scholarly journals Dendrochronological dating as the basis for developing a landslide hazard map – An example from the Western Carpathians, Poland

2018 ◽  
Vol 45 (1) ◽  
pp. 173-184 ◽  
Author(s):  
Katarzyna Łuszczyńska ◽  
Małgorzata Wistuba ◽  
Ireneusz Malik ◽  
Marek Krąpiec ◽  
Bartłomiej Szypuła
Keyword(s):  
Low Cost ◽  
Sampling Site ◽  
Ring Width ◽  
Landslide Hazard ◽  
Hazard Map ◽  
Large Area ◽  
Landslide Occurrence ◽  
Landslide Activity ◽  
Landslide Event ◽  
Landslide Hazard Map

Abstract Most landslide hazard maps are developed on the basis of an area’s susceptibility to a landslide occurrence, but dendrochronological techniques allows one to develop maps based on past landslide activity. The aim of the study was to use dendrochronological techniques to develop a landslide hazard map for a large area, covering 3.75 km2. We collected cores from 131 trees growing on 46 sampling sites, measured tree-ring width, and dated growth eccentricity events (which occur when tree rings of different widths are formed on opposite sides of a trunk), recording the landslide events which had occurred over the previous several dozen years. Then, the number of landslide events per decade was calculated at every sampling site. We interpolated the values obtained, added layers with houses and roads, and developed a landslide hazard map. The map highlights areas which are potentially safe for existing buildings, roads and future development. The main advantage of a landslide hazard map developed on the basis of dendrochronological data is the possibility of acquiring long series of data on landslide activity over large areas at a relatively low cost. The main disadvantage is that the results obtained relate to the measurement of anatomical changes and the macroscopic characteristics of the ring structure occurring in the wood of tilted trees, and these factors merely provide indirect information about the time of the landslide event occurrence.

scholarly journals Solving the dilemma of transforming landslide hazard maps into effective policy and regulations

2012 ◽  
Vol 12 (1) ◽  
pp. 53-60 ◽  
Author(s):  
J. V. DeGraff
Keyword(s):  
Risk Reduction ◽  
Scientific Information ◽  
Landslide Hazard ◽  
Landslide Risk ◽  
Hazard Map ◽  
Hazard Maps ◽  
Populations At Risk ◽  
Landslide Event ◽  
Effective Policy ◽  
Landslide Hazard Map

Abstract. As geoscientists, we often perceive the production of a map or model to adequately define landslide hazard for an area as the answer or end point for reducing risk to people and property. In reality, the risk to people and property remains pretty much the same as it did before the map existed. Real landslide risk reduction takes place when the activities and populations at risk are changed so the consequences of a landslide event results in lower losses. Commonly, this takes place by translating the information embodied in the landslide hazard map into some change in policy and regulation applying to the affected area. This is where the dilemma arises. Scientific information generally has qualifications, gradations, and conditions associated with it. Regulations are necessarily written in language that tries to avoid any need for interpretation. Effectively incorporating geologic information into regulations and ordinances requires continued involvement with their development and implementation. Unless geoscientists are willing to participate in that process, sustainable risk reduction is unlikely to occur.

scholarly journals Landslide hazard zonation using logistic regression technique: the case of Shafe and Baso catchments, Gamo highland, Ethiopia

2021 ◽  
Author(s):  
Leulalem Shano ◽  
Tarun Kumar Raghuvanshi ◽  
Matebie Meten
Keyword(s):  
Land Use ◽  
Logistic Regression ◽  
Influencing Factors ◽  
Landslide Hazard ◽  
Slope Aspect ◽  
Hazard Map ◽  
Hazard Zonation ◽  
Landslide Hazard Zonation ◽  
Landslide Hazard Map ◽  
Very High

