Mapping hazard risk: A case study of Ubatuba, Brazil

Steep slopes in subtropical zones are always at risk from landslides. The risk greatly increases when there is rapid, unplanned urban growth. This has happened at Ubatuba on the Brazilian coast - tourism-related development has forced local people into narrow valleys with steep slopes. In this article the authors describe how the hazard risk can be mapped, helping the local authorities to control the problem.

A COMPARISON OF PIXEL-BASED VERSUS OBJECT ORIENTED ANALYSIS OF LANDSLIDES USING HISTORICAL REMOTE SENSING DATA

With recent advances in remote sensing processing technology, it has become more feasible to begin analysis of the enormous historic archive of remotely sensed data. This historical data provides valuable information on a wide variety of topics which can influence the lives of millions of people if processed correctly and in a timely manner. One such field of benefit is that of landslide mapping and inventory. This data provides a historical reference to those who live near high risk areas so future disasters may be avoided. In order to properly map landslides remotely, an optimum method must first be determined. Historically, mapping has been attempted using pixel based methods such as unsupervised and supervised classification. These methods are limited by their ability to only characterize an image spectrally based on single pixel values. This creates a result prone to false positives and often without meaningful objects created. Recently, several reliable methods of Object Oriented Analysis (OOA) have been developed which utilize a full range of spectral, spatial, textural, and contextual parameters to delineate regions of interest. A comparison of these two methods on a historical dataset of the landslide affected city of San Juan La Laguna, Guatemala has proven the benefits of OOA methods over those of unsupervised classification. Overall accuracies of 96.5% and 94.3% and F-score of 84.3% and 77.9% were achieved for OOA and unsupervised classification methods respectively. The greater difference in F-score is a result of the low precision values of unsupervised classification caused by poor false positive removal, the greatest shortcoming of this method.

Landslide susceptibility mapping in the downstream region of Sharavathi river basin, Central Western Ghats

Landslides are hazards encountered during monsoon in undulating terrains of Western Ghats causing geomorphic make over of earth surface resulting in significant damages to life and property. An attempt is made in this paper to identify landslides susceptibility regions in the Sharavathi river basin downstream using frequency ratio method based on the field investigations during July- November 2007. In this regard, base layers of spatial data such as topography, land cover, geology and soil were considered. This is supplemented with the field investigations of landslides. Factors that influence landslide were extracted from the spatial database. The probabilistic model -frequency ratio is computed based on these factors. Landslide susceptibility indices were computed and grouped into five classes. Validation of LHS, showed an accuracy of 89% as 25 of the 28 regions tallied with the field condition of highly vulnerable landslide regions. The landslide susceptible map generated for the downstream would be useful for the district officials to implement appropriate mitigation measures to reduce hazards.

Mapping of risk and susceptibility of shallow-landslide in the city of Sao Paulo, Brazil

In the city of Sao Paulo, where about 11 million people live, landslides and flooding occur frequently, especially during the summer. These landslides cause the destruction of houses and urban equipment, economic damage, and the loss of lives. The number of areas threatened by landslides has been increasing each year. The objective of this article is to analyze the probability of risk and susceptibility to shallow landslides in the Limoeiro River basin, which is located at the head of the Aricanduva River basin, one of the main hydrographic basins in the city of Sao Paulo. To map areas of risk, we created a cadastral survey form to evaluate landslide risk in the field. Risk was categorized into four levels based on natural and anthropogenic factors: R1 (low risk), R2 (average risk), R3 (high risk), and R4 (very high risk). To analyze susceptibility to shallow landslides, we used the SHALSTAB (Shallow Landsliding Stability) mathematical model and calculated the Distribution Frequency (DF) of the susceptibility classes for the entire basin. Finally, we performed a joint analysis of the average Risk Concentration (RC) and Risk Potential (RP). We mapped 14 risk sectors containing approximately 685 at-risk homes, more than half of which presented a high (R3) or very high (R4) probability of risk to the population. In the susceptibility map, 41% of the area was classified as stable and 20% as unconditionally unstable. Although the latter category accounted a smaller proportion of the total area, it contained a concentration (RC) of 41% of the mapped risk areas with a risk potential (RP) of 12%. We found that the locations of areas predicted to be unstable by the model coincided with the risk areas mapped in the field. This combination of methods can be applied to evaluate the risk of shallow landslides in densely populated areas and can assist public managers in defining areas that are unstable and inappropriate for occupation. (C) 2012 Elsevier B.V. All rights reserved.

