scholarly journals A geomorphological approach to the estimation of landslide hazards and risks in Umbria, Central Italy

2002 ◽  
Vol 2 (1/2) ◽  
pp. 57-72 ◽  
Author(s):  
M. Cardinali ◽  
P. Reichenbach ◽  
F. Guzzetti ◽  
F. Ardizzone ◽  
G. Antonini ◽  
...  
Keyword(s):  
Central Italy ◽  
Landslide Hazard ◽  
Aerial Photographs ◽  
Site Specific ◽  
Landslide Hazards ◽  
Umbria Region ◽  
Multi Temporal ◽  
Landslide Inventory Map ◽  
Hazard And Risk ◽  
Inventory Map

Abstract. We present a geomorphological method to evaluate landslide hazard and risk. The method is based on the recognition of existing and past landslides, on the scrutiny of the local geological and morphological setting, and on the study of site-specific and historical information on past landslide events. For each study area a multi-temporal landslide inventory map has been prepared through the interpretation of various sets of stereoscopic aerial photographs taken over the period 1941–1999, field mapping carried out in the years 2000 and 2001, and the critical review of site-specific investigations completed to solve local instability problems. The multi-temporal landslide map portrays the distribution of the existing and past landslides and their observed changes over a period of about 60 years. Changes in the distribution and pattern of landslides allow one to infer the possible evolution of slopes, the most probable type of failures, and their expected frequency of occurrence and intensity. This information is used to evaluate landslide hazard, and to estimate the associated risk. The methodology is not straightforward and requires experienced geomorphologists, trained in the recognition and analysis of slope processes. Levels of landslide hazard and risk are expressed using an index that conveys, in a simple and compact format, information on the landslide frequency, the landslide intensity, and the likely damage caused by the expected failure. The methodology was tested in 79 towns, villages, and individual dwellings in the Umbria Region of central Italy.

scholarly journals Landslide hazard assessment in the Collazzone area, Umbria, Central Italy

2006 ◽  
Vol 6 (1) ◽  
pp. 115-131 ◽  
Author(s):  
F. Guzzetti ◽  
M. Galli ◽  
P. Reichenbach ◽  
F. Ardizzone ◽  
M. Cardinali
Keyword(s):  
Probability Model ◽  
Central Italy ◽  
Joint Probability ◽  
Landslide Hazard ◽  
Aerial Photographs ◽  
Exceedance Probability ◽  
Slope Unit ◽  
Multi Temporal ◽  
Inventory Map ◽  
Italian Apennines

Abstract. We present the results of the application of a recently proposed model to determine landslide hazard. The model predicts where landslides will occur, how frequently they will occur, and how large they will be in a given area. For the Collazzone area, in the central Italian Apennines, we prepared a multi-temporal inventory map through the interpretation of multiple sets of aerial photographs taken between 1941 and 1997 and field surveys conducted in the period between 1998 and 2004. We then partitioned the 79 square kilometres study area into 894 slope units, and obtained the probability of spatial occurrence of landslides by discriminant analysis of thematic variables, including morphology, lithology, structure and land use. For each slope unit, we computed the expected landslide recurrence by dividing the total number of landslide events inventoried in the terrain unit by the time span of the investigated period. Assuming landslide recurrence was constant, and adopting a Poisson probability model, we determined the exceedance probability of having one or more landslides in each slope unit, for different periods. We obtained the probability of landslide size, a proxy for landslide magnitude, by analysing the frequency-area statistics of landslides, obtained from the multi-temporal inventory map. Lastly, assuming independence, we determined landslide hazard for each slope unit as the joint probability of landslide size, of landslide temporal occurrence, and of landslide spatial occurrence.

scholarly journals The impact of landslides in the Umbria region, central Italy

2003 ◽  
Vol 3 (5) ◽  
pp. 469-486 ◽  
Author(s):  
F. Guzzetti ◽  
P. Reichenbach ◽  
M. Cardinali ◽  
F. Ardizzone ◽  
M. Galli
Keyword(s):  
Transportation Network ◽  
Central Italy ◽  
Landslide Inventory ◽  
Slope Failures ◽  
Umbria Region ◽  
Landslide Inventory Map ◽  
Inventory Map ◽  
Triggering Events ◽  
The Impact ◽  
Landslide Triggering