Abstract Landslide hazard zonation plays an important role in safe and viable infrastructure development, urbanization, land use, and environmental planning. The Shafe and Baso catchments are found in the Gamo highland which has been highly degraded by erosion and landslides thereby affecting the lives of the local people. In recent decades, recurrent landslide incidences were frequently occurring in this Highland region of Ethiopia in almost every rainy season. This demands landslide hazard zonation in the study area in order to alleviate the problems associated with these landslides. The main objectives of this study are to identify the spatiotemporal landslide distribution of the area; evaluate the landslide influencing factors and prepare the landslide hazard map. In the present study, lithology, groundwater conditions, distance to faults, morphometric factors (slope, aspect and curvature), and land use/land cover were considered as landslide predisposing/influencing factors while precipitation was a triggering factor. All these factor maps and landslide inventory maps were integrated using ArcGIS 10.4 environment. For data analysis, the principle of logistic regression was applied in a statistical package for social sciences (SPSS). The result from this statistical analysis showed that the landslide influencing factors like distance to fault, distance to stream, groundwater zones, lithological units and aspect have revealed the highest contribution to landslide occurrence as they showed greater than a unit odds ratio. The resulting landslide hazard map was divided into five classes: very low (13.48%), low (28.67%), moderate (31.62%), high (18%), and very high (8.2%) hazard zones which was then validated using the goodness of fit techniques and receiver operating characteristic curve (ROC) with an accuracy of 85.4. The high and very high landslide hazard zones should be avoided from further infrastructure and settlement planning unless proper and cost-effective landslide mitigation measures are implemented.

scholarly journals An approach of preparing earthquake induced landslide hazard map: a case study of Nuwakot District, central Nepal

2019 ◽  
Vol 58 ◽  
pp. 153-162
Author(s):  
Harish Dangi ◽  
Tara Nidhi Bhattarai ◽  
Prem Bahadur Thapa
Keyword(s):  
Residential Buildings ◽  
Landslide Hazard ◽  
Infrastructure Development ◽  
Hazard Map ◽  
Gorkha Earthquake ◽  
Quantification Theory ◽  
Central Nepal ◽  
Major Disaster ◽  
Physical Infrastructure ◽  
Landslide Hazard Map

The Gorkha Earthquake-2015 triggered landslides which are widespread in central Nepal. The landslides swept away physical infrastructures like roads, schools, public and residential buildings, and cultivated lands at several locations. This indicated that the decision makers were not aware of the fact that the locations for possible earthquake-induced landslides can be predicted, and physical infrastructure development can be planned accordingly. What is needed for the purpose is an earthquake-induced landslide hazard map which is a useful tool in decision making, particularly for finding safer geographical locations for residential and public building construction, and also for other physical infrastructure development. Immediately after the Gorkha Earthquake-2015, JICA prepared an earthquake-induced landslide hazard map of the Gorkha and the Sindhupalchowak Districts using a certain methodology. But there remains a research question regarding whether the same methodology can be applied in preparing earthquake-induced landslide hazard maps of other earthquake-affected districts located away from the epicenter area. The main purpose of this research was to apply the JICA methodology to prepare an earthquake-induced landslide hazard map of the Nuwakot District, central Nepal which is the one if the most affected district by Gorkha earthquake 2015. The second purpose was to examine whether the map captured the ground reality or not. While preparing the input data required, four major disaster factors were taken into consideration which includes, among others, slope inclination, slope direction, relationship with the major thrust and distance from the epicenter. These factors were classified and characterized according to their nature and condition. The result was then analyzed by using quantification theory. An earthquake-induced landslide hazard map was then prepared using QGIS as a major software tool. The map was also verified through ground-truthing visiting several locations of the study site. The proposed methodology can be used to prepare similar maps in other affected districts of Gorkha earthquake 2015, and suitable sites for constructing physical infrastructures like roads, residential and public buildings can also be identified using the maps.

scholarly journals Landslide hazard and risk zonation of Thankot – Chalnakhel area,

1970 ◽  
Vol 31 ◽  
pp. 43-50 ◽  
Author(s):  
Pradeep Paudyal ◽  
Megh Raj Dhital
Keyword(s):  
Landslide Hazard ◽  
Geographical Information ◽  
Hazard Map ◽  
Risk Map ◽  
Risk Zonation ◽  
Hazard Zone ◽  
Risk Zones ◽  
Vulnerability Map ◽  
Landslide Hazard Map ◽  
Moderate Hazard

The rocks in the Thankot–Chalnakhel area constitute the Chandragiri Range bordering the Kathmandu valley. The Phulchauki Group of rocks comprise its steep and rugged south slope, whereas the gentle north slope is covered by fluvio-lacustrine deposits of the Kathmandu basin with some recent alluvial fans. During the field study, 94 landslides (covering about 0.24 sq km) were mapped. Most of them were triggered by intense rainfall within the last two years. Landslides are generally found on steep colluvial slope (25°–35°) and dry cultivated land. Based on a computer-based geographical information system, a landslide hazard map, a vulnerability map, and a risk map were prepared. The landslide hazard map shows 20% of the area under high hazard zone, 41% under moderate hazard zone, and 39% under low hazard zone. The risk map generated by combining the hazard map and vulnerability map shows 19% of the area under high and very high risk zones, 33% under moderate risk zone, and 48% under low and very low risk zones.