Mapping Whidbey Island and Possession Sound landslide susceptibility using an additive linear model

Senior thesis written for Oceanography 445

Remote Sensing and GIScience in Geomorphological Mapping

The rapid proliferation of remote sensing and geographic information systems (GIS) into geomorphologic mapping has increased the objectivity and efficiency of landform segmentation, measurement, and classification. The near ubiquitous presence of Earth-observing satellites provides an array of perspectives to visualize the biophysical characteristics of landscapes, access inhospitable terrain on a predictable schedule, and study landscape processes when conditions are hazardous. GIS technology has altered the analysis, visualization, and dissemination of landform data due to the shared theoretical concepts that are fundamental to geomorphology and GIScience. The authors review geospatial technology applications in landform mapping (including emerging issues) within glacial, volcanic, landslide, and fluvial research.

Use of LIDAR in landslide investigations: A review

This paper presents a short history of the appraisal of laser scanner technologies in geosciences used for imaging relief by high-resolution digital elevation models (HRDEMs) or 3D models. A general overview of light detection and ranging (LIDAR) techniques applied to landslides is given, followed by a review of different applications of LIDAR for landslide, rockfall and debris-flow. These applications are classified as: (1) Detection and characterization of mass movements; (2) Hazard assessment and susceptibility mapping; (3) Modelling; (4) Monitoring. This review emphasizes how LIDARderived HRDEMs can be used to investigate any type of landslides. It is clear that such HRDEMs are not yet a common tool for landslides investigations, but this technique has opened new domains of applications that still have to be developed.

Automatic landslide recognition through Optimum-Path Forest

In this paper we shed light over the problem of landslide automatic recognition using supervised classification, and we also introduced the OPF classifier in this context. We employed two images acquired from Geoeye-MS satellite at March-2010 in the northwest (high steep areas) and north sides (pipeline area) covering the area of Duque de Caxias city, Rio de Janeiro State, Brazil. The landslide recognition rate has been assessed through a cross-validation with 10 runnings. In regard to the classifiers, we have used OPF against SVM with Radial Basis Function for kernel mapping and a Bayesian classifier. We can conclude that OPF, Bayes and SVM achieved high recognition rates, being OPF the fastest approach. © 2012 IEEE.

Slope stability analysis by multi-temporal DEMs and 3D modelling: The 2002 and 2007 Stromboli landslide events

Natural hazard related to the volcanic activity represents a potential risk factor, particularly in the vicinity of human settlements. Besides to the risk related to the explosive and effusive activity, the instability of volcanic edifices may develop into large landslides often catastrophically destructive, as shown by the collapse of the northern flank of Mount St. Helens in 1980. A combined approach was applied to analyse slope failures that occurred at Stromboli volcano. SdF slope stability was evaluated by using high-resolution multi-temporal DTMMs and performing limit equilibrium stability analyses. High-resolution topographical data collected with remote sensing techniques and three-dimensional slope stability analysis play a key role in understanding instability mechanism and the related risks. Analyses carried out on the 2002–2003 and 2007 Stromboli eruptions, starting from high-resolution data acquired through airborne remote sensing surveys, permitted the estimation of the lava volumes emplaced on the SdF slope and contributed to the investigation of the link between magma emission and slope instabilities. Limit Equilibrium analyses were performed on the 2001 and 2007 3D models, in order to simulate the slope behavior before 2002-2003 landslide event and after the 2007 eruption. Stability analyses were conducted to understand the mechanisms that controlled the slope deformations which occurred shortly after the 2007 eruption onset, involving the upper part of slope. Limit equilibrium analyses applied to both cases yielded results which are congruent with observations and monitoring data. The results presented in this work undoubtedly indicate that hazard assessment for the island of Stromboli should take into account the fact that a new magma intrusion could lead to further destabilisation of the slope, which may be more significant than the one recently observed because it will affect an already disarranged deposit and fractured and loosened crater area. The two-pronged approach based on the analysis of 3D multi-temporal mapping datasets and on the application of LE methods contributed to better understanding volcano flank behaviour and to be prepared to undertake actions aimed at risk mitigation.

