scholarly journals Landslide susceptibility analysis using decision tree method, Phidim, Eastern Nepal

2013 ◽  
Vol 15 ◽  
pp. 69-76 ◽  
Author(s):  
Chandra Prakash Poudyal
Keyword(s):  
Decision Tree ◽  
Landslide Susceptibility ◽  
Power Index ◽  
Geographical Information ◽  
Susceptibility Map ◽  
Effective Parameters ◽  
Stream Power ◽  
Topographic Wetness Index ◽  
Landslide Susceptibility Map ◽  
Stream Power Index

The decision tree is one of the new methods used for the determination of landslide susceptibility in the study area. The Phidim area is selected for the application of this method. The total surface area is 168.07 sq. km, and is located at the eastern part of Nepal. There are total of 10 different data bases used for this study which are; geological formation, elevation, slope, curvature, aspect, stream power index, topographic wetness index, distance from drainage, lineaments, and slope length, and are considered as landslide conditioning factors. Geographical information system (GIS) is used as basic tools and ARC/View is used for the processing data analysis and final map preparation. For the decision tree analysis the PASW 18 (statistical tool) is used to generate values of each factor. According to the results of decision tree, two geological formations; stream power index and slope are found as the most effective parameters on the landslide occurrence in the study area. Using the predicted values, the landslide susceptibility map of the study area is produced. To assess the performance of the produced susceptibility map, the area under curve (AUC) is drawn. The AUC value of the produced landslide susceptibility map has been obtained as 95.9%. According to the results of the AUC evaluation, the produced map has showed a good performance. As to wrap up, the produced map is able to be used for medium scaled and regional planning purposes. DOI: http://dx.doi.org/10.3126/bdg.v15i0.7419 Bulletin of the Department of Geology, Vol. 15, 2012, pp. 69-76

scholarly journals Assessment of Landslide Susceptibility by Decision Trees in the Metropolitan Area of Istanbul, Turkey

2010 ◽  
Vol 2010 ◽  
pp. 1-15 ◽  
Author(s):  
H. A. Nefeslioglu ◽  
E. Sezer ◽  
C. Gokceoglu ◽  
A. S. Bozkir ◽  
T. Y. Duman
Keyword(s):  
Decision Tree ◽  
Metropolitan Area ◽  
Landslide Susceptibility ◽  
Susceptibility Map ◽  
Northern Coast ◽  
Stream Power ◽  
Landslide Susceptibility Map ◽  
Conditioning Factors ◽  
Stream Power Index ◽  
Predicted Values

The main purpose of the present study is to investigate the possible application of decision tree in landslide susceptibility assessment. The study area having a surface area of 174.8  locates at the northern coast of the Sea of Marmara and western part of Istanbul metropolitan area. When applying data mining and extracting decision tree, geological formations, altitude, slope, plan curvature, profile curvature, heat load and stream power index parameters are taken into consideration as landslide conditioning factors. Using the predicted values, the landslide susceptibility map of the study area is produced. The AUC value of the produced landslide susceptibility map has been obtained as 89.6%. According to the results of the AUC evaluation, the produced map has exhibited a good enough performance.

scholarly journals Harris Hawks Optimization: A Novel Swarm Intelligence Technique for Spatial Assessment of Landslide Susceptibility

Sensors ◽  
2019 ◽  
Vol 19 (16) ◽  
pp. 3590 ◽  
Author(s):  
Bui ◽  
Moayedi ◽  
Kalantar ◽  
Osouli ◽  
Gör ◽  
...  
Keyword(s):  
Landslide Susceptibility ◽  
Characteristic Curve ◽  
Absolute Error ◽  
Slope Aspect ◽  
Stream Power ◽  
Topographic Wetness Index ◽  
Conditioning Factors ◽  
Performance Error ◽  
Stream Power Index ◽  
Artificial Neural Network Ann

In this research, the novel metaheuristic algorithm Harris hawks optimization (HHO) is applied to landslide susceptibility analysis in Western Iran. To this end, the HHO is synthesized with an artificial neural network (ANN) to optimize its performance. A spatial database comprising 208 historical landslides, as well as 14 landslide conditioning factors—elevation, slope aspect, plan curvature, profile curvature, soil type, lithology, distance to the river, distance to the road, distance to the fault, land cover, slope degree, stream power index (SPI), topographic wetness index (TWI), and rainfall—is prepared to develop the ANN and HHO–ANN predictive tools. Mean square error and mean absolute error criteria are defined to measure the performance error of the models, and area under the receiving operating characteristic curve (AUROC) is used to evaluate the accuracy of the generated susceptibility maps. The findings showed that the HHO algorithm effectively improved the performance of ANN in both recognizing (AUROCANN = 0.731 and AUROCHHO–ANN = 0.777) and predicting (AUROCANN = 0.720 and AUROCHHO–ANN = 0.773) the landslide pattern.

scholarly journals Landform classification using GIS techniques. The case of Kimi municipality area, Euboea Island, Greece.

