InSAR Monitoring of Landslide Activity in Dominica

Dominica is a geologically young, volcanic island in the eastern Caribbean. Due to its rugged terrain, substantial rainfall, and distinct soil characteristics, it is highly vulnerable to landslides. The dominant triggers of these landslides are hurricanes, tropical storms, and heavy prolonged rainfall events. These events frequently lead to loss of life and the need for a growing portion of the island’s annual budget to cover the considerable cost of reconstruction and recovery. For disaster risk mitigation and landslide risk assessment, landslide inventory and susceptibility maps are essential. Landslide inventory maps record existing landslides and include details on their type, location, spatial extent, and time of occurrence. These data are integrated (when possible) with the landslide trigger and pre-failure slope conditions to generate or validate a susceptibility map. The susceptibility map is used to identify the level of potential landslide risk (low, moderate, or high). In Dominica, these maps are produced using optical satellite and aerial images, digital elevation models, and historic landslide inventory data. This study illustrates the benefits of using satellite Interferometric Synthetic Aperture Radar (InSAR) to refine these maps. Our study shows that when using continuous high-resolution InSAR data, active slopes can be identified and monitored. This information can be used to highlight areas most at risk (for use in validating and updating the susceptibility map), and can constrain the time of occurrence of when the landslide was initiated (for use in landslide inventory mapping). Our study shows that InSAR can be used to assist in the investigation of pre-failure slope conditions. For instance, our initial findings suggest there is more land motion prior to failure on clay soils with gentler slopes than on those with steeper slopes. A greater understanding of pre-failure slope conditions will support the generation of a more dependable susceptibility map. Our study also discusses the integration of InSAR deformation-rate maps and time-series analysis with rainfall data in support of the development of rainfall thresholds for different terrains. The information provided by InSAR can enhance inventory and susceptibility mapping, which will better assist with the island’s current disaster mitigation and resiliency efforts.

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Landslide Characteristics and Evolution: What We Can Learn from Three Adjacent Landslides

Remote Sensing ◽

10.3390/rs13224579 ◽

2021 ◽

Vol 13 (22) ◽

pp. 4579

Author(s):

Dongdong Yang ◽

Haijun Qiu ◽

Yaru Zhu ◽

Zijing Liu ◽

Yanqian Pei ◽

...

Keyword(s):

Time Series ◽

Risk Mitigation ◽

Landslide Risk ◽

Significant Heterogeneity ◽

Interferometric Synthetic Aperture Radar ◽

Antecedent Precipitation ◽

Surface Time ◽

Field Investigations ◽

Landslide Processes ◽

Slow Moving

Landslide processes are a consequence of the interactions between their triggers and the surrounding environment. Understanding the differences in landslide movement processes and characteristics can provide new insights for landslide prevention and mitigation. Three adjacent landslides characterized by different movement processes were triggered from August to September in 2018 in Hualong County, China. A combination of surface and subsurface characteristics illustrated that Xiongwa (XW) landslides 1 and 2 have deformed several times and exhibit significant heterogeneity, whereas the Xiashitang (XST) landslide is a typical retrogressive landslide, and its material has moved downslope along a shear surface. Time-series Interferometric Synthetic Aperture Radar (InSAR) and Differential InSAR (DInSAR) techniques were used to detect the displacement processes of these three landslides. The pre-failure displacement signals of a slow-moving landslide (the XST landslide) can be clearly revealed by using time-series InSAR. However, these sudden landslides, which are a typical catastrophic natural hazard across the globe, are easily ignored by time-series InSAR. We confirmed that effective antecedent precipitation played an important role in the three landslides’ occurrence. The deformation of an existing landslide itself can also trigger new adjacent landslides in this study. These findings indicate that landslide early warnings are still a challenge since landslide processes and mechanisms are complicated. We need to learn to live with natural disasters, and more relevant detection and field investigations should be conducted for landslide risk mitigation.

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LANDSLIDE SUSCEPTIBILITY MODELLING IN SELECTED STATES ACROSS SE. NIGERIA

Environment & Ecosystem science ◽

10.26480/ees.01.2020.23.27 ◽

2020 ◽

Vol 4 (1) ◽

pp. 23-27

Author(s):

R. O. E. Ulakpa ◽

V.U.D. Okwu ◽

K. E. Chukwu ◽

M. O. Eyankware

Keyword(s):