Abstract. The Umbria Region of Central Italy has a long history of mass movements. Landslides range from fast moving rock falls and debris flows, most abundant in mountain areas, to slow moving complex failures extending up to several hectares in the hilly part of the Region. Despite landslides occurring every year in Umbria, their impact remains largely unknown. We present an estimate of the impact of slope failures in the Umbria region based on the analysis of a catalogue of historical information on landslide events, a recent and detailed regional landslide inventory map, and three event inventories prepared after major landslide triggering events. Emphasis is given to the impact of landslides on the population, the transportation network, and the built-up areas. Analysis of the available historical information reveals that 1488 landslide events occurred at 1292 sites in Umbria between 1917 and 2001. In the same period 16 people died or were missing and 31 people were injured by slope movements. Roads and railways were damaged by slope failures at 661 sites, and 281 built-up areas suffered landslide damage. Three event inventories showing landslides triggered by high intensity rainfall events in the period 1937–1941, rapid snow melting in January 1997, and earthquakes in September–October 1997, indicate the type, abundance and distribution of damage to the population, the built-up areas and the transportation network caused by typical landslide-triggering events. Analysis of a geomorphological landslide inventory map reveals that in some of the municipalities in the region total landslide area exceeds 25%. Of the more than 45 700 landslide areas shown in the geomorphological inventory map, 4115 intersect a road or railway, and 6119 intersect a built-up area. In these areas slope failures can be expected during future landslide triggering events.

Gis-Based Determination of Landslide Properties in Regional Scale: Karabuk Province (NW Turkey)

2017 ◽  
Vol 17 (1) ◽  
pp. 37-46 ◽  
Author(s):  
Berk Duruturk ◽  
Nermin Demir ◽  
Irmak Koseoglu ◽  
Ugur Berkay Onal ◽  
Murat Ercanoglu
Keyword(s):  
Regional Scale ◽  
Geographical Information ◽  
Slope Aspect ◽  
Nw Turkey ◽  
The World ◽  
Landslide Inventory Map ◽  
Hazard And Risk ◽  
Inventory Map ◽  
Point Vector

Abstract Natural hazards and their consequences are of great importance throughout the world. In Turkey, landslides constitute approximately 5% of the overall damage. The most important part of any landslide study is to extract landslide properties and database. In this study, Karabük city was selected as a study area which is known as one of the most landslide prone areas in Turkey. The study area contains the official borders of Karabük province. The area surrounded by the coordinates of 4518148N-4603891N and 424593E-512511E which has an areal extent of 4067 km square. The data of 1663 occurred landslides in Karabük, were digitized from 1/500.000 scale Turkey Landslide Inventory Map by considering the scarps with point vector format. Considering the literature, parameters of lithology, slope, topographical elevation, NDVI and aspect, which were frequently used among the researchers in landslide assessments, were produced and analyzed a GIS (Geographical Information System) platform. In order to perform analyses, the study area was divided into 62 watersheds. Then, lithology, slope, aspect, topographical elevation and NVDI characteristics of the region were automatically extracted by considering the landslide locations. In this type of study, GIS provides many advantages. For the next stages of landslide assessments such as susceptibility, hazard and risk, this stage provides important inputs and can be considered as the most important stage.

Semiautomatic Landslide Detection Using Remote Sensing and Slope Units

2017 ◽  
Vol 2604 (1) ◽  
pp. 104-110
Author(s):  
Yange Li ◽  
Jianling Huang ◽  
Hao Pu ◽  
Zheng Han ◽  
Wei Li ◽  
...  
Keyword(s):  
High Speed ◽  
Accuracy Assessment ◽  
Seismic Intensity ◽  
Long Term Effects ◽  
Landslide Event ◽  
Multi Temporal ◽  
Landslide Inventory Map ◽  
Inventory Map ◽  
Multi Classification

Landslides induced by earthquakes and rainfall pose severe threats to the infrastructure of highways and high-speed railways. To plan an immediate emergency response, the location and scale of these landslides should be known beforehand. Traditionally, to detect multitemporal landslides induced by earthquakes and the long-term effects, along with other factors such as subsequent rainfall, one had to carry out image classification multiple times to calculate the variance information. The accuracy of that method is affected by accumulated errors from multi-classification, and the process is very time-consuming. In this paper, a semiautomatic approach is proposed for rapid mapping of multi-temporal landslides. The approach can obtain the variance information of each landslide event in one detection process. In addition, slope units are introduced to separate the extracted conjoined landslides. The area of Chenjiaba, China, which is located in the highest seismic intensity zone of the Wenchuan earthquake in Beichuan and had strong rainfall 4 months after the earthquake, was selected as a case study to demonstrate the validity of this methodology. Accuracy assessment was carried out by comparing extracted landslides with a manually prepared landslide inventory map. Correctly detected were 90.1% and 94.2% of earthquake- and rainfall-induced landslides, respectively. Results show that this approach is capable of mapping temporal landslides efficiently and quickly.

scholarly journals Rainfall induced landslides in December 2004 in south-western Umbria, central Italy: types, extent, damage and risk assessment