2016 ◽  
Vol 47 (1) ◽  
pp. 264 ◽  
Author(s):  
I. Ilia ◽  
D. Rozos ◽  
I. Koumantakis
Keyword(s):  
Spatial Analysis ◽  
Power Index ◽  
Stream Power ◽  
Topographic Wetness Index ◽  
Wetness Index ◽  
Topographic Position Index ◽  
Landform Classification ◽  
Essential Parameter ◽  
Position Index ◽  
Stream Power Index

The main objective of this paper is to classify landforms in Kimi municipality area of Euboea Island, Greece using advanced spatial techniques. Landform categories were determined by conducting morphometric analysis through the use of advanced GIS functions. In particular, the process of classifying the landscape into landform categories was based on Topographic Position Index (TPI). The main topographic elements such as slope inclination, aspect, slope shape (curvature), topographic wetness index and stream power index were obtained from the DEM file of the study area. Landform classification was obtained using TPI grids and the classes were related with the geological pattern and the land cover by sophisticated spatial analysis function. The knowledge obtained from the present study could be useful in identifying areas prone to land degradation and instability problems in which landforms are identified as an essential parameter

Landslide variation with morphometric factors using the GIS techniques: The case of Shaqlawa Forest

2021 ◽  
Vol 28 (3) ◽  
pp. 117-128
Author(s):  
Sara Zaki ◽  
Jehan Suleimany
Keyword(s):  
Landslide Susceptibility ◽  
Geographical Information ◽  
Susceptibility Map ◽  
Kurdistan Region ◽  
Ahp Method ◽  
Landslide Susceptibility Map ◽  
Landslide Susceptibility Index ◽  
Map Data ◽  
Very High ◽  
Landslide Zone

This study deals with the application of geographical information system (GIS) datasets and methods to assess the landslide susceptibility in Wadi Hujran. The area has a rocky terrain and belongs to the Shaqlawa district of the Kurdistan Region of Iraq. The region is placed towards the Northeast side of Erbil city. The region covers an area of 18.56 Km2 (1856.1 ha) and consists of rough broken and stones. The watershed area is surrounded by North latitudes 36° 21' 53.514" to 36° 17' 49.7796" and East longitudes 44° 17' 5.658" to 44° 20' 9.06". Three factors, namely the morphometric, geological, and environmental, were used to prepare the landslide susceptibility index. The study made use of AHP method and prepared a landslide susceptibility map. Data related to geology, topography, hydrology, rainfall, and land use were used to prepare the map. Physical and statistical methods were used to validate the map. A heuristic approach was incorporated to produce the final susceptibility map. ArcGIS software was used to generate the landslide zones. A total of five landslide zones were generated, which varied from very low landslide zones (80.5) to very high landslide zone (84.5). The zones also included low landslide zone (1262.2), moderate landslide zone (1505.9), and high landslide zone (566.8), and the ratio of consistency in the present study was 0.06 AHP less than 1, and all the five zones in the study were compiled landslide zonation estimated.

scholarly journals Evaluation of the Effect of Hydroseeded Vegetation for Slope Reinforcement

Land ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 995
Author(s):  
Okoli Jude Emeka ◽  
Haslinda Nahazanan ◽  
Bahareh Kalantar ◽  
Zailani Khuzaimah ◽  
Ojogbane Success Sani
Keyword(s):  
Landslide Susceptibility ◽  
Ground Cover ◽  
Slope Aspect ◽  
Susceptibility Map ◽  
Water Runoff ◽  
Operating Characteristics ◽  
Topographic Wetness Index ◽  
Landslide Susceptibility Map ◽  
Ahp Model ◽  
Slope Reinforcement

A landslide is a significant environmental hazard that results in an enormous loss of lives and properties. Studies have revealed that rainfall, soil characteristics, and human errors, such as deforestation, are the leading causes of landslides, reducing soil water infiltration and increasing the water runoff of a slope. This paper introduces vegetation establishment as a low-cost, practical measure for slope reinforcement through the ground cover and the root of the vegetation. This study reveals the level of complexity of the terrain with regards to the evaluation of high and low stability areas and has produced a landslide susceptibility map. For this purpose, 12 conditioning factors, namely slope, aspect, elevation, curvature, hill shade, stream power index (SPI), topographic wetness index (TWI), terrain roughness index (TRI), distances to roads, distance to lakes, distance to trees, and build-up, were used through the analytic hierarchy process (AHP) model to produce landslide susceptibility map. Receiver operating characteristics (ROC) was used for validation of the results. The area under the curve (AUC) values obtained from the ROC method for the AHP model was 0.865. Four seed samples, namely ryegrass, rye corn, signal grass, and couch, were hydroseeded to determine the vegetation root and ground cover’s effectiveness on stabilization and reinforcement on a high-risk susceptible 65° slope between August and December 2020. The observed monthly vegetation root of couch grass gave the most acceptable result. With a spreading and creeping vegetation ground cover characteristic, ryegrass showed the most acceptable monthly result for vegetation ground cover effectiveness. The findings suggest that the selection of couch species over other species is justified based on landslide control benefits.