Landslide Susceptibility ◽

Landsat Imagery ◽

Control Measures ◽

Landslide Risk ◽

Susceptibility Map ◽

Landsat 8 ◽

Aerial Photos ◽

Anambra State ◽

Digital Elevation ◽

Elevation Model

Identification and mapping of landslide is essential for landslide risk and hazard assessment. This paper gives information on the uses of landsat imagery for mapping landslide areas ranging in size from safe area to highly prone areas. Landslide mitigation largely depends on the understanding of the nature of the factors namely: slope, soil type, lineament, lineament density, elevation, rainfall and vegetation. These factors have direct bearing on the occurrence of landslide. Identification of these factors is of paramount importance in setting out appropriate and strategic landslides control measures. Images for this study was downloaded by using remote sensing with landsat 8 ETM and aerial photos using ArcGIS 10.7 and Surfer 8 software, while Digital Elevation Model (DEM) and Google EarthPro TM were used to produce slope, drainage, lineament and elevation. From the processed landsat 8 imagery, landslide susceptibility map was produced, and landslide was category into various class; low, medium and high. From the study, it was observed that Enugu and Anambra state ranges from high to medium in terms of landslide susceptibility, Imo state ranges from medium to low.

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APPLICATION OF AHP METHOD FOR MAPPING SLOPE GEOMORPHIC PHENOMENA

10.31219/osf.io/69xc5 ◽

2017 ◽

Author(s):

Florin Constantin MIHAI

Keyword(s):

Risk Mitigation ◽

Characteristic Curve ◽

Confusion Matrix ◽

Predictive Performance ◽

Landslide Risk ◽

Good Correspondence ◽

Topographic Features ◽

Digital Elevation ◽

Elevation Model ◽

Hierarchy Process

Landslides are common and frequent geomorphic phenomena for the plateau regions in Romania having important consequences, especially economic ones, that needs designing scientific and technical plans for landslide risk mitigation. For this, an important preliminary step is assessing and mapping the landslide susceptibility. This paper examines a plateau zone in eastern Romania providing such a map, based on the landslides inventory, the digital elevation model (DEM) and the thematic layers of several factors thought to be potential predictors of landslides occurrence: topographic features, land use, and lithology. The methodological framework is based on the analytical hierarchy process (AHP) principles and factors weights attributed based on frequency of landslides. The predictive performance of the model was assessed using the confusion matrix, the ROC (receiver operating characteristic) curve and the AUC (area under curve) parameter. The results indicate a good correspondence between the susceptibility estimated for the test samples and for the validation samples

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Landslide Susceptibility in Majalengka Regency, West Java Province

IOP Conference Series Earth and Environmental Science ◽

10.1088/1755-1315/884/1/012053 ◽

2021 ◽

Vol 884 (1) ◽

pp. 012053

Author(s):

S Selaby ◽

E Kusratmoko ◽

A Rustanto

Keyword(s):

Landslide Susceptibility ◽

Public Works ◽

Disaster Mitigation ◽

Susceptibility Map ◽

Landslide Susceptibility Map ◽

Multi Criteria Evaluation ◽

Susceptibility Maps ◽

The Government ◽

The Impact ◽

Landslide Susceptibility Maps

Abstract Majalengka is one of districts in Indonesia which is susceptible to landslides. Landslides in Majalengka caused enormous losses such as damage to infrastructure, loss of property, and even human fatalities. Seeing of the impact, mitigation efforts are needed to reduce risks and losses by making landslide susceptibility maps. This study aims to map areas landslide susceptibility and as a reference for the government and related agencies to reduce losses. The method used overlay using Spatial Multi-Criteria Evaluation (SMCE), using weighting values from the Minister Public Works Regulation NO.22/PRT/M/2007, Puslittanak Bogor (2014) and Directorate Volcanology and Disaster Mitigation (DVMBG) (2004). Then comparison of these sources is carried out to determine weighting value with the highest accuracy. The variables are slope, rainfall, soil type, lithology, and land use. The results of this study indicate that landslide susceptibility areas are divided into non-susceptible, low, moderate, and high areas. Where areas Majalengka Regency is dominated by moderate susceptibility level. For the accuracy value of the landslide susceptibility map produced by the weighted value source from the Minister of Public Works Regulation NO.22/PRT/M/2007 has the highest accuracy value of 76%. For weighting from the Bogor Puslittanak is 73%, while weighting source from DVMBG is 68%.

