - geographic areas that have high-quality RE resources, suitable topography and land-use designations, and demonstrated developer interest - to the power system. The REZ process helps to increase the share of solar photovoltaic (PV), wind, and other resources while also maintaining reliability and economics.

  18. Assessment of landslide distribution map reliability in Niigata prefecture - Japan using frequency ratio approach

    Science.gov (United States)

    Rahardianto, Trias; Saputra, Aditya; Gomez, Christopher

    2017-07-01

    Research on landslide susceptibility has evolved rapidly over the few last decades thanks to the availability of large databases. Landslide research used to be focused on discreet events but the usage of large inventory dataset has become a central pillar of landslide susceptibility, hazard, and risk assessment. Indeed, extracting meaningful information from the large database is now at the forth of geoscientific research, following the big-data research trend. Indeed, the more comprehensive information of the past landslide available in a particular area is, the better the produced map will be, in order to support the effective decision making, planning, and engineering practice. The landslide inventory data which is freely accessible online gives an opportunity for many researchers and decision makers to prevent casualties and economic loss caused by future landslides. This data is advantageous especially for areas with poor landslide historical data. Since the construction criteria of landslide inventory map and its quality evaluation remain poorly defined, the assessment of open source landslide inventory map reliability is required. The present contribution aims to assess the reliability of open-source landslide inventory data based on the particular topographical setting of the observed area in Niigata prefecture, Japan. Geographic Information System (GIS) platform and statistical approach are applied to analyze the data. Frequency ratio method is utilized to model and assess the landslide map. The outcomes of the generated model showed unsatisfactory results with AUC value of 0.603 indicate the low prediction accuracy and unreliability of the model.

  19. Evaluating the Implementation and Effectiveness of GIS-Based Application in Secondary School Geography Lessons

    OpenAIRE

    Ali Ali

    2008-01-01

    The purpose of the study was to investigate the barriers preventing the use of Geographic Information Systems (GIS) in secondary school geography lessons and to determine its effectiveness on students success. A workshop focusing on ways to implement GIS-based application in the classroom for 14 teachers from nine high schools was conducted in 2006. The teachers were given GIS software, digital data for an application, and the necessary written documents describing the application. Due to var...

  20. IMPLEMENTATION OF GIS-BASED MULTICRITERIA DECISION ANALYSIS WITH VB IN ArcGIS

    OpenAIRE

    DERYA OZTURK; FATMAGUL BATUK

    2011-01-01

    This article focuses on the integration of multicriteria decision analysis (MCDA) and geographical information systems (GIS) and introduces a tool, GIS–MCDA, written in visual basic in ArcGIS for GIS-based MCDA. The GIS–MCDA deals with raster-based data sets and includes standardization, weighting and decision analysis methods, and sensitivity analysis. Simple additive weighting, weighted product method, technique for order preference by similarity to ideal solution, compromise programming, a...

  1. Integrating spatial, temporal, and size probabilities for the annual landslide hazard maps in the Shihmen watershed, Taiwan

    Directory of Open Access Journals (Sweden)

    C. Y. Wu

    2013-09-01

    Full Text Available Landslide spatial, temporal, and size probabilities were used to perform a landslide hazard assessment in this study. Eleven intrinsic geomorphological, and two extrinsic rainfall factors were evaluated as landslide susceptibility related factors as they related to the success rate curves, landslide ratio plots, frequency distributions of landslide and non-landslide groups, as well as probability–probability plots. Data on landslides caused by Typhoon Aere in the Shihmen watershed were selected to train the susceptibility model. The landslide area probability, based on the power law relationship between the landslide area and a noncumulative number, was analyzed using the Pearson type 5 probability density function. The exceedance probabilities of rainfall with various recurrence intervals, including 2, 5, 10, 20, 50, 100 and 200 yr, were used to determine the temporal probabilities of the events. The study was conducted in the Shihmen watershed, which has an area of 760 km2 and is one of the main water sources for northern Taiwan. The validation result of Typhoon Krosa demonstrated that this landslide hazard model could be used to predict the landslide probabilities. The results suggested that integration of spatial, area, and exceedance probabilities to estimate the annual probability of each slope unit is feasible. The advantage of this annual landslide probability model lies in its ability to estimate the annual landslide risk, instead of a scenario-based risk.

  2. Methodology for a GIS-based damage assessment for researchers following large scale disasters

    Science.gov (United States)

    Crawford, Patrick Shane

    The 1990s were designated the International Decade for Natural Disaster Reduction by the United Nations General Assembly. This push for decrease of loss of life, property destruction, and social and economic disruption brought advancements in disaster management, including damage assessment. Damage assessment in the wake of natural and manmade disasters is a useful tool for government agencies, insurance companies, and researchers. As technologies evolve damage assessment processes constantly evolve as well. Alongside the advances in Geographic Information Systems (GIS), remote sensing, and Global Positioning System (GPS) technology, as well as the growing awareness of the needs of a standard operating procedure for GIS-based damage assessment and a need to make the damage assessment process as quick and accurate as possible, damage assessment procedures are becoming easier to execute and the results are becoming more accurate and robust. With these technological breakthroughs, multi-disciplinary damage assessment reconnaissance teams have become more efficient in their assessment methods through better organization and more robust through addition of new datasets. Damage assessment personnel are aided by software tools that offer high-level analysis and increasingly rapid damage assessment methods. GIS software has advanced the damage assessment methods of these teams by combining remotely sensed aerial imagery, GPS, and other technologies to expand the uses of the data. GIS allows researchers to use aerial imagery to show field collected data in the geographic location that it was collected so that information can be revisited, measurements can be taken, and data can be disseminated to other researchers and the public. The GIS-based data available to the reconnaissance team includes photographs of damage, worksheets, calculations, voice messages collected while studying the affected area, and many other datasets which are based on the type of disaster and the

  3. Mechanisms of Forest Restoration in Landslide Treatment Areas

    Directory of Open Access Journals (Sweden)

    Yi-Chang Chen

    2014-09-01

    Full Text Available Reforestation after a landslide facilitates competition between herbaceous plants and arborous plants. Tangible variations in grassland areas in regions susceptible to landslides can only be found within collections of trees. A landslide area in the Sule Watershed was investigated. Relative illuminance results reveal that the Rhodes grass (Chloris gayana Kunth biomass in this landslide area increases with relative illuminance. A comparison of regions with tree islands indicates that the size of the grassland areas decreased and the number of tree islands increased during 2005–2010. Furthermore, a germination experiment in a soil-seed bank indicates that more woody plant species exist around the tree island than in other areas in the landslide region. Trees in a tree island change the micro-climate of the landslide region, and they gather as many nutrients and as much moisture as possible, enabling vegetation to expand around the tree island. Additionally, the area with Rhodes grass and its biomass declined annually in the tree island region. Investigation results show that tree islands and soil-seed banks are suited to reforestation in landslide regions. The pioneering research will assist regional landslide management in Taiwan.

  4. Assessing landslide exposure in areas with limited landslide information

    NARCIS (Netherlands)

    Pellicani, R.; van Westen, C.J.; Spilotro, G.

    2014-01-01

    Landslide risk assessment is often a difficult task due to the lack of temporal data on landslides and triggering events (frequency), run-out distance, landslide magnitude and vulnerability. The probability of occurrence of landslides is often very difficult to predict, as well as the expected

  5. The preparation of landslide map by Landslide Numerical Risk Factor (LNRF model and Geographic Information System (GIS

    Directory of Open Access Journals (Sweden)

    Ali Mohammadi Torkashvand

    2014-12-01

    Full Text Available One of the risks to threaten mountainous areas is that hillslope instability caused damage to lands. One of the most dangerous instabilities is mass movement and much movement occurs due to slip. The aim of this study is zonation of landslide hazards in a basin of the Ardebil province, the eastern slopes of Sabalan, Iran. Geological and geomorphologic conditions, climate and type of land use have caused susceptibility of this watershed to landslides. Firstly, maps of the main factors affecting landslide occurrence including slope, distance from faults, lithology, elevation and precipitation were prepared and digitized. Then, by using interpretation of aerial photos and satellite images and field views, the ground truth map of landslides was prepared. Each basic layer (factor and landslide map were integrated to compute the numeric value of each factor with the help of a Landslide Numerical Risk Factor (LNRF model and landslide occurrence percent obtained in different units from each of the maps. Finally, with overlapping different data layers, a landslide hazard zonation map was prepared. Results showed that 67.85% of the basin has high instability, 7.76% moderate instability and 24.39% low instability.

  6. GEOSTATISTICAL BASED SUSCEPTIBILITY MAPPING OF SOIL EROSION AND OPTIMIZATION OF ITS CAUSATIVE FACTORS: A CONCEPTUAL FRAMEWORK

    Directory of Open Access Journals (Sweden)

    ABDULKADIR T. SHOLAGBERU

    2017-11-01

    Full Text Available Soil erosion hazard is the second biggest environmental challenges after population growth causing land degradation, desertification and water deterioration. Its impacts on watersheds include loss of soil nutrients, reduced reservoir capacity through siltation which may lead to flood risk, landslide, high water turbidity, etc. These problems become more pronounced in human altered mountainous areas through intensive agricultural activities, deforestation and increased urbanization among others. However, due to challenging nature of soil erosion management, there is great interest in assessing its spatial distribution and susceptibility levels. This study is thus intend to review the recent literatures and develop a novel framework for soil erosion susceptibility mapping using geostatistical based support vector machine (SVM, remote sensing and GIS techniques. The conceptual framework is to bridge the identified knowledge gaps in the area of causative factors’ (CFs selection. In this research, RUSLE model, field studies and the existing soil erosion maps for the study area will be integrated for the development of inventory map. Spatial data such as Landsat 8, digital soil and geological maps, digital elevation model and hydrological data shall be processed for the extraction of erosion CFs. GISbased SVM techniques will be adopted for the establishment of spatial relationships between soil erosion and its CFs, and subsequently for the development of erosion susceptibility maps. The results of this study include evaluation of predictive capability of GIS-based SVM in soil erosion mapping and identification of the most influential CFs for erosion susceptibility assessment. This study will serve as a guide to watershed planners and to alleviate soil erosion challenges and its related hazards.

  7. Use of GIS-Based Sampling to Inform Food Security Assessments and Decision Making in Kenya

    Science.gov (United States)

    Wahome, A.; Ndubi, A. O.; Ndungu, L. W.; Mugo, R. M.; Flores Cordova, A. I.

    2017-12-01

    Kenya relies on agricultural production for supporting local consumption and other processing value chains. With changing climate in a rain-fed dependent agricultural production system, cropping zones are shifting and proper decision making will require updated data. Where up-to-date data is not available it is important that it is generated and passed over to relevant stakeholders to inform their decision making. The process of generating this data should be cost effective and less time consuming. The Kenyan State Department of Agriculture (SDA) runs an insurance programme for maize farmers in a number of counties in Kenya. Previously, SDA was using a list of farmers to identify the crop fields for this insurance programme. However, the process of listing of all farmers in each Unit Area of Insurance (UAI) proved to be tedious and very costly, hence need for an alternative approach, but acceptable sampling methodology. Building on the existing cropland maps, SERVIR, a joint NASA-USAID initiative that brings Earth observations (EO) for improved environmental decision making in developing countries, specifically its hub in Eastern and Soutehrn Africa developed a High Resolution Map based on 10m Sentinel satellite images from which a GIS based sampling frame for identifying maize fields was developed. Sampling points were randomly generated in each UAI and navigated to using hand-held GPS units for identification of maize farmers. In the GIS-based identification of farmers SDA uses 1 day to cover an area covered in 1 week by list identification of farmers. Similarly, SDA spends approximately 3,000 USD per sub-county to locate maize fields using GIS-based sampling as compared 10,000 USD they used to spend before. This has resulted in 70% cost reduction.

  8. Evaluation of AirGIS: a GIS-based air pollution and human exposure modelling system

    DEFF Research Database (Denmark)

    Ketzel, Matthias; Berkowicz, Ruwim; Hvidberg, Martin

    2011-01-01

    This study describes in brief the latest extensions of the Danish Geographic Information System (GIS)-based air pollution and human exposure modelling system (AirGIS), which has been developed in Denmark since 2001 and gives results of an evaluation with measured air pollution data. The system...... shows, in general, a good performance for both long-term averages (annual and monthly averages), short-term averages (hourly and daily) as well as when reproducing spatial variation in air pollution concentrations. Some shortcomings and future perspectives of the system are discussed too....

  9. A GIS-based method for household recruitment in a prospective pesticide exposure study

    Directory of Open Access Journals (Sweden)

    Phillips Michael J

    2008-04-01

    Full Text Available Abstract Background Recent advances in GIS technology and remote sensing have provided new opportunities to collect ecologic data on agricultural pesticide exposure. Many pesticide studies have used historical or records-based data on crops and their associated pesticide applications to estimate exposure by measuring residential proximity to agricultural fields. Very few of these studies collected environmental and biological samples from study participants. One of the reasons for this is the cost of identifying participants who reside near study fields and analyzing samples obtained from them. In this paper, we present a cost-effective, GIS-based method for crop field selection and household recruitment in a prospective pesticide exposure study in a remote location. For the most part, our multi-phased approach was carried out in a research facility, but involved two brief episodes of fieldwork for ground truthing purposes. This method was developed for a larger study designed to examine the validity of indirect pesticide exposure estimates by comparing measured exposures in household dust, water and urine with records-based estimates that use crop location, residential proximity and pesticide application data. The study focused on the pesticide atrazine, a broadleaf herbicide used in corn production and one of the most widely-used pesticides in the U.S. Results We successfully used a combination of remotely-sensed data, GIS-based methods and fieldwork to select study fields and recruit participants in Illinois, a state with high corn production and heavy atrazine use. Our several-step process consisted of the identification of potential study fields and residential areas using aerial photography; verification of crop patterns and land use via site visits; development of a GIS-based algorithm to define recruitment areas around crop fields; acquisition of geocoded household-level data within each recruitment area from a commercial vendor; and

  10. Landslides of Palestinian Region

    Science.gov (United States)

    Alwahsh, H.

    2013-12-01

    Natural disasters are extreme sudden events caused by environmental and natural actors that take away the lives of many thousands of people each year and damage large amount of properties. They strike anywhere on earth, often without any warning. A risk maps of natural disaster are very useful to identify the places that might be adversely affected in the event of natural disaster. The earthquakes are one of natural disaster that have the greatest hazards and will cause loss of life and properties due to damaging the structures of building, dams, bridges. In addition, it will affect local geology and soil conditions. The site effects play an important role in earthquake risk because of its amplification or damping simulation. Another parameter in developing risk map is landslide, which is also one of the most important topics in site effect hazards. Palestine region has been suffering landslide hazards because of the topographical and geological conditions of this region. Most Palestine consists of mountainous area, which has great steep slopes and the type of soil is mainly grayish to yellowish silty clay (Marl Soil). Due to the above mentioned factors many landslides have been occurred from Negev south to the northern borders of Palestine. An example of huge and destruction landslide in a Palestine authority is the landslide in the White Mountain area in the city of Nablus, which occurred in 1997. The geotechnical and geophysical investigation as well as slope stability analysis should be considered in making landslide maps that are necessary to develop risk levels of the natural disaster. Landslides occurred in slopes that are created naturally or by human beings. Failure of soil mass occurs, and hence landslide of soil mass happen due to sliding of soil mass along a plane or curved surface. In general, the slopes become unstable when the shear stresses (driving force) generated in the soil mass exceed the available shearing resistance on the rupture surface

  11. Assessment of landslide risk using gis and statistical methods in kysuce region

    Directory of Open Access Journals (Sweden)

    Barančoková Mária

    2014-03-01

    Full Text Available The landslide susceptibility was assessed based on multivariation analysis. The input parameters were represented by lithology, land use, slope inclination and average annual precipitation. These parameters were evaluated as independent variables, and the existing landslides as dependent variables. The individual input parameters were reclassified and spatially adjusted. Spatial analysis resulted in 15 988 combinations of input parameters representing the homogeneous condition unit (HCU . Based on the landslide density within individual units, the HCU polygons have been classified according to landslide risk into stable, conditionally stable, conditionally stable and unstable (subdivided into low, medium and high landslide risk. A total of 2002 HCU s were affected by landslides, and the remaining 13 986 were not affected. The total HCU area affected by landslides is about 156.92 km2 (20.1%. Stable areas covered 623.01 km2 (79.8%, and conditionally stable areas covered 228.77 km2 (29.33% out of this area. Unstable areas were divided into three levels of landslide risk - low, medium and high risk. An area of 111.19 km2 (14.3% represents low landslide risk, medium risk 29.7 km2 (3.8% and 16.01 km2 (2% represents high risk. Since Zlín Formation lithological unit covers approximately one-third of the study area, it also influences the overall landslide risk assessment. This lithological formation covers the largest area within all landslide risk classes as well as in conditionally stable areas. The most frequent slope class was in the range of 14-19. The higher susceptibility of Zlín Formation to landslides is caused mainly by different geomorphological value of claystone and sandstone sequence. The higher share of claystone results in higher susceptibility of this formation to exogenous degradation processes.

  12. GIS-based biomass resource utilization for rice straw cofiring in the Taiwanese power market

    International Nuclear Information System (INIS)

    Hu, Ming-Che; Huang, An-Lei; Wen, Tzai-Hung

    2013-01-01

    Rice straw, a rich agricultural byproduct in Taiwan, can be used as biomass feedstock for cofiring systems. In this study, we analyzed the penetration of rice straw cofiring systems in the Taiwanese power market. In the power generation system, rice straw is cofired with fossil fuel in existing electricity plants. The benefits of cofiring systems include increasing the use of renewable energy, decreasing the fuel cost, and lowering greenhouse gas emissions. We established a linear complementarity model to simulate the power market equilibrium with cofiring systems in Taiwan. GIS-based analysis was then used to analyze the geospatial relationships between paddy rice farms and power plants to assess potential biomass for straw-power generation. Additionally, a sensitivity analysis of the biomass feedstock supply system was conducted for various cofiring scenarios. The spatial maps and equilibrium results of rice straw cofiring in Taiwanese power market are presented in the paper. - Highlights: ► The penetration of straw cofiring systems in the power market is analyzed. ► GIS-based analysis assesses potential straw-power generation. ► The spatial maps and equilibrium results of rice straw cofiring are presented

  13. GIS-based rare events logistic regression for mineral prospectivity mapping

    Science.gov (United States)

    Xiong, Yihui; Zuo, Renguang

    2018-02-01

    Mineralization is a special type of singularity event, and can be considered as a rare event, because within a specific study area the number of prospective locations (1s) are considerably fewer than the number of non-prospective locations (0s). In this study, GIS-based rare events logistic regression (RELR) was used to map the mineral prospectivity in the southwestern Fujian Province, China. An odds ratio was used to measure the relative importance of the evidence variables with respect to mineralization. The results suggest that formations, granites, and skarn alterations, followed by faults and aeromagnetic anomaly are the most important indicators for the formation of Fe-related mineralization in the study area. The prediction rate and the area under the curve (AUC) values show that areas with higher probability have a strong spatial relationship with the known mineral deposits. Comparing the results with original logistic regression (OLR) demonstrates that the GIS-based RELR performs better than OLR. The prospectivity map obtained in this study benefits the search for skarn Fe-related mineralization in the study area.

  14. Landslides Mapped from LIDAR Imagery, Kitsap County, Washington

    Science.gov (United States)

    McKenna, Jonathan P.; Lidke, David J.; Coe, Jeffrey A.

    2008-01-01

    Landslides are a recurring problem on hillslopes throughout the Puget Lowland, Washington, but can be difficult to identify in the densely forested terrain. However, digital terrain models of the bare-earth surface derived from LIght Detection And Ranging (LIDAR) data express topographic details sufficiently well to identify landslides. Landslides and escarpments were mapped using LIDAR imagery and field checked (when permissible and accessible) throughout Kitsap County. We relied almost entirely on derivatives of LIDAR data for our mapping, including topographic-contour, slope, and hill-shaded relief maps. Each mapped landslide was assigned a level of 'high' or 'moderate' confidence based on the LIDAR characteristics and on field observations. A total of 231 landslides were identified representing 0.8 percent of the land area of Kitsap County. Shallow debris topples along the coastal bluffs and large (>10,000 m2) landslide complexes are the most common types of landslides. The smallest deposit mapped covers an area of 252 m2, while the largest covers 0.5 km2. Previous mapping efforts that relied solely on field and photogrammetric methods identified only 57 percent of the landslides mapped by LIDAR (61 percent high confidence and 39 percent moderate confidence), although nine landslides previously identified were not mapped during this study. The remaining 43 percent identified using LIDAR have 13 percent high confidence and 87 percent moderate confidence. Coastal areas are especially susceptible to landsliding; 67 percent of the landslide area that we mapped lies within 500 meters of the present coastline. The remaining 33 percent are located along drainages farther inland. The LIDAR data we used for mapping have some limitations including (1) rounding of the interface area between low slope surfaces and vertical faces (that is, along the edges of steep escarpments) which results in scarps being mapped too far headward (one or two meters), (2) incorrect laser

  15. Development of potential map for landslides by comparing instability indices of various time periods

    Science.gov (United States)

    Chiang, Jie-Lun; Tian, Yu-Qing; Chen, Yie-Ruey; Tsai, Kuang-Jung

    2017-04-01

    In recent years, extreme rainfall events occur frequently and induced serious landslides and debris flow disasters in Taiwan. The instability indices will differ when using landslide maps of different time periods. We analyzed the landslide records during the period year, 2008 2012, the landslide area contributed 0.42% 2.94% of the total watershed area, the 2.94% was caused by the typhoon Morakot in August, 2009, which brought massive rainfall in which the cumulative maximum rainfall was up to 2900 mm. We analyzed the instability factors including elevation, slope, aspect, soil, and geology. And comparing the instability indices by using individual landslide map of 2008 2012, the landslide maps of the union of the five years, and interaction of the five years. The landslide area from union of the five years contributed 3.71%,the landslide area from interaction of the five years contributed 0.14%. In this study, Kriging was used to establish the susceptibility map in selected watershed. From interaction of the five years, we found the instability index above 4.3 can correspond to those landslide records. The potential landslide area of the selected watershed, where collapses occur more likely, belongs to high level and medium-high level; the area is 13.43% and 3.04% respectively.

  16. Rainfall-induced landslides in Europe: hotspots and thresholds (Invited)

    Science.gov (United States)

    Cepeda, J.; Jaedicke, C.; Nadim, F.; Kalsnes, B.

    2010-12-01

    This contribution presents preliminary results of the European project SafeLand. SafeLand is a large-scale integrating collaborative research project on landslide risks in Europe, funded by the Seventh Framework Programme for research and technological development (FP7) of the European Commission. SafeLand was launched in May 2009 and will run for three years. The project team, which comprises 27 institutions from 12 European countries, is coordinated by the International Centre for Geohazards (ICG) in Norway. SafeLand aims to develop and implement an integrated and comprehensive approach to help and guide decision-making in connection with mitigation of landslide risks. Quantifying the effects of global change (changes in demography and climate change) on evolution of landslide risk in Europe is one of the main goals of SafeLand. The methodologies are tested in selected hazard and risk "hotspots” in Europe, in turn improving knowledge, methodologies and integration strategies for the management of landslide risk. The present contribution is focused on two components of SafeLand: (1) the identification of landslide hazard and risk hotspots and (2) the estimation and assessment of rainfall thresholds for triggering of landslides. Hotspots of landslide hazard and risk were identified by an objective GIS-based analysis. The results show clearly where landslide pose the largest hazard in Europe and the objective approach allows a ranking of the countries by exposed area and population. In absolute numbers, Italy is the country with the highest amount of area and population exposed. Relative to absolute number of inhabitants and area, small alpine countries such as Lichtenstein and Montenegro score highest where as much as 40% of the population could be exposed. It is obvious that the type and quality of the input data are decisive for the quality of the results. Especially the estimation of extreme precipitation events needs improvement. These preliminary results are

  17. Gis-based assessment of marine oil spill hazard and environmental vulnerability for the coasts of Crete in South Aegean Sea

    Science.gov (United States)

    Spanoudaki, Katerina; Nikiforakis, Ioannis K.; Kampanis, Nikolaos A.

    2017-04-01

    Developing effective early warning and coordination systems can save thousands of lives and protect people, property and the environment in the event of natural and man-made disasters. In its document "Towards Better Protection of Citizens against Disaster Risks: Strengthening Early Warning Systems in Europe", the Commission points out that it seeks to follow a multi-hazard approach, to develop near real time alert systems, to ensure a near real time dissemination of alerts to Participating States, and to improve its rapid analytical capacity. In this context, the EU project DECATASTROPHIZE (http://decatastrophize.eu/project/) co-financed by the EU Humanitarian Aid and Civil Protection aims to develop a Geospatial Early warning Decision Support System (GE-DSS) to assess, prepare for and respond to multiple and/or simultaneous natural and man-made hazards, disasters, and environmental incidents by using existing models/systems in each partner country (Cyprus, France, Greece, Italy and Spain) in a synergistic way on ONE multi-platform, called DECAT. Specifically, project partners will establish appropriate geo-databases for test areas and use existing hazard models to produce hazard and vulnerability geo-spatial information for earthquakes, landslides, tsunamis, floods, forest fires and marine oil spills. The GE-DSS in will consist of one source code with six geodatabases, i.e., one for each partner and risk data in the respective test area. Each partner organization will be able to manage and monitor its own data/database and their results using Multi-Criteria Decision Analysis (MCDA). The GE-DSS will be demonstrated at the local, regional and national levels through a set of Command Post and Table Top Disaster Exercises. As part of the DECAT GE-DSS, the gis-based geo-database and assessment of marine oil spill hazard and environmental vulnerability for the coasts of Crete in South Aegean Sea are presented here. Environmental Sensitivity Index (ESI) maps are

  18. Gis Based Analysis For Suitability Location Finding In The Residential Development Areas Of Greater Matara Region

    Directory of Open Access Journals (Sweden)

    H.K.G.M Madurika

    2017-02-01

    Full Text Available Urban Planning and Land utilization for the Residential is one of crucial factors in high density Cities. Many theories in Planning explain the Residential areas are moving to periphery areas in cities by its commercial development. Martara is one of developing city in Southern Sri Lanka and Residential land value are comparative high in city sub urban areas. In this study it is examined that where is the best locations for residential development in Grater Matara Region by using five criteria. GIS based Multi Criteria Method MCE method have been applied to find the suitable locations. The results of analysis have been shown that there are 5378.99 hectares area suitable within study area and however extremely importance areas only 1.40 hectares accordingly given criteria but very strongly importance and importance category have 1560.51 and 2468.22 respectively.