scholarly journals LANDSLIDE HAZARD MAPPING ALONG RANTEPAO – PALOPO ROAD SECTION, SOUTH SULAWESI PROVINCE

2015 ◽  
Vol 1 (3) ◽  
pp. 93
Author(s):  
Dian Pratiwi Anggeraini
Keyword(s):  
Human Activity ◽  
Spatial Data ◽  
Water System ◽  
Landslide Hazard ◽  
Geographical Information ◽  
Hazard Mapping ◽  
Hazard Map ◽  
The Road ◽  
Road Section ◽  
Landslide Hazard Map

Rantepao – Palopo Road Section is 61 km long, which provides a connection between Palopo City and North Toraja District. Geographically, the road is winding, located in a hilly area with steep canyon. This condition makes the road vulnerable to soil movement or landslide. On 8 November 2009, a landslide, which caused a huge material and immaterial loss, took place. The scale of the disaster was so large that it was classified as a national disaster. In the landslide disaster management, the mitigation and preparedness effort will be more focused if complemented with spatial data in the form of landslide hazard map in Rantepao – Palopo road section. This research uses Public Works Minister Regulation No.22/PRT/M/2007 concerning landslide hazard area spatial planning as the reference which is modified and assisted with the application of Geographical Information System (GIS). Based on the hydro-morphology condition, the research location can be classified into three, namely typology A (> 1000 mdpl), typology B (500 – 1000 mdpl), and typology C (<500 mdpl). Each typology consists of natural physical aspects with slope indicator, soil type, geology, rainfall, distance from the river/slope water system, distance from seismic fault and vegetation. Human activity aspects comprise planting pattern indicator, slope cutting, pond, population density, and mitigation effort. Based on the regulation, several indicators are difficult to apply in the road section study. Therefore, in this research, some modifications are made to several indicators. In the slope cutting indicator, to obtain slope cutting map, overlay process on topography map, slope variation map, and road section map was performed. The distance from the river/slope water system was obtained by calculating the distance from the river to the road, the closer the river to the road, the bigger the vulnerability. Meanwhile, the distance from the fault was evaluated based on the existence of seismic faults in the research location. Landslide hazard map was obtained by applying overlay process to natural physical aspects map and human activity map. To obtain a hazard map for Rantepao – Palopo road section, a modification by applying overlay to road section map and landslide hazard map was performed. Hazard map on Ranteo-Palopo is divided into three types, i.e. low risk, medium risk, and high risk.

scholarly journals Applying logistic regression method to determine combinatorial optimization of landslide-related factors and construct landslide hazard map in Khanh Vinh district, Khanh Hoa Province

2017 ◽  
Vol 20 (K4) ◽  
pp. 76-83
Author(s):  
Danh Thanh Nguyen ◽  
Ngo Van Dau ◽  
Dung Quoc Ta
Keyword(s):  
Logistic Regression ◽  
Combinatorial Optimization ◽  
Regression Method ◽  
Landslide Hazard ◽  
Optimization Models ◽  
Hazard Map ◽  
Related Factors ◽  
Maximum Precipitation ◽  
Logistic Regression Method ◽  
Landslide Hazard Map

The purpose of this study is to produce landslide hazard map in Khanh Vinh district, Khanh Hoa province using logistic regression method integrated with GIS analytical tools. The spatial relationship between landslide-related factors such as topography; lithology; vegetation; maximum precipitation in year; distance from roads; distance from drainages; distance from faults and the distribution of landslides were used in the landslide hazard analyses. Using success rate and prediction rate curve assess the fit and accuracy of logistic regression method. The results show that this method have the goodness of fit and the high accuracy (Areas Under Curves - AUC = 0.8 ~ 0.9). Bayesian Model Average (BMA) of the R statistical software was applied to identify the most influential factors and the combinatorial optimization models of landslide-related factors. There are four the most important landslide-related factors and five combinatorial optimization models of landslide-related factors. Model 3 (slope angle, slope aspect, altitude, distance from roads and maximum precipitation in year) is the best optimization.

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