scholarly journals Evaluation of landslide hazard and its impacts on hilly environment of the Nilgiris District - a geospatial approach

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Edison Thennavan ◽  
Ganapathy Pattukandan Ganapathy

AbstractLandslide Hazard Zonation (LSH) maps play a key role in landuse planning particularly in landslide prone areas. LSH mapping is globally accepted one for analyzing the area for landslide susceptibility. Different approaches were followed by many researchers in India to prepare landslide hazard zonation mapping depending upon their need and requirement. The Nilgiris district in Western Ghats of India is one of the severe to high landslide hazard prone areas of India. Many agencies have carried out research on LSH mapping for the Nilgiris district with different scales. A systematic study of inventory and zonation was 122carried out in 1980’s by government agencies. However there is no proper updation or documentation on landslides after 1980’s in the district The purpose of this paper is to review the existing landslide-related studies in the district of The Nilgiris and review the district’s existing landslide hazard map with updated information. Landslide hazard maps in The Nilgiris were compiled in the GIS platform from various authenticated sources. Data on landslides from 1824 to 2014 were collected and a spatial database on landslides was created. A detailed inventory was analyzed and used for revision of the district’s landslide hazard impact on the 2009 landslides.. Based on the landslide inventory and densely populated areas and repeated landslides at the same locations, the most landslide hazard areas were identified.

2021 ◽  
Author(s):  
Leulalem Shano ◽  
Tarun Kumar Raghuvanshi ◽  
Matebie Meten

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.


2018 ◽  
Vol 2 (1) ◽  
pp. 36
Author(s):  
Heru Sri Naryanto

ABSTRACTBanggai Laut District which consists of islands has many threats to natural disaster, one of them is landslide hazard. The landslides hazard in Banggai Laut District is formed due to morphology which mostly in the form of wavy morphology up to the hills. The thematic map data used in landslide hazard map analysis is the official data held by the Banggai Laut District Government. The weighting and rating system is carried out on several parameters: geology (15%), slope (40%), land cover (25%) and rainfall (20%). Data from these parameters are overlaid with geographic information system (GIS) to obtain the classification of landslide hazard maps, ie: high landslide hazard zones, moderate landslide hazard zones and low landslide hazard zones. High landslide hazard zones are evenly spread over 4 large islands, namely Banggai Island, Bangkurung Island, Labobo Island and Bokan Kepulauan Islands. The potential for high landslide hazard will become bigger with added disturbance of human activities. To smooth the development process in integrated Banggai Laut District, landslide hazard maps and other hazard maps are very necessary. The limited availability of data and information on the disaster in Banggai Laut District, the creation of landslide hazard map is very important as one of the parts to complement the data. With the establishment of Regional Disaster Management Agency (BPBD) of Banggai Laut District, disaster risk reduction is expected to be implemented more focused, integrated, comprehensive and well coordinated with related institutions. Keywords: Landslides, Hazard Maps, Banggai Laut, Disaster Risk Reduction, Focused and Integrated Development.   ABSTRAKKabupaten Banggai Laut yang terdiri dari kepulauan mempunyai banyak ancaman terhadap bencana alam, salah satunya adalah bencana tanah longsor (gerakan tanah). Bahaya tanah longsor di Kabupaten Banggai Laut terbentuk akibat morfofologi yang sebagian besar berupa morfologi bergelombang sampai perbukitan. Data peta tematik yang digunakan dalam analisis peta bahaya tanah longsor adalah data resmi yang dimiliki oleh Pemerintah Kabupaten Banggai Laut. Sistem pembobotan dan penilaian dilakukan pada beberapa parameter yaitu: geologi (15%), lereng (40%), tutupan lahan (25%) dan curah hujan (20%). Data dari parameter-parameter tersebut dioverlay dengan sistem informasi geografi untuk mendapatkan klasifikasi peta bahaya tanah longsor, yaitu: zona bahaya tanah longsor tinggi, zona bahaya tanah longsor sedang dan zona bahaya tanah longsor rendah. Zona bahaya tanah longsor tinggi merata tersebar di 4 pulau besar, yaitu Pulau Banggai, Pulau Bangkurung, Pulau Labobo dan Bokan Kepulauan. Potensi bahaya longsor tinggi tersebut akan menjadi semakin besar dengan tambahan gangguan aktivitas manusia. Untuk kelancaran proses pembangunan secara terpadu di Kabupaten Banggai Laut, peta bahaya longsor dan peta-peta bahaya lainnya sangat diperlukan. Ketersediaan data dan informasi tentang kebencanaan yang masih terbatas di Kabupaten Banggai Laut, maka pembuatan peta kawasan rawan bahaya tanah longsor sangat penting sebagai salah satu bagian untuk melengkapi data tersebut. Dengan terbentuknya BPBD Kabupaten Banggai Laut, maka pengurangan risiko bencana diharapkan dapat dilaksanakan dengan lebih terarah, terpadu, menyeluruh serta terkoordinasi dengan baik dengan instansi terkait. Kata kunci: Tanah Longsor, Peta Bahaya, Banggai Laut, Pengurangan Risiko Bencana, Pembangunan Terarah dan Terpadu.


2012 ◽  
Vol 12 (1) ◽  
pp. 53-60 ◽  
Author(s):  
J. V. DeGraff

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.


Author(s):  
Ilyas A Huqqani ◽  
Lea Tien Tay ◽  
Junita Mohamad Saleh

Landslide is one of the disasters which cause property damages, infrastructure destruction, injury and death. This paper presents the analysis of landslide hazard mapping of Penang Island Malaysia using bivariate statistical methods. Bivariate statistical methods are simple approach which are capable to produce good results in short computational time. In this study, three bivariate statistical methods, i.e. Frequency Ratio (FR), Information Value (IV) and Modified Information Value (MIV) are used to generate the landslide hazard maps of Penang Island. These bivariate statistical methods are computed using MATLAB tool. Landslide hazard map is categorized into 4 levels of hazard. The accuracy of each method and effectiveness in predicating landslides are validated and determined by using Receiver of Characteristics curve. The accuracies of FR, IV and MIV methods are 79.58%, 79.14% and 79.37% respectively.


2018 ◽  
Vol 45 (1) ◽  
pp. 173-184 ◽  
Author(s):  
Katarzyna Łuszczyńska ◽  
Małgorzata Wistuba ◽  
Ireneusz Malik ◽  
Marek Krąpiec ◽  
Bartłomiej Szypuła

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.


Author(s):  
M. K. Tripathi ◽  
H. Govil ◽  
P. K. Champati ray ◽  
I. C. Das

<p><strong>Abstract.</strong> Landslides are very common problem in hilly terrain. Chamoli region of Himalaya is highest sensitive zone of the landslide hazards. The purpose of Chamoli landslide study, to observe the important terrain factors and parameters responsible for landslide initiation. Lithological, geomorphological, slope, aspect, landslide, drainage density and lineament density map generated in remote sensing and GIS environment. Data information of related geological terrain obtain through topographic maps, remote sensing images, field visits and geological maps. Geodatabases of all thematic layers prepared through digitization of topographic map and satellite imageries (LISS-III, LISS-IV &amp;amp; ASTER DEM). Integrated all thematic layers applying information value method under GIS environment to map the zonation of landslide hazard zonation map validation and verification completed by field visit. The landslide hazard zonation map classified in four classes very high, high, medium and low.</p>


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