  19. GIS-Based Noise Simulation Open Source Software: N-GNOIS

    Science.gov (United States)

    Vijay, Ritesh; Sharma, A.; Kumar, M.; Shende, V.; Chakrabarti, T.; Gupta, Rajesh

    2015-12-01

    Geographical information system (GIS)-based noise simulation software (N-GNOIS) has been developed to simulate the noise scenario due to point and mobile sources considering the impact of geographical features and meteorological parameters. These have been addressed in the software through attenuation modules of atmosphere, vegetation and barrier. N-GNOIS is a user friendly, platform-independent and open geospatial consortia (OGC) compliant software. It has been developed using open source technology (QGIS) and open source language (Python). N-GNOIS has unique features like cumulative impact of point and mobile sources, building structure and honking due to traffic. Honking is the most common phenomenon in developing countries and is frequently observed on any type of roads. N-GNOIS also helps in designing physical barrier and vegetation cover to check the propagation of noise and acts as a decision making tool for planning and management of noise component in environmental impact assessment (EIA) studies.

  20. A European perspective on GIS-based walkability and active modes of transport.

    Science.gov (United States)

    Grasser, Gerlinde; van Dyck, Delfien; Titze, Sylvia; Stronegger, Willibald J

    2017-02-01

    The association between GIS-based walkability and walking for transport is considered to be well established in USA and in Australia. Research on the association between walkability and cycling for transport in European cities is lacking. The aim of this study was to test the predictive validity of established walkability measures and to explore alternative walkability measures associated with walking and cycling for transport in a European context. Outcome data were derived from the representative cross-sectional survey ( n  = 843) ‘Radfreundliche Stadt’ of adults in the city of Graz (Austria). GIS-based walkability was measured using both established measures (e.g. gross population density, household unit density, entropy index, three-way intersection density, IPEN walkability index) and alternative measures (e.g. proportion of mixed land use, four-way intersection density, Graz walkability index). ANCOVAs were conducted to examine the adjusted association between walkability measures and outcomes. Household unit density, proportion of mixed land use, three-way intersection density and IPEN walkability index were positively associated with walking for transport, but the other measures were not. All walkability measures were positively associated with cycling for transport. The established walkability measures were applicable to a European city such as Graz. The alternative walkability measures performed well in a European context. Due to measurement issues the association between these walkability measures and walking for transport needs to be investigated further. © The Author 2016. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.

  1. GIS-Based Planning and Modeling for Renewable Energy: Challenges and Future Research Avenues

    Directory of Open Access Journals (Sweden)

    Bernd Resch

    2014-05-01

    Full Text Available In the face of the broad political call for an “energy turnaround”, we are currently witnessing three essential trends with regard to energy infrastructure planning, energy generation and storage: from planned production towards fluctuating production on the basis of renewable energy sources, from centralized generation towards decentralized generation and from expensive energy carriers towards cost-free energy carriers. These changes necessitate considerable modifications of the energy infrastructure. Even though most of these modifications are inherently motivated by geospatial questions and challenges, the integration of energy system models and Geographic Information Systems (GIS is still in its infancy. This paper analyzes the shortcomings of previous approaches in using GIS in renewable energy-related projects, extracts distinct challenges from these previous efforts and, finally, defines a set of core future research avenues for GIS-based energy infrastructure planning with a focus on the use of renewable energy. These future research avenues comprise the availability base data and their “geospatial awareness”, the development of a generic and unified data model, the usage of volunteered geographic information (VGI and crowdsourced data in analysis processes, the integration of 3D building models and 3D data analysis, the incorporation of network topologies into GIS, the harmonization of the heterogeneous views on aggregation issues in the fields of energy and GIS, fine-grained energy demand estimation from freely-available data sources, decentralized storage facility planning, the investigation of GIS-based public participation mechanisms, the transition from purely structural to operational planning, data privacy aspects and, finally, the development of a new dynamic power market design.

  2. GIS-based interactive tool to map the advent of world conquerors

    Science.gov (United States)

    Lakkaraju, Mahesh

    The objective of this thesis is to show the scale and extent of some of the greatest empires the world has ever seen. This is a hybrid project between the GIS based interactive tool and the web-based JavaScript tool. This approach lets the students learn effectively about the emperors themselves while understanding how long and far their empires spread. In the GIS based tool, a map is displayed with various points on it, and when a user clicks on one point, the relevant information of what happened at that particular place is displayed. Apart from this information, users can also select the interactive animation button and can walk through a set of battles in chronological order. As mentioned, this uses Java as the main programming language, and MOJO (Map Objects Java Objects) provided by ESRI. MOJO is very effective as its GIS related features can be included in the application itself. This app. is a simple tool and has been developed for university or high school level students. D3.js is an interactive animation and visualization platform built on the Javascript framework. Though HTML5, CSS3, Javascript and SVG animations can be used to derive custom animations, this tool can help bring out results with less effort and more ease of use. Hence, it has become the most sought after visualization tool for multiple applications. D3.js has provided a map-based visualization feature so that we can easily display text-based data in a map-based interface. To draw the map and the points on it, D3.js uses data rendered in TOPO JSON format. The latitudes and longitudes can be provided, which are interpolated into the Map svg. One of the main advantages of doing it this way is that more information is retained when we use a visual medium.

  3. Landslides - Cause and effect

    Science.gov (United States)

    Radbruch-Hall, D. H.; Varnes, D.J.

    1976-01-01

    Landslides can cause seismic disturbances; landslides can also result from seismic disturbances, and earthquake-induced slides have caused loss of life in many countries. Slides can cause disastrous flooding, particularly when landslide dams across streams are breached, and flooding may trigger slides. Slope movement in general is a major process of the geologic environment that places constraints on engineering development. In order to understand and foresee both the causes and effects of slope movement, studies must be made on a regional scale, at individual sites, and in the laboratory. Areal studies - some embracing entire countries - have shown that certain geologic conditions on slopes facilitate landsliding; these conditions include intensely sheared rocks; poorly consolidated, fine-grained clastic rocks; hard fractured rocks underlain by less resistant rocks; or loose accumulations of fine-grained surface debris. Field investigations as well as mathematical- and physical-model studies are increasing our understanding of the mechanism of slope movement in fractured rock, and assist in arriving at practical solutions to landslide problems related to all kinds of land development for human use. Progressive failure of slopes has been studied in both soil and rock mechanics. New procedures have been developed to evaluate earthquake response of embankments and slopes. The finite element method of analysis is being extensively used in the calculation of slope stability in rock broken by joints, faults, and other discontinuities. ?? 1976 International Association of Engineering Geology.

  4. Guidance Index for Shallow Landslide Hazard Analysis

    Directory of Open Access Journals (Sweden)

    Cheila Avalon Cullen

    2016-10-01

    Full Text Available Rainfall-induced shallow landslides are one of the most frequent hazards on slanted terrains. Intense storms with high-intensity and long-duration rainfall have high potential to trigger rapidly moving soil masses due to changes in pore water pressure and seepage forces. Nevertheless, regardless of the intensity and/or duration of the rainfall, shallow landslides are influenced by antecedent soil moisture conditions. As of this day, no system exists that dynamically interrelates these two factors on large scales. This work introduces a Shallow Landslide Index (SLI as the first implementation of antecedent soil moisture conditions for the hazard analysis of shallow rainfall-induced landslides. The proposed mathematical algorithm is built using a logistic regression method that systematically learns from a comprehensive landslide inventory. Initially, root-soil moisture and rainfall measurements modeled from AMSR-E and TRMM respectively, are used as proxies to develop the index. The input dataset is randomly divided into training and verification sets using the Hold-Out method. Validation results indicate that the best-fit model predicts the highest number of cases correctly at 93.2% accuracy. Consecutively, as AMSR-E and TRMM stopped working in October 2011 and April 2015 respectively, root-soil moisture and rainfall measurements modeled by SMAP and GPM are used to develop models that calculate the SLI for 10, 7, and 3 days. The resulting models indicate a strong relationship (78.7%, 79.6%, and 76.8% respectively between the predictors and the predicted value. The results also highlight important remaining challenges such as adequate information for algorithm functionality and satellite based data reliability. Nevertheless, the experimental system can potentially be used as a dynamic indicator of the total amount of antecedent moisture and rainfall (for a given duration of time needed to trigger a shallow landslide in a susceptible area. It is

  5. Plan curvature and landslide probability in regions dominated by earth flows and earth slides

    Science.gov (United States)

    Ohlmacher, G.C.

    2007-01-01

    Damaging landslides in the Appalachian Plateau and scattered regions within the Midcontinent of North America highlight the need for landslide-hazard mapping and a better understanding of the geomorphic development of landslide terrains. The Plateau and Midcontinent have the necessary ingredients for landslides including sufficient relief, steep slope gradients, Pennsylvanian and Permian cyclothems that weather into fine-grained soils containing considerable clay, and adequate precipitation. One commonly used parameter in landslide-hazard analysis that is in need of further investigation is plan curvature. Plan curvature is the curvature of the hillside in a horizontal plane or the curvature of the contours on a topographic map. Hillsides can be subdivided into regions of concave outward plan curvature called hollows, convex outward plan curvature called noses, and straight contours called planar regions. Statistical analysis of plan-curvature and landslide datasets indicate that hillsides with planar plan curvature have the highest probability for landslides in regions dominated by earth flows and earth slides in clayey soils (CH and CL). The probability of landslides decreases as the hillsides become more concave or convex. Hollows have a slightly higher probability for landslides than noses. In hollows landslide material converges into the narrow region at the base of the slope. The convergence combined with the cohesive nature of fine-grained soils creates a buttressing effect that slows soil movement and increases the stability of the hillside within the hollow. Statistical approaches that attempt to determine landslide hazard need to account for the complex relationship between plan curvature, type of landslide, and landslide susceptibility. ?? 2007 Elsevier B.V. All rights reserved.

  6. GIS-based maps and area estimates of Northern Hemisphere permafrost extent during the Last Glacial Maximum

    NARCIS (Netherlands)

    Lindgren, A.; Hugelius, G.; Kuhry, P.; Christensen, T.R.; Vandenberghe, J.F.

    2016-01-01

    This study presents GIS-based estimates of permafrost extent in the northern circumpolar region during the Last Glacial Maximum (LGM), based on a review of previously published maps and compilations of field evidence in the form of ice-wedge pseudomorphs and relict sand wedges. We focus on field

  7. Development of Web GIS-Based VFSMOD System with Three Modules for Effective Vegetative Filter Strip Design

    Directory of Open Access Journals (Sweden)

    Dong Soo Kong

    2013-08-01

    Full Text Available In recent years, Non-Point Source Pollution has been rising as a significant environmental issue. The sediment-laden water problem is causing serious impacts on river ecosystems not only in South Korea but also in most countries. The vegetative filter strip (VFS has been thought to be one of the most effective methods to reduce the transport of sediment to down-gradient area. However, the effective width of the VFS first needs to be determined before VFS installation in the field. To provide an easy-to-use interface with a scientific VFS modeling engine, the Web GIS-based VFSMOD system was developed in this study. The Web GIS-based VFSMOD uses the UH and VFSM executable programs from the VFSMOD-w model as core engines to simulate rainfall-runoff and sediment trapping. To provide soil information for a point of interest, the Google Map interface to the MapServer soil database system was developed using the Google Map API, Javascript, Perl/CGI, and Oracle DB programming. Three modules of the Web GIS-based VFSMOD system were developed for various VFS designs under single storm, multiple storm, and long-term period scenarios. These modules in the Web GIS-based VFSMOD system were applied to the study watershed in South Korea and these were proven as efficient tools for the VFS design for various purposes.

  8. Geospatial Data Availability for Haiti: An Aid in the Development of GIS-Based Natural Resource Assessments for Conservation Planning.

    Science.gov (United States)

    Maya Quinones; William Gould; Carlos D. Rodriguez-Pedraza

    2007-01-01

    This report documents the type and source of geospatial data available for Haiti. It was compiled to serve as a resource for geographic information system (GIS)-based land management and planning. It will be useful for conservation planning, reforestation efforts, and agricultural extension projects. Our study indicates that there is a great deal of geospatial...

  9. DTMs Assessment to the Definition of Shallow Landslides Prone Areas

    Science.gov (United States)

    Martins, Tiago D.; Oka-Fiori, Chisato; Carvalho Vieira, Bianca; Montgomery, David R.

    2017-04-01

    Predictive methods have been developed, especially since the 1990s, to identify landslide prone areas. One of the examples it is the physically based model SHALSTAB (Shallow Landsliding Stability Model), that calculate the potential instability for shallow landslides based on topography and physical soil properties. Normally, in such applications in Brazil, the Digital Terrain Model (DTM), is obtained mainly from conventional contour lines. However, recently the LiDAR (Light Detection and Ranging) system has been largely used in Brazil. Thus, this study aimed to evaluate different DTM's, generated from conventional data and LiDAR, and their influence in generating susceptibility maps to shallow landslides using SHALSTAB model. For that were analyzed the physical properties of soil, the response of the model when applying conventional topographical data and LiDAR's in the generation of DTM, and the shallow landslides susceptibility maps based on different topographical data. The selected area is in the urban perimeter of the municipality of Antonina (PR), affected by widespread landslides in March 2011. Among the results, it was evaluated different LiDAR data interpolation, using GIS tools, wherein the Triangulation/Natural Neighbor presented the best performance. It was also found that in one of evaluation indexes (Scars Concentration), the LiDAR derived DTM presented the best performance when compared with the one originated from contour lines, however, the Landslide Potential index, has presented a small increase. Consequently, it was possible to assess the DTM's, and the one derived from LiDAR improved very little the certitude percentage. It is also noted a gap in researches carried out in Brazil on the use of products generated from LiDAR data on geomorphological analysis.

  10. Multiple Landslide-Hazard Scenarios Modeled for the Oakland-Berkeley Area, Northern California

    Science.gov (United States)

    Pike, Richard J.; Graymer, Russell W.

    2008-01-01

    With the exception of Los Angeles, perhaps no urban area in the United States is more at risk from landsliding, triggered by either precipitation or earthquake, than the San Francisco Bay region of northern California. By January each year, seasonal winter storms usually bring moisture levels of San Francisco Bay region hillsides to the point of saturation, after which additional heavy rainfall may induce landslides of various types and levels of severity. In addition, movement at any time along one of several active faults in the area may generate an earthquake large enough to trigger landslides. The danger to life and property rises each year as local populations continue to expand and more hillsides are graded for development of residential housing and its supporting infrastructure. The chapters in the text consist of: *Introduction by Russell W. Graymer *Chapter 1 Rainfall Thresholds for Landslide Activity, San Francisco Bay Region, Northern California by Raymond C. Wilson *Chapter 2 Susceptibility to Deep-Seated Landsliding Modeled for the Oakland-Berkeley Area, Northern California by Richard J. Pike and Steven Sobieszczyk *Chapter 3 Susceptibility to Shallow Landsliding Modeled for the Oakland-Berkeley Area, Northern California by Kevin M. Schmidt and Steven Sobieszczyk *Chapter 4 Landslide Hazard Modeled for the Cities of Oakland, Piedmont, and Berkeley, Northern California, from a M=7.1 Scenario Earthquake on the Hayward Fault Zone by Scott B. Miles and David K. Keefer *Chapter 5 Synthesis of Landslide-Hazard Scenarios Modeled for the Oakland-Berkeley Area, Northern California by Richard J. Pike The plates consist of: *Plate 1 Susceptibility to Deep-Seated Landsliding Modeled for the Oakland-Berkeley Area, Northern California by Richard J. Pike, Russell W. Graymer, Sebastian Roberts, Naomi B. Kalman, and Steven Sobieszczyk *Plate 2 Susceptibility to Shallow Landsliding Modeled for the Oakland-Berkeley Area, Northern California by Kevin M. Schmidt and Steven

  11. Integrating statistical and process-based models to produce probabilistic landslide hazard at regional scale

    Science.gov (United States)

    Strauch, R. L.; Istanbulluoglu, E.

    2017-12-01

    We develop a landslide hazard modeling approach that integrates a data-driven statistical model and a probabilistic process-based shallow landslide model for mapping probability of landslide initiation, transport, and deposition at regional scales. The empirical model integrates the influence of seven site attribute (SA) classes: elevation, slope, curvature, aspect, land use-land cover, lithology, and topographic wetness index, on over 1,600 observed landslides using a frequency ratio (FR) approach. A susceptibility index is calculated by adding FRs for each SA on a grid-cell basis. Using landslide observations we relate susceptibility index to an empirically-derived probability of landslide impact. This probability is combined with results from a physically-based model to produce an integrated probabilistic map. Slope was key in landslide initiation while deposition was linked to lithology and elevation. Vegetation transition from forest to alpine vegetation and barren land cover with lower root cohesion leads to higher frequency of initiation. Aspect effects are likely linked to differences in root cohesion and moisture controlled by solar insulation and snow. We demonstrate the model in the North Cascades of Washington, USA and identify locations of high and low probability of landslide impacts that can be used by land managers in their design, planning, and maintenance.

  12. Landslide Spatial Distribution Analysis Using GIS. Case Study Secașelor Plateau.

    Directory of Open Access Journals (Sweden)

    Gheorghe Rosian

    2017-05-01

    Full Text Available Landslides represent an extremely frequent geomorphological phenomenon in the Secașelor Plateau. The regional unit is located in the South-Eastern part of the Transylvanian Basin (large basin within the Carpathian Mountains. In this paper, we analyzed the distribution of the landslides through spatial statistics techniques and GIS. In order to analyze the distribution of the landslides we took into consideration 5 criteria: geology, height, slope, exposition and the territorial administrative units. This type of study is necessary to find out the way in which the actual landslides are distributed and on the other hand, the research will collect information on the susceptible fields which are favored by these geomorphological processes. After the visual analysis of the area using the 1:5000 aerial photography and topographic maps, 835 landslides were identified and vectorized. At the level of administrative-territorial units, these cover mostly agricultural areas. Given the lithological conditions (the presence of friable rocks of marl, clay and poorly cemented sands and the land use (mostly agricultural it can be said that in the future new landslides will ocure in similar conditions of slope, exposition and geological characteristic etc. The identification of areas that are susceptible to landslides is beneficial for the future territorial planning actions and also to avoid building on areas which are prone to landslides.

  13. Satellite-Based Assessment of Rainfall-Triggered Landslide Hazard for Situational Awareness

    Science.gov (United States)

    Kirschbaum, Dalia; Stanley, Thomas

    2018-03-01

    Determining the time, location, and severity of natural disaster impacts is fundamental to formulating mitigation strategies, appropriate and timely responses, and robust recovery plans. A Landslide Hazard Assessment for Situational Awareness (LHASA) model was developed to indicate potential landslide activity in near real-time. LHASA combines satellite-based precipitation estimates with a landslide susceptibility map derived from information on slope, geology, road networks, fault zones, and forest loss. Precipitation data from the Global Precipitation Measurement (GPM) mission are used to identify rainfall conditions from the past 7 days. When rainfall is considered to be extreme and susceptibility values are moderate to very high, a "nowcast" is issued to indicate the times and places where landslides are more probable. When LHASA nowcasts were evaluated with a Global Landslide Catalog, the probability of detection (POD) ranged from 8% to 60%, depending on the evaluation period, precipitation product used, and the size of the spatial and temporal window considered around each landslide point. Applications of the LHASA system are also discussed, including how LHASA is used to estimate long-term trends in potential landslide activity at a nearly global scale and how it can be used as a tool to support disaster risk assessment. LHASA is intended to provide situational awareness of landslide hazards in near real-time, providing a flexible, open-source framework that can be adapted to other spatial and temporal scales based on data availability.

  14. A new methodology for modeling of direct landslide costs for transportation infrastructures

    Science.gov (United States)

    Klose, Martin; Terhorst, Birgit

    2014-05-01

    The world's transportation infrastructure is at risk of landslides in many areas across the globe. A safe and affordable operation of traffic routes are the two main criteria for transportation planning in landslide-prone areas. The right balancing of these often conflicting priorities requires, amongst others, profound knowledge of the direct costs of landslide damage. These costs include capital investments for landslide repair and mitigation as well as operational expenditures for first response and maintenance works. This contribution presents a new methodology for ex post assessment of direct landslide costs for transportation infrastructures. The methodology includes tools to compile, model, and extrapolate landslide losses on different spatial scales over time. A landslide susceptibility model enables regional cost extrapolation by means of a cost figure obtained from local cost compilation for representative case study areas. On local level, cost survey is closely linked with cost modeling, a toolset for cost estimation based on landslide databases. Cost modeling uses Landslide Disaster Management Process Models (LDMMs) and cost modules to simulate and monetize cost factors for certain types of landslide damage. The landslide susceptibility model provides a regional exposure index and updates the cost figure to a cost index which describes the costs per km of traffic route at risk of landslides. Both indexes enable the regionalization of local landslide losses. The methodology is applied and tested in a cost assessment for highways in the Lower Saxon Uplands, NW Germany, in the period 1980 to 2010. The basis of this research is a regional subset of a landslide database for the Federal Republic of Germany. In the 7,000 km² large Lower Saxon Uplands, 77 km of highway are located in potential landslide hazard area. Annual average costs of 52k per km of highway at risk of landslides are identified as cost index for a local case study area in this region. The

  15. GIS based analysis of Intercity Fatal Road Traffic Accidents in Iran.

    Science.gov (United States)

    Alizadeh, A; Zare, M; Darparesh, M; Mohseni, S; Soleimani-Ahmadi, M

    2015-01-01

    Road traffic accidents including intercity car traffic accidents (ICTAs) are among the most important causes of morbidity and mortality due to the growing number of vehicles, risky behaviors, and changes in lifestyle of the general population. A sound knowledge of the geographical distribution of car traffic accidents can be considered as an approach towards the accident causation and it can be used as an administrative tool in allocating the sources for traffic accidents prevention. This study was conducted to investigate the geographical distribution and the time trend of fatal intercity car traffic accidents in Iran. To conduct this descriptive study, all Iranian intercity road traffic mortality data were obtained from the Police reports in the Statistical Yearbook of the Governor's Budget and Planning. The obtained data were for 17 complete Iranian calendar years from March 1997 to March 2012. The incidence rate (IR) of fatal ICTAs for each year was calculated as the total number of fatal ICTAs in every 100000 population in specified time intervals. Figures and maps indicating the trends and geographical distribution of fatal ICTAs were prepared while using Microsoft Excel and ArcGis9.2 software. The number of fatal car accidents showed a general increasing trend from 3000 in 1996 to 13500 in 2012. The incidence of fatal intercity car accidents has changed from six in 100000 population in 1996 to 18 in 100000 population in 2012. GIS based data showed that the incidence rate of ICTAs in different provinces of Iran was very divergent. The highest incidence of fatal ICTAs was in Semnan province (IR= 35.2), followed by North Khorasan (IR=22.7), and South Khorasan (IR=22). The least incidence of fatal ICTAs was in Tehran province (IR=2.4) followed by Khozestan (IR=6.5), and Eastern Azarbayejan (IR=6.6). The compensation cost of fatal ICTAs also showed an increasing trend during the studied period. Since an increasing amount of money was being paid yearly for the car

  16. GIS based analysis of Intercity Fatal Road Traffic Accidents in Iran

    Science.gov (United States)

    Alizadeh, A; Zare, M; Darparesh, M; Mohseni, S; Soleimani-Ahmadi, M

    2015-01-01

    Road traffic accidents including intercity car traffic accidents (ICTAs) are among the most important causes of morbidity and mortality due to the growing number of vehicles, risky behaviors, and changes in lifestyle of the general population. A sound knowledge of the geographical distribution of car traffic accidents can be considered as an approach towards the accident causation and it can be used as an administrative tool in allocating the sources for traffic accidents prevention. This study was conducted to investigate the geographical distribution and the time trend of fatal intercity car traffic accidents in Iran. To conduct this descriptive study, all Iranian intercity road traffic mortality data were obtained from the Police reports in the Statistical Yearbook of the Governor’s Budget and Planning. The obtained data were for 17 complete Iranian calendar years from March 1997 to March 2012. The incidence rate (IR) of fatal ICTAs for each year was calculated as the total number of fatal ICTAs in every 100000 population in specified time intervals. Figures and maps indicating the trends and geographical distribution of fatal ICTAs were prepared while using Microsoft Excel and ArcGis9.2 software. The number of fatal car accidents showed a general increasing trend from 3000 in 1996 to 13500 in 2012. The incidence of fatal intercity car accidents has changed from six in 100000 population in 1996 to 18 in 100000 population in 2012. GIS based data showed that the incidence rate of ICTAs in different provinces of Iran was very divergent. The highest incidence of fatal ICTAs was in Semnan province (IR= 35.2), followed by North Khorasan (IR=22.7), and South Khorasan (IR=22). The least incidence of fatal ICTAs was in Tehran province (IR=2.4) followed by Khozestan (IR=6.5), and Eastern Azarbayejan (IR=6.6). The compensation cost of fatal ICTAs also showed an increasing trend during the studied period. Since an increasing amount of money was being paid yearly for the

  17. Comparing the Performance of Commonly Available Digital Elevation Models in GIS-based Flood Simulation

    Science.gov (United States)

    Ybanez, R. L.; Lagmay, A. M. A.; David, C. P.

    2016-12-01

    With climatological hazards increasing globally, the Philippines is listed as one of the most vulnerable countries in the world due to its location in the Western Pacific. Flood hazards mapping and modelling is one of the responses by local government and research institutions to help prepare for and mitigate the effects of flood hazards that constantly threaten towns and cities in floodplains during the 6-month rainy season. Available digital elevation maps, which serve as the most important dataset used in 2D flood modelling, are limited in the Philippines and testing is needed to determine which of the few would work best for flood hazards mapping and modelling. Two-dimensional GIS-based flood modelling with the flood-routing software FLO-2D was conducted using three different available DEMs from the ASTER GDEM, the SRTM GDEM, and the locally available IfSAR DTM. All other parameters kept uniform, such as resolution, soil parameters, rainfall amount, and surface roughness, the three models were run over a 129-sq. kilometer watershed with only the basemap varying. The output flood hazard maps were compared on the basis of their flood distribution, extent, and depth. The ASTER and SRTM GDEMs contained too much error and noise which manifested as dissipated and dissolved hazard areas in the lower watershed where clearly delineated flood hazards should be present. Noise on the two datasets are clearly visible as erratic mounds in the floodplain. The dataset which produced the only feasible flood hazard map is the IfSAR DTM which delineates flood hazard areas clearly and properly. Despite the use of ASTER and SRTM with their published resolution and accuracy, their use in GIS-based flood modelling would be unreliable. Although not as accessible, only IfSAR or better datasets should be used for creating secondary products from these base DEM datasets. For developing countries which are most prone to hazards, but with limited choices for basemaps used in hazards

  18. Economic assessment of landslide risks in the Swabian Alb, Germany ‒ research framework and first results of homeowners' and experts' surveys

    Directory of Open Access Journals (Sweden)

    A. Blöchl

    2005-01-01

    Full Text Available Landslide risks are frequently underestimated by political and economic actors as well as by the local population. The InterRisk Assess research project is working to develop a systematic approach to the analysis and evaluation of economic landslide risks at a local and regional scale. Its major aims are to determine the extent of potential damage and economic losses caused by landslides, to analyze individual and collective patterns of risk assessment and to develop recommendations for pro-active risk management. The research methodology includes GIS-based risk analyses and interviews with relevant actors in politics, administration and planning, private households and land owners. The research findings will facilitate a better-informed, efficient and sustainable use of natural resources and natural risks. The research project also aims to contribute to methodological progress in risk research.