2006 ◽  
Vol 6 (2) ◽  
pp. 237-260 ◽  
Author(s):  
M. Cardinali ◽  
M. Galli ◽  
F. Guzzetti ◽  
F. Ardizzone ◽  
P. Reichenbach ◽  
...  
Keyword(s):  
Central Italy ◽  
Recent Event ◽  
Rock Falls ◽  
Cumulative Rainfall ◽  
Landslide Hazards ◽  
Umbria Region ◽  
Risk Scenario ◽  
Extent Of Damage ◽  
The Village ◽  
The Town

Abstract. The autumn of 2004 was particularly wet in Umbria, with cumulative rainfall in the period from October to December exceeding 600 mm. On 4–6 December and on 25–27 December 2004, two storms hit the Umbria Region producing numerous landslides, which were abundant near the town of Orvieto where they affected volcanic deposits and marine sediments. In this work, we document the type and abundance of the rainfall-induced landslides in the Orvieto area, in south-western Umbria, we study the rainfall conditions that triggered the landslides, including the timing of the slope failures, we determine the geotechnical properties of the failed volcanic materials, and we discuss the type and extent of damage produced by the landslides. We then use the recent event landslide information to test a geomorphological assessment of landslide hazards and risk prepared for the village of Sugano, in the Orvieto area. Based on the results of the test, we update the existing landslide hazards and risk scenario for extremely rapid landslides, mostly rock falls, and we introduce a new landslide scenario for rapid and very rapid landslides, including soil slides, debris flows and debris avalanches.

scholarly journals The Impact of Probability Density Functions Assessment on Model Performance for Slope Stability Analysis

Geosciences ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 322
Author(s):  
Evelina Volpe ◽  
Luca Ciabatta ◽  
Diana Salciarini ◽  
Stefania Camici ◽  
Elisabetta Cattoni ◽  
...  
Keyword(s):  
Probability Density ◽  
Central Italy ◽  
Model Performance ◽  
Probability Density Functions ◽  
Slope Instability ◽  
Complex Nature ◽  
Density Functions ◽  
Umbria Region ◽  
Input Variables ◽  
The Impact

The development of forecasting models for the evaluation of potential slope instability after rainfall events represents an important issue for the scientific community. This topic has received considerable impetus due to the climate change effect on territories, as several studies demonstrate that an increase in global warming can significantly influence the landslide activity and stability conditions of natural and artificial slopes. A consolidated approach in evaluating rainfall-induced landslide hazard is based on the integration of rainfall forecasts and physically based (PB) predictive models through deterministic laws. However, considering the complex nature of the processes and the high variability of the random quantities involved, probabilistic approaches are recommended in order to obtain reliable predictions. A crucial aspect of the stochastic approach is represented by the definition of appropriate probability density functions (pdfs) to model the uncertainty of the input variables as this may have an important effect on the evaluation of the probability of failure (PoF). The role of the pdf definition on reliability analysis is discussed through a comparison of PoF maps generated using Monte Carlo (MC) simulations performed over a study area located in the Umbria region of central Italy. The study revealed that the use of uniform pdfs for the random input variables, often considered when a detailed geotechnical characterization for the soil is not available, could be inappropriate.

GIS-based landslide hazard assessment: an overview

2005 ◽  
Vol 29 (4) ◽  
pp. 548-567 ◽  
Author(s):  
Wang Huabin ◽  
Liu Gangjun ◽  
Xu Weiya ◽  
Wang Gonghui
Keyword(s):  
Hazard Assessment ◽  
Landslide Hazard ◽  
Integrated System ◽  
Process Models ◽  
Land Utilization ◽  
Property A ◽  
Landslide Hazard Assessment ◽  
Landslide Hazards ◽  
Digital Elevation ◽  
Slope Management

In recent years, landslide hazard assessment has played an important role in developing land utilization regulations aimed at minimizing the loss of lives and damage to property. A variety of approaches has been used in landslide assessment and these can be classified into qualitative factor overlay, statistical models, geotechnical process models, etc. However, there is little work on the satisfactory integration of these models with geographic information systems (GIS) to support slope management and landslide hazard mitigation. This paper deals with several aspects of landslide hazard assessment by presenting a focused review of GIS-based landslide hazard assessment: it starts with a framework for GIS-based assessment of landslide hazard; continues with a critical review of the state of the art in using GIS and digital elevation models (DEM) for mapping and modelling landslide hazards; and concludes with a description of an integrated system for effective landslide hazard assessment and zonation incorporating artificial intelligence and data mining technology in a GIS-based framework of knowledge discovery.

scholarly journals Impact of mapping errors on the reliability of landslide hazard maps

