Abstract
Landslides are among the most costly and damaging natural hazards in mountainous regions, triggered mainly under the influence of earthquakes and/or rainfall. In the present study, Landslide Hazard Zonation (LHZ) of Dikrong river basin of Arunachal Pradesh was carried out using Remote Sensing and Geographic Information System (GIS). Various thematic layers namely slope, photo-lineament buffer, thrust buffer, relative relief map, geology and land use / land cover map were generated using remote sensing data and GIS. The weighting-rating system based on the relative importance of various causative factors as derived from remotely sensed data and other thematic maps were used for the LHZ. The different classes of thematic layers were assigned the corresponding rating value as attribute information in the GIS and an “attribute map” was generated for each data layer. Each class within a thematic layer was assigned an ordinal rating from 0 to 9. Summation of these attribute maps were then multiplied by the corresponding weights to yield the Landslide Hazard Index (LHI) for each cell. Using trial and error method the weight-rating values have been re-adjusted. The LHI threshold values used were: 142, 165, 189 and 216. A LHZ map was prepared showing the five zones, namely “very low hazard”, “low hazard”, “moderate hazard”, “high hazard” and “very high hazard” by using the “slicing” operation.
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References
Arora MK, Das Gupta AS, Gupta RP (2004) An artificial neural network approach for landslide hazard zonation in the Bhagirathi (Ganga) Valley, Himalayas. Int J Remote Sens 25(3):559–572
Beek LPHV, Asch TWJV (2004) Regional assessment of the effects of land use change on landslide hazard by means of physically based modelling. Nat Hazards 31:289–304
Brardinoni F, Slaymaker O, Hassan MA (2003) Landslide inventory in a rugged forested watershed: a comparison between air-photo and field survey data. Geomorphology 54:179–196
Carrara A, Guzzetti F, Cardinali M, Reichenbach P (1999) Use of GIS technology in the prediction and monitoring of landslide hazard. Nat Hazards 20:117–135
Casson B, Delacourt C, Baratoux D, Allemand P (2003) Seventeen years of the “La Clapière” landslide evolution analysed from ortho-rectified aerial photographs. Eng Geol 68:123–139
Chen H, Lee CF (2003) A dynamic model for rainfall-induced landslides on natural slopes. Geomorphology 51:269–288
Cohen J (1960) A coefficient of agreement of nominal scales. Educ Psychol Meas 20:37–46
Dattilo G, Spezzano G (2003) Simulation of a cellular landslide model with CAMELOT on high performance computers. Parallel Comput 29:1403–1418
Ercanoglu M, Gokceoglu C, Asch TWJV (2004) Landslide Susceptibility Zoning North of Yenice (NW Turkey) by multivariate statistical techniques. Nat Hazards 32:1–23
Fraser A, Huggins P, Rees J, Cleverly P (1997) A satellite remote sensing technique for geological structure horizon mapping. Int J Remote Sens 18(7):1607–1615
Glade T (2003) Landslide occurrence as a response to land use change: a review of evidence from New Zealand. Catena 51:297–314
Glassey P, Barrell D, Forsyth J, Macleod R (2003) The geology of Dunedin, New Zealand, and the management of geological hazards. Quat Int 103:23–40
Hervás J., Barredo JI, Rosin PL, Pasuto A, Mantovani F, Silvano S (2003) Monitoring landslides from optical remotely sensed imagery: the case history of Tessina landslide, Italy. Geomorphology 54:63–67
Kilburn CRJ, Pasuto A (2003) Major risk from rapid, large-volume landslides in Europe (EU Project RUNOUT). Geomorphology 54:3–9
Kienzle SW (1996) Using DTMs and GIS to define input variables for hydrological and geomorphological analysis. In: Kovar K, Nachtnebet H (eds) Applications of geographical information systems in hydrology and water resources management, IAHS-AISH Publication No. 235. pp 183–190
Kumar KV, Nair RR, Lakhera RC (1993) Digital image enhancement for delineating active landslide areas. Asia-Pac Remote Sens J 6(1):63–66
Kunte SV, Ganju JL, Dutta NK (1983) Geology and structure of the Teritary Bely between bargang and Pachin Rivers, Arunachal Pradesh. Misc. Pub. No. 43 Proceedings of the Symposium on Geology and Mineral resources of North eastern Himalayas during May 28–30, 1976 at Shillong. Geological Survey of India, Calcutta, pp 125–129
Lazzari M, Salvaneschi P (1999) Embedding a Geographic Information System in a decision support system for landslide hazard monitoring. Nat Hazards 20:185–195
Lee S, Choi J, Min K (2004) Probabilistic landslide hazard mapping using GIS and remote sensing data at Boun, Korea. Int J Remote Sens 25(11):2037–2052
Lee S, Ryu JH, Won J-S, Park HJ (2003) Determination and application of the weights for landslide susceptibility mapping using an artificial neural network. Eng Geol 71(3–4):289–302
Manserud RA, Leemans R (1992) Comparing global vegetation maps with the kappa statistics. Ecol Model 62:275–279
Michael-Leiba M, Baynes F, Scott G, Granger K (2003) Regional landslide risk to the Cairns community. Nat Hazards 30:233–249
Nagarajan R, Mukherjee A, Roy A, Khire MV (1998) Temporal remote sensing data and GIS application in landslide hazard zonation of part of Western ghat, India. Int J Remote Sens 19(4):573–585
Nath SK (2004) Seismic hazard mapping and microzonation in the Sikkim Himalaya through GIS integration of site effects and strong ground motion attributes. Nat Hazards 