  19. A GIS-based Quantitative Approach for the Search of Clandestine Graves, Italy.

    Science.gov (United States)

    Somma, Roberta; Cascio, Maria; Silvestro, Massimiliano; Torre, Eliana

    2018-05-01

    Previous research on the RAG color-coded prioritization systems for the discovery of clandestine graves has not considered all the factors influencing the burial site choice within a GIS project. The goal of this technical note was to discuss a GIS-based quantitative approach for the search of clandestine graves. The method is based on cross-referenced RAG maps with cumulative suitability factors to host a burial, leading to the editing of different search scenarios for ground searches showing high-(Red), medium-(Amber), and low-(Green) priority areas. The application of this procedure allowed several outcomes to be determined: If the concealment occurs at night, then the "search scenario without the visibility" will be the most effective one; if the concealment occurs in daylight, then the "search scenario with the DSM-based visibility" will be most appropriate; the different search scenarios may be cross-referenced with offender's confessions and eyewitnesses' testimonies to verify the veracity of their statements. © 2017 American Academy of Forensic Sciences.

  20. A GIS-based atmospheric dispersion model for pollutants emitted by complex source areas.

    Science.gov (United States)

    Teggi, Sergio; Costanzini, Sofia; Ghermandi, Grazia; Malagoli, Carlotta; Vinceti, Marco

    2018-01-01

    Gaussian dispersion models are widely used to simulate the concentrations and deposition fluxes of pollutants emitted by source areas. Very often, the calculation time limits the number of sources and receptors and the geometry of the sources must be simple and without holes. This paper presents CAREA, a new GIS-based Gaussian model for complex source areas. CAREA was coded in the Python language, and is largely based on a simplified formulation of the very popular and recognized AERMOD model. The model allows users to define in a GIS environment thousands of gridded or scattered receptors and thousands of complex sources with hundreds of vertices and holes. CAREA computes ground level, or near ground level, concentrations and dry deposition fluxes of pollutants. The input/output and the runs of the model can be completely managed in GIS environment (e.g. inside a GIS project). The paper presents the CAREA formulation and its applications to very complex test cases. The tests shows that the processing time are satisfactory and that the definition of sources and receptors and the output retrieval are quite easy in a GIS environment. CAREA and AERMOD are compared using simple and reproducible test cases. The comparison shows that CAREA satisfactorily reproduces AERMOD simulations and is considerably faster than AERMOD. Copyright © 2017 Elsevier B.V. All rights reserved.

  1. Mapping Urban Heat Demand with the Use of GIS-Based Tools

    Directory of Open Access Journals (Sweden)

    Artur Wyrwa

    2017-05-01

    Full Text Available This article presents a bottom-up approach for calculation of the useful heat demand for space heating and hot water preparation using geo-referenced datasets for buildings at the city level. This geographic information system (GIS based approach was applied in the case study for the city of Krakow, where on the one hand the district heat network is well developed, while on the other hand there are still substantial number of buildings burning solid fuels in individual boilers and stoves, causing air pollution. The calculated heat demand was aggregated in the grid with 100 m × 100 m spatial resolution to deliver the heat map depicting the current situation for 21 buildings types. The results show that the residential buildings, in particular one- and multi-family buildings, have the highest share in overall demand for heat. By combining the results with location of the district heat (DH network, the potential areas in its close vicinity that have sufficient heat demand density for developing the net were pointed out. Future evolution in heat demand for space heating in one-family houses was evaluated with the use of deterministic method employing building stock model. The study lays a foundation for planning the development of the heating system at the city level.

  2. A GIS-Based 3D Simulation for Occupant Evacuation in a Building

    Institute of Scientific and Technical Information of China (English)

    TANG Fangqin; ZHANG Xin

    2008-01-01

    The evacuation efficiency of building plans is of obvious importance to the public safety.The cem- plexity of building plans,however,makes it difficult for the efficiency evaluation.This paper presents a com- putational model AutoEscape,which can simulate the evacuation process for any given occupant distribu. Uon in buildings.Designed as an extensible multi-level structure, the model constructs the geometry level and occupant level and establishes the interactions between levels.The GIS-based environmental analysis is realized to automatically generate the geometric representation and formulate the cognition of agents. The multi-agent based technology is employed to simulate the crowd behaviom with autonomously acting individuals.A visualization component,which provides 3D free observations for the simulation process,is developed on the platform of OGRE and integrated into the system interface in form of ActiveX control.Fi- nally,a case study has been conducted and the results have been compared with the results of an existing model to show the reliability and capacity of AutoEscape simulation.

  3. GIS-based Approach to Estimate Surface Runoff in Small Catchments: A Case Study

    Directory of Open Access Journals (Sweden)

    Vojtek Matej

    2016-09-01

    Full Text Available The issue of surface runoff assessment is one of the important and relevant topics of hydrological as well as geographical research. The aim of the paper is therefore to estimate and assess surface runoff on the example of Vyčoma catchment which is located in the Western Slovakia. For this purpose, SCS runoff curve number method, modeling in GIS and remote sensing were used. An important task was the creation of a digital elevation model (DEM, which enters the surface runoff modeling and affects its accuracy. Great attention was paid to the spatial interpretation of land use categories applying aerial imagery from 2013 and hydrological soil groups as well as calculation of maximum daily rainfall with N-year return periods as partial tasks in estimating surface runoff. From the methodological point of view, the importance of the paper can be seen in the use of a simple GIS-based approach to assess the surface runoff conditions in a small catchment.

  4. Cost optimization of a real-time GIS-based management system for hazardous waste transportation.

    Science.gov (United States)

    Zhu, Yun; Lin, Che-Jen; Zhong, Yilong; Zhou, Qing; Lin, Che-Jen; Chen, Chunyi

    2010-08-01

    In this paper, the design and cost analysis of a real-time, geographical information system (GIS) based management system for hazardous waste transportation are described. The implementation of such a system can effectively prevent illegal dumping and perform emergency responses during the transportation of hazardous wastes. A case study was conducted in Guangzhou, China to build a small-scale, real-time management system for waste transportation. Two alternatives were evaluated in terms of system capability and cost structure. Alternative I was the building of a complete real-time monitoring and management system in a governing agency; whereas alternative II was the combination of the existing management framework with a commercial Telematics service to achieve the desired level of monitoring and management. The technological framework under consideration included locating transportation vehicles using a global positioning system (GPS), exchanging vehicle location data via the Internet and Intranet, managing hazardous waste transportation using a government management system and responding to emergencies during transportation. Analysis of the cost structure showed that alternative II lowered the capital and operation cost by 38 and 56% in comparison with alternative I. It is demonstrated that efficient management can be achieved through integration of the existing technological components with additional cost benefits being achieved by streamlined software interfacing.

  5. GIS-based examination of peats and soils in Surfers Paradise, Australia

    Directory of Open Access Journals (Sweden)

    Al-Ani Haider

    2014-03-01

    Full Text Available The subsoil conditions of Surfers Paradise in Southeast Queensland of Australia have been examined in terms of soil stiffness by using geographic information system (GIS. Peat is a highly organic and compressible material. Surfers Paradise (as a study area has problematic peat layer due to its high water content, high compressibility, and low shear strength. This layer has various thicknesses at different locations ranging between R.L. . 10 to R.L. -19.6 m. Buildings in Surfers Paradise are using piled foundations to avoid the high compressibility and low shear strength peat layer. Spatial Analyst extension in the GIS ArcMap10 has been utilised to develop zonation maps for different depths in the study area. Each depth has been interpolated as a surface to create Standard Penetration Test SPT-N value GIS-based zonation maps for each depth. In addition, 8 interpolation techniques have been examined to evaluate which technique gives better representation for the Standard Penetration Test (SPT data. Inverse Distance weighing (IDW method in Spatial Analyst extension gives better representation for the utilised data with certain parameters. Two different cross sections have been performed in the core of the study area to determine the extent and the depth of the peat layer underneath already erected buildings. Physical and engineering properties of the Surfers Paradise peat have been obtained and showed that this peat falls within the category of tropical peat.

  6. Automated riverine landscape characterization: GIS-based tools for watershed-scale research, assessment, and management.

    Science.gov (United States)

    Williams, Bradley S; D'Amico, Ellen; Kastens, Jude H; Thorp, James H; Flotemersch, Joseph E; Thoms, Martin C

    2013-09-01

    River systems consist of hydrogeomorphic patches (HPs) that emerge at multiple spatiotemporal scales. Functional process zones (FPZs) are HPs that exist at the river valley scale and are important strata for framing whole-watershed research questions and management plans. Hierarchical classification procedures aid in HP identification by grouping sections of river based on their hydrogeomorphic character; however, collecting data required for such procedures with field-based methods is often impractical. We developed a set of GIS-based tools that facilitate rapid, low cost riverine landscape characterization and FPZ classification. Our tools, termed RESonate, consist of a custom toolbox designed for ESRI ArcGIS®. RESonate automatically extracts 13 hydrogeomorphic variables from readily available geospatial datasets and datasets derived from modeling procedures. An advanced 2D flood model, FLDPLN, designed for MATLAB® is used to determine valley morphology by systematically flooding river networks. When used in conjunction with other modeling procedures, RESonate and FLDPLN can assess the character of large river networks quickly and at very low costs. Here we describe tool and model functions in addition to their benefits, limitations, and applications.

  7. GIS Based System for Post-Earthquake Crisis Managment Using Cellular Network

    Science.gov (United States)

    Raeesi, M.; Sadeghi-Niaraki, A.

    2013-09-01

    Earthquakes are among the most destructive natural disasters. Earthquakes happen mainly near the edges of tectonic plates, but they may happen just about anywhere. Earthquakes cannot be predicted. Quick response after disasters, like earthquake, decreases loss of life and costs. Massive earthquakes often cause structures to collapse, trapping victims under dense rubble for long periods of time. After the earthquake and destroyed some areas, several teams are sent to find the location of the destroyed areas. The search and rescue phase usually is maintained for many days. Time reduction for surviving people is very important. A Geographical Information System (GIS) can be used for decreasing response time and management in critical situations. Position estimation in short period of time time is important. This paper proposes a GIS based system for post-earthquake disaster management solution. This system relies on several mobile positioning methods such as cell-ID and TA method, signal strength method, angel of arrival method, time of arrival method and time difference of arrival method. For quick positioning, the system can be helped by any person who has a mobile device. After positioning and specifying the critical points, the points are sent to a central site for managing the procedure of quick response for helping. This solution establishes a quick way to manage the post-earthquake crisis.

  8. GIS Based Distributed Runoff Predictions in Variable Source Area Watersheds Employing the SCS-Curve Number

    Science.gov (United States)

    Steenhuis, T. S.; Mendoza, G.; Lyon, S. W.; Gerard Marchant, P.; Walter, M. T.; Schneiderman, E.

    2003-04-01

    Because the traditional Soil Conservation Service Curve Number (SCS-CN) approach continues to be ubiquitously used in GIS-BASED water quality models, new application methods are needed that are consistent with variable source area (VSA) hydrological processes in the landscape. We developed within an integrated GIS modeling environment a distributed approach for applying the traditional SCS-CN equation to watersheds where VSA hydrology is a dominant process. Spatial representation of hydrologic processes is important for watershed planning because restricting potentially polluting activities from runoff source areas is fundamental to controlling non-point source pollution. The methodology presented here uses the traditional SCS-CN method to predict runoff volume and spatial extent of saturated areas and uses a topographic index to distribute runoff source areas through watersheds. The resulting distributed CN-VSA method was incorporated in an existing GWLF water quality model and applied to sub-watersheds of the Delaware basin in the Catskill Mountains region of New York State. We found that the distributed CN-VSA approach provided a physically-based method that gives realistic results for watersheds with VSA hydrology.

  9. Application of GIS-based SCS-CN method in West Bank catchments, Palestine

    Directory of Open Access Journals (Sweden)

    Sameer Shadeed

    2010-03-01

    Full Text Available Among the most basic challenges of hydrology are the prediction and quantification of catchment surface runoff. The runoff curve number (CN is a key factor in determining runoff in the SCS (Soil Conservation Service based hydrologic modeling method. The traditional SCS-CN method for calculating the composite curve number is very tedious and consumes a major portion of the hydrologic modeling time. Therefore, geographic information systems (GIS are now being used in combination with the SCS-CN method. This paper assesses the modeling of flow in West Bank catchments using the GIS-based SCS-CN method. The West Bank, Palestine, is characterized as an arid to semi-arid region with annual rainfall depths ranging between 100 mm in the vicinity of the Jordan River to 700 mm in the mountains extending across the central parts of the region. The estimated composite curve number for the entire West Bank is about 50 assuming dry conditions. This paper clearly demonstrates that the integration of GIS with the SCS-CN method provides a powerful tool for estimating runoff volumes in West Bank catchments, representing arid to semi-arid catchments of Palestine.

  10. GIS-based models for ambient PM exposure and health impact assessment for the UK

    International Nuclear Information System (INIS)

    Stedman, John R; Grice, Susannah; Kent, Andrew; Cooke, Sally

    2009-01-01

    GIS-based models have been developed to map ambient PM 10 and PM 25 mass concentrations across the UK. The resulting maps are used for the assessments of air quality required by the EU ambient air quality directives, health impact assessment and the development of UK air quality policy. Maps are presented for 2006 along with projections to 2020. The largest single contribution to the UK population-weighted mean annual mean background concentrations of PM 10 in 2006 is estimated to be from secondary PM (43%), followed by the contribution from primary PM (24%). Concentrations are predicted to decline by 15% for PM 10 and 13% for PM 25 over the period from 2006 to 2020. The extent of exceedence of the 24-hour limit value is predicted to decline from 1.9% to 0.1% of urban major roads over the same period. The potential health benefits of reductions in ambient PM are large. A reduction in concentration of 0.93 μg m -3 as a result of a possible package of measures has been estimated within the UK Air Quality Strategy to result in a reduction in life years lost of approximately 2 - 4 million over a period of 100 years.

  11. GIS based generation of dynamic hydrological and land patch simulation models for rural watershed areas

    Directory of Open Access Journals (Sweden)

    M. Varga

    2016-03-01

    Full Text Available This paper introduces a GIS based methodology to generate dynamic process model for the simulation based analysis of a sensitive rural watershed. The Direct Computer Mapping (DCM based solution starts from GIS layers and, via the graph interpretation and graphical edition of the process network, the expert interface is able to integrate the field experts’ knowledge in the computer aided generation of the simulation model. The methodology was applied and tested for the Southern catchment basin of Lake Balaton, Hungary. In the simplified hydrological model the GIS description of nine watercourses, 121 water sections, 57 small lakes and 20 Lake Balaton compartments were mapped through the expert interface to the dynamic databases of the DCM model. The hydrological model involved precipitation, evaporation, transpiration, runoff, infiltration. The COoRdination of INformation on the Environment (CORINE land cover based simplified “land patch” model considered the effect of meteorological and hydrological scenarios on freshwater resources in the land patches, rivers and lakes. The first results show that the applied model generation methodology helps to build complex models, which, after validation can support the analysis of various land use, with the consideration of environmental aspects.

  12. GIS-based bivariate statistical techniques for groundwater potential analysis (an example of Iran)

    Science.gov (United States)

    Haghizadeh, Ali; Moghaddam, Davoud Davoudi; Pourghasemi, Hamid Reza

    2017-12-01

    Groundwater potential analysis prepares better comprehension of hydrological settings of different regions. This study shows the potency of two GIS-based data driven bivariate techniques namely statistical index (SI) and Dempster-Shafer theory (DST) to analyze groundwater potential in Broujerd region of Iran. The research was done using 11 groundwater conditioning factors and 496 spring positions. Based on the ground water potential maps (GPMs) of SI and DST methods, 24.22% and 23.74% of the study area is covered by poor zone of groundwater potential, and 43.93% and 36.3% of Broujerd region is covered by good and very good potential zones, respectively. The validation of outcomes displayed that area under the curve (AUC) of SI and DST techniques are 81.23% and 79.41%, respectively, which shows SI method has slightly a better performance than the DST technique. Therefore, SI and DST methods are advantageous to analyze groundwater capacity and scrutinize the complicated relation between groundwater occurrence and groundwater conditioning factors, which permits investigation of both systemic and stochastic uncertainty. Finally, it can be realized that these techniques are very beneficial for groundwater potential analyzing and can be practical for water-resource management experts.

  13. A novel GIS-based approach to assess beekeeping suitability of Mediterranean lands.

    Science.gov (United States)

    Zoccali, Paolo; Malacrinò, Antonino; Campolo, Orlando; Laudani, Francesca; Algeri, Giuseppe M; Giunti, Giulia; Strano, Cinzia P; Benelli, Giovanni; Palmeri, Vincenzo

    2017-07-01

    Honeybees are critically important for the environment and to the economy. However, there are in substantial decline worldwide, leading to serious threat to the stability and yield of food crops. Beekeeping is of pivotal importance, combining the wide economical aspect of honey production and the important ecological services provided by honeybees. In this scenario, the prompt identification of beekeeping areas is strategic, since it maximised productivity and lowered the risks of colony losses. Fuzzy logic is an ideal approach for problem-solving tasks, as it is specifically designed to manage problems with a high degree of uncertainty. This research tested a novel GIS-based approach to assess beekeeping suitability of lands located in Calabria (Southern Italy), without relying to Analytic Hierarchy Process - Multiple Criteria Decision Making (AHP-MCDM), thus avoiding the constraints due to the technique and decision makers' influences. Furthermore, the data used here were completely retrieved from open access sources, highlighting that our approach is characterized by low costs and can be easily reproduced for a wide arrays of geographical contexts. Notably, the results obtained by our experiments were validated by the actual beekeeping reality. Besides beekeeping, the use of this system could not only be applied in beekeeping land suitability evaluations, but may be successfully extended to other types of land suitability evaluations.

  14. GIS - Based data presentation and interactive communication system for public involvement in EIA

    International Nuclear Information System (INIS)

    Oprea, I.; Oprea, M.; Guta, V.; Pirvu, V.

    2001-01-01

    The data presentation and interactive communication system has as main task to integrate technical and administrative information, as well as to ensure an efficient public participation. The system can achieve desired inter-operability between specialists, government and public in decision-making and environmental impact assessment (EIA). It incorporates different modules relative to specific types of parameters and authorities involved. The GIS-based system provides mapping, database, automatic information collection and advanced presentation techniques. It includes a graphically oriented executive support, which has the ability to present information by geographical representation of the zones on the map. The public opinion is taking into account by consideration of alternatives and providing access to the monitoring of environmental effects. The system offers an effective way to avoid negative reactions by interactive communication based on real-time information exchange. The system can be integrated into national or international management systems, being a useful tool for an efficient communication, handling and exchanging a vast amount of information. (authors)

  15. GIS-based modelling of odour emitted from the waste processing plant: case study

    Directory of Open Access Journals (Sweden)

    Sόwka Izabela

    2017-01-01

    Full Text Available The emission of odours into the atmospheric air from the municipal economy and industrial plants, especially in urbanized areas, causes a serious problem, which the mankind has been struggling with for years. The excessive exposure of people to odours may result in many negative health effects, including, for example, headaches and vomiting. There are many different methods that are used in order to evaluate the odour nuisance. The results obtained through those methods can then be used to carry out a visualization and an analysis of a distribution of the odour concentrations in a given area by using the GIS (Geographic Information System. By their application to the spatial analysis of the impact of odours, we can enable the assessment of the magnitude and likelihood of the occurrence of odour nuisance. Modelling using GIS tools and spatial interpolation like IDW method and kriging can provide an alternative to the standard modelling tools, which generally use the emission values from sources that are identified as major emitters of odours. The work presents the result, based on the odour measurements data from waste processing plant, of the attempt to connect two different tools – the reference model OPERAT FB and GIS-based dispersion modelling performed using IDW method and ordinary kriging to analyse their behaviour in terms of limited observation values.

  16. WISDOM: A GIS-based supply demand mapping tool for woodfuel management

    International Nuclear Information System (INIS)

    Masera, Omar; Ghilardi, Adrian; Drigo, Rudi; Angel Trossero, Miguel

    2006-01-01

    In this paper, it is argued that adequately assessing the implications of the current patterns of woodfuel production and use, and the sustainable potentials of woodfuel resources, requires a holistic view and a better knowledge of the spatial patterns of woodfuel supply and demand. There is a need to conduct multi-scale spatially explicit analyses of woodfuel supply and demand that are able to articulate local heterogeneity at the regional and national levels. Studies that provide full-country coverage and are based on consistent integration of data at lower geographical scales are woefully lacking. This paper describes the Woodfuel Integrated Supply/Demand Overview Mapping model (WISDOM). This is a GIS-based tool, aimed at analyzing woodfuel demand and supply spatial patterns from a new perspective that includes: (a) the assembling of existing but dispersed information into single data sets, (b) a modular integration of these data sets, based on the analysis of key variables associated with woodfuel demand and supply patterns, and (c) a multiple-scale and spatially explicit representation of the results, in order to rank or highlight areas in which several criteria of interest coincide. The final objective of WISDOM is to assess the sustainability of woodfuel as a renewable and widespread energy source, while supporting strategic planning and policy formulation. Three case studies for Mexico, Slovenia, and Senegal illustrate the practical implementation and innovative results of using WISDOM. (author)

  17. THE UNCERTAINTIES ON THE GIS BASED LAND SUITABILITY ASSESSMENT FOR URBAN AND RURAL PLANNING

    Directory of Open Access Journals (Sweden)

    H. Liu

    2017-09-01

    Full Text Available The majority of the research on the uncertainties of spatial data and spatial analysis focuses on some specific data feature or analysis tool. Few have accomplished the uncertainties of the whole process of an application like planning, making the research of uncertainties detached from practical applications. The paper discusses the uncertainties of the geographical information systems (GIS based land suitability assessment in planning on the basis of literature review. The uncertainties considered range from index system establishment to the classification of the final result. Methods to reduce the uncertainties arise from the discretization of continuous raster data and the index weight determination are summarized. The paper analyzes the merits and demerits of the “Nature Breaks” method which is broadly used by planners. It also explores the other factors which impact the accuracy of the final classification like the selection of class numbers, intervals and the autocorrelation of the spatial data. In the conclusion part, the paper indicates that the adoption of machine learning methods should be modified to integrate the complexity of land suitability assessment. The work contributes to the application of spatial data and spatial analysis uncertainty research on land suitability assessment, and promotes the scientific level of the later planning and decision-making.

  18. GIS-Based Evaluation of Spatial Interactions by Geographic Disproportionality of Industrial Diversity

    Directory of Open Access Journals (Sweden)

    Jemyung Lee

    2017-11-01

    Full Text Available Diversity of regional industry is regarded as a key factor for regional development, as it has a positive relationship with economic stability, which attracts population. This paper focuses on how the spatial imbalance of industrial diversity contributes to the population change caused by inter-regional migration. This paper introduces a spatial interaction model for the Geographic Information System (GIS-based simulation of the spatial interactions to evaluate the demographic attraction force. The proposed model adopts the notions of gravity, entropy, and virtual work. An industrial classification by profit level is introduced and its diversity is quantified with the entropy of information theory. The introduced model is applied to the cases of 207 regions in South Korea. Spatial interactions are simulated with an optimized model and their resultant forces, the demographic attraction forces, are compared with observed net migration for verification. The results show that the evaluated attraction forces from industrial diversity have a very significant, positive, and moderate relationship with net migration, while other conventional factors of industry, population, economy, and the job market do not. This paper concludes that the geographical quality of industrial diversity has positive and significant effects on population change by migration.

  19. GIS BASED SYSTEM FOR POST-EARTHQUAKE CRISIS MANAGMENT USING CELLULAR NETWORK

    Directory of Open Access Journals (Sweden)

    M. Raeesi

    2013-09-01

    Full Text Available Earthquakes are among the most destructive natural disasters. Earthquakes happen mainly near the edges of tectonic plates, but they may happen just about anywhere. Earthquakes cannot be predicted. Quick response after disasters, like earthquake, decreases loss of life and costs. Massive earthquakes often cause structures to collapse, trapping victims under dense rubble for long periods of time. After the earthquake and destroyed some areas, several teams are sent to find the location of the destroyed areas. The search and rescue phase usually is maintained for many days. Time reduction for surviving people is very important. A Geographical Information System (GIS can be used for decreasing response time and management in critical situations. Position estimation in short period of time time is important. This paper proposes a GIS based system for post–earthquake disaster management solution. This system relies on several mobile positioning methods such as cell-ID and TA method, signal strength method, angel of arrival method, time of arrival method and time difference of arrival method. For quick positioning, the system can be helped by any person who has a mobile device. After positioning and specifying the critical points, the points are sent to a central site for managing the procedure of quick response for helping. This solution establishes a quick way to manage the post–earthquake crisis.