2002 ◽  
Vol 2 (1/2) ◽  
pp. 3-14 ◽  
Author(s):  
F. Ardizzone ◽  
M. Cardinali ◽  
A. Carrara ◽  
F. Guzzetti ◽  
P. Reichenbach
Keyword(s):  
Statistical Modelling ◽  
Landslide Hazard ◽  
Great Effort ◽  
Hazard Maps ◽  
Data Errors ◽  
Inventory Map ◽  
Terrain Unit ◽  
Discriminant Models ◽  
The Impact ◽  
Landslide Deposit

Abstract. Identification and mapping of landslide deposits are an intrinsically difficult and subjective operation that requires a great effort to minimise the inherent uncertainty. For the Staffora Basin, which extends for almost 300 km2 in the northern Apennines, three landslide inventory maps were independently produced by three groups of geomorphologists. In comparing each map with the others, large positional discrepancies arise (in the range of 55–65%). When all three maps are overlain, the locational mismatch of landslide deposit polygons increases to over 80%. To assess the impact of these errors on predictive models of landslide hazard, for the study area discriminant models were built up from the same set of geological-geomorphological factors as predictors, and the occurrence of landslide deposits within each terrain-unit, derived from each inventory map, as dependent variable. The comparison of these models demonstrates that statistical modelling greatly minimises the impact of input data errors which remain, however, a major limitation on the reliability of landslide hazard maps.

scholarly journals Rapid mapping of landslides in the Western Ghats (India) triggered by 2018 extreme monsoon rainfall using a deep learning approach

Landslides ◽  
2021 ◽  
Author(s):  
Sansar Raj Meena ◽  
Omid Ghorbanzadeh ◽  
Cees J. van Westen ◽  
Thimmaiah Gudiyangada Nachappa ◽  
Thomas Blaschke ◽  
...  
Keyword(s):  
Deep Learning ◽  
Western Ghats ◽  
Auxiliary Information ◽  
Optical Data ◽  
Spectral Information ◽  
Topographic Slope ◽  
Western Ghats Of India ◽  
Landslide Inventory Map ◽  
Inventory Map ◽  
The Western Ghats

AbstractRainfall-induced landslide inventories can be compiled using remote sensing and topographical data, gathered using either traditional or semi-automatic supervised methods. In this study, we used the PlanetScope imagery and deep learning convolution neural networks (CNNs) to map the 2018 rainfall-induced landslides in the Kodagu district of Karnataka state in the Western Ghats of India. We used a fourfold cross-validation (CV) to select the training and testing data to remove any random results of the model. Topographic slope data was used as auxiliary information to increase the performance of the model. The resulting landslide inventory map, created using the slope data with the spectral information, reduces the false positives, which helps to distinguish the landslide areas from other similar features such as barren lands and riverbeds. However, while including the slope data did not increase the true positives, the overall accuracy was higher compared to using only spectral information to train the model. The mean accuracies of correctly classified landslide values were 65.5% when using only optical data, which increased to 78% with the use of slope data. The methodology presented in this research can be applied in other landslide-prone regions, and the results can be used to support hazard mitigation in landslide-prone regions.

Factors Contributing to Landslide Susceptibility of the Kope Formation, Cincinnati, Ohio

2021 ◽  
Author(s):  
Michael P. Glassmeyer ◽  
Abdul Shakoor
Keyword(s):  
Shear Strength ◽  
Landslide Susceptibility ◽  
Stream Water ◽  
Strength Parameters ◽  
Slake Durability Index ◽  
Landslide Inventory Map ◽  
Inventory Map ◽  
Colluvial Soil ◽  
Kope Formation ◽  
Representative Samples

ABSTRACT The objective of this study was to evaluate the factors that contribute to the high frequency of landslides in the Kope Formation and the overlying colluvial soil present in the Cincinnati area, southwestern Ohio. The Kope Formation consists of approximately 80 percent shale inter-bedded with 20 percent limestone. The colluvium that forms from the weathering of the shale bedrock consists of a low-plasticity clay. Based on field observations, LiDAR data, and information gathered from city and county agencies, we created a landslide inventory map for the Cincinnati area, identifying 842 landslides. From the inventory map, we selected 10 landslides that included seven rotational and three translational slides for detailed investigations. Representative samples were collected from the landslide sites for determining natural water content, Atterberg limits, grain size distribution, shear strength parameters, and slake durability index. For the translational landslides, strength parameters were determined along the contact between the bedrock and the overlying colluvium. The results of the study indicate that multiple factors contribute to landslide susceptibility of the Kope Formation and the overlying colluvium, including low shear strength of the colluvial soil, development of porewater pressure within the slope, human activity such as loading the top or cutting the toe of a slope, low to very low durability of the bedrock that allows rapid disintegration of the bedrock and accumulation of colluvial soil, undercutting of the slope toe by stream water, and steepness of the slopes.

Sign in / Sign up

Export Citation Format

Share Document