A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Sarkar, N. K.
- Volcanic eruption of the Barren Island Volcano, Andaman Sea
Authors
1 Geological Survey of India, IN
Source
Journal of Geological Society of India (Online archive from Vol 1 to Vol 78), Vol 39, No 5 (1992), Pagination: 411-419Abstract
Geotectonically the Barren and Narcondum islands lie on the Neogene Inner volcanic are, which proceeds from the recent volcanoes of Central Burma in the North to the Miocene to Recent volcanoes of Indonesia in the SE and are believed to have evolved as a result of eastward subduction of the Indian Ocean lithosphere below the SE Asian plate. The Barren island volcano is characterised by resurgent volcanism; so far, three distinct volcanic episodes have been recorded. An initially submarine volcanism, possibly taking place in late to Post-Pleistocene time formed a giant volcanic cone representing the ancestral Barren island. This ancient volcanic cone was at times, blown out and a thick pile of pyroclastics got deposited over the surface of the relict cauldron. Historical records reveal that the volcano became active again in 1789 when the existing cone with a crater and three subsidiary vents were developed. The present eruption initially starting from the NE subsidiary vent, subsequently merged with the main crater. The intensity of volcanic eruption gradually gathered momentum and continued unabated with thundering explosions till the end of September, 1991. Since November it is lying dormant. There is no major disastrous effect.
The lava of the first phase was olivine basalt and that of the second pbase a high-alumina olivine basalt.
Keywords
Volcanoes, Ezrren-Island, Andaman Sea, Natural Hazards.- GIS Based Landslide Susceptibility Mapping-A Study from Darjeeling-Kalimpong Area, Eastern Himalaya, India
Authors
1 Geological Survey of India, Engineering Geology Division, Salt Lake City, Kolkata - 700 091, IN
Source
Journal of Geological Society of India (Online archive from Vol 1 to Vol 78), Vol 72, No 6 (2008), Pagination: 763-773Abstract
Macro scale (1:50,000) Landslide Susceptibility Map (LSM) of 290.33 sq km area in part of Survey of India Topographical sheet 78A/8 in Darjeeling district categorizes the hill slope into five susceptibility classes based on their estimated landslide susceptibility. The LSM was prepared by facet-wise integration of thematic maps on six causative geofactors (lithology, structure, slope morphometry, relative relief, landuse and land cover and hydrogeology) using a knowledge-based rating system proposed by Bureau of Indian Standards (BIS). The facet and related slope morphometry parameters were derived from the Digital Elevation Model (DEM) which was derived from elevation data using both raster and vector GIS techniques. The thematic maps of geofactors were prepared through detailed field studies and augmentation of existing database. The ARC/INFO 9.1 software was extensively used to handle a large volume of thematic database for multiple retrieval, operation and generation of LSM. The spatial distribution of thematic classes vis-à-vis landslide incidence of the area indicates (a) relative abundance of landslide area is maximum in case of phyllite-phyllitic quartzite-schist assemblages of the Daling Group and minimum in the quartzo-feldspathic gneiss of Central Crystalline Gneissic Complex (CCGC), (b) a slightly higher concentration of landslide incidences in and around the prominent regional thrust (MCT), (c) a progressive increase of landslides abundance in successive higher categories of slopes, (d) highest relative abundance of landslides in the "barren" landuse and landcover categories and (e) higher relative abundance of landslides in 'dripping' and 'flowing' categories of hydrogeological situations. The LSM database reveals that 18.08% of the studied area comes under high and very high susceptibility categories, while the moderately susceptibility class and low and very low susceptibility classes constitute 42.94% and 38.98% of the study area respectively. The landslide incidence map when validated against the prepared LSM indicates (a) no landslide incidence in very low susceptibility zone, (b) a progressive increase in the relative abundance values of landslide for successive higher categories of susceptibility zones and (c) high value (64.80) for high and very high susceptibility zones together. It is felt that factors like antecedent rainfall, erodability of the drainages, large-scale anthropogenic interferences are also important in inducing instability in an area. Therefore, locally, the present susceptibility status of the existing slope may undergo significant changes due to the effect of the above-mentioned factors.Keywords
Landslide, GIS, Eastern Himalaya.- A Quantitative Approach for Improving the BIS (Indian) Method of Medium-Scale Landslide Susceptibility
Authors
1 Geological Survey of India, Engineering Geology Division, DK-6, Sector - II, Salt Lake, Kolkata - 700 091, IN
2 Geological Survey of India, Department of Earth System Analysis, International Institute for Geo-Information Science and Earth Observation (ITC), NL
3 Geological Survey of India, Map and Publication Division, Hyderabad - 500 068, IN
Source
Journal of Geological Society of India (Online archive from Vol 1 to Vol 78), Vol 74, No 5 (2009), Pagination: 625-638Abstract
In India, the Bureau of Indian Standards (BIS) recommends a heuristic method for medium-scale (1:25,000/1:50,000) landslide susceptibility mapping. This is based on fixed ratings of geofactors, without the inclusion of landslide inventory information. In BIS method, the pre-defined ratings of geofactors are applied over diverse areas, irrespective of the terrain-specific spatial inter-dependence of geofactors and landslide types, which leads to rather moderate prediction. In this paper, we evaluate the effectiveness of the existing BIS method in Darjeeling Himalaya through a quantitative method adapting weights of evidence (WofE) modeling. The quantified spatial associations between specific geofactors for different landslide types and failure mechanisms that were generated, using this method showed improved prediction rates as compared to the BIS method of fixed ratings of geofactors. We therefore recommend adjusting the existing BIS guidelines by inclusions of weights, derived locally through quantitative spatial analysis of landslide inventories and geofactor maps.Keywords
Landslide Susceptibility, BIS Method, Weights of Evidence, Darjeeling Himalaya.References
- ANBALAGAN, R. (1992) Landslide hazard evaluation and zonation mapping in mountainous terrain. Engg. Geol., v.32(4), pp.269-277.