  20. GIS-based landscape design research: Stourhead landscape garden as a case study

    Directory of Open Access Journals (Sweden)

    Steffen Nijhuis

    2017-11-01

    analysed, such as the visible form and the shape of the walk, and serves as the basis for the landscape architectonic analysis in which GIS is used as the primary analytical tool.  GIS-based design research has the possibility to cultivate spatial intelligence in landscape architecture through three fields of operation: • GIS-based modelling: description of existing and future landscape architectonic compositions in digital form; • GIS-based analysis: exploration, analysis and synthesis of landscape architectonic compositions in order to reveal latent architectonic relationships and principles, while utilizing the processing capacities and possibilities of computers for ex-ante and ex-post simulation and evaluation; • GIS-based visual representation: representation of (virtual landscape architectonic compositions in space and time, in order to retrieve and communicate information and knowledge of the landscape design.  Though there are limitations, this study exemplifies that GIS is a powerful instrument to acquire knowledge from landscape architectonic compositions. The study points out that the application of GIS in landscape design research can be seen as an extension of the fundamental cycle of observation, visual representation, analysis and interpretation in the process of knowledge acquisition, with alternative visualisations and digital landscape models as important means for this process. Using the calculating power of computers, combined with inventive modelling, analysis and visualisation concepts in an interactive process, opened up possibilities to reveal new information and knowledge about the basic, spatial, symbolic and programmatic form of Stourhead. GIS extended the design researchers’ perception via measurement, simulation and experimentation, and at the same time offered alternative ways of understanding the landscape architectonic composition. This gave rise to the possibility of exploring new elements in the framework of landscape design

  1. Comparing GIS-based habitat models for applications in EIA and SEA

    International Nuclear Information System (INIS)

    Gontier, Mikael; Moertberg, Ulla; Balfors, Berit

    2010-01-01

    Land use changes, urbanisation and infrastructure developments in particular, cause fragmentation of natural habitats and threaten biodiversity. Tools and measures must be adapted to assess and remedy the potential effects on biodiversity caused by human activities and developments. Within physical planning, environmental impact assessment (EIA) and strategic environmental assessment (SEA) play important roles in the prediction and assessment of biodiversity-related impacts from planned developments. However, adapted prediction tools to forecast and quantify potential impacts on biodiversity components are lacking. This study tested and compared four different GIS-based habitat models and assessed their relevance for applications in environmental assessment. The models were implemented in the Stockholm region in central Sweden and applied to data on the crested tit (Parus cristatus), a sedentary bird species of coniferous forest. All four models performed well and allowed the distribution of suitable habitats for the crested tit in the Stockholm region to be predicted. The models were also used to predict and quantify habitat loss for two regional development scenarios. The study highlighted the importance of model selection in impact prediction. Criteria that are relevant for the choice of model for predicting impacts on biodiversity were identified and discussed. Finally, the importance of environmental assessment for the preservation of biodiversity within the general frame of biodiversity conservation is emphasised.

  2. Application of radioisotopes in investigating landslides

    International Nuclear Information System (INIS)

    Turcek, P.; Ravinger, R.; Hulla, J.

    1983-01-01

    Radiotracer techniques have been used for geological investigations of landslide areas. It was possible to localize a landslide area and a weakened zone. Based on the results forecasts have been made of further possible landslide in the area

  3. Landsliding in partially saturated materials

    Science.gov (United States)

    Godt, J.W.; Baum, R.L.; Lu, N.

    2009-01-01

    [1] Rainfall-induced landslides are pervasive in hillslope environments around the world and among the most costly and deadly natural hazards. However, capturing their occurrence with scientific instrumentation in a natural setting is extremely rare. The prevailing thinking on landslide initiation, particularly for those landslides that occur under intense precipitation, is that the failure surface is saturated and has positive pore-water pressures acting on it. Most analytic methods used for landslide hazard assessment are based on the above perception and assume that the failure surface is located beneath a water table. By monitoring the pore water and soil suction response to rainfall, we observed shallow landslide occurrence under partially saturated conditions for the first time in a natural setting. We show that the partially saturated shallow landslide at this site is predictable using measured soil suction and water content and a novel unified effective stress concept for partially saturated earth materials. Copyright 2009 by the American Geophysical Union.

  4. GIS-based hazard and risk maps of the Douro river basin (north-eastern Portugal

    Directory of Open Access Journals (Sweden)

    José Gomes Santos

    2015-02-01

    Full Text Available The Douro river basin, in north-eastern Portugal, is a very complex region in terms of its geomorphological structure and morphodynamics. More specifically, the region – the Port Wine-growing region, a UNESCO heritage site – is a landslide-prone area resulting from several factors intrinsic to the bedrock and its detritic cover, combined with factors capable of triggering slope instability mechanisms, such as intense rainfall and human activities. Recently, due to intense rainfall and human activities, frequent rock and mud slides occurred, some of them catastrophic, killing people and damaging property. In the last decade (2000–2010, an accurate inventory of these catastrophic events was made, showing that these events occurred near local small towns, Peso da Régua (2001, Armamar (2003 and Carrazeda de Ansiães (2007. In this paper, we present a case study using field data and Geographic Information Systems (GIS tools to evaluate landslide hazard and risk assessment following multicriteria evaluation techniques.

  5. Combining heuristic and statistical techniques in landslide hazard assessments

    Science.gov (United States)

    Cepeda, Jose; Schwendtner, Barbara; Quan, Byron; Nadim, Farrokh; Diaz, Manuel; Molina, Giovanni

    2014-05-01

    As a contribution to the Global Assessment Report 2013 - GAR2013, coordinated by the United Nations International Strategy for Disaster Reduction - UNISDR, a drill-down exercise for landslide hazard assessment was carried out by entering the results of both heuristic and statistical techniques into a new but simple combination rule. The data available for this evaluation included landslide inventories, both historical and event-based. In addition to the application of a heuristic method used in the previous editions of GAR, the availability of inventories motivated the use of statistical methods. The heuristic technique is largely based on the Mora & Vahrson method, which estimates hazard as the product of susceptibility and triggering factors, where classes are weighted based on expert judgment and experience. Two statistical methods were also applied: the landslide index method, which estimates weights of the classes for the susceptibility and triggering factors based on the evidence provided by the density of landslides in each class of the factors; and the weights of evidence method, which extends the previous technique to include both positive and negative evidence of landslide occurrence in the estimation of weights for the classes. One key aspect during the hazard evaluation was the decision on the methodology to be chosen for the final assessment. Instead of opting for a single methodology, it was decided to combine the results of the three implemented techniques using a combination rule based on a normalization of the results of each method. The hazard evaluation was performed for both earthquake- and rainfall-induced landslides. The country chosen for the drill-down exercise was El Salvador. The results indicate that highest hazard levels are concentrated along the central volcanic chain and at the centre of the northern mountains.

  6. GIS-based seismic shaking slope vulnerability map of Sicily (Central Mediterranean)

    Science.gov (United States)

    Nigro, Fabrizio; Arisco, Giuseppe; Perricone, Marcella; Renda, Pietro; Favara, Rocco

    2010-05-01

    Earthquakes often represent very dangerouses natural events in terms of human life and economic losses and their damage effects are amplified by the synchronous occurrence of seismically-induced ground-shaking failures in wide regions around the seismogenic source. In fact, the shaking associated with big earthquakes triggers extensive landsliding, sometimes at distances of more than 100 km from the epicenter. The active tectonics and the geomorphic/morphodinamic pattern of the regions affected by earthquakes contribute to the slopes instability tendency. In fact, earthquake-induced groun-motion loading determines inertial forces activation within slopes that, combined with the intrinsic pre-existing static forces, reduces the slope stability towards its failure. Basically, under zero-shear stress reversals conditions, a catastrophic failure will take place if the earthquake-induced shear displacement exceeds the critical level of undrained shear strength to a value equal to the gravitational shear stress. However, seismic stability analyses carried out for various infinite slopes by using the existing Newmark-like methods reveal that estimated permanent displacements smaller than the critical value should also be regarded as dangerous for the post-earthquake slope safety, in terms of human activities use. Earthquake-induced (often high-speed) landslides are among the most destructive phenomena related to slopes failure during earthquakes. In fact, damage from earthquake-induced landslides (and other ground-failures), sometimes exceeds the buildings/infrastructures damage directly related to ground-shaking for fault breaking. For this matter, several hearthquakes-related slope failures methods have been developed, for the evaluation of the combined hazard types represented by seismically ground-motion landslides. The methodologies of analysis of the engineering seismic risk related to the slopes instability processes is often achieved through the evaluation of the

  7. An Overview of GIS-Based Modeling and Assessment of Mining-Induced Hazards: Soil, Water, and Forest.

    Science.gov (United States)

    Suh, Jangwon; Kim, Sung-Min; Yi, Huiuk; Choi, Yosoon

    2017-11-27

    In this study, current geographic information system (GIS)-based methods and their application for the modeling and assessment of mining-induced hazards were reviewed. Various types of mining-induced hazard, including soil contamination, soil erosion, water pollution, and deforestation were considered in the discussion of the strength and role of GIS as a viable problem-solving tool in relation to mining-induced hazards. The various types of mining-induced hazard were classified into two or three subtopics according to the steps involved in the reclamation procedure, or elements of the hazard of interest. Because GIS is appropriated for the handling of geospatial data in relation to mining-induced hazards, the application and feasibility of exploiting GIS-based modeling and assessment of mining-induced hazards within the mining industry could be expanded further.

  8. An Overview of GIS-Based Modeling and Assessment of Mining-Induced Hazards: Soil, Water, and Forest

    Science.gov (United States)

    Kim, Sung-Min; Yi, Huiuk; Choi, Yosoon

    2017-01-01

    In this study, current geographic information system (GIS)-based methods and their application for the modeling and assessment of mining-induced hazards were reviewed. Various types of mining-induced hazard, including soil contamination, soil erosion, water pollution, and deforestation were considered in the discussion of the strength and role of GIS as a viable problem-solving tool in relation to mining-induced hazards. The various types of mining-induced hazard were classified into two or three subtopics according to the steps involved in the reclamation procedure, or elements of the hazard of interest. Because GIS is appropriated for the handling of geospatial data in relation to mining-induced hazards, the application and feasibility of exploiting GIS-based modeling and assessment of mining-induced hazards within the mining industry could be expanded further. PMID:29186922

  9. An Overview of GIS-Based Modeling and Assessment of Mining-Induced Hazards: Soil, Water, and Forest

    Directory of Open Access Journals (Sweden)

    Jangwon Suh

    2017-11-01

    Full Text Available In this study, current geographic information system (GIS-based methods and their application for the modeling and assessment of mining-induced hazards were reviewed. Various types of mining-induced hazard, including soil contamination, soil erosion, water pollution, and deforestation were considered in the discussion of the strength and role of GIS as a viable problem-solving tool in relation to mining-induced hazards. The various types of mining-induced hazard were classified into two or three subtopics according to the steps involved in the reclamation procedure, or elements of the hazard of interest. Because GIS is appropriated for the handling of geospatial data in relation to mining-induced hazards, the application and feasibility of exploiting GIS-based modeling and assessment of mining-induced hazards within the mining industry could be expanded further.

  10. An Overview of GIS-Based Modeling and Assessment of Mining-Induced Hazards: Soil, Water, and Forest

    OpenAIRE

    Suh, Jangwon; Kim, Sung-Min; Yi, Huiuk; Choi, Yosoon

    2017-01-01

    In this study, current geographic information system (GIS)-based methods and their application for the modeling and assessment of mining-induced hazards were reviewed. Various types of mining-induced hazard, including soil contamination, soil erosion, water pollution, and deforestation were considered in the discussion of the strength and role of GIS as a viable problem-solving tool in relation to mining-induced hazards. The various types of mining-induced hazard were classified into two or t...

  11. Rainfall-runoff modeling of the Chapel Branch Creek Watershed using GIS-based rational and SCS-CN methods

    Science.gov (United States)

    Elizabeth N. Mihalik; Norm S. Levine; Devendra M. Amatya

    2008-01-01

    Chapel Branch Creek (CBC), located within the Town of Santee adjacent to Lake Marion in Orangeburg County, SC, is listed on the SC 2004 303(d) list of impaired waterbodies due to elevated levels of nitrogen (N), phosphorus (P), chlorophyll-a, and pH. In this study, using a GIS-based approach, two runoff modeling methods, the Rational and SCS-CN methods, have been...

  12. Quantifying the performance of automated GIS-based geomorphological approaches for riparian zone delineation using digital elevation models

    OpenAIRE

    D. Fernández; J. Barquín; M. Álvarez-Cabria; F. J. Peñas

    2012-01-01

    Riparian zone delineation is a central issue for managing rivers and adjacent areas; however, criteria used to delineate them are still under debate. The area inundated by a 50-yr flood has been indicated as an optimal hydrological descriptor for riparian areas. This detailed hydrological information is usually only available for populated areas at risk of flooding. In this work we created several floodplain surfaces by means of two different GIS-based geomorphological appro...

  13. Verification of a GIS-based system for identification of potential hydro power plant sites in Uganda

    OpenAIRE

    Gimbo, Florence

    2015-01-01

    Hydropower makes and is expected to continue to make a significant contribution to meeting the electricity demand in many countries. The information on hydropower potential is many places is often incomplete. A GIS based tool is under development is expected to help in quickly identifying possible hydropower plant locations over a large area in a short time. This study is aimed at evaluating how well this GIS tool is able to estimate the hydropower potential from the runoff maps and terrain/e...

  14. Shallow and Deep-Seated Landslide Differentiation Using Support Vector Machines: A Case Study of the Chuetsu Area, Japan

    Directory of Open Access Journals (Sweden)

    Jie Dou

    2015-01-01

    Full Text Available Landslides are one of the most destructive geological disasters affecting Japan every year, resulting in huge losses in life and property. Numerous susceptibility studies have been conducted to minimize the risk of landslides; however, most of these studies do not differentiate landslide types. This study examines the differences in landslide depth, volume and the risk imposed between shallow and deep-seated landslide types. Shallow and deep-seated landslide prediction is useful in utilizing emergency resources by prioritizing target areas while responding to sediment related disasters. This study utilizes a 2-m DEM derived from airborne Light detection and ranging (Lidar, geological information and support vector machines (SVMs to study the 1225 landslides triggered by the M 6.8 Chuetsu earthquake in Japan and the successive aftershocks. Ten factors, including elevation, slope, aspect, curvature, lithology, distance from the nearest geologic boundary, density of geologic boundaries, distance from drainage network, the compound topographic index (CTI and the stream power index (SPI derived from the DEM and a geological map were analyzed. Iterated over 10 random instances the average training and testing accuracy of landslide type prediction was found to be 89.2 and 77.8%, respectively. We also found that the overall accuracy of SVMs does not rapidly decrease with a decrease in training samples. The trained model was then used to prepare a map showing probable future landslides differentiated into shallow and deep-seated landslides.

  15. Landslide hazard assessment along a mountain highway in the Indian Himalayan Region (IHR) using remote sensing and computational models

    Science.gov (United States)

    Krishna, Akhouri P.; Kumar, Santosh

    2013-10-01

    Landslide hazard assessments using computational models, such as artificial neural network (ANN) and frequency ratio (FR), were carried out covering one of the important mountain highways in the Central Himalaya of Indian Himalayan Region (IHR). Landslide influencing factors were either calculated or extracted from spatial databases including recent remote sensing data of LANDSAT TM, CARTOSAT digital elevation model (DEM) and Tropical Rainfall Measuring Mission (TRMM) satellite for rainfall data. ANN was implemented using the multi-layered feed forward architecture with different input, output and hidden layers. This model based on back propagation algorithm derived weights for all possible parameters of landslides and causative factors considered. The training sites for landslide prone and non-prone areas were identified and verified through details gathered from remote sensing and other sources. Frequency Ratio (FR) models are based on observed relationships between the distribution of landslides and each landslide related factor. FR model implementation proved useful for assessing the spatial relationships between landslide locations and factors contributing to its occurrence. Above computational models generated respective susceptibility maps of landslide hazard for the study area. This further allowed the simulation of landslide hazard maps on a medium scale using GIS platform and remote sensing data. Upon validation and accuracy checks, it was observed that both models produced good results with FR having some edge over ANN based mapping. Such statistical and functional models led to better understanding of relationships between the landslides and preparatory factors as well as ensuring lesser levels of subjectivity compared to qualitative approaches.

  16. Discrete rough set analysis of two different soil-behavior-induced landslides in National Shei-Pa Park, Taiwan

    Directory of Open Access Journals (Sweden)

    Shih-Hsun Chang

    2015-11-01

    Full Text Available The governing factors that influence landslide occurrences are complicated by the different soil conditions at various sites. To resolve the problem, this study focused on spatial information technology to collect data and information on geology. GIS, remote sensing and digital elevation model (DEM were used in combination to extract the attribute values of the surface material in the vast study area of Shei-Pa National Park, Taiwan. The factors influencing landslides were collected and quantification values computed. The major soil component of loam and gravel in the Shei-Pa area resulted in different landslide problems. The major factors were successfully extracted from the influencing factors. Finally, the discrete rough set (DRS classifier was used as a tool to find the threshold of each attribute contributing to landslide occurrence, based upon the knowledge database. This rule-based knowledge database provides an effective and urgent system to manage landslides. NDVI (Normalized Difference Vegetation Index, VI (Vegetation Index, elevation, and distance from the road are the four major influencing factors for landslide occurrence. The landslide hazard potential diagrams (landslide susceptibility maps were drawn and a rational accuracy rate of landslide was calculated. This study thus offers a systematic solution to the investigation of landslide disasters.

  17. A GIS-based methodology for the estimation of potential volcanic damage and its application to Tenerife Island, Spain

    Science.gov (United States)

    Scaini, C.; Felpeto, A.; Martí, J.; Carniel, R.

    2014-05-01

    This paper presents a GIS-based methodology to estimate damages produced by volcanic eruptions. The methodology is constituted by four parts: definition and simulation of eruptive scenarios, exposure analysis, vulnerability assessment and estimation of expected damages. Multi-hazard eruptive scenarios are defined for the Teide-Pico Viejo active volcanic complex, and simulated through the VORIS tool. The exposure analysis identifies the elements exposed to the hazard at stake and focuses on the relevant assets for the study area. The vulnerability analysis is based on previous studies on the built environment and complemented with the analysis of transportation and urban infrastructures. Damage assessment is performed associating a qualitative damage rating to each combination of hazard and vulnerability. This operation consists in a GIS-based overlap, performed for each hazardous phenomenon considered and for each element. The methodology is then automated into a GIS-based tool using an ArcGIS® program. Given the eruptive scenarios and the characteristics of the exposed elements, the tool produces expected damage maps. The tool is applied to the Icod Valley (North of Tenerife Island) which is likely to be affected by volcanic phenomena in case of eruption from both the Teide-Pico Viejo volcanic complex and North-West basaltic rift. Results are thematic maps of vulnerability and damage that can be displayed at different levels of detail, depending on the user preferences. The aim of the tool is to facilitate territorial planning and risk management in active volcanic areas.

  18. A GIS-based 3D online information system for underground energy storage in northern Germany

    Science.gov (United States)

    Nolde, Michael; Malte, Schwanebeck; Ehsan, Biniyaz; Rainer, Duttmann

    2015-04-01

    We would like to present the concept and current state of development of a GIS-based 3D online information system for underground energy storage. Its aim is to support the local authorities through pre-selection of possible sites for thermal, electrical and substantial underground energy storages. Since the extension of renewable energies has become legal requirement in Germany, the underground storing of superfluously produced green energy (such as during a heavy wind event) in the form of compressed air, gas or heated water has become increasingly important. However, the selection of suitable sites is a complex task. The presented information system uses data of geological features such as rock layers, salt domes and faults enriched with attribute data such as rock porosity and permeability. This information is combined with surface data of the existing energy infrastructure, such as locations of wind and biogas stations, powerline arrangement and cable capacity, and energy distribution stations. Furthermore, legal obligations such as protected areas on the surface and current underground mining permissions are used for the process of pre-selecting sites suitable for energy storage. Not only the current situation but also prospective scenarios, such as expected growth in produced amount of energy are incorporated in the system. While the process of pre-selection itself is completely automated, the user has full control of the weighting of the different factors via the web interface. The system is implemented as an online 3D server GIS environment, so that it can easily be utilized in any web browser. The results are visualized online as interactive 3d graphics. The information system is implemented in the Python programming language in combination with current Web standards, and is build using only free and open source software. It is being developed at Kiel University as part of the ANGUS+ project (lead by Prof. Sebastian Bauer) for the federal state of

  19. Potential Coastal Pumped Hydroelectric Energy Storage Locations Identified using GIS-based Topographic Analysis

    Science.gov (United States)

    Parsons, R.; Barnhart, C. J.; Benson, S. M.

    2013-12-01

    Large-scale electrical energy storage could accommodate variable, weather dependent energy resources such as wind and solar. Pumped hydroelectric energy storage (PHS) and compressed energy storage area (CAES) have life cycle energy and financial costs that are an order of magnitude lower than conventional electrochemical storage technologies. However PHS and CAES storage technologies require specific geologic conditions. Conventional PHS requires an upper and lower reservoir separated by at least 100 m of head, but no more than 10 km in horizontal distance. Conventional PHS also impacts fresh water supplies, riparian ecosystems, and hydrologic environments. A PHS facility that uses the ocean as the lower reservoir benefits from a smaller footprint, minimal freshwater impact, and the potential to be located near off shore wind resources and population centers. Although technologically nascent, today one coastal PHS facility exists. The storage potential for coastal PHS is unknown. Can coastal PHS play a significant role in augmenting future power grids with a high faction of renewable energy supply? In this study we employ GIS-based topographic analysis to quantify the coastal PHS potential of several geographic locations, including California, Chile and Peru. We developed automated techniques that seek local topographic minima in 90 m spatial resolution shuttle radar topography mission (SRTM) digital elevation models (DEM) that satisfy the following criteria conducive to PHS: within 10 km from the sea; minimum elevation 150 m; maximum elevation 1000 m. Preliminary results suggest the global potential for coastal PHS could be very significant. For example, in northern Chile we have identified over 60 locations that satisfy the above criteria. Two of these locations could store over 10 million cubic meters of water or several GWh of energy. We plan to report a global database of candidate coastal PHS locations and to estimate their energy storage capacity.

  20. Renewable energy: GIS-based mapping and modelling of potentials and demand

    Science.gov (United States)

    Blaschke, Thomas; Biberacher, Markus; Schardinger, Ingrid.; Gadocha, Sabine; Zocher, Daniela

    2010-05-01

    Worldwide demand of energy is growing and will continue to do so for the next decades to come. IEA has estimated that global primary energy demand will increase by 40 - 50% from 2003 to 2030 (IEA, 2005) depending on the fact whether currently contemplated energy policies directed towards energy-saving and fuel-diversification will be effectuated. The demand for Renewable Energy (RE) is undenied but clear figures and spatially disaggregated potentials for the various energy carriers are very rare. Renewable Energies are expected to reduce pressures on the environment and CO2 production. In several studies in Germany (North-Rhine Westphalia and Lower Saxony) and Austria we studied the current and future pattern of energy production and consumption. In this paper we summarize and benchmark different RE carriers, namely wind, biomass (forest and non-forest, geothermal, solar and hydro power. We demonstrate that GIS-based scalable and flexible information delivery sheds new light on the prevailing metaphor of GIS as a processing engine serving needs of users more on demand rather than through ‘maps on stock'. We compare our finding with those of several energy related EU-FP7 projects in Europe where we have been involved - namely GEOBENE, REACCESS, ENERGEO - and demonstrate that more and more spatial data will become available together with tools that allow experts to do their own analyses and to communicate their results in ways which policy makers and the public can readily understand and use as a basis for their own actions. Geoportals in combination with standardised geoprocessing today supports the older vision of an automated presentation of data on maps, and - if user privileges are given - facilities to interactively manipulate these maps. We conclude that the most critical factor in modelling energy supply and demand remain the economic valuation of goods and services, especially the forecast of future end consumer energy costs.

  1. Gis-Based Multi-Criteria Decision Analysis for Forest Fire Risk Mapping

    Science.gov (United States)

    Akay, A. E.; Erdoğan, A.

    2017-11-01

    The forested areas along the coastal zone of the Mediterranean region in Turkey are classified as first-degree fire sensitive areas. Forest fires are major environmental disaster that affects the sustainability of forest ecosystems. Besides, forest fires result in important economic losses and even threaten human lives. Thus, it is critical to determine the forested areas with fire risks and thereby minimize the damages on forest resources by taking necessary precaution measures in these areas. The risk of forest fire can be assessed based on various factors such as forest vegetation structures (tree species, crown closure, tree stage), topographic features (slope and aspect), and climatic parameters (temperature, wind). In this study, GIS-based Multi-Criteria Decision Analysis (MCDA) method was used to generate forest fire risk map. The study was implemented in the forested areas within Yayla Forest Enterprise Chiefs at Dursunbey Forest Enterprise Directorate which is classified as first degree fire sensitive area. In the solution process, "extAhp 2.0" plug-in running Analytic Hierarchy Process (AHP) method in ArcGIS 10.4.1 was used to categorize study area under five fire risk classes: extreme risk, high risk, moderate risk, and low risk. The results indicated that 23.81 % of the area was of extreme risk, while 25.81 % was of high risk. The result indicated that the most effective criterion was tree species, followed by tree stages. The aspect had the least effective criterion on forest fire risk. It was revealed that GIS techniques integrated with MCDA methods are effective tools to quickly estimate forest fire risk at low cost. The integration of these factors into GIS can be very useful to determine forested areas with high fire risk and also to plan forestry management after fire.