Shallow Landslide Risk Assessment of the Westerly Bluffs of the 7.5-minute Freeland Quadrangle, Whidbey Island, Washington

Landslides often occur on slopes rendered unstable by underlying geology, geomorphology, hydrology, weather-climate, slope modifications, or deforestation. Unfortunately, humans commonly exacerbate such unstable conditions through careless or imprudent development practices. Due to local geology, geography, and climatic conditions, Puget Sound of western Washington State is especially landslide-prone. Despite this known issue, detailed analyses of landslide risks for specific communities are few. This study aims to classify areas of high landslide risk on the westerly bluffs of the 7.5 minute Freeland quadrangle based on a combined approach: mapping using LiDAR imagery and the Landform Remote Identification Model (LRIM) to identify landslides, and implementation of the Shallow Slope Stability Model (SHALSTAB) to establish a landslide exceedance probability. The objective is to produce a risk assessment from two shallow landslide scenarios: (1) minimum bluff setback and runout and (2) maximum bluff setback and runout. A simple risk equation that takes into account the probability of hazard occurrence with physical and economic vulnerability (van Westen, 2004) was applied to both scenarios. Results indicate an possible total loss as much as $32.6b from shallow landslides, given a setback of 12 m and a runout of 235 m.

Using Terrestrial LiDAR to Monitor Erosion within the Gold Basin Landslide Complex, Verlot, WA

In 2014 the United States Forest Service closed the Gold Basin Campground of western Washington in an effort to protect the public from unstable hillslopes directly adjacent to the campground. The Gold Basin Landslide Complex (GBLC) is actively eroding via block fall, dry ravel, and debris flows, which contribute sediment into the South Fork of the Stillaguamish River. This sediment diminishes the salmonid population within the South Fork of the Stillaguamish River by reducing habitable spawning grounds, which is a big concern to the Stillaguamish Tribe of Indians. In this investigation, I quantified patterns of degradation and total volume of sediment erosion from the middle lobe of the GBLC over the period of July 2015 through January 2016 using terrestrial (ground-based) LiDAR (TLS). I characterized site specific stratigraphy and geomorphic processes, and laid the groundwork for future, long-term monitoring of this site. Results of this investigation determined that ~ 4,800m3 of sediment was eroded from the middle lobe of the GBLC during the 6 month study period (July 2015 – January 2016). This erosion likely occurred from debris flows, raveling of poorly sorted sand and gravel deposits and block failures of high plasticity silts and clays, and/or other mass wasting mechanisms. The generalized stratigraphic sequence in the GBLC consists of alternating massive beds of sand and gravel with silts and clays. The low permeability of these silts and clays provide a perfect venue for groundwater to percolate, as I observed during field investigations, which likely contributes to the active instability of the hillslopes. Continued monitoring and mapping of this complex will lead to viable information that could help both the United States Forest Service and the Stillaguamish Tribe.

A comparison of landslide inventories along the shoreline of Steamboat Island Peninsula, Thurston County, WA: office based protocol vs. field based protocol