- BHATTACHARYA, A., MISHRA, P., GHOSHAL, T.B., BAHUGUNA, H. and GHATAK, T. (1998) A geotechnical appraisal of landslides on 7th July, 1998 along National Highway No. 55. Geol. Surv. India, Progress Report.
- BIS (1998) Preparation of landslide hazard zonation maps in mountainous terrains - Guidelines, Bureau of Indian Standards IS 14496 (Part - 2).
- BONHAM-CARTER, G.F. (1994) Geographic Information Systems for Geoscientists: Modelling with GIS. Pergamon Press, Oxford.
- CARRANZA, E.J.M. and CASTRO, O.T. (2006) Predicting laharinundation zones: case study in west Mount Pinatubo, Philippines. Natural Hazards, v.37(3), pp.331-372.
- CARRARA, A., CARDINALI, M., DETTI, R., GUZZETTI, F., PASQUI, V. and REICHENBACH, P. (1991) GIS techniques and statistical models in evaluating landslide hazard. Earth Surface Processes and Landforms, v.16(5), pp.427-445.
- CHATTERJEE, B. (1983) A geological approach to the landslide hazard zonation in Darjeeling Himalaya. Geol. Surv. India, Progress Report (F.S. 1981-83).
- CHUNG, C.J.F. and FABBRI, A.G., 1999. Probabilistic prediction models for landslide hazard mapping. Photogrammetric Engineering and Remote Sensing, 65(12): 1389-1399.
- CHUNG, C.-J.F. and FABBRI, A.G. (2003), Validation of Spatial Prediction Models for Landslide Hazard Mapping. Natural Hazards, v.30(3), pp.451-472.
- GHOSHAL, T.B., SARKAR, N.K., GHOSH, S. and SURENDRANATH, M. (2008) GIS based landslide susceptibility mapping - a study from Darjeeling-Kalimpong area, Eastern Himalaya, India. Jour. Geol. Soc. India, v.72, pp.763-773.
- SENGUPTA, C.K. (1995) Detailed study of geofactors in selected hazard prone stretches along the surface communication routes in parts of Darjeeling and Sikkim Himalaya, Phase-I, Part-I (Rongtong-Kurseong road section). Geol. Surv. India, Progress Report (F.S. 1993-94).
- SURENDRANATH, M., GHOSH, S., GHOSHAL, T.B. and RAJENDRAN, N. (2008) Landslide hazard zonation in Darjeeling Himalayas: a case study on integration of IRS and SRTM Data. In: N. Sailesh. and S. Zlatanova (Eds.), Remote sensing and GIS technologies for monitoring and prediction of disasters. Environmental Science and Engineering, Springer, pp.121-135.
- HANSEN, A. (1984), Landslide hazard analysis. In: Brunsden and Prior (Eds.), Slope Instability. John Wiley & Sons, New York, pp.523-602.
- LU, P. and ROSENBAUM, M.S. (2003) Artificial neural networks and grey systems for the prediction of slope stability. Natural Hazards, v.30(3), pp.383-398.
- MARK, R.K. and ELLEN, S.D. (1995) Statistical and simulation models for mapping debris-flow hazard. In: A. Carrara and F. Guzzetti (Eds.), Geographical Information Systems in Assessing Natural Hazards. Kluwer Academic Publishers, Dordrecht, pp.93-106.
- MATHEW, J., JHA, V.K. and RAWAT, G.S. (2007) Weights of evidence modelling for landslide hazard zonation mapping in part of Bhagirathi valley, Uttarakhand. Curr. Sci., v.92, no.5, pp.628-638.
- SOETERS, R. and VAN WESTEN, C.J. (1996) Slope Instability: Recognition, analysis and zonation. In: A.K. Turner and R.L. Schuster (Eds.), Landslide: Investigations and Mitigation. Special Report 247. Transportation Research Board. National Research Council. National Academy Press, Washington DC, pp.129-177.
- SURENDRANATH, M., GHOSH, S., GHOSHAL, T.B. and RAJENDRAN, N. (2008) Landslide hazard zonation in Darjeeling Himalayas: a case study on integration of IRS and SRTM Data. In: N. Sailesh and S. Zlatanova (Eds.), Remote sensing and GIS technologies for monitoring and prediction of disasters. Environmental Science and Engineering, Springer, pp.121-135.
- VAN WESTEN, C. J. (1993) GISSIZ: training package for Geographic Information Systems in slope instability zonation: Part 1. theory, ITC Publication No. 15, ITC, The Netherlands.
- VAN WESTEN, C. J. (2000) The modelling of landslide hazards using GIS. Surveys in Geophysics, v.21, pp.241-255.
- VARNES, D.J. (2000) Landslide Hazard Zonation: a review of principles and practice. UNESCO, Darantiere, Paris, pp.61.
- YIN, K.L. and YAN, T.Z. (1988) Statistical prediction models for slope instability of metamorphosed rocks. In: C.H. Bonnard (Ed.), Proceedings of the 5th International Symposium on Landslides, vol. 2, Balkema, Rotterdam, pp.1269-1272.