  2. Using catenas for GIS-based mapping of NW Mediterranean littoral habitats

    Science.gov (United States)

    Mariani, Simone; Cefalì, Maria Elena; Terradas, Marc; Chappuis, Eglantine; Ballesteros, Enric

    2014-06-01

    Studies aimed at describing habitats and mapping their distributions are pivotal to implementing management plans and to effectively guide conservation measures. We developed a novel approach of data collection and entry (CAT-LIT) to establish a detailed cartography of the littoral habitats found along the Catalan coast (Spain). Field data were recorded using coded, two-digit hierarchical lists (e.g. Aa, Ab, etc.) of horizons found at each point along the coast, called catenas. The horizons were either dominated by species (on the rocky bottoms) or sediment types (on the beaches) and corresponded to LPRE, EUNIS and CORINE habitats. Catenas were transferred into a database and calculations about the extent of bottom types, habitats, and catenas themselves along the coast were carried out with GIS tools. In addition, habitat link richness was calculated and represented using network analysis programs. The application of CAT-LIT to the Catalan coast showed that the habitats dominated by the lichen Verrucaria amphibia and the flattened barnacle Euraphia depressa and those dominated by the barnacle Chthamalus spp. were almost ubiquitous. Those dominated by the red alga Corallina elongata, the mussel Mytilus galloprovincialis and the red alga Rissoella verruculosa were also common. Because of the frequency of their connections, those habitats formed a huge hub of links in the networks. By using catenas, the habitats can be viewed using GIS based programs keeping the catena as the main informational and ecological unit. The catenas allow maximum compactness when vertically distributed habitats are to be shown on a 2D map. The complete cartography and dataset on the spatial distribution of the littoral habitats from Catalonia is valuable for coastal management and conservation to study changes in the habitat distribution and relate such changes to anthropogenic pressures. Furthermore, the CAT-LIT can be easily adapted to shores of other seas and oceans to obtain accurate

  3. Comparison of Artificial Neural Networks and GIS Based Solar Analysis for Solar Potential Estimation

    Science.gov (United States)

    Konakoǧlu, Berkant; Usta, Ziya; Cömert, Çetin; Gökalp, Ertan

    2016-04-01

    Nowadays, estimation of solar potential plays an important role in planning process for sustainable cities. The use of solar panels, which produces electricity directly from the sun, has become popular in accordance with developing technologies. Since the use of solar panels enables the users to decrease costs and increase yields, the use of solar panels will be more popular in the future. Production of electricity is not convenient for all circumstances. Shading effects, massive clouds and rainy weather are some factors that directly affect the production of electricity from solar energy. Hence, before the installation of solar panels, it is crucial to conduct spatial analysis and estimate the solar potential of the place that the solar panel will be installed. There are several approaches to determine the solar potential. Examination of the applications in the literature reveals that the applications conducted for determining the solar potential are divided into two main categories. Solar potential is estimated either by using artificial neural network approach in which statistical parameters such as the duration of sun shine, number of clear days, solar radiation etc. are used, or by spatial analysis conducted in GIS approaches in which spatial parameters such as, latitude, longitude, slope, aspect etc. are used. In the literature, there are several studies that use both approaches but the literature lacks of a study related to the comparison of these approaches. In this study, Karadeniz Technical University campus has been selected as study area. Monthly average values of the number of clear sky days, air temperature, atmospheric pressure, relative humidity, sunshine duration and solar radiation parameters obtained for the years between 2005 and 2015 will be used to perform artificial neural network analysis to estimate the solar potential of the study area. The solar potential will also be estimated by using GIS-based solar analysis modules. The results of

  4. Landslide prediction using combined deterministic and probabilistic methods in hilly area of Mt. Medvednica in Zagreb City, Croatia

    Science.gov (United States)

    Wang, Chunxiang; Watanabe, Naoki; Marui, Hideaki

    2013-04-01

    The hilly slopes of Mt. Medvednica are stretched in the northwestern part of Zagreb City, Croatia, and extend to approximately 180km2. In this area, landslides, e.g. Kostanjek landslide and Črešnjevec landslide, have brought damage to many houses, roads, farmlands, grassland and etc. Therefore, it is necessary to predict the potential landslides and to enhance landslide inventory for hazard mitigation and security management of local society in this area. We combined deterministic method and probabilistic method to assess potential landslides including their locations, size and sliding surfaces. Firstly, this study area is divided into several slope units that have similar topographic and geological characteristics using the hydrology analysis tool in ArcGIS. Then, a GIS-based modified three-dimensional Hovland's method for slope stability analysis system is developed to identify the sliding surface and corresponding three-dimensional safety factor for each slope unit. Each sliding surface is assumed to be the lower part of each ellipsoid. The direction of inclination of the ellipsoid is considered to be the same as the main dip direction of the slope unit. The center point of the ellipsoid is randomly set to the center point of a grid cell in the slope unit. The minimum three-dimensional safety factor and corresponding critical sliding surface are also obtained for each slope unit. Thirdly, since a single value of safety factor is insufficient to evaluate the slope stability of a slope unit, the ratio of the number of calculation cases in which the three-dimensional safety factor values less than 1.0 to the total number of trial calculation is defined as the failure probability of the slope unit. If the failure probability is more than 80%, the slope unit is distinguished as 'unstable' from other slope units and the landslide hazard can be mapped for the whole study area.

  5. Precursory landforms and geologic structures of catastrophic landslides induced by typhoon Talas 2011 Japan (Invited)

    Science.gov (United States)

    Chigira, M.; Matsushi, Y.; Tsou, C.

    2013-12-01

    Our experience of catastrophic landslides induced by rainstorms and earthquakes in recent years suggests that many of them are preceded by deep-seated gravitational slope deformation. Deep-seated gravitational slope deformation continues slowly and continually and some of them transform into catastrophic failures, which cause devastating damage in wide areas. Some other types, however, do not change into catastrophic failure. Deep-seated gravitational slope deformation that preceded catastrophic failures induced by typhoon Talas 2011 Japan, had been surveyed with airborne laser scanner beforehand, of which high-resolution DEMs gave us an important clue to identify which type of topographic features of gravitational slope deformation is susceptible to catastrophic failure. We found that 26 of 39 deep-seated catastrophic landslides had small scarps along the heads of future landslides. These scarps were caused by gravitational slope deformation that preceded the catastrophic failure. Although the scarps may have been enlarged by degradation, their sizes relative to the whole slopes suggest that minimal slope deformation had occurred in the period immediately before the catastrophic failure. The scarp ratio, defined as the ratio of length of a scarp to that of the whole slope both measured along the slope line, ranged from 1% to 23%. 38% of the landslides with small scarps had scarp ratios less than 4%, and a half less than 8%. This fact suggests that the gravitational slope deformation preceded catastrophic failure was relatively small and may suggest that those slopes were under critical conditions just before catastrophic failure. The above scarp ratios may be characteristic to accretional complex with undulating, anastomosing thrust faults, which were major sliding surfaces of the typhoon-induced landslides. Eleven of the remaining 13 landslides occurred in landslide scars of previous landslides or occurred as an extension of landslide scars at the lower parts of

  6. Evaluation of Landslide Mapping Techniques and LiDAR-based Conditioning Factors

    Science.gov (United States)

    Mahalingam, R.; Olsen, M. J.

    2014-12-01

    Landslides are a major geohazard, which result in significant human, infrastructure, and economic losses. Landslide susceptibility mapping can help communities to plan and prepare for these damaging events. Mapping landslide susceptible locations using GIS and remote sensing techniques is gaining popularity in the past three decades. These efforts use a wide variety of procedures and consider a wide range of factors. Unfortunately, each study is often completed differently and independently of others. Further, the quality of the datasets used varies in terms of source, data collection, and generation, which can propagate errors or inconsistencies into the resulting output maps. Light detection and ranging (LiDAR) has proved to have higher accuracy in representing the continuous topographic surface, which can help minimize this uncertainty. The primary objectives of this paper are to investigate the applicability and performance of terrain factors in landslide hazard mapping, determine if LiDAR-derived datasets (slope, slope roughness, terrain roughness, stream power index and compound topographic index) can be used for predictive mapping without data representing other common landslide conditioning factors, and evaluate the differences in landslide susceptibility mapping using widely-used statistical approaches. The aforementioned factors were used to produce landslide susceptibility maps for a 140 km2 study area in northwest Oregon using six representative techniques: frequency ratio, weights of evidence, logistic regression, discriminant analysis, artificial neural network, and support vector machine. Most notably, the research showed an advantage in selecting fewer critical conditioning factors. The most reliable factors all could be derived from a single LiDAR DEM, reducing the need for laborious and costly data gathering. Most of the six techniques showed similar statistical results; however, ANN showed less accuracy for predictive mapping. Keywords : Li

  7. The National Landslide Information Center; data to reduce landslide damage

    Science.gov (United States)

    Brown, W. M.

    1992-01-01

    Almost every day a landslide disasters occurs somewhere in the world. Nearly any time there is heavy rainfall, an earthquake, a volcanic eruption, strong wave action on a shoreline, or some ill-considered alteration of sloping land by humans, landslides occur.

  8. On the characteristics of landslide tsunamis.

    Science.gov (United States)

    Løvholt, F; Pedersen, G; Harbitz, C B; Glimsdal, S; Kim, J

    2015-10-28

    This review presents modelling techniques and processes that govern landslide tsunami generation, with emphasis on tsunamis induced by fully submerged landslides. The analysis focuses on a set of representative examples in simplified geometries demonstrating the main kinematic landslide parameters influencing initial tsunami amplitudes and wavelengths. Scaling relations from laboratory experiments for subaerial landslide tsunamis are also briefly reviewed. It is found that the landslide acceleration determines the initial tsunami elevation for translational landslides, while the landslide velocity is more important for impulsive events such as rapid slumps and subaerial landslides. Retrogressive effects stretch the tsunami, and in certain cases produce enlarged amplitudes due to positive interference. In an example involving a deformable landslide, it is found that the landslide deformation has only a weak influence on tsunamigenesis. However, more research is needed to determine how landslide flow processes that involve strong deformation and long run-out determine tsunami generation. © 2015 The Authors.

  9. A GRASS GIS Semi-Stochastic Model for Evaluating the Probability of Landslides Impacting Road Networks in Collazzone, Central Italy

    Science.gov (United States)

    Taylor, Faith E.; Santangelo, Michele; Marchesini, Ivan; Malamud, Bruce D.

    2013-04-01

    During a landslide triggering event, the tens to thousands of landslides resulting from the trigger (e.g., earthquake, heavy rainfall) may block a number of sections of the road network, posing a risk to rescue efforts, logistics and accessibility to a region. Here, we present initial results from a semi-stochastic model we are developing to evaluate the probability of landslides intersecting a road network and the network-accessibility implications of this across a region. This was performed in the open source GRASS GIS software, where we took 'model' landslides and dropped them on a 79 km2 test area region in Collazzone, Umbria, Central Italy, with a given road network (major and minor roads, 404 km in length) and already determined landslide susceptibilities. Landslide areas (AL) were randomly selected from a three-parameter inverse gamma probability density function, consisting of a power-law decay of about -2.4 for medium and large values of AL and an exponential rollover for small values of AL; the rollover (maximum probability) occurs at about AL = 400 m.2 The number of landslide areas selected for each triggered event iteration was chosen to have an average density of 1 landslide km-2, i.e. 79 landslide areas chosen randomly for each iteration. Landslides were then 'dropped' over the region semi-stochastically: (i) random points were generated across the study region; (ii) based on the landslide susceptibility map, points were accepted/rejected based on the probability of a landslide occurring at that location. After a point was accepted, it was assigned a landslide area (AL) and length to width ratio. Landslide intersections with roads were then assessed and indices such as the location, number and size of road blockage recorded. The GRASS-GIS model was performed 1000 times in a Monte-Carlo type simulation. Initial results show that for a landslide triggering event of 1 landslide km-2 over a 79 km2 region with 404 km of road, the number of road blockages

  10. The use of remote sensing for landslide studies in Europe

    Science.gov (United States)

    Tofani, Veronica; Agostini, Andrea; Segoni, Samuele; Catani, Filippo; Casagli, Nicola

    2013-04-01

    The existing remote sensing techniques and their actual application in Europe for landslide detection, mapping and monitoring have been investigated. Data and information necessary to evaluate the subjects have been collected through a questionnaire, designed using a Google form, which was disseminated among end-users and researchers involved in landslide. In total, 49 answers were collected, coming from 17 European countries and from different kinds of institutions (universities, research institutes, public institutes and private companies). The spatial distribution of the answers is consistent with the distribution of landslides in Europe, the significance of landslides impact on society and the estimated landslide susceptibility in the various countries. The outcomes showed that landslide detection and mapping is mainly performed with aerial photos, often associated with optical and radar imagery. Concerning landslide monitoring, satellite radars prevail over the other types of data followed by aerial photos and meteorological sensors. Since subsampling the answers according to the different typology of institutions it is not noticeable a clear gap between research institutes and end users, it is possible to infer that in landslide remote sensing the research is advancing at the same pace as its day-to-day application. Apart from optical and radar imagery, other techniques are less widespread and some of them are not so well established, notwithstanding their performances are increasing at a fast rate as scientific and technological improvements are accomplished. Remote sensing is mainly used for detection/mapping and monitoring of slides, flows and lateral spreads with a preferably large scale of analysis (1:5000 - 1:25000). All the compilers integrate remote sensing data with other thematic data, mainly geological maps, landslide inventory maps and DTMs and derived maps. Concerning landslide monitoring, the results of the questionnaire stressed that the best

  11. A GIS Based 3D Online Decision Assistance System for Underground Energy Storage in Northern Germany

    Science.gov (United States)

    Nolde, M.; Schwanebeck, M.; Biniyaz, E.; Duttmann, R.

    2014-12-01

    We would like to present a GIS-based 3D online decision assistance system for underground energy storage. Its aim is to support the local land use planning authorities through pre-selection of possible sites for thermal, electrical and substantial underground energy storages. Since the extension of renewable energies has become legal requirement in Germany, the underground storing of superfluously produced green energy (such as during a heavy wind event) in the form of compressed air, gas or heated water has become increasingly important. However, the selection of suitable sites is a complex task. The assistance system uses data of geological features such as rock layers, salt caverns and faults enriched with attribute data such as rock porosity and permeability. This information is combined with surface data of the existing energy infrastructure, such as locations of wind and biogas stations, power line arrangement and cable capacity, and energy distribution stations. Furthermore, legal obligations such as protected areas on the surface and current underground mining permissions are used for the decision finding process. Not only the current situation but also prospective scenarios, such as expected growth in produced amount of energy are incorporated in the system. The decision process is carried out via the 'Analytic Hierarchy Process' (AHP) methodology of the 'Multi Object Decision Making' (MODM) approach. While the process itself is completely automated, the user has full control of the weighting of the different factors via the web interface. The system is implemented as an online 3D server GIS environment, with no software needed to be installed on the user side. The results are visualized as interactive 3d graphics. The implementation of the assistance system is based exclusively on free and open source software, and utilizes the 'Python' programming language in combination with current web technologies, such as 'HTML5', 'CSS3' and 'JavaScript'. It is

  12. Characteristics and Impact of Imperviousness From a GIS-based Hydrological Perspective

    Science.gov (United States)

    Moglen, G. E.; Kim, S.

    2005-12-01

    With the concern that imperviousness can be differently quantified depending on data sources and methods, this study assessed imperviousness estimates using two different data sources: land use and land cover. Year 2000 land use developed by the Maryland Department of Planning was utilized to estimate imperviousness by assigning imperviousness coefficients to unique land use categories. These estimates were compared with imperviousness estimates based on satellite-derived land cover from the 2001 National Land Cover Dataset. Our study developed the relationships between these two estimates in the form of regression equations to convert imperviousness derived from one data source to the other. The regression equations are considered reliable, based on goodness-of-fit measures. Furthermore, this study examined how quantitatively different imperviousness estimates affect the prediction of hydrological response both in the flow regime and in the thermal regime. We assessed the relationships between indicators of hydrological response and imperviousness-descriptors. As indicators of flow variability, coefficient of variance, lag-one autocorrelation, and mean daily flow change were calculated based on measured mean daily stream flow from the water year 1997 to 2003. For thermal variability, indicators such as percent-days of surge, degree-day, and mean daily temperature difference were calculated base on measured stream temperature over several basins in Maryland. To describe imperviousness through the hydrological process, GIS-based spatially distributed hydrological models were developed based on a water-balance method and the SCS-CN method. Imperviousness estimates from land use and land cover were used as predictors in these models to examine the effect of imperviousness using different data sources on the prediction of hydrological response. Indicators of hydrological response were also regressed on aggregate imperviousness. This allowed for identifying if

  13. Documentation of Cultural Heritages Using a GIS Based Information and Management System; Case Study of Safranbolu

    Science.gov (United States)

    Seker, D. Z.; Alkan, M.; Kutoglu, S. S.; Akcin, H.

    2010-12-01

    Documentation of the cultural heritage sites is extremely important for monitoring and preserves them from natural disasters and human made activities. Due to its very rich historical background from the first human settlements in Catalhoyuk and Alacahoyuk and civilizations such as Byzantine, Seljuk and Ottoman, there are lots of cultural heritage sites in Turkey. 3D modeling and recording of historical buildings using modern tools and techniques in several locations of Turkey have been conducted and still continuing. The nine cultural sites in Turkey are included in the protection list of UNESCO as cultural heritage and one of them is the township of Safranbolu, which is the one of the most outstanding example of the traditional Turkish Architecture and also unique itself in terms of conservation of the human settlement in their authentic environmental motif up till now. In this study outcomes and further studies of a research project related to study area which is supported by the Turkish National Research Center (TUBITAK) with the project number 106Y157, will be presented in details. The basic aim of the study is development a GIS based information and management system for the city of Safranbolu. All historical buildings which are registered are assigned with the database. 3D modeling some of the selected building among the buildings which are registered as historical monuments using different data comes from different sources similar to their original constructions were realized and then it will be distributed via internet by a web-based information system designed during the project. Also some of the buildings were evaluated using close range photogrammetric technique to obtain their façade reliefs, were also assigned with the database. Designed database consists of 3D models, locations, historical information, cadastral and land register data of the selected buildings together with the other data collected during the project related to buildings. Using this

  14. Using GIS-based methods of multicriteria analysis to construct socio-economic deprivation indices

    Directory of Open Access Journals (Sweden)

    Hayes Michael V

    2007-05-01

    Full Text Available Abstract Background Over the past several decades researchers have produced substantial evidence of a social gradient in a variety of health outcomes, rising from systematic differences in income, education, employment conditions, and family dynamics within the population. Social gradients in health are measured using deprivation indices, which are typically constructed from aggregated socio-economic data taken from the national census – a technique which dates back at least until the early 1970's. The primary method of index construction over the last decade has been a Principal Component Analysis. Seldom are the indices constructed from survey-based data sources due to the inherent difficulty in validating the subjectivity of the response scores. We argue that this very subjectivity can uncover spatial distributions of local health outcomes. Moreover, indication of neighbourhood socio-economic status may go underrepresented when weighted without expert opinion. In this paper we propose the use of geographic information science (GIS for constructing the index. We employ a GIS-based Order Weighted Average (OWA Multicriteria Analysis (MCA as a technique to validate deprivation indices that are constructed using more qualitative data sources. Both OWA and traditional MCA are well known and used methodologies in spatial analysis but have had little application in social epidemiology. Results A survey of British Columbia's Medical Health Officers (MHOs was used to populate the MCA-based index. Seven variables were selected and weighted based on the survey results. OWA variable weights assign both local and global weights to the index variables using a sliding scale, producing a range of variable scenarios. The local weights also provide leverage for controlling the level of uncertainty in the MHO response scores. This is distinct from traditional deprivation indices in that the weighting is simultaneously dictated by the original respondent scores

  15. Burden of disease attributed to ambient air pollution in Thailand: A GIS-based approach.

    Directory of Open Access Journals (Sweden)

    Chayut Pinichka

    Full Text Available Growing urbanisation and population requiring enhanced electricity generation as well as the increasing numbers of fossil fuel in Thailand pose important challenges to air quality management which impacts on the health of the population. Mortality attributed to ambient air pollution is one of the sustainable development goals (SDGs. We estimated the spatial pattern of mortality burden attributable to selected ambient air pollution in 2009 based on the empirical evidence in Thailand.We estimated the burden of disease attributable to ambient air pollution based on the comparative risk assessment (CRA framework developed by the World Health Organization (WHO and the Global Burden of Disease study (GBD. We integrated geographical information systems (GIS-based exposure assessments into spatial interpolation models to estimate ambient air pollutant concentrations, the population distribution of exposure and the concentration-response (CR relationship to quantify ambient air pollution exposure and associated mortality. We obtained air quality data from the Pollution Control Department (PCD of Thailand surface air pollution monitoring network sources and estimated the CR relationship between relative risk (RR and concentration of air pollutants from the epidemiological literature.We estimated 650-38,410 ambient air pollution-related fatalities and 160-5,982 fatalities that could have been avoided with a 20 reduction in ambient air pollutant concentrations. The summation of population-attributable fraction (PAF of the disease burden for all-causes mortality in adults due to NO2 and PM2.5 were the highest among all air pollutants at 10% and 7.5%, respectively. The PAF summation of PM2.5 for lung cancer and cardiovascular disease were 16.8% and 14.6% respectively and the PAF summations of mortality attributable to PM10 was 3.4% for all-causes mortality, 1.7% for respiratory and 3.8% for cardiovascular mortality, while the PAF summation of mortality

  16. Burden of disease attributed to ambient air pollution in Thailand: A GIS-based approach.

    Science.gov (United States)

    Pinichka, Chayut; Makka, Nuttapat; Sukkumnoed, Decharut; Chariyalertsak, Suwat; Inchai, Puchong; Bundhamcharoen, Kanitta

    2017-01-01

    Growing urbanisation and population requiring enhanced electricity generation as well as the increasing numbers of fossil fuel in Thailand pose important challenges to air quality management which impacts on the health of the population. Mortality attributed to ambient air pollution is one of the sustainable development goals (SDGs). We estimated the spatial pattern of mortality burden attributable to selected ambient air pollution in 2009 based on the empirical evidence in Thailand. We estimated the burden of disease attributable to ambient air pollution based on the comparative risk assessment (CRA) framework developed by the World Health Organization (WHO) and the Global Burden of Disease study (GBD). We integrated geographical information systems (GIS)-based exposure assessments into spatial interpolation models to estimate ambient air pollutant concentrations, the population distribution of exposure and the concentration-response (CR) relationship to quantify ambient air pollution exposure and associated mortality. We obtained air quality data from the Pollution Control Department (PCD) of Thailand surface air pollution monitoring network sources and estimated the CR relationship between relative risk (RR) and concentration of air pollutants from the epidemiological literature. We estimated 650-38,410 ambient air pollution-related fatalities and 160-5,982 fatalities that could have been avoided with a 20 reduction in ambient air pollutant concentrations. The summation of population-attributable fraction (PAF) of the disease burden for all-causes mortality in adults due to NO2 and PM2.5 were the highest among all air pollutants at 10% and 7.5%, respectively. The PAF summation of PM2.5 for lung cancer and cardiovascular disease were 16.8% and 14.6% respectively and the PAF summations of mortality attributable to PM10 was 3.4% for all-causes mortality, 1.7% for respiratory and 3.8% for cardiovascular mortality, while the PAF summation of mortality attributable to

  17. The National Landslide Database of Great Britain: Acquisition, communication and the role of social media

    Science.gov (United States)

    Pennington, Catherine; Freeborough, Katy; Dashwood, Claire; Dijkstra, Tom; Lawrie, Kenneth

    2015-11-01

    The British Geological Survey (BGS) is the national geological agency for Great Britain that provides geoscientific information to government, other institutions and the public. The National Landslide Database has been developed by the BGS and is the focus for national geohazard research for landslides in Great Britain. The history and structure of the geospatial database and associated Geographical Information System (GIS) are explained, along with the future developments of the database and its applications. The database is the most extensive source of information on landslides in Great Britain with over 17,000 records of landslide events to date, each documented as fully as possible for inland, coastal and artificial slopes. Data are gathered through a range of procedures, including: incorporation of other databases; automated trawling of current and historical scientific literature and media reports; new field- and desk-based mapping technologies with digital data capture, and using citizen science through social media and other online resources. This information is invaluable for directing the investigation, prevention and mitigation of areas of unstable ground in accordance with Government planning policy guidelines. The national landslide susceptibility map (GeoSure) and a national landslide domains map currently under development, as well as regional mapping campaigns, rely heavily on the information contained within the landslide database. Assessing susceptibility to landsliding requires knowledge of the distribution of failures, an understanding of causative factors, their spatial distribution and likely impacts, whilst understanding the frequency and types of landsliding present is integral to modelling how rainfall will influence the stability of a region. Communication of landslide data through the Natural Hazard Partnership (NHP) and Hazard Impact Model contributes to national hazard mitigation and disaster risk reduction with respect to weather and

  18. Short Term Patterns of Landslides Causing Death in Latin America and the Caribbean

    Science.gov (United States)

    Sepulveda, S. A.; Petley, D. N.

    2015-12-01

    Among natural hazards, landslides represent a significant source of loss of life in mountainous terrains. Many regions of Latin America and the Caribbean are prone to landslide activity, due to strong topographic relief, high tectonic uplift rates, seismicity and/or climate. Further, vulnerable populations are often concentrated in deep valleys or mountain foothills susceptible to catastrophic landslides, with vulnerability further increased by dense urbanization and precarious settlements in some large cities. While historic extremely catastrophic events such as the 1999 Vargas flows in Venezuela or the 1970 Huascaran rock avalanche in Peru are commonly cited to characterize landslide hazards in this region, less known is the landslide activity in periods without such large disasters. This study assesses the occurrence of fatal landslides in Latin America and the Caribbean between 2004 and 2013. Over this time period we recorded 611 landslides that caused 11,631 deaths in 25 countries, mostly as a result of rainfall triggers. The countries with the highest number of fatal landslides are Brazil, Colombia, Mexico, Guatemala, Peru and Haiti. The highest death toll for a single event was ca.3000. The dataset has not captured a strong El Niño event or large earthquakes in landslide prone areas, thus the analysis is indicative of short term rather than long term spatial and temporal patterns. Results show that at continental scale, the spatial distribution of landslides in the 2004-2013 period correlates well with relief, precipitation and population density, while the temporal distribution reflects the regional annual rainfall patterns. In urban areas, the presence of informal settlements has a big impact on the number of fatalities, while at national level weaker correlations with gross income, human development and corruption indices can be found. This work was funded by the Durham International Fellowships for Research and Enterprise and Fondecyt project 1140317.

  19. Modeling regional initiation of rainfall-induced shallow landslides in the eastern Umbria Region of central Italy

    Science.gov (United States)

    Salciarini, D.; Godt, J.W.; Savage, W.Z.; Conversini, P.; Baum, R.L.; Michael, J.A.

    2006-01-01

    We model the rainfall-induced initiation of shallow landslides over a broad region using a deterministic approach, the Transient Rainfall Infiltration and Grid-based Slope-stability (TRIGRS) model that couples an infinite-slope stability analysis with a one-dimensional analytical solution for transient pore pressure response to rainfall infiltration. This model permits the evaluation of regional shallow landslide susceptibility in a Geographic Information System framework, and we use it to analyze susceptibility to shallow landslides in an area in the eastern Umbria Region of central Italy. As shown on a landslide inventory map produced by the Italian National Research Council, the area has been affected in the past by shallow landslides, many of which have transformed into debris flows. Input data for the TRIGRS model include time-varying rainfall, topographic slope, colluvial thickness, initial water table depth, and material strength and hydraulic properties. Because of a paucity of input data, we focus on parametric analyses to calibrate and test the model and show the effect of variation in material properties and initial water table conditions on the distribution of simulated instability in the study area in response to realistic rainfall. Comparing the results with the shallow landslide inventory map, we find more than 80% agreement between predicted shallow landslide susceptibility and the inventory, despite the paucity of input data.