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Assessment of earthquake-induced landslide inventories and susceptibility maps using slope unit-based logistic regression and geospatial statistics

Scientific Reports ◽

10.1038/s41598-021-00780-y ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Badal Pokharel ◽

Massimiliano Alvioli ◽

Samsung Lim

Keyword(s):

Logistic Regression ◽

Landslide Susceptibility ◽

Hot Spot ◽

Predisposing Factors ◽

Landslide Inventory ◽

Susceptibility Map ◽

Essential Information ◽

Susceptibility Maps ◽

2015 Gorkha Earthquake ◽

Error Index

AbstractInventories of seismically induced landslides provide essential information about the extent and severity of ground effects after an earthquake. Rigorous assessment of the completeness of a landslide inventory and the quality of a landslide susceptibility map derived from the inventory is of paramount importance for disaster management applications. Methods and materials applied while preparing inventories influence their quality, but the criteria for generating an inventory are not standardized. This study considered five landslide inventories prepared by different authors after the 2015 Gorkha earthquake, to assess their differences, understand the implications of their use in producing landslide susceptibility maps in conjunction with standard landslide predisposing factors and logistic regression. We adopted three assessment criteria: (1) an error index to identify the mutual mismatches between the inventories; (2) statistical analysis, to study the inconsistency in predisposing factors and performance of susceptibility maps; and (3) geospatial analysis, to assess differences between the inventories and the corresponding susceptibility maps. Results show that substantial discrepancies exist among the mapped landslides. Although there is no distinct variation in the significance of landslide causative factors and the performance of susceptibility maps, a hot spot analysis and cluster/outlier analysis of the maps revealed notable differences in spatial patterns. The percentages of landslide-prone hot spots and clustered areas are directly proportional to the size of the landslide inventory. The proposed geospatial approaches provide a new perspective to the investigators for the quantitative analysis of earthquake-triggered landslide inventories and susceptibility maps.

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LANDSLIDE SUSCEPTIBILITY MAPPING WITH RANDOM FOREST MODEL FOR ORDU, TURKEY

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xliii-b3-2020-1229-2020 ◽

2020 ◽

Vol XLIII-B3-2020 ◽

pp. 1229-1236 ◽

Cited By ~ 1

Author(s):

G. Karakas ◽

R. Can ◽

S. Kocaman ◽

H. A. Nefeslioglu ◽

C. Gokceoglu

Keyword(s):

Random Forest ◽

Landslide Susceptibility ◽

Digital Terrain Model ◽

Disaster Mitigation ◽

Landslide Susceptibility Mapping ◽

Susceptibility Map ◽

Effective Parameters ◽

Landslide Susceptibility Map ◽

Random Forest Method ◽

Susceptibility Maps

Abstract. Landslides are among commonly observed natural hazards all over the world and can be quite destructive for infrastructure and in settlement areas. Their occurrences are often related with extreme meteorological events and seismic activities. Preparation of landslide susceptibility maps is important for disaster mitigation efforts and to increase the resilience. The factors effective on landslide susceptibility map production depend mainly on the topography, land use and the geological characteristics of the region. The up-to-date and accurate data needed for extracting the effective parameters can be obtained by using photogrammetric techniques with high spatial resolution. Data driven ensemble methods are being increasingly used for landslide susceptibility map production and accurate results can be obtained. In this study, regional landslide susceptibility map of a landslide-prone area in a part of Ordu Province in northern Turkey is produced using topographic and lithological parameters by employing the random forest method. An actual landslide inventory delineated manually by geologists using the produced orthophotos and the digital terrain model (DTM) is used for training the model. The results show that an accuracy of 83% and precision of 92% can obtained from the data and the random forest method. The approach can be applied for generation of regional susceptibility maps semi-automatically.

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Heavy Rainfall Triggering Shallow Landslides: A Susceptibility Assessment by a GIS-Approach in a Ligurian Apennine Catchment (Italy)

Water ◽

10.3390/w11030605 ◽

2019 ◽

Vol 11 (3) ◽

pp. 605 ◽

Cited By ~ 11

Author(s):

Anna Roccati ◽

Francesco Faccini ◽

Fabio Luino ◽

Andrea Ciampalini ◽

Laura Turconi

Keyword(s):

Landslide Susceptibility ◽

Shallow Landslides ◽

Decision Makers ◽

Slope Instability ◽

Landslide Risk ◽

Susceptibility Map ◽

Susceptibility Assessment ◽

Rainfall Events ◽

Earth Flows ◽

Weighted Values

In recent decades, the Entella River basin (eastern Liguria) has been affected by several rainfall events that induced widespread shallow landslides and earth flows on the slopes; roads, buildings, structures and infrastructure suffered extensive damage due to the instability processes. In this paper, a GIS-based approach for analyzing and assessing a simplified landslide susceptibility in the Entella River catchment is presented. Starting from landslide information mainly provided from newspaper articles and unpublished reports from municipal archives, we performed a series of comparative analyses using a set of thematic maps to assess the influence of predisposing natural and anthropic factors. By evaluating the statistical distribution of landslides in different categories, we assigned weighted values to each parameter, according to their influence on the instability processes. A simplified, reproducible, but effective approach to assess landslide susceptibility in the study area was performed by combining all predisposing factors. The resulting scores in proneness to slope instability classes may be used to generate a simplified landslides susceptibility map of the catchment area which would be easy to regularly update every time a rainfall event that is able to trigger shallow landslides occurs; this would provide a useful tool for local authorities and decision makers for identifying areas which could potentially be affected by instability processes, and would help in determining the most suitable measures in land-planning and landslide risk management.