scholarly journals LANDSLIDE SUSCEPTIBILITY MAPPING WITH RANDOM FOREST MODEL FOR ORDU, TURKEY

2020 ◽  
Vol XLIII-B3-2020 ◽  
pp. 1229-1236 ◽  
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.

scholarly journals ON THE USE OF SENTINEL-2 IMAGES AND HIGH RESOLUTION DTM FOR LANDSLIDE SUSCEPTIBILITY MAPPING IN A DEVELOPING URBAN SETTLEMENT (MAMAK, ANKARA, TURKEY)

2019 ◽  
Vol XLII-3/W8 ◽  
pp. 469-476 ◽  
Author(s):  
T. Yanar ◽  
S. Kocaman ◽  
C. Gokceoglu
Keyword(s):  
High Resolution ◽  
Urban Planning ◽  
Landslide Susceptibility ◽  
Earth Observation ◽  
Slope Aspect ◽  
Susceptibility Map ◽  
Topographic Wetness Index ◽  
Landslide Susceptibility Map ◽  
Earth Observation Satellites ◽  
Sentinel 2

<p><strong>Abstract.</strong> Urban planning starts with the selection of suitable sites. The main factors and components for site selection are the geological-geotechnical parameters that directly affect the natural hazards, such as landslide and flood, construction costs and the location and distribution of existing infrastructure. The presence and accuracy of up-to-date maps in planning are very important. With the increase of high resolution Earth observation satellites, the required data can be obtained with high temporal frequency and spatial availability. From these data, the base parameters for planning can be extracted with semi- or fully-automatic methods. Among the Earth observation satellites, the Sentinel-2 mission of European Space Agency (ESA) provides high resolution optical images and the data are freely available also at different processing levels such as orthorectified images.</p> <p>In this study, the possibility of the landslide susceptibility map production which should be one of the base maps in urban planning by using Sentinel-2 satellite images was investigated in Mamak District of Ankara City, Turkey. The land cover and land use data were produced from Sentinel-2 images by using a supervised classification method in SNAP Tool provided by ESA. The lithological definitions were received from the General Directorate of Mineral Research and Explorations. The topographical parameters such as slope, aspect, topographic wetness index, etc. were extracted from a high resolution digital terrain model (DTM) of the area. Manually extracted landslide inventory data were employed in the logistic regression method and the produced landslide susceptibility map of the study area is presented here.</p>

scholarly journals DEVELOPING TROPICAL LANDSLIDE SUSCEPTIBILITY MAP USING DINSAR TECHNIQUE OF JERS-1 SAR DATA

2013 ◽  
Vol 8 (1) ◽  
Author(s):  
Ilham Alimuddin ◽  
Luhur Bayuaji ◽  
Haeruddin C. Maddi3 ◽  
Josaphat Tetuko Sri Sumantyo ◽  
Hiroaki Kuze1
Keyword(s):  
Natural Disasters ◽  
Natural Disaster ◽  
Landslide Susceptibility ◽  
Volcanic Eruptions ◽  
Geographical Information ◽  
Susceptibility Map ◽  
Landslide Susceptibility Map ◽  
Landslide Event ◽  
Before And After ◽  
Sar Data