  20. Geological control of earthquake induced landslide in El Salvador

    Science.gov (United States)

    Tsige Aga, Meaza

    2010-05-01

    the mechanism and size of the slide, they may become the centre of seismic wave guiding and therefore of seismic energy entrapment producing a larger ground movement. On the other hand, the flow-like behavior of the landslide mass after failer is suggested to be controlled by the nature of the geological and geotechnical aspects of the materials. After seismic shaking the landslide mass mobilizes downslope up to hundreds of meters. This mobilization seemed to be due to a large deformation as a consecuence of structure colapse during seismic shaking. These generally are Miocene to Quaternary-aged thick volcanic pyroclasts, fall deposits and breccted tuffs inter-beded frequently by a thin volcanic ash. They consist of 50-60 per cent silt and sand particles with a few amount of clay which are evolving large andesitic blocks. Have a very open texture with a high void ratio and low density which confers an anomalous post-failure deformation. At their in situ state these materials possess high apparent strength due to primary weak chemical and silty-clay cementation but they are susceptible to large reductions in their strength due to shaking and flow like a semi-liquid mass (quick-silt), so that the mass will long run-out.

  1. Assessment of ecological passages along road networks within the Mediterranean forest using GIS-based multi criteria evaluation approach.

    Science.gov (United States)

    Gülci, Sercan; Akay, Abdullah Emin

    2015-12-01

    Major roads cause barrier effect and fragmentation on wildlife habitats that are suitable places for feeding, mating, socializing, and hiding. Due to wildlife collisions (Wc), human-wildlife conflicts result in lost lives and loss of biodiversity. Geographical information system (GIS)-based multi criteria evaluation (MCE) methods have been successfully used in short-term planning of road networks considering wild animals. Recently, wildlife passages have been effectively utilized as road engineering structures provide quick and certain solutions for traffic safety and wildlife conservation problems. GIS-based MCE methods provide decision makers with optimum location for ecological passages based on habitat suitability models (HSMs) that classify the areas based on ecological requirements of target species. In this study, ecological passages along Motorway 52 within forested areas in Mediterranean city of Osmaniye in Turkey were evaluated. Firstly, HSM coupled with nine eco-geographic decision variables were developed based on ecological requirements of roe deer (Capreolus capreolus) that were chosen as target species. Then specified decision variables were evaluated using GIS-based weighted linear combination (WLC) method to estimate movement corridors and mitigation points along the motorway. In the solution process, two linkage nodes were evaluated for eco-passages which were determined based on the least-cost movement corridor intersecting with the motorway. One of the passages was identified as a natural wildlife overpass while the other was suggested as underpass construction. The results indicated that computer-based models provide accurate and quick solutions for positioning ecological passages to reduce environmental effects of road networks on wild animals.

  2. Integrated GIS-Based Site Selection of Hillside Development for Future Growth of Urban Areas

    Directory of Open Access Journals (Sweden)

    Imtiaz Ahmed Chandio

    2016-04-01

    Full Text Available Urbanization is a challenging issue for developing countries, like Malaysia. Penang Island is one of the states of Malaysia selected as a study area where limited flat land exists. As a result, this would create urban environmental problems, such as unstable slopes and landslides due to uneven topography. The purpose of this study was to develop land suitability model for hillside development. Hence, this research aims land suitability analysis modelling for hillside development by using integrated GIS (Geographic Information System based MCDM (Multi-Criteria Decision Making approach. The hill land portion of Penang Island was selected for hillside site development using GIS and AHP (Analytic Hierarchy Process as a MCDM method for sustainable hillside development. This study found that 15% of land was highly suitable, 27% moderately suitable, 41% less suitable, and 17% not suitable. Therefore, this research can be consistently used by the concerned authorities for sustainable hillside urban planning and development. This approach can be used as a policy tool in decision making of urban planning and development.

  3. The role of land use changes in the distribution of shallow landslides.

    Science.gov (United States)

    Persichillo, Maria Giuseppina; Bordoni, Massimiliano; Meisina, Claudia

    2017-01-01

    The role of land use dynamics on shallow landslide susceptibility remains an unresolved problem. Thus, this work aims to assess the influence of land use changes on shallow landslide susceptibility. Three shallow landslide-prone areas that are representative of peculiar land use settings in the Oltrepò Pavese (North Apennines) are analysed: the Rio Frate, Versa and Alta Val Tidone catchments. These areas were affected by widespread land abandonment and modifications in agricultural practices from 1954 to 2012 and relevant shallow landslide phenomena in 2009, 2013 and 2014. A multi-temporal land use change analysis allows us to evaluate the degree of transformation in the three investigated areas and the influence of these changes on the susceptibility to shallow landslides. The results show that the three catchments were characterised by pronounced land abandonment and important changes in agricultural practices. In particular, abandoned cultivated lands that gradually recovered through natural grasses, shrubs and woods were identified as the land use change classes that were most prone to shallow landslides. Additionally, the negative qualities of the agricultural maintenance practices increased the surface water runoff and consequently intensified erosion processes and instability phenomena. Although the land use was identified as the most important predisposing factor in all the study areas, some cases existed in which the predisposition of certain areas to shallow landslides was influenced by the combined effect of land use changes and the geological conditions, as highlighted by the high susceptibility of slopes that are characterised by adverse local geological (thick soils derived from clayey-marly bedrocks) and geomorphological (slope angle higher than 25°) conditions. Thus, the achieved results are particularly useful to understand the best land conservation strategies to be adopted to reduce instability phenomena and the consequent economic losses in

  4. Characteristic and Behavior of Rainfall Induced Landslides in Java Island, Indonesia : an Overview

    Science.gov (United States)

    Christanto, N.; Hadmoko, D. S.; Westen, C. J.; Lavigne, F.; Sartohadi, J.; Setiawan, M. A.

    2009-04-01

    frequency both annual and monthly level during the periods of 1981 - 2007. Simple statistical analysis was done to correlate landslide events, antecedent rainfall during 30 consecutive days and daily rainfall during the landslide day. Analysis the relationship between landslide events and their controlling factors (e.g. slope, geology, geomorphology and landuse) were carried out in GIS environment. The results show that the slope gradient has a good influence to landslides events. The number of landslides increases significantly from slopes inferior to 10° and from 30° to 40°. However, inverse correlation between landslides events occurs on slope steepness more than 40° when the landslide frequency tends to decline with an increasing of slope angle. The result from landuse analysis shows that most of landslides occur on dryland agriculture, followed by paddy fields and artificial. This data indicates that human activities play an important role on landslide occurrence. Dryland agriculture covers not only the lower part of land, but also reached middle and upper slopes; with terraces agriculture that often accelerate landslide triggering. During the period 1981-2007, the annual landslide frequency varies significantly, with an average of 49 events per year. Within a year, the number of landslides increases from June to November and decreases significantly from January to July. Statistically, both January and November are the most susceptible months for landslide generation, with respectively nine and seven events on average. This distribution is closely related to the rainfall monthly variations. Landslides in Java are unevenly distributed. Most landslides are concentrated in West Java Region, followed by Central Java and East Java. The overall landslide density in Java reached 1x10 events/km with the annual average was 3.6 x 10 event/km /year. The amount of annual precipitation is significantly higher in West Java than further East, decreasing with a constant W

  5. A GIS based district information system for water resources management and planning

    Science.gov (United States)

    Tzabiras, John; Spiliotopoulos, Marios; Kokkinos, Kostantinos; Fafoutis, Chrysostomos; Sidiropoulos, Pantelis; Vasiliades, Lampros; Loukas, Athanasios; Mylopoulos, Nikitas

    2014-05-01

    In many watersheds of the Mediterranean Countries, water resources are presently fully or overcommitted. Irrigators are the largest consumers of fresh water in Mediterranean Countries using up to 80% of all allocated water in some regions. Administrative efforts should be directed towards an integrated policy of water allocation which accounts for the characteristics and specificity of each farm, requiring the availability of data bases and management tools (decision support systems) specifically designed to fulfil the objectives of maximizing water use efficiency. The overall objective of this program was the development of a District Information System (DIS) which could be used by stakeholders at purposes of irrigation district day-to-day management as well as for planning and strategic decision-making. The DIS was developed from a GIS-based modelling approach which integrates a generic crop model, a hydraulic module for the water transfer/distribution system and uses remote sensing information. The main sub-objectives were: (i) the development of an operational algorithm to retrieve crop evapotranspiration from remote sensing data, (ii) the development of an information system with friendly user interface for the data base, the crop module and the hydraulic module and (iii) the analysis and validation of management scenarios from model simulations predicting the respective behaviour. Surface Energy Balance Algorithm for Land (SEBAL) was used to derive monthly actual evapotranspiration (ET) values from Landsat TM imagery. Meteorological data from the archive of the Institute for Research and Technology, Thessaly (I.RE.TE.TH) have also been used. The methodology was developed using high quality Landsat TM images during 2007 growing season. Monthly ET values are then used as an input to CROPWAT model. Outputs of CROPWAT model are then used as input for the hydraylic module consisted of TECHNOLOGISMIKI, WATERCAD and WEAP model. Hence, a reference scenario was

  6. Rainfall-induced landslide vulnerability Assessment in urban area reflecting Urban structure and building characteristics

    Science.gov (United States)

    Park, C.; Cho, M.; Lee, D.

    2017-12-01

    Landslide vulnerability assessment methodology of urban area is proposed with urban structure and building charateristics which can consider total damage cost of climate impacts. We used probabilistic analysis method for modeling rainfall-induced shallow landslide susceptibility by slope stability analysis and Monte Carlo simulations. And We combined debris flows with considering spatial movements under topographical condition and built environmental condition. Urban vulnerability of landslide is assessed by two categories: physical demages and urban structure aspect. Physical vulnerability is related to buildings, road, other ubran infra. Urban structure vulnerability is considered a function of the socio-economic factors, trigger factor of secondary damage, and preparedness level of the local government. An index-based model is developed to evaluate the life and indirect damage under landslide as well as the resilience ability against disasters. The analysis was performed in a geographic information system (GIS) environment because GIS can deal efficiently with a large volume of spatial data. The results of the landslide susceptibility assessment were compared with the landslide inventory, and the proposed approach demonstrated good predictive performance. The general trend found in this study indicates that the higher population density areas under a weaker fiscal condition that are located at the downstream of mountainous areas are more vulnerable than the areas in opposite conditions.

  7. Comparison of event landslide inventories: the Pogliaschina catchment test case, Italy

    Science.gov (United States)

    Mondini, A. C.; Viero, A.; Cavalli, M.; Marchi, L.; Herrera, G.; Guzzetti, F.

    2014-07-01

    Event landslide inventory maps document the extent of populations of landslides caused by a single natural trigger, such as an earthquake, an intense rainfall event, or a rapid snowmelt event. Event inventory maps are important for landslide susceptibility and hazard modelling, and prove useful to manage residual risk after a landslide-triggering event. Standards for the preparation of event landslide inventory maps are lacking. Traditional methods are based on the visual interpretation of stereoscopic aerial photography, aided by field surveys. New and emerging techniques exploit remotely sensed data and semi-automatic algorithms. We describe the production and comparison of two independent event inventories prepared for the Pogliaschina catchment, Liguria, Northwest Italy. The two inventories show landslides triggered by an intense rainfall event on 25 October 2011, and were prepared through the visual interpretation of digital aerial photographs taken 3 days and 33 days after the event, and by processing a very-high-resolution image taken by the WorldView-2 satellite 4 days after the event. We compare the two inventories qualitatively and quantitatively using established and new metrics, and we discuss reasons for the differences between the two landslide maps. We expect that the results of our work can help in deciding on the most appropriate method to prepare reliable event inventory maps, and outline the advantages and the limitations of the different approaches.

  8. Uncertainty evaluation of a regional real-time system for rain-induced landslides

    Science.gov (United States)

    Kirschbaum, Dalia; Stanley, Thomas; Yatheendradas, Soni

    2015-04-01

    A new prototype regional model and evaluation framework has been developed over Central America and the Caribbean region using satellite-based information including precipitation estimates, modeled soil moisture, topography, soils, as well as regionally available datasets such as road networks and distance to fault zones. The algorithm framework incorporates three static variables: a susceptibility map; a 24-hr rainfall triggering threshold; and an antecedent soil moisture variable threshold, which have been calibrated using historic landslide events. The thresholds are regionally heterogeneous and are based on the percentile distribution of the rainfall or antecedent moisture time series. A simple decision tree algorithm framework integrates all three variables with the rainfall and soil moisture time series and generates a landslide nowcast in real-time based on the previous 24 hours over this region. This system has been evaluated using several available landslide inventories over the Central America and Caribbean region. Spatiotemporal uncertainty and evaluation metrics of the model are presented here based on available landslides reports. This work also presents a probabilistic representation of potential landslide activity over the region which can be used to further refine and improve the real-time landslide hazard assessment system as well as better identify and characterize the uncertainties inherent in this type of regional approach. The landslide algorithm provides a flexible framework to improve hazard estimation and reduce uncertainty at any spatial and temporal scale.

  9. Source characterization and tsunami modeling of submarine landslides along the Yucatán Shelf/Campeche Escarpment, southern Gulf of Mexico

    Science.gov (United States)

    Chaytor, Jason D.; Geist, Eric L.; Paull, Charles K.; Caress, David W; Gwiazda, Roberto; Urrutia Fucugauchi, Jaime; Rebolledo Vieyra, Mario

    2016-01-01

    Submarine landslides occurring along the margins of the Gulf of Mexico (GOM) represent a low-likelihood, but potentially damaging source of tsunamis. New multibeam bathymetry coverage reveals that mass wasting is pervasive along the Yucatán Shelf edge with several large composite landslides possibly removing as much as 70 km3 of the Cenozoic sedimentary section in a single event. Using GIS-based analysis, the dimensions of six landslides from the central and northern sections of the Yucatán Shelf/Campeche Escarpment were determined and used as input for preliminary tsunami generation and propagation models. Tsunami modeling is performed to compare the propagation characteristics and distribution of maximum amplitudes throughout the GOM among the different landslide scenarios. Various factors such as landslide geometry, location along the Yucatán Shelf/Campeche Escarpment, and refraction during propagation result in significant variations in the affected part of the Mexican and US Gulf Coasts. In all cases, however, tsunami amplitudes are greatest along the northern Yucatán Peninsula.

  10. Methodologies for the assessment of earthquake-triggered landslides hazard. A comparison of Logistic Regression and Artificial Neural Network models.

    Science.gov (United States)

    García-Rodríguez, M. J.; Malpica, J. A.; Benito, B.

    2009-04-01

    In recent years, interest in landslide hazard assessment studies has increased substantially. They are appropriate for evaluation and mitigation plan development in landslide-prone areas. There are several techniques available for landslide hazard research at a regional scale. Generally, they can be classified in two groups: qualitative and quantitative methods. Most of qualitative methods tend to be subjective, since they depend on expert opinions and represent hazard levels in descriptive terms. On the other hand, quantitative methods are objective and they are commonly used due to the correlation between the instability factors and the location of the landslides. Within this group, statistical approaches and new heuristic techniques based on artificial intelligence (artificial neural network (ANN), fuzzy logic, etc.) provide rigorous analysis to assess landslide hazard over large regions. However, they depend on qualitative and quantitative data, scale, types of movements and characteristic factors used. We analysed and compared an approach for assessing earthquake-triggered landslides hazard using logistic regression (LR) and artificial neural networks (ANN) with a back-propagation learning algorithm. One application has been developed in El Salvador, a country of Central America where the earthquake-triggered landslides are usual phenomena. In a first phase, we analysed the susceptibility and hazard associated to the seismic scenario of the 2001 January 13th earthquake. We calibrated the models using data from the landslide inventory for this scenario. These analyses require input variables representing physical parameters to contribute to the initiation of slope instability, for example, slope gradient, elevation, aspect, mean annual precipitation, lithology, land use, and terrain roughness, while the occurrence or non-occurrence of landslides is considered as dependent variable. The results of the landslide susceptibility analysis are checked using landslide

  11. A satellite-based global landslide model

    Directory of Open Access Journals (Sweden)

    A. Farahmand

    2013-05-01

    Full Text Available Landslides are devastating phenomena that cause huge damage around the world. This paper presents a quasi-global landslide model derived using satellite precipitation data, land-use land cover maps, and 250 m topography information. This suggested landslide model is based on the Support Vector Machines (SVM, a machine learning algorithm. The National Aeronautics and Space Administration (NASA Goddard Space Flight Center (GSFC landslide inventory data is used as observations and reference data. In all, 70% of the data are used for model development and training, whereas 30% are used for validation and verification. The results of 100 random subsamples of available landslide observations revealed that the suggested landslide model can predict historical landslides reliably. The average error of 100 iterations of landslide prediction is estimated to be approximately 7%, while approximately 2% false landslide events are observed.

  12. Characterisation of weathered clayey soils responsible for shallow landslides

    Directory of Open Access Journals (Sweden)

    C. Meisina

    2006-01-01

    Full Text Available Shallow earth translational slides and earth flows, affecting colluvial soils derived by the weathering of the clayey bedrock, are a recurrent problem causing damage to buildings and roads in many areas of Apennines. The susceptibility assessment, e.g. slope stability models, requires the preliminary characterization of these superficial covers (lithology, geotechnical and hydraulic parameters. The aim of the work is to develop and test a methodology for the identification and mapping of weathered clayey soils responsible for shallow landslides. A test site in Northern Apennines (Province of Pavia was selected. Argillaceous and marly successions characterize the area. Shallow landslides occurred periodically due to high intensity rainfalls. Trench pits were used for the soil profile description (lithology, structure, grade of weathering, thickness and sampling. The main geological, topographic and geomorphologic parameters of shallow landslides were analysed. Field surveys were integrated with some geotechnical laboratory tests (index properties, suction and volumetric characteristic determination, methylene blue adsorption test, linear shrinkage, swell strain. Engineering geological zoning was carried out by grouping the superficial soils on the basis of the following attributes: topographic conditions (slope angle, landslide occurrence, lithology (grain size, geometry (thickness, lithology of the bedrock, hydrogeological and geotechnical characteristics. The resulting engineering-geological units (areas that may be regarded as homogeneous from the geomorphologic and engineering – geological point of view were analysed in terms of shallow slope instability.

  13. The impact of landslides on urban areas and infrastructure in Italy

    Science.gov (United States)

    Trigila, Alessandro; Spizzichino, Daniele; Iadanza, Carla

    2010-05-01

    Landslide risk in Italy is particularly high since in addition to the geological, geomorphological, seismic and structural settings which render it susceptible to frequent and widespread landslide phenomena, the Italian territory is also densely populated and highly urbanized. In terms of landslide hazard, 485,004 landslides occurred between A.D. 1116 and 2006 within Italy, with a landslide area of 20,721 km2 equal to 6.9% of the national territory. 5,708 municipal districts are affected by landslides (70.5% of the total), of which 2,940 with extremely high levels of criticality due to landslides affecting urban centres. This data emerges from the IFFI Project (Italian Landslide Inventory) which, set up by ISPRA - Institute for Environmental Protection and Research/Geological Survey of Italy and the Regions and self-governing Provinces, identifies landslide phenomena across Italy in accordance with standardized methods of data collection, recording and mapping. With regard to exposure and vulnerability, urban areas in Italy account for 17,929 km2, equal to 5.9% of the national territory. In the past 50 years, urban areas in Italy underwent a dramatic increase, whose surface has more than doubled. Often building areas did not benefit from any form of proper land use planning and management or detailed landslide hazard assessment. Moreover unauthorized building has reached levels as high as 60% in regions of Southern Italy. This study assesses the incidence of landslide phenomena and their impacts within urban areas of Italian provincial capitals in terms of number of landslides, surface area and type of movement. The people exposed to landslide risk at national level and critical points along highways, railways and road network has been also estimated. Landslides have been classified in two main categories: rapid and slow movements. The rapid phenomena are strictly correlated to the people safety, while the slow ones concern mainly losses and usability of buildings

  14. GIS-Based KW-GIUH hydrological model of semiarid catchments: The case of Faria Catchment, Palestine

    International Nuclear Information System (INIS)

    Shadeed, S.; Shaheen, H.; Jayyousi, A.

    2007-01-01

    Among the most basic challenges of hydrology are the quantitative understanding of the processes of runoff generation and prediction of flow hydrographs. Traditional techniques have been widely applied for the estimation of runoff hydrographs of gauged catchments using historical rainfall-runoff data and unit hydrographs. Such procedures are questioned as to their reliability and their application to ungauged, arid and semiarid catchments. To overcome such difficulties, the use of physically based rainfall-runoff process of Faria Catchment using the lately developed KW-GIUH. Faria catchment, located in the northeastern part of the West Bank, Palestine, is characterized as a semiarid region with annual rainfall depths ranging on average from 150 to 640 mm at both ends of the catchment. The Geographical Information System (GIS) techniques were used to shape the geomorphological features of the catchment. A GIS based KW-GIUH hydrological model was used to stimulate the rainfall-runoff process in the three sub-catchments of Faria, namely: Al-Badan, Al-Faria and Al-Malaqi. The simulated runoff hydrographs proved that the GIS-based KW-GIUH model is applicable to semiarid regions and can be used to estimate the unit hydrographs in the West Bank catchments. (author)

  15. IDENTIFYING HIGH-RISK POPULATIONS OF TUBERCULOSIS USING ENVIRONMENTAL FACTORS AND GIS BASED MULTI-CRITERIA DECISION MAKING METHOD

    Directory of Open Access Journals (Sweden)

    A. R. Abdul Rasam

    2016-09-01

    Full Text Available Development of an innovative method to enhance the detection of tuberculosis (TB in Malaysia is the latest agenda of the Ministry of Health. Therefore, a geographical information system (GIS based index model is proposed as an alternative method for defining potential high-risk areas of local TB cases at Section U19, Shah Alam. It is adopted a spatial multi-criteria decision making (MCDM method for ranking environmental risk factors of the disease in a standardised five-score scale. Scale 1 and 5 illustrate the lowest and the highest risk of the TB spread respectively, while scale from 3 to 5 is included as a potential risk level. These standardised scale values are then combined with expert normalised weights (0 to 1 to calculate the overall index values and produce a TB ranked map using a GIS overlay analysis and weighted linear combination. It is discovered that 71.43% of the Section is potential as TB high risk areas particularly at urban and densely populated settings. This predictive result is also reliable with the current real cases in 2015 by 76.00% accuracy. A GIS based MCDM method has demonstrated analytical capabilities in targeting high-risk spots and TB surveillance monitoring system of the country, but the result could be strengthened by applying other uncertainty assessment method.

  16. GIS-based multicriteria municipal solid waste landfill suitability analysis: a review of the methodologies performed and criteria implemented.

    Science.gov (United States)

    Demesouka, O E; Vavatsikos, A P; Anagnostopoulos, K P

    2014-04-01

    Multicriteria spatial decision support systems (MC-SDSS) have emerged as an integration of the geographical information systems (GIS) and multiple criteria decision analysis (MCDA) methods. GIS-based MCDA allows the incorporation of conflicting objectives and decision maker (DM) preferences into spatial decision models. During recent decades, a variety of research articles have been published regarding the implementation of methods and/or tools in a variety of real-world case studies. The article discusses, in detail, the criteria and methods that are implemented in GIS-based landfill siting suitability analysis and especially the exclusionary and non-exclusionary criteria that can be considered when selecting sites for municipal solid waste (MSW) landfills. This paper reviews 36 seminal articles in which the evaluation of candidate landfill sites is conducted using MCDA methods. After a brief description of the main components of a MC-SDSS and the applied decision rules, the review focuses on the criteria incorporated into the decision models. The review provides a comprehensive guide to the landfill siting analysis criteria, providing details regarding the utilization methods, their decision or exclusionary nature and their monotonicity.