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Mapeamento geoecológico da susceptibilidade à ocorrência de incêndios no maciço da Pedra Branca, município do Rio de Janeiro

Anuário do Instituto de Geociências - UFRJ ◽

10.11137/2009_2_14-25 ◽

2009 ◽

Vol 32 (2) ◽

pp. 14-25

Author(s):

Pedro Henrique Ferreira Coura ◽

Gustavo Mota de Sousa ◽

Manoel Do Couto Fernandes

Keyword(s):

Forest Fires ◽

Rio De Janeiro ◽

Flood Plain ◽

Integrative Approach ◽

Susceptibility Map ◽

Burned Areas ◽

Susceptibility Maps ◽

Digital Elevation ◽

Elevation Model ◽

The City

The city of Rio de Janeiro has two different relief compartments, the coastal massives and flood plain areas. One of these is the Pedra Branca massif, with 197.27 KmÂ², situated in the western part of the municipality, between 22º 55' and 23º 05' S and 43º 20'and 43º 40' W. Pedra Branca has suffered forest fires frequently over its history, which is one of the main actors of its changing landuse. The aim of this paper is to develop a susceptibility map of fires occurrence in the Pedra Branca massif / RJ, using a geoecological approach. For this purpose, several layers of functional and structures as shape in 1:10.000 scale, Digital Elevation Model (DEM), aspect, geomorphology and solar radiation was introduced through an analytical-integrative approach. All maps were 1:10.000 catastral maps from Pereira Passos Institute - IPP. The landuse was interpreted from 18 orthophotos in the same scale. Two geoecological susceptibility maps of fire, which show the susceptibility areas to fire occurrence in the Pedra Branca Massif have been generated. These maps were validated from the analysis of two burned areas identified, where the best adjusted map recognizes 93.8% of areas to fire. The susceptibility map developed presents susceptible fires areas and is expected to be used in strategic planning to combat wildfires.

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Liquefaction susceptibility maps for the Aqaba–Elat region with projections of future hazards with sea-level rise

Quarterly Journal of Engineering Geology and Hydrogeology ◽

10.1144/qjegh2020-039 ◽

2020 ◽

pp. qjegh2020-039 ◽

Cited By ~ 1

Author(s):

Abdel-Rahman A. Abueladas ◽

Tina M. Niemi ◽

Abdallah Al-Zoubi ◽

Gideon Tibor ◽

Mor Kanari ◽

...

Keyword(s):

Sea Level ◽

Water Table ◽

Active Faults ◽

Gulf Of Aqaba ◽

Susceptibility Map ◽

Northern Coast ◽

Borehole Data ◽

Ground Acceleration ◽

Liquefaction Susceptibility ◽

Susceptibility Maps

The cities of Aqaba, Jordan and Elat, Israel are vulnerable to seismic damage because they are built over the active faults of the Dead Sea Transform that are the source of historically destructive earthquakes. A liquefaction susceptibility map was generated for the Aqaba–Elat region. Borehole data from 149 locations and the water table depth were used to calculate effective overburden stress in the Seed–Idriss simplified method. The liquefaction analysis was based on applying a cyclic loading scenario with horizontal peak ground acceleration of 0.3 g in a major earthquake. The liquefaction map, compiled using a GIS platform, shows high and moderate liquefaction susceptibility zones along the northern coast of the Gulf of Aqaba that extend 800 m inland from the shoreline. In Aqaba, several hotels, luxury apartment complexes, archaeological sites, ports and commercial districts are located within high and moderate liquefaction zones. In Elat, the seaport and the coastal hotel district are located within a high susceptibility zone. Most residential areas, schools and hospitals in both cities are located within zones not susceptible to liquefaction based on the methods of this study. The total area with the potential to be liquefied along the Gulf of Aqaba is c. 10 km2. Given predictions for global sea-level, we ran three liquefaction models utilizing projected water table rises of 0.5, 1 and 2 m. These models yielded an increase in the area of high liquefaction ranging from 26 to 49%. Given the high potential of future earthquakes, our liquefaction susceptibility maps should help inform city officials for hazard mitigation planning.

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