Comprehensive information in natural disaster area is essential to prevent and mitigate people from further damage that might occur before and after such event. Mapping this area is one way to comprehend the situation when disaster strikes. Remote sensing data have been widely used along with GIS to create a susceptibility map. The objective of this study was to develop existing landslides susceptibility map by integrating optical satellite images of Landsat ETM and ASTER with Japanese Earth Resource Satellites (JERS-1) Synthetic Aperture Radar (SAR) data complemented by ground GPS and feature measurement into a Geographical Information Systems (GIS) platform. The study area was focused on a landslide event occurred on 26 March 2004 in Jeneberang Watershed of South Sulawesi, Indonesia. Change detection analysis was used to extract thematic information and the technique of Differential SAR Interferometry (DInSAR) was employed to detect slight surface displacement before the landslide event. The DInSAR processed images would be used to add as one weighted analysis factor in creating landslide susceptibility map. The result indicated that there was a slight movement of the slope prior to the event of landslide during the JERS-1 SAR data acquisition period of 1993-1998. Keywords: Optical Images, JERS-1 SAR, DInSAR, Tropical Landslide, GIS, Susceptibility Map 1. Introduction Recently, natural disasters increased in terms of frequency, complexity, scope, and destructive capacity. They have been particularly severe during the last few years when the world has experienced several large-scale natural disasters such as the Indian Ocean earthquake and tsunami; floods and forest fires in Europe, India and China, and drought in Africa (Sassa, 2005). Mapping such natural disaster areas is essential to prevent and mitigate people from further damage that might occur before and after such event. In Indonesia in particular, in these recent years natural disasters occurred more frequently compared to the last decade (BNPB, 2008). Once within a month in 2011, in three different islands, Indonesia was stricken by earthquake, tsunami, flash floods, and volcanic eruptions with severe fatalities to the people and environment. It was obvious that Indonesia was prone to natural disaster due to its position of being squeezed geologically by three major world plates and this fact makes Indonesia one of the most dangerous

Quantitative Hazard Analysis for Landslides in Hulu Kelang area, Malaysia

2015 ◽  
Vol 73 (1) ◽  
Author(s):  
Nader Saadatkhah ◽  
Azman Kassim ◽  
Lee Min Lee ◽  
Gambo Haruna Yunusa
Keyword(s):  
Landslide Susceptibility ◽  
Frequency Ratio ◽  
Hazard Analysis ◽  
Drainage Density ◽  
Weighting Factor ◽  
Slope Aspect ◽  
Susceptibility Map ◽  
Operating Characteristics ◽  
Stream Power ◽  
Topographic Wetness Index

Hulu Kelang is a region in Malaysia which is very susceptible to landslides. From 1990 to 2011, a total of 28 major landslide events had been reported in this area. This paper evaluates and compares the probability-frequency ratio (FR), statistical index (Wi), and weighting factor (Wf), used for assessing landslide susceptibility in the study area. Eleven landslide influencing factors were considered in the analyses. These factors included lithology, land cover, curvature, slope inclination, slope aspect, drainage density, elevation, distance to lake and stream, distance to road and trenches and two indices (the stream power index (SPI) and the topographic wetness index (TWI)) found in the area. The accuracy of the maps produced from the three models was verified using a receiver operating characteristics (ROC). The verification results indicated that the probability-frequency ratio (FR) model which was developed quantitatively based on probabilistic analysis of spatial distribution of historical landslide events was capable of producing a more reliable landslide susceptibility map in this study area compared to its other counterparts. About 89% of the landslide locations have been predicted accurately by using the FR map. 

scholarly journals Ameliorative, Ecological and Landscape Roles of Făget Forest, Cluj-Napoca, Romania, and Possibilities of Avoiding Risks Based on GIS Landslide Susceptibility Map

2018 ◽  
Vol 46 (1) ◽  
pp. 292-300 ◽  
Author(s):  
Paul SESTRAS ◽  
Mircea V. BONDREA ◽  
Horațiu CETEAN ◽  
Tudor SĂLĂGEAN ◽  
Ştefan BILAŞCO ◽  
...  
Keyword(s):  
Tree Species ◽  
Landslide Susceptibility ◽  
Prunus Avium ◽  
Residential Buildings ◽  
Geographical Information ◽  
Forest Composition ◽  
Susceptibility Map ◽  
Gis Technology ◽  
Landslide Susceptibility Map ◽  
North West

In the case of forests located in the close proximity of urban centres, the functions and conventional roles of the forests have to be largely reconsidered. An experimental study area was located in Făget Forest, near the city of Cluj-Napoca, North-West of Romania, as a subject to evaluate different natural risks, especially landslides. Although most of this area is stabilized, human activity became in the last period the most aggressive and active factor that can induce changes in slopes stability. The evaluation based on new changes on the terrain and constructions has clearly revealed the effect of the unprecedented urban sprawl and the expansion of infrastructure elements and residential buildings. Landslide susceptibility map was elaborated using a multivariate statistical analysis and the Geographical Information System (GIS) technology on a predetermined path inside the forest, as well as obtaining valuable information about the tree species. Based on 14 surveys, each of them covering an area of 500 m2 on a longitudinal transect of the forest, there were identified relatively few tree species with a significant share: Carpinus betulus (42.9%), Fagus sylvatica (24.9%), Quercus petraea (23.2%), Q. robur (6.3%), Prunus avium (1.2%). Their positive roles on avoiding or limiting the flow on slopes, flooding, landslides etc. are different depending on the position, terrain, forest composition, trees density, slope, exposition, but it is fundamental beneficial. However, these species can assure productive (as wood), ameliorative, ecological, landscape, cultural, educational, relaxation roles, and consequently inestimable values.

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