  17. Landslide hazard assessment : LIFE+IMAGINE project methodology and Liguria region use case

    Science.gov (United States)

    Spizzichino, Daniele; Campo, Valentina; Congi, Maria Pia; Cipolloni, Carlo; Delmonaco, Giuseppe; Guerrieri, Luca; Iadanza, Carla; Leoni, Gabriele; Trigila, Alessandro

    2015-04-01

    Scope of the work is to present a methodology developed for analysis of potential impacts in areas prone to landslide hazard in the framework of the EC project LIFE+IMAGINE. The project aims to implement a web services-based infrastructure addressed to environmental analysis, that integrates, in its own architecture, specifications and results from INSPIRE, SEIS and GMES. Existing web services has been customized to provide functionalities for supporting environmental integrated management. The implemented infrastructure has been applied to landslide risk scenarios, developed in selected pilot areas, aiming at: i) application of standard procedures to implement a landslide risk analysis; ii) definition of a procedure for assessment of potential environmental impacts, based on a set of indicators to estimate the different exposed elements with their specific vulnerability in the pilot area. The landslide pilot and related scenario are focused at providing a simplified Landslide Risk Assessment (LRA) through: 1) a landslide inventory derived from available historical and recent databases and maps; 2) landslide susceptibility and hazard maps; 3) assessment of exposure and vulnerability on selected typologies of elements at risk; 4) implementation of a landslide risk scenario for different sets of exposed elements 5) development of a use case; 6) definition of guidelines, best practices and production of thematic maps. The LRA has been implemented in Liguria region, Italy, in two different catchment areas located in the Cinque Terre National Park, characterized by a high landslide susceptibility and low resilience. The landslide risk impact analysis has been calibrated taking into account the socio-economic damage caused by landslides triggered by the October 2011 meteorological event. During this event, over 600 landslides were triggered in the selected pilot area. Most of landslides affected the diffuse system of anthropogenic terraces and caused the direct

  18. Evaluation of the influence of source and spatial resolution of DEMs on derivative products used in landslide mapping

    Directory of Open Access Journals (Sweden)

    Rubini Mahalingam

    2016-11-01

    Full Text Available Landslides are a major geohazard, which result in significant human, infrastructure, and economic losses. Landslide susceptibility mapping can help communities plan and prepare for these damaging events. Digital elevation models (DEMs are one of the most important data-sets used in landslide hazard assessment. Despite their frequent use, limited research has been completed to date on how the DEM source and spatial resolution can influence the accuracy of the produced landslide susceptibility maps. The aim of this paper is to analyse the influence of spatial resolutions and source of DEMs on landslide susceptibility mapping. For this purpose, Advanced Spaceborne Thermal Emission and Reflection (ASTER, National Elevation Dataset (NED, and Light Detection and Ranging (LiDAR DEMs were obtained for two study sections of approximately 140 km2 in north-west Oregon. Each DEM was resampled to 10, 30, and 50 m and slope and aspect grids were derived for each resolution. A set of nine spatial databases was constructed using geoinformation science (GIS for each of the spatial resolution and source. Additional factors such as distance to river and fault maps were included. An analytical hierarchical process (AHP, fuzzy logic model, and likelihood ratio-AHP representing qualitative, quantitative, and hybrid landslide mapping techniques were used for generating landslide susceptibility maps. The results from each of the techniques were verified with the Cohen's kappa index, confusion matrix, and a validation index based on agreement with detailed landslide inventory maps. The spatial resolution of 10 m, derived from the LiDAR data-set showed higher predictive accuracy in all the three techniques used for producing landslide susceptibility maps. At a resolution of 10 m, the output maps based on NED and ASTER had higher misclassification compared to the LiDAR-based outputs. Further, the 30-m LiDAR output showed improved results over the 10-m NED and 10-m

  19. Landslide hazard mapping with selected dominant factors: A study case of Penang Island, Malaysia

    International Nuclear Information System (INIS)

    Tay, Lea Tien; Alkhasawneh, Mutasem Sh.; Ngah, Umi Kalthum; Lateh, Habibah

    2015-01-01

    Landslide is one of the destructive natural geohazards in Malaysia. In addition to rainfall as triggering factos for landslide in Malaysia, topographical and geological factors play important role in the landslide susceptibility analysis. Conventional topographic factors such as elevation, slope angle, slope aspect, plan curvature and profile curvature have been considered as landslide causative factors in many research works. However, other topographic factors such as diagonal length, surface area, surface roughness and rugosity have not been considered, especially for the research work in landslide hazard analysis in Malaysia. This paper presents landslide hazard mapping using Frequency Ratio (FR) and the study area is Penang Island of Malaysia. Frequency ratio approach is a variant of probabilistic method that is based on the observed relationships between the distribution of landslides and each landslide-causative factor. Landslide hazard map of Penang Island is produced by considering twenty-two (22) landslide causative factors. Among these twenty-two (22) factors, fourteen (14) factors are topographic factors. They are elevation, slope gradient, slope aspect, plan curvature, profile curvature, general curvature, tangential curvature, longitudinal curvature, cross section curvature, total curvature, diagonal length, surface area, surface roughness and rugosity. These topographic factors are extracted from the digital elevation model of Penang Island. The other eight (8) non-topographic factors considered are land cover, vegetation cover, distance from road, distance from stream, distance from fault line, geology, soil texture and rainfall precipitation. After considering all twenty-two factors for landslide hazard mapping, the analysis is repeated with fourteen dominant factors which are selected from the twenty-two factors. Landslide hazard map was segregated into four categories of risks, i.e. Highly hazardous area, Hazardous area, Moderately hazardous area

  20. Landslide hazard mapping with selected dominant factors: A study case of Penang Island, Malaysia

    Energy Technology Data Exchange (ETDEWEB)

    Tay, Lea Tien; Alkhasawneh, Mutasem Sh.; Ngah, Umi Kalthum [School of Electrical and Electronic Engineering, Engineering Campus, Universiti Sains Malaysia, 14300 Nibong Tebal, Penang (Malaysia); Lateh, Habibah [School of Distance Education, Universiti Sains Malaysia, 11600 Penang (Malaysia)

    2015-05-15

    Landslide is one of the destructive natural geohazards in Malaysia. In addition to rainfall as triggering factos for landslide in Malaysia, topographical and geological factors play important role in the landslide susceptibility analysis. Conventional topographic factors such as elevation, slope angle, slope aspect, plan curvature and profile curvature have been considered as landslide causative factors in many research works. However, other topographic factors such as diagonal length, surface area, surface roughness and rugosity have not been considered, especially for the research work in landslide hazard analysis in Malaysia. This paper presents landslide hazard mapping using Frequency Ratio (FR) and the study area is Penang Island of Malaysia. Frequency ratio approach is a variant of probabilistic method that is based on the observed relationships between the distribution of landslides and each landslide-causative factor. Landslide hazard map of Penang Island is produced by considering twenty-two (22) landslide causative factors. Among these twenty-two (22) factors, fourteen (14) factors are topographic factors. They are elevation, slope gradient, slope aspect, plan curvature, profile curvature, general curvature, tangential curvature, longitudinal curvature, cross section curvature, total curvature, diagonal length, surface area, surface roughness and rugosity. These topographic factors are extracted from the digital elevation model of Penang Island. The other eight (8) non-topographic factors considered are land cover, vegetation cover, distance from road, distance from stream, distance from fault line, geology, soil texture and rainfall precipitation. After considering all twenty-two factors for landslide hazard mapping, the analysis is repeated with fourteen dominant factors which are selected from the twenty-two factors. Landslide hazard map was segregated into four categories of risks, i.e. Highly hazardous area, Hazardous area, Moderately hazardous area

  1. Digital inventory of landslides and related deposits in Honduras triggered by Hurricane Mitch

    Science.gov (United States)

    Harp, Edwin L.; Hagaman, Kirk W.; Held, Matthew D.; McKenna, Jonathan P.

    2002-01-01

    by local contractors. Through the use of digital elevation models derived from 1:50,000-scale topographic maps and geologic maps, landslide susceptibility maps will be derived to aid land-use planning and relocation efforts.

  2. Hydrologic Impacts of Landslide Disturbances: Implications for Remobilization and Hazard Persistence

    Science.gov (United States)

    Mirus, Benjamin B.; Smith, Joel B.; Baum, Rex L.

    2017-10-01

    Landslides typically alter hillslope topography, but may also change the hydrologic connectivity and subsurface water-storage dynamics. In settings where mobile materials are not completely evacuated from steep slopes, influences of landslide disturbances on hillslope hydrology and susceptibility to subsequent failures remain poorly characterized. Since landslides often recur at the site of previous failures, we examine differences between a stable vegetated hillslope (VH) and a recent landslide (LS). These neighboring hillslopes exhibit similar topography and are situated on steep landslide-prone coastal bluffs of glacial deposits along the northeastern shore of Puget Sound, Washington. Our control hillslope, VH, is mantled by a heterogeneous colluvium, supporting a dense forest. In early 2013, our test hillslope, LS, also supported a forest before a landslide substantially altered the topography and disturbed the hillslope. In 2015, we observed a clay-rich landslide deposit at LS with sparse vegetation and limited root reinforcement, soil structures, and macropores. Our characterization of the sites also found matrix porosity and hydraulic conductivity are both lower at LS. Continuous monitoring during 2015-2016 revealed reduced effective precipitation at VH (due to canopy interception), an earlier seasonal transition to near-saturated conditions at LS, and longer persistence of positive pore pressures and slower drainage at LS (both seasonally and between major storm events). These differences, along with episodic, complex slope failures at LS support the hypothesis that, despite a reduced average slope, other disturbances introduced by landsliding may promote the hydrologic conditions leading to slope instability, thus contributing to the persistence of landslide hazards.

  3. The landslide database for Germany: Closing the gap at national level

    Science.gov (United States)

    Damm, Bodo; Klose, Martin

    2015-11-01

    The Federal Republic of Germany has long been among the few European countries that lack a national landslide database. Systematic collection and inventory of landslide data still has a long research history in Germany, but one focussed on the development of databases with local or regional coverage. This has changed in recent years with the launch of a database initiative aimed at closing the data gap existing at national level. The present paper reports on this project that is based on a landslide database which evolved over the last 15 years to a database covering large parts of Germany. A strategy of systematic retrieval, extraction, and fusion of landslide data is at the heart of the methodology, providing the basis for a database with a broad potential of application. The database offers a data pool of more than 4,200 landslide data sets with over 13,000 single data files and dates back to the 12th century. All types of landslides are covered by the database, which stores not only core attributes, but also various complementary data, including data on landslide causes, impacts, and mitigation. The current database migration to PostgreSQL/PostGIS is focused on unlocking the full scientific potential of the database, while enabling data sharing and knowledge transfer via a web GIS platform. In this paper, the goals and the research strategy of the database project are highlighted at first, with a summary of best practices in database development providing perspective. Next, the focus is on key aspects of the methodology, which is followed by the results of three case studies in the German Central Uplands. The case study results exemplify database application in the analysis of landslide frequency and causes, impact statistics, and landslide susceptibility modeling. Using the example of these case studies, strengths and weaknesses of the database are discussed in detail. The paper concludes with a summary of the database project with regard to previous

  4. Hydrologic impacts of landslide disturbances: Implications for remobilization and hazard persistence

    Science.gov (United States)

    Mirus, Benjamin B.; Smith, Joel B.; Baum, Rex L.

    2017-01-01

    Landslides typically alter hillslope topography, but may also change the hydrologic connectivity and subsurface water-storage dynamics. In settings where mobile materials are not completely evacuated from steep slopes, influences of landslide disturbances on hillslope hydrology and susceptibility to subsequent failures remain poorly characterized. Since landslides often recur at the site of previous failures, we examine differences between a stable vegetated hillslope (VH) and a recent landslide (LS). These neighboring hillslopes exhibit similar topography and are situated on steep landslide-prone coastal bluffs of glacial deposits along the northeastern shore of Puget Sound, Washington. Our control hillslope, VH, is mantled by a heterogeneous colluvium, supporting a dense forest. In early 2013, our test hillslope, LS, also supported a forest before a landslide substantially altered the topography and disturbed the hillslope. In 2015, we observed a clay-rich landslide deposit at LS with sparse vegetation and limited root reinforcement, soil structures, and macropores. Our characterization of the sites also found matrix porosity and hydraulic conductivity are both lower at LS. Continuous monitoring during 2015-2016 revealed reduced effective precipitation at VH (due to canopy interception), an earlier seasonal transition to near-saturated conditions at LS, and longer persistence of positive pore pressures and slower drainage at LS (both seasonally and between major storm events). These differences, along with episodic, complex slope failures at LS support the hypothesis that, despite a reduced average slope, other disturbances introduced by landsliding may promote the hydrologic conditions leading to slope instability, thus contributing to the persistence of landslide hazards.

  5. Landslide triggering by rain infiltration

    Science.gov (United States)

    Iverson, Richard M.

    2000-01-01

    Landsliding in response to rainfall involves physical processes that operate on disparate timescales. Relationships between these timescales guide development of a mathematical model that uses reduced forms of Richards equation to evaluate effects of rainfall infiltration on landslide occurrence, timing, depth, and acceleration in diverse situations. The longest pertinent timescale is A/D0, where D0 is the maximum hydraulic diffusivity of the soil and A is the catchment area that potentially affects groundwater pressures at a prospective landslide slip surface location with areal coordinates x, y and depth H. Times greater than A/D0 are necessary for establishment of steady background water pressures that develop at (x, y, H) in response to rainfall averaged over periods that commonly range from days to many decades. These steady groundwater pressures influence the propensity for landsliding at (x, y, H), but they do not trigger slope failure. Failure results from rainfall over a typically shorter timescale H2/D0 associated with transient pore pressure transmission during and following storms. Commonly, this timescale ranges from minutes to months. The shortest timescale affecting landslide responses to rainfall is √(H/g), where g is the magnitude of gravitational acceleration. Postfailure landslide motion occurs on this timescale, which indicates that the thinnest landslides accelerate most quickly if all other factors are constant. Effects of hydrologic processes on landslide processes across these diverse timescales are encapsulated by a response function, R(t*) = √(t*/π) exp (-1/t*) - erfc (1/√t*), which depends only on normalized time, t*. Use of R(t*) in conjunction with topographic data, rainfall intensity and duration information, an infinite-slope failure criterion, and Newton's second law predicts the timing, depth, and acceleration of rainfall-triggered landslides. Data from contrasting landslides that exhibit rapid, shallow

  6. A GIS-based approach to prevent contamination of groundwater at regional scale

    Science.gov (United States)

    Balderacchi, M.; Vischetti, C.; di Guardo, A.; Trevisan, M.

    2009-04-01

    Sustainable development is a fundamental objective of the European Union. Since 1991, the use of numerical models has been used to assess the environmental fate of pesticides (directive 91/414 EC). Since then, new approaches to assess pesticide contamination have been developed. This is an ongoing process, with approaches getting increasingly close to reality. Actually, there is a new challenge to integrate the most advanced and cost-effective monitoring strategies with simulation models so that reliable indicators of unsaturated flow and transport can be suitably mapped and coupled with other indicators related to productivity and sustainability. The most relevant role of GIS in the analysis of pesticide fate in soil is its application to process together input data and the results of distribution model based simulations of pesticide transport. FitoMarche is a GIS-based software tool that estimates pesticide movement in the unsaturated zone using MACRO 5 and it is able to simulate complex and real crop rotations at the regional scale. Crop rotation involves the sequential production of different plant species on the same land, every crop is characterized by different agricultural practices that involve the use of different pesticides at different doses. FitoMarche extracts MACRO input data from a series of geographic data sets (shapefiles) and an internal database, writes input files for MACRO, executes the simulation and extracts solute and water fluxes from MACRO output files. The study has been performed in the Marche region, located in central Italy along the Adriatic coast. Soil, climate, land use shapefiles were provided from public authorities, crop rotation schemes were estimated from ISTAT (the national statistics institute) 5th agricultural census database using a municipality detail and agricultural practices following the local customs. Two herbicides have been tested: "A" is employed on maize crop, and "B" on maize, sunflower and sugarbeet. In the

  7. Challenges for operational forecasting and early warning of rainfall induced landslides

    Science.gov (United States)

    Guzzetti, Fausto

    2017-04-01

    models. Building on the experience gained in designing, implementing, and operating national and regional landslide forecasting systems in Italy, and on a preliminary review of the existing literature on regional landslide early warning systems, the talk discusses concepts, limitations and challenges inherent to the design of reliable forecasting and early warning systems for rainfall-triggered landslides, the evaluation of the performances of the systems, and on problems related to the use of the forecasts and the issuing of landslide warnings. Several of the typical elements of an operational landslide forecasting system are considered, including: (i) the rainfall and landslide information used to establish the threshold models, (ii) the methods and tools used to define the empirical rainfall thresholds, and their associated uncertainty, (iii) the quality (e.g., the temporal and spatial resolution) of the rainfall information used for operational forecasting, including rain gauge and radar measurements, satellite estimates, and quantitative weather forecasts, (iv) the ancillary information used to prepare the forecasts, including e.g., the terrain subdivisions and the landslide susceptibility zonations, (v) the criteria used to transform the forecasts into landslide warnings and the methods used to communicate the warnings, and (vi) the criteria and strategies adopted to evaluate the performances of the systems, and to define minimum or optimal performance levels.

  8. Spatio Temporal Detection and Virtual Mapping of Landslide Using High-Resolution Airborne Laser Altimetry (lidar) in Densely Vegetated Areas of Tropics

    Science.gov (United States)

    Bibi, T.; Azahari Razak, K.; Rahman, A. Abdul; Latif, A.

    2017-10-01

    Landslides are an inescapable natural disaster, resulting in massive social, environmental and economic impacts all over the world. The tropical, mountainous landscape in generally all over Malaysia especially in eastern peninsula (Borneo) is highly susceptible to landslides because of heavy rainfall and tectonic disturbances. The purpose of the Landslide hazard mapping is to identify the hazardous regions for the execution of mitigation plans which can reduce the loss of life and property from future landslide incidences. Currently, the Malaysian research bodies e.g. academic institutions and government agencies are trying to develop a landslide hazard and risk database for susceptible areas to backing the prevention, mitigation, and evacuation plan. However, there is a lack of devotion towards landslide inventory mapping as an elementary input of landslide susceptibility, hazard and risk mapping. The developing techniques based on remote sensing technologies (satellite, terrestrial and airborne) are promising techniques to accelerate the production of landslide maps, shrinking the time and resources essential for their compilation and orderly updates. The aim of the study is to provide a better perception regarding the use of virtual mapping of landslides with the help of LiDAR technology. The focus of the study is spatio temporal detection and virtual mapping of landslide inventory via visualization and interpretation of very high-resolution data (VHR) in forested terrain of Mesilau river, Kundasang. However, to cope with the challenges of virtual inventory mapping on in forested terrain high resolution LiDAR derivatives are used. This study specifies that the airborne LiDAR technology can be an effective tool for mapping landslide inventories in a complex climatic and geological conditions, and a quick way of mapping regional hazards in the tropics.

  9. GIS-based rapid-assessment of bighead carp Hypophthalmichthys nobilis (Richardson, 1845) suitability in reservoirs

    Science.gov (United States)

    Long, James M.; Liang, Yu; Shoup, Daniel E.; Dzialowski, Andrew R.; Bidwell, Joseph R.

    2014-01-01

    Broad-scale niche models are good for examining the potential for invasive species occurrences, but can fall short in providing managers with site-specific locations for monitoring. Using Oklahoma as an example, where invasive bighead carp (Hypophthalmichthys nobilis) are established in certain reservoirs, but predicted to be widely distributed based on broad-scale niche models, we cast bighead carp reproductive ecology in a site-specific geospatial framework to determine their potential establishment in additional reservoirs. Because bighead carp require large, long free-flowing rivers with suitable hydrology for reproduction but can persist in reservoirs, we considered reservoir tributaries with mean annual daily discharge ≥8.5 cubic meters per second (m3 /s) and quantified the length of their unimpeded portions. In contrast to published broad-scale niche models that identified nearly the entire state as susceptible to invasion, our site-specific models showed that few reservoirs in Oklahoma (N = 9) were suitable for bighead carp establishment. Moreover, this method was rapid and identified sites that could be prioritized for increased study or scrutiny. Our results highlight the importance of considering the environmental characteristics of individual sites, which is often the level at which management efforts are implemented when assessing susceptibility to invasion.

  10. Global Landslide Total Economic Loss Risk Deciles

    Data.gov (United States)

    National Aeronautics and Space Administration — Global Landslide Total Economic Loss Risk Deciles is a 2.5 minute grid of global landslide total economic loss risks. A process of spatially allocating Gross...

  11. Assessing population exposure for landslide risk analysis using dasymetric cartography

    Science.gov (United States)

    Garcia, Ricardo A. C.; Oliveira, Sergio C.; Zezere, Jose L.

    2015-04-01

    Exposed Population is a major topic that needs to be taken into account in a full landslide risk analysis. Usually, risk analysis is based on an accounting of inhabitants number or inhabitants density, applied over statistical or administrative terrain units, such as NUTS or parishes. However, this kind of approach may skew the obtained results underestimating the importance of population, mainly in territorial units with predominance of rural occupation. Furthermore, the landslide susceptibility scores calculated for each terrain unit are frequently more detailed and accurate than the location of the exposed population inside each territorial unit based on Census data. These drawbacks are not the ideal setting when landslide risk analysis is performed for urban management and emergency planning. Dasymetric cartography, which uses a parameter or set of parameters to restrict the spatial distribution of a particular phenomenon, is a methodology that may help to enhance the resolution of Census data and therefore to give a more realistic representation of the population distribution. Therefore, this work aims to map and to compare the population distribution based on a traditional approach (population per administrative terrain units) and based on dasymetric cartography (population by building). The study is developed in the Region North of Lisbon using 2011 population data and following three main steps: i) the landslide susceptibility assessment based on statistical models independently validated; ii) the evaluation of population distribution (absolute and density) for different administrative territorial units (Parishes and BGRI - the basic statistical unit in the Portuguese Census); and iii) the dasymetric population's cartography based on building areal weighting. Preliminary results show that in sparsely populated administrative units, population density differs more than two times depending on the application of the traditional approach or the dasymetric

  12. Dendrogeomorphology in landslide analysis: State of art

    Energy Technology Data Exchange (ETDEWEB)

    Margottini, C [ENEA, Casaccia (Italy). Area Energia Ambiente e Salute; Fantucci, R

    1994-01-01

    This article summarizes the uses of dendrogeomorphological techniques in landslide analysis. It shows how to study different landslides events through the analysis of living trees. Living trees record any slope inclination variation as if they were natural inclinometers moreover they can be used to date landslide and their stabilization process with time.

  13. Assessment of agricultural drought vulnerability in the Philippines using remote sensing and GIS-based techniques

    International Nuclear Information System (INIS)

    Macapagal, Marco D.; Olivares, Resi O.; Perez, Gay Jane P.

    2015-01-01

    Drought is a recurrent extreme climate event that can cause crop damage and yield loss, thereby inflicting negative socioeconomic impacts all over the world. According to several climate studies, drought events may be more frequent and more severe as global warming progresses. As an agricultural country, the Philippines is highly susceptible to adverse impacts of drought using remotely sensed information and geographic processing techniques. An agricultural drought vulnerability map identifying croplands that are least vulnerable, moderately vulnerable, and most vulnerable to crop water-related stress, was developed. Vulnerability factors, including land use system, irrigation support. Available soil-water holding capacity, as well as satellite-derived evapotranspiration and rainfall, were taken into consideration in classifying and mapping agricultural drought vulnerability at a national level. (author)

  14. Quantifying the performance of automated GIS-based geomorphological approaches for riparian zone delineation using digital elevation models

    Directory of Open Access Journals (Sweden)

    D. Fernández

    2012-10-01

    Full Text Available Riparian zone delineation is a central issue for managing rivers and adjacent areas; however, criteria used to delineate them are still under debate. The area inundated by a 50-yr flood has been indicated as an optimal hydrological descriptor for riparian areas. This detailed hydrological information is usually only available for populated areas at risk of flooding. In this work we created several floodplain surfaces by means of two different GIS-based geomorphological approaches using digital elevation models (DEMs, in an attempt to find hydrologically meaningful potential riparian zones for river networks at the river basin scale. Objective quantification of the performance of the two geomorphologic models is provided by analysing coinciding and exceeding areas with respect to the 50-yr flood surface in different river geomorphological types.

  15. A GIS-based approach for the screening assessment of noise and vibration impacts from transit projects.

    Science.gov (United States)

    Hamed, Maged; Effat, Waleed

    2007-08-01

    Urban transportation projects are essential in increasing the efficiency of moving people and goods within a city, and between cities. Environmental impacts from such projects must be evaluated and mitigated, as applicable. Spatial modeling is a valuable tool for quantifying the potential level of environmental consequences within the context of an environmental impact assessment (EIA) study. This paper presents a GIS-based tool for the assessment of airborne-noise and ground-borne vibration from public transit systems, and its application to an actual project. The tool is based on the US Federal Transit Administration's (FTA) approach, and incorporates spatial information, satellite imaging, geostatistical modeling, and software programming. The tool is applied on a case study of initial environmental evaluation of a light rail transit project in an urban city in the Middle East, to evaluate alternative layouts. The tool readily allowed the alternative evaluation and the results were used as input to a multi-criteria analytic framework.

  16. Campgrounds Suitability Evaluation Using GIS-based Multiple Criteria Decision Analysis: A Case Study of Kuerdening, China

    Science.gov (United States)

    Cuirong, Wang; Zhaoping, Yang; Huaxian, Liu; Fang, Han; Wenjin, Xia

    2016-04-01

    The main objective of this study was to evaluate the suitability and select the most appropriate areas for building campgrounds in Kuerdening, China. To achieve this aim, AHP and GIS-based weighted overlay methods were adopted. AHP was used to determine the weights of the indexes, and ArcGIS 10 was used to calculate and map the campground suitability. In pursuit of minimum environmental effects and sustainable development, this paper identifies four factors to evaluate the suitability of areas for building campgrounds: natural environment condition, landscape condition, safety condition and infrastructure condition. The final outcome of this studywas the suitability map for building campgrounds. This research not only provides a theoretical guide for the construction of campgrounds in this area but also provides a scientific and efficientworkflow to evaluate the appropriateness of other areas. The result is reasonable and operable for camping facilities development and also useful for managers and planners working in local governments as well as investors.

  17. Identification of Suitable Indices for Identification of Potential Sites ...

    African Journals Online (AJOL)

    system (GIS)-based decision support system (DSS) can be a valuable tool for such a task. However, key to .... The data were processed in a GIS ..... Landslide susceptibility mapping by GIS-based ... remote sensing and GIS in the Makanya.

  18. Easy To Use Remote Sensing and GIS Analysis for Landslide Risk Assessment.

    Directory of Open Access Journals (Sweden)

    Hayder Dibs

    2017-12-01

    Full Text Available Many countries throughout the world suffered from the natural risks, they cause a large damage in property and loss in human lives, we cannot prevent the occurring of these hazards but, it is possible to reduce their affect in saving human lives and reducing the damage in properties. Several methodologies have been conducted to predict the suitable model for landslide assessment. The susceptibility maps of landslide hazard generated by combining the remote sensed data with the capability of GIS (geographic information system. We discussed different type of algorithms and factors for modeling the prediction of landslide risk assessment such as SVM (support vector machine, DT (decision tree, ANFIS (adaptive neural-fuzzy inference system, AHP (analytic hierarchy process, ANN (artificial neural network, probability frequency of landslides occurrence factors model and empirical model. The study evaluated various parameters that are responsible for landslide occurrence and the weighting for each parameter and its importance to probable of landslide activity. AHP method, Weights of evidence model, and back propagation method have been applied for weighting the factors.  We found that using ANN algorithm with more than ten factors will give high accuracy result especially if the validation performs by field surveys data.

  19. Landslide risk impact management and web services for improving resilience: the LIFE+IMAGINE project approach

    Science.gov (United States)

    Congi, Maria Pia; Campo, Valentina; Cipolloni, Carlo; Delmonaco, Giuseppe; Guerrieri, Luca; Iadanza, Carla; Spizzichino, Daniele; Trigila, Alessandro

    2014-05-01

    The increasing damage caused by natural disasters in the last decades points out the need for interoperable added-value services to support environmental safety and human protection, by reducing vulnerability of exposed elements as well as improving the resilience of the involved communities. For this reason, to provide access to harmonized and customized data is only one of several steps towards delivering adequate support to risk assessment, reduction and management. Scope of the present work is to illustrate a methodology under development for analysis of potential impacts in areas prone to landslide hazard in the framework of the EC project LIFE+IMAGINE. The project aims to implement an infrastructure based on web services for environmental analysis, that integrates in its own architecture specifications and results from INSPIRE, SEIS and GMES. Existing web services will be customized during the project to provide functionalities for supporting the environmental integrated management. The implemented infrastructure will be applied to landslide risk scenarios, to be developed in selected pilot areas, aiming at: i) application of standard procedures to implement a landslide risk analysis; ii) definition of a procedure for assessment of potential environmental impacts, based on a set of indicators to estimate the different exposed elements with their specific vulnerability in the pilot area. More in detail, the landslide pilot will be aimed at providing a landslide risk scenario through the implementation and analysis of: 1) a landslide inventory from available historical databases and maps; 2) landslide susceptibility and hazard maps; 3) assessment of exposure and vulnerability on selected typologies of elements at risk; 4) implementation of a landslide risk scenario for different sets of exposed elements (e.g. population, road network, residential area, cultural heritage). The pilot will be implemented in Liguria, Italy, in two different catchment areas located

  20. Assessment of risks of loose landslide deposits formed by the 2008 Wenchuan earthquake

    Science.gov (United States)

    Zhang, S.; Zhang, L. M.; Peng, M.; Zhang, L. L.; Zhao, H. F.; Chen, H. X.