The mountain ranges and coastlines of Washington State have steep slopes, and they are susceptible to landslides triggered by intense rainstorms, rapid snow melts, earthquakes, and rivers and waves removing slope stability. Over a 30-year timespan (1984-2014 and includes State Route (SR) 530), a total of 28 deep-seated landslides caused 300 million dollars of damage and 45 deaths (DGER, 2015). During that same timeframe, ten storm events triggered shallow landslides and debris flows across the state, resulting in nine deaths (DGER, 2015). The loss of 43 people, due to the SR 530 complex reactivating and moving at a rate and distance unexpected to residents, highlighted the need for an inventory of the stateís landslides. With only 13% of the state mapped (Lombardo et al., 2015), the intention of this statewide inventory is to communicate hazards to citizens and decision makers. In order to compile an accurate and consistent landslide inventory, Washington needs to adopt a graphic information system (GIS) based mapping protocol. A mapping protocol provides consistency for measuring and recording information about landslides, including such information as the type of landslide, the material involved, and the size of the movement. The state of Oregon shares similar landslide problems as Washington, and it created a GIS-based mapping protocol designed to inform its residents, while also saving money and reducing costly hours in the field (Burns and Madin, 2009). In order to determine if the Oregon Department of Geology and Mineral Industries (DOGAMI) protocol, developed by Burns and Madin (2009), could serve as the basis for establishing Washingtonís protocol, I used the office-based DOGAMI protocol to map landslides along a 40-50 km (25-30 mile) shoreline in Thurston County, Washington. I then compared my results to the field-based landslide inventory created in 2009 by the Washington Division of Geology and Earth Resources (DGER) along this same shoreline. If the landslide area I mapped reasonably equaled the area of the DGER (2009) inventory, I would consider the DOGAMI protocol useful for Washington, too. Utilizing 1m resolution lidar flown for Thurston County in 2011 and a GIS platform, I mapped 36 landslide deposits and scarp flanks, covering a total area of 879,530 m2 (9,467,160 ft2). I also found 48 recent events within these deposits. With an exception of two slides, all of the movements occurred within the last fifty years. Along this same coastline, the DGER (2009) recorded 159 individual landslides and complexes, for a total area of 3,256,570 m2 (35,053,400 ft2). At a first glance it appears the DGER (2009) effort found a larger total number and total area of landslides. However, in addition to their field inventory, they digitized landslides previously mapped by other researchers, and they did not field confirm these landslides, which cover a total area of 2,093,860 m2 (22,538,150 ft2) (DGER, 2009). With this questionable landslide area removed and the toes and underwater landslides accounted for because I did not have a bathymetry dataset, my results are within 6,580 m2 (70,840 ft2) of the DGERís results. This similarity shows that the DOGAMI protocol provides a consistent and accurate approach to creating a landslide inventory. With a few additional modifications, I recommend that Washington State adopts the DOGAMI protocol. Acquiring additional 1m lidar and adopting a modified DOGAMI protocol poises the DGER to map the remaining 87% of the state, with an ultimate goal of informing citizens and decision makers of the locations and frequencies of landslide hazards on a user-friendly GIS platform.

The Pico de Navas slump (Burgos, Spain): a large rocky landslide caused by underlying clayey sand fluidification

The Pico de Navas landslide was a large-magnitude rotational movement, affecting 50x106m3 of hard to soft rocks. The objectives of this study were: (1) to characterize the landslide in terms of geology, geomorphological features and geotechnical parameters; and (2) to obtain an adequate geomechanical model to comprehensively explain its rupture, considering topographic, hydro-geological and geomechanical conditions. The rupture surface crossed, from top to bottom: (a) more than 200 m of limestone and clay units of the Upper Cretaceous, affected by faults; and (b) the Albian unit of Utrillas facies composed of silty sand with clay (Kaolinite) of the Lower Cretaceous. This sand played an important role in the basal failure of the slide due to the influence of fine particles (silt and clay), which comprised on average more than 70% of the sand, and the high content presence of kaolinite (>40%) in some beds. Its geotechnical parameters are: unit weight (δ) = 19-23 KN/m3; friction angle (φ) = 13º-38º and cohesion (c) = 10-48 KN/m2. Its microstructure consists of accumulations of kaolinite crystals stuck to terrigenous grains, making clayey peds. We hypothesize that the presence of these aggregates was the internal cause of fluidification of this layer once wet. Besides the faulted structure of the massif, other conditioning factors of the movement were: the large load of the upper limestone layers; high water table levels; high water pore pressure; and the loss of strength due to wet conditions. The 3D simulation of the stability conditions concurs with our hypothesis. The landslide occurred in the Recent or Middle Holocene, certainly before at least 500 BC and possibly during a wet climate period. Today, it appears to be inactive. This study helps to understand the frequent slope instabilities all along the Iberian Range when facies Utrillas is present.