    2012-05-01

    A Geographic Information System (GIS)-based quantitative risk assessment methodology was adopted to evaluate the risks of loose deposits formed by the 2008 Wenchuan earthquake along a highway near the epicenter. A total of 305 loose deposits with a total volume of 4.0 × 107 m3 has been identified. A physical model was used to determine the failure probability of these loose deposits under six rainfall scenarios, assuming the loose deposits as infinite slopes. The calculated probability of rain-induced slope failures is verified by the recorded landslides at the same site during a storm in 2010. Seventy-nine out of the 112 rain-induced loose deposit failures are predicted by the reliability analysis, with an accuracy of 71%. The results of reliability analysis and information on the consequence of these rain-induced landslides enable the estimation of the annual societal and individual risks of the loose deposits. Under the rainfall scenarios of 30 mm/12 h and 70 mm/12 h, the estimated annual societal risks reach 8.8 and 7.5, respectively, and the individual risks reach 0.05 and 0.04, respectively, which are very high compared with present risk acceptance criteria. The preliminary assessment provides a benchmark for studying the long-term risks of these loose deposits and engineering decision.

  1. The landslide problem

    Directory of Open Access Journals (Sweden)

    G. Shanmugam

    2015-04-01

    Full Text Available The synonymous use of the general term “landslide”, with a built-in reference to a sliding motion, for all varieties of mass-transport deposits (MTD, which include slides, slumps, debrites, topples, creeps, debris avalanches etc. in subaerial, sublacustrine, submarine, and extraterrestrial environments has created a multitude of conceptual and nomenclatural problems. In addition, concepts of triggers and long-runout mechanisms of mass movements are loosely applied without rigor. These problems have enormous implications for studies in process sedimentology, sequence stratigraphy, palaeogeography, petroleum geology, and engineering geology. Therefore, the objective of this critical review is to identify key problems and to provide conceptual clarity and possible solutions. Specific issues are the following: (1 According to “limit equilibrium analyses” in soil mechanics, sediment failure with a sliding motion is initiated over a shear surface when the factor of safety for slope stability (F is less than 1. However, the term landslide is not meaningful for debris flows with a flowing motion. (2 Sliding motion can be measured in oriented core and outcrop, but such measurement is not practical on seismic profiles or radar images. (3 Although 79 MTD types exist in the geological and engineering literature, only slides, slumps, and debrites are viable depositional facies for interpreting ancient stratigraphic records. (4 The use of the term landslide for highvelocity debris avalanches is inappropriate because velocities of mass-transport processes cannot be determined in the rock record. (5 Of the 21 potential triggering mechanisms of sediment failures, frequent short-term events that last for only a few minutes to several hours or days (e.g., earthquakes, meteorite impacts, tsunamis, tropical cyclones, etc. are more relevant in controlling deposition of deep-water sands than sporadic long-term events that last for thousands to millions of

  2. Landscape susceptibility, hazard and risk assessments along pipeline corridors in Canada

    Energy Technology Data Exchange (ETDEWEB)

    Blais-Stevens, A.; Couture, R.; Page, A. [Natural Resources Canada, Ottawa, ON (Canada). Geological Survey of Canada; Koch, J.; Clague, J.J. [Simon Fraser Univ., Burnaby, BC (Canada); Lipovsky, P.S. [Yukon Geological Survey, Whitehorse, YT (Canada)

    2010-07-01

    This article discussed work that was carried out to inventory landslides and assess hazards along two proposed gas-pipeline routes in the North. Landslide inventories and hazard assessments are necessary to quantify and qualify the risk of environmental impacts from landslides on linear infrastructure. The Yukon Alaska Highway Pipeline and the Mackenzie Gas Project Pipeline, which will both be over 800 kilometres in length, will cross harsh landscapes characterized by permafrost terrain and will be at risk from geological hazards, including landslides with debris flows, earthquakes, subsidence, and permafrost degradation. The work involved inventorying and mapping landslides via aerial photography and field visits to identify the frequency-magnitude relationships for debris flow fans along the route and the creation of qualitative parametric landslide maps for both proposed pipeline corridors. A good correlation was found between actual landslide distribution and the landslide susceptibility maps. For the Mackenzie Valley Pipeline Corridor, most landslides have occurred in fine unconsolidated sediments and shallow slopes. Landslides in the Yukon Alaska Highway Corridor mostly happened in unconsolidated sediments, but a few took place in bedrock with high relief. The preliminary investigation revealed that a slope hazard exists in both corridors and must be taken into account during pipeline development. The results are intended to facilitate better decision-making for planning, constructing, and maintaining safe and economically viable pipeline routes in Northern Canada. The mapping methodology was outlined. 13 refs., 1 tab., 6 figs.

  3. Landslide Hazard in Georgia

    Science.gov (United States)

    Gaprindashvili, George; Tsereteli, Emil; Gaprindashvili, Merab

    2014-05-01

    In the last decades of the XX century, protect the population from geological hazards, to maintain land and safe operation of the engineering facilities has become the most important social - economic, demographic, political and environmental problems for the whole world. Georgia, with its scales of origination of the natural-catastrophic processes (landslide, mudflow, rockfall, erosion and etc.), their re-occurrence and with the negative results inflicted by these processes to the population, agricultural lands and engineering objects, is one of the most complex mountainous region. The extremely sensitive conditions were conditioned by: 1. Activation of highly intense earthquakes; 2. Activation of the negative meteorological events provoking the disaster processes on the background of global climatic changes and their abnormally frequent occurrence (mostly increased atmospheric precipitations, temperature and humidity); 3. Large-scale Human impact on the environment. Following the problem urgency, a number of departmental and research institutions have made their operations more intense in the given direction within the limits of their competence. First of all, the activity of the Department of Geology of Georgia (which is at present included in the National Environmental Agency of the Ministry of Environment and Natural Resources Protection), which mapped, identified and cataloged the hazardous processes on the territory of the country and identified the spatial limits and developmental regularities of these processes for tens of years. The increased risk of Geological catastrophes in Georgia first of all is caused by insufficient information between society and responsible persons toward this event. The existed situation needs the base assessment of natural disasters level, the identification of events, to determine their caused reasons, to develop special maps in GIS system, and continuous functioning of geo monitoring researches for develop safety early

  4. Quantification of Urban Environment's Role in Slope Stability for Landslide Events.

    Science.gov (United States)

    Bozzolan, E.; Holcombe, E.; Wagener, T.; Pianosi, F.

    2017-12-01

    The combination of a rapid and unplanned urban development with a likely future climate change could significantly affect landslide occurrences in the humid tropics, where rainfall events of high intensity and duration are the dominant trigger for landslide risk. The attention of current landslide hazard studies is largely focussed on natural slope processes based on combinations of environmental factors, excluding the role of urbanisation on slope stability. This project aims to understand the relative influence of urbanisation features on local slope stability and to translate the findings to a wider region. Individual slopes are firstly analysed with the software CHASM, a physically based model which combines soil hydrology and slope stability assessment. Instead of relying on existing records, generally lacking for landslides, ranges of plausible preparatory (such as slope, cohesion, friction angles), triggering (rainfall) and aggravating factors (deforestation, house density and water network) are defined and possible combinations of these factors are created by sampling from those ranges. The influence of urban features on site hydrology and stability mechanisms are evaluated and then implemented in denser urban contexts, characteristic of unplanned settlements. The results of CHASMS can be transferred to regional maps in order to identify the areas belonging to the triggering combinations of factors previously found. In this way, areas susceptible to landslides can be detected not only in terms of natural factors but also in relation to the degree of urbanisation. Realistic scenarios can be extrapolated from the areas considered and then analysed again with CHASM. This permits to adapt (and improve) the initial variability ranges of the factors, creating a general-specific cycle able to identify the landslide susceptibility regions and outline a hazard map. Once the triggers are understood, possible consequences can be assessed and mitigation strategies can

  5. GIS-based terrain analysis of linear infrastructure corridors in the Mackenzie River Valley, NWT

    International Nuclear Information System (INIS)

    Ednie, M.; Wright, J.F.; Duchesne, C.

    2007-01-01

    The impact of global warming on permafrost terrain was discussed with particular reference to the structural stability and performance reliability of the proposed pipelines and roads in the Mackenzie River Valley in the Northwest Territories. Engineers, regulators and decision makers responsible for the development of these networks must have access to information about current and future terrain conditions, both local and regional. The Geological Survey of Canada is developing an ArcGIS resident, multi-component terrain analysis methodology for evaluating permafrost terrain in terms of the probable geothermal and geomorphological responses to climate warming. A GIS-integrated finite-element transient ground thermal model (T-ONE) can predict local-regional permafrost conditions and future responses of permafrost to climate warming. The influences of surface and channel hydrology on local erosion potentials can be determined by analyzing the topographic and topologic characteristics of the terrain. A weights of evidence-based landscape-process model, currently under development, will consider multiple terrain factors for mapping terrain that is susceptible to slope failure, subsidence or erosion. This terrain analysis methodology is currently being applied to a 2 km buffer spanning the proposed Mackenzie Gas Pipeline right-of-way, and along winter and all-weather road networks in the Mackenzie River Valley. Initial ground thermal modeling has identified thermally sensitive terrain for which permafrost will either completely disappear or warm significantly to near isothermal conditions within the next 25 to 55 years

  6. Development of a GIS-based failure investigation system for highway soil slopes

    Science.gov (United States)

    Ramanathan, Raghav; Aydilek, Ahmet H.; Tanyu, Burak F.

    2015-06-01

    A framework for preparation of an early warning system was developed for Maryland, using a GIS database and a collective overlay of maps that highlight highway slopes susceptible to soil slides or slope failures in advance through spatial and statistical analysis. Data for existing soil slope failures was collected from geotechnical reports and field visits. A total of 48 slope failures were recorded and analyzed. Six factors, including event precipitation, geological formation, land cover, slope history, slope angle, and elevation were considered to affect highway soil slope stability. The observed trends indicate that precipitation and poor surface or subsurface drainage conditions are principal factors causing slope failures. 96% of the failed slopes have an open drainage section. A majority of the failed slopes lie in regions with relatively high event precipitation ( P>200 mm). 90% of the existing failures are surficial erosion type failures, and only 1 out of the 42 slope failures is deep rotational type failure. More than half of the analyzed slope failures have occurred in regions having low density land cover. 46% of failures are on slopes with slope angles between 20° and 30°. Influx of more data relating to failed slopes should give rise to more trends, and thus the developed slope management system will aid the state highway engineers in prudential budget allocation and prioritizing different remediation projects based on the literature reviewed on the principles, concepts, techniques, and methodology for slope instability evaluation (Leshchinsky et al., 2015).

  7. Integration of spatial and temporal data for the definition of different landslide hazard scenarios in the area north of Lisbon (Portugal

    Directory of Open Access Journals (Sweden)

    J. L. Zêzere

    2004-01-01

    Full Text Available A general methodology for the probabilistic evaluation of landslide hazard is applied, taking in account both the landslide susceptibility and the instability triggering factors, mainly rainfall. The method is applied in the Fanhões-Trancão test site (north of Lisbon, Portugal where 100 shallow translational slides were mapped and integrated into a GIS database. For the landslide susceptibility assessment it is assumed that future landslides can be predicted by statistical relationships between past landslides and the spatial data set of the predisposing factors (slope angle, slope aspect, transversal slope profile, lithology, superficial deposits, geomorphology, and land use. Susceptibility is evaluated using algorithms based on statistical/probabilistic analysis (Bayesian model over unique-condition terrain units in a raster basis. The landslide susceptibility map is prepared by sorting all pixels according to the pixel susceptibility value in descending order. In order to validate the results of the susceptibility ana- lysis, the landslide data set is divided in two parts, using a temporal criterion. The first subset is used for obtaining a prediction image and the second subset is compared with the prediction results for validation. The obtained prediction-rate curve is used for the quantitative interpretation of the initial susceptibility map. Landslides in the study area are triggered by rainfall. The integration of triggering information in hazard assessment includes (i the definition of thresholds of rainfall (quantity-duration responsible for past landslide events; (ii the calculation of the relevant return periods; (iii the assumption that the same rainfall patterns (quantity/duration which produced slope instability in the past will produce the same effects in the future (i.e. same types of landslides and same total affected area. The landslide hazard is present as the probability of each pixel to be affected by a slope movement

  8. A GIS-based tool for estimating tree canopy cover on fixed-radius plots using high-resolution aerial imagery

    Science.gov (United States)

    Sara A. Goeking; Greg C. Liknes; Erik Lindblom; John Chase; Dennis M. Jacobs; Robert. Benton

    2012-01-01

    Recent changes to the Forest Inventory and Analysis (FIA) Program's definition of forest land precipitated the development of a geographic information system (GIS)-based tool for efficiently estimating tree canopy cover for all FIA plots. The FIA definition of forest land has shifted from a density-related criterion based on stocking to a 10 percent tree canopy...

  9. Modeling the location of the forest line in northeast European Russia with remotely sensed vegetation and GIS-based climate and terrain data

    DEFF Research Database (Denmark)

    Virtanen, Tarmo; Mikkola, Kari; Nikula, Ari

    2004-01-01

    GIS-based data sets were used to analyze the structure of the forest line at the landscape level in the lowlands of the Usa River Basin, in northeast European Russia. Vegetation zones in the area range from taiga in the south to forest-tundra and tundra in the north. We constructed logistic...

  10. Database Organisation in a Web-Enabled Free and Open-Source Software (foss) Environment for Spatio-Temporal Landslide Modelling

    Science.gov (United States)

    Das, I.; Oberai, K.; Sarathi Roy, P.

    2012-07-01

    Landslides exhibit themselves in different mass movement processes and are considered among the most complex natural hazards occurring on the earth surface. Making landslide database available online via WWW (World Wide Web) promotes the spreading and reaching out of the landslide information to all the stakeholders. The aim of this research is to present a comprehensive database for generating landslide hazard scenario with the help of available historic records of landslides and geo-environmental factors and make them available over the Web using geospatial Free & Open Source Software (FOSS). FOSS reduces the cost of the project drastically as proprietary software's are very costly. Landslide data generated for the period 1982 to 2009 were compiled along the national highway road corridor in Indian Himalayas. All the geo-environmental datasets along with the landslide susceptibility map were served through WEBGIS client interface. Open source University of Minnesota (UMN) mapserver was used as GIS server software for developing web enabled landslide geospatial database. PHP/Mapscript server-side application serve as a front-end application and PostgreSQL with PostGIS extension serve as a backend application for the web enabled landslide spatio-temporal databases. This dynamic virtual visualization process through a web platform brings an insight into the understanding of the landslides and the resulting damage closer to the affected people and user community. The landslide susceptibility dataset is also made available as an Open Geospatial Consortium (OGC) Web Feature Service (WFS) which can be accessed through any OGC compliant open source or proprietary GIS Software.

  11. GIS BASED AQUIFER VULNERABILITY ASSESSMENT IN HANGZHOU-JIAXINGHUZHOU PLAIN, CHINA

    Directory of Open Access Journals (Sweden)

    Jean de Dieu Bazimenyera

    2014-01-01

    Full Text Available Hangzhou-Jiaxing-Huzhou plain is among the regions which faces the shortage of water due to its increasing population, industrialization, agriculture and domestic use; hence the high dependence on groundwater. In China, the exploitation of aquifers has been historically undertaken without proper concern for environmental impacts or even the concept of sustainable yield. In order to maintain basin aquifer as a source of water for the area, it is necessary to find out whether certain locations in this groundwater basin are susceptible to receive and transmit pollution, this is why the main objective of this research is to find out the groundwater vulnerable zones using Geographical Information System (GIS model in Hangzhou-Jiaxing-Huzhou plain. GIS was used to create groundwater vulnerability map by overlaying hydro-geological data. The input of the model was provided by the following seven data layers: Depth to water, net Recharge, Aquifer media, Soil media, Topography, Impact of vadose zone and hydraulic Conductivity. This study showed that Hangzhou-Jiaxing-Huzhou area is grouped into three categories: High vulnerable zone with 27.4% of the total area, moderate vulnerable zone which occupy the great part of that area 60.5% and low vulnerable zone with 12.1%. This research suggests first the prioritization of high vulnerable areas in order to prevent the further pollution to already polluted areas; next the frequent monitoring of vulnerable zones to monitor the changing level of pollutants; and finally suggests that this model can be an effective tool for local authorities who are responsible for managing groundwater resources in that area.

  12. Does Geology Matter? Post-Hurricane Maria Landslide Distribution Across the Mountainous Regions of Puerto Rico, USA

    Science.gov (United States)

    Cerovski-Darriau, C.; Bessette-Kirton, E.; Schulz, W. H.; Kean, J. W.; Godt, J.; Coe, J. A.

    2017-12-01

    debris flows. More clay-rich units generated some deeper slumps or shallow flows. Correlations with the 1:100K geologic map revealed that 62% of the high-density areas occurred within granodiorite. Therefore, we hypothesize that when rainfall is not limiting, geology is a major control of landslide susceptibility.

  13. Mass movement susceptibility mapping - A comparison of logistic regression and Weight of evidence methods in Taounate-Ain Aicha region (Central Rif, Morocco

    Directory of Open Access Journals (Sweden)

    JEMMAH A I

    2018-01-01

    Full Text Available Taounate region is known by a high density of mass movements which cause several human and economic losses. The goal of this paper is to assess the landslide susceptibility of Taounate using the Weight of Evidence method (WofE and the Logistic Regression method (LR. Seven conditioning factors were used in this study: lithology, fault, drainage, slope, elevation, exposure and land use. Over the years, this site and its surroundings have experienced repeated landslides. For this reason, landslide susceptibility mapping is mandatory for risk prevention and land-use management. In this study, we have focused on recent large-scale mass movements. Finally, the ROC curves were established to evaluate the degree of fit of the model and to choose the best landslide susceptibility zonation. A total mass movements location were detected; 50% were randomly selected as input data for the entire process using the Spatial Data Model (SDM and the remaining locations were used for validation purposes. The obtained WofE’s landslide susceptibility map shows that high to very high susceptibility zones contain 62% of the total of inventoried landslides, while the same zones contain only 47% of landslides in the map obtained by the LR method. This landslide susceptibility map obtained is a major contribution to various urban and regional development plans under the Taounate Region National Development Program.

  14. A Cascading Storm-Flood-Landslide Guidance System: Development and Application in China

    Science.gov (United States)

    Zeng, Ziyue; Tang, Guoqiang; Long, Di; Ma, Meihong; Hong, Yang

    2016-04-01

    than other parts, while the northeast of Yunnan are most susceptible to floods and landslides, which agrees with the distribution of observed flood and landslide events. Moreover, risks for the multi-hazards were classified into four categories. Results show a strong correlation between the distributions of flash flood prone and landslide-prone regions and also highlight the counties with high risk of storms (e.g., Funing and Malipo), flash floods (e.g., Gongshan and Yanjing) and landslides (e.g., Zhaotong and Luxi). Compared to other approaches, the Cascading Storm-Flood-Landslide Guidance System uses a straightforward yet useful indicator-based weighted linear combination method and could be a useful prototype in mapping characteristics of storm-triggered hazards for users at different administrative levels (e.g., catchment, town, county, province and even nation) in China.

  15. LANDSLIDES INCIDENCE IN THE PIEDMONT OF BAIA MARE URBAN AREA (CASE STUDIES

    Directory of Open Access Journals (Sweden)

    S. ZAHARIA

    2012-12-01

    Full Text Available The landslides incidence in the piedmont of baia mare urbana area cae studies. The General Urban Plan (GUP of Baia Mare municipality requires the study of expected susceptibility for landslides in order to build infrastructure within sustainable development conditions. The complexity and diversity of local geographic area factors, strongly affected by the human pressure, favours the triggering and extension of slope processes in the municipality’s piedmont area. To prevent some major imbalances it is imperative to implement some adequate measures based on in-depth studies.

  16. Estimating volume of deposits associated with landslides on volcanic landscapes in the SW flank of the volcano Pico de Orizaba, Puebla-Veracruz

    Directory of Open Access Journals (Sweden)

    Gabriel Legorreta Paulín

    2017-03-01

    Full Text Available Landslides that occur along river systems are very common and have the potential to cause harm to human, to its infrastructure or affect their socio-economic activity. This dynamic is magnified in territories where morphological contrasts are very marked; as in the border between the mountains and subhorizontal land. This is especially true for volcanic terrains where volcanic activity can trigger voluminous landslides along stream systems by sector and flank collapse and where high seasonal rainfall on terrains covered by poorly consolidated materials produces small but hazardous landslides and debris flows that occur continually along stream systems during the volcanic repose periods. Those type of landslides can deliver volumes of hundreds and millions cubic meters that create a potentially hazardous situation for people and property down the valleys. The study of landslides in volcanic terrains through a Geographic Information System (GIS and under a geomorphological criterion, have allowed to develop a comprehensive methodology linked to the development of multi-temporal inventory, with susceptibility and volume estimation of displaced material. The aim of this research is to develop a method (protocol for landslide susceptibility and landslide volume assessment of potentially unstable volcanic landscapes in order to be helpful in mitigating landslide damages to human settlements. Pico de Orizaba volcano is the highest volcano in Mexico. The volcano has been affected by large flank collapse landslides throughout its geological history. These events have partially destroyed the cone as it happened in Bezymianny volcano and St. Elena volcano. In this volcano, the risk associated with landslide and debris flows, is increased by the growing of human settlements along the hillslopes and by the subsistence agriculture, and deforestation. This situation is favored by a volcanic calm that has lasted 147 years, approximate. These conditions create a

  17. Landslide databases for applied landslide impact research: the example of the landslide database for the Federal Republic of Germany

    Science.gov (United States)

    Damm, Bodo; Klose, Martin

    2014-05-01

    This contribution presents an initiative to develop a national landslide database for the Federal Republic of Germany. It highlights structure and contents of the landslide database and outlines its major data sources and the strategy of information retrieval. Furthermore, the contribution exemplifies the database potentials in applied landslide impact research, including statistics of landslide damage, repair, and mitigation. The landslide database offers due to systematic regional data compilation a differentiated data pool of more than 5,000 data sets and over 13,000 single data files. It dates back to 1137 AD and covers landslide sites throughout Germany. In seven main data blocks, the landslide database stores besides information on landslide types, dimensions, and processes, additional data on soil and bedrock properties, geomorphometry, and climatic or other major triggering events. A peculiarity of this landslide database is its storage of data sets on land use effects, damage impacts, hazard mitigation, and landslide costs. Compilation of landslide data is based on a two-tier strategy of data collection. The first step of information retrieval includes systematic web content mining and exploration of online archives of emergency agencies, fire and police departments, and news organizations. Using web and RSS feeds and soon also a focused web crawler, this enables effective nationwide data collection for recent landslides. On the basis of this information, in-depth data mining is performed to deepen and diversify the data pool in key landslide areas. This enables to gather detailed landslide information from, amongst others, agency records, geotechnical reports, climate statistics, maps, and satellite imagery. Landslide data is extracted from these information sources using a mix of methods, including statistical techniques, imagery analysis, and qualitative text interpretation. The landslide database is currently migrated to a spatial database system

  18. Forecast model of landslides in a short time

    International Nuclear Information System (INIS)

    Sanchez Lopez, Reinaldo

    2006-01-01

    The IDEAM in development of their functions as member of the national technical committee for the prevention and disasters attention (SNPAD) accomplishes the follow-up, monitoring and forecast in real time of the environmental dynamics that in extreme situations constitute threats and natural risks. One of the frequent dynamics and of greater impact is related to landslides, those that affect persistently the life of the persons, the infrastructure, the socioeconomic activities and the balance of the environment. The landslide in Colombia and in the world are caused mainly by effects of the rain, due to that, IDEAM has come developing forecast model, as an instrument for risk management in a short time. This article presents aspects related to their structure, operation, temporary space resolution, products, results, achievements and projections of the model. Conceptually, the model is support by the principle of the dynamic temporary - space, of the processes that consolidate natural hazards, particularly in areas where the man has come building the risk. Structurally, the model is composed by two sub-models; the general susceptibility of the earthly model and the critical rain model as a denotative factor, that consolidate the hazard process. In real time, the model, works as a GIS, permitting the automatic zoning of the landslides hazard for issue public advisory warming to help makers decisions on the risk that cause frequently these events, in the country

  19. Numerical Modeling of the 2014 Oso, Washington, Landslide.

    Science.gov (United States)

    George, D. L.; Iverson, R. M.

    2014-12-01

    Numerical simulations of alternative scenarios that could have transpired during the Oso, Washington, landslide of 22 March 2014 provide insight into factors responsible for the landslide's devastating high-speed runout.We performed these simulations using D-Claw, a numerical model we recently developed to simulate landslide and debris-flow motion from initiation to deposition. D-Claw solves a hyperbolic system of five partial differential equations that describe simultaneous evolution of the thickness,solid volume fraction, basal pore-fluid pressure, and two components of momentum of the moving mass. D-Claw embodies the concept ofstate-dependent dilatancy, which causes the solid volume fraction m to evolve toward a value that is equilibrated to the ambient stress state andshear rate. As the value of m evolves, basal pore-fluid pressure coevolves,and thereby causes an evolution in frictional resistance to motion. Our Oso simulations considered alternative scenarios in which values of all model parameters except the initial solid volume fraction m0 were held constant.These values were: basal friction angle = 36°; static critical-state solidvolume fraction = 0.64; initial sediment permeability = 10-8 m2; pore-fluid density = 1100 kg/m3; sediment grain density = 2700 kg/m3; pore-fluid viscosity = 0.005 Pa-s; and dimensionless sediment compressibility coefficient = 0.03. Simulations performed using these values and m0 = 0.62 produced widespread landslide liquefaction, runaway acceleration, andlandslide runout distances, patterns and speeds similar to those observed or inferred for the devastating Oso event. Alternative simulations that usedm0 = 0.64 produced a much slower landslide that did not liquefy and that traveled only about 100 m before stopping. This relatively benign behavioris similar to that of several landslides at the Oso site prior to 2014. Our findings illustrate a behavioral bifurcation that is highly sensitive to the initial solid volume fraction

  20. San Francisco-Pacifica Coast Landslide Susceptibility 2011

    Data.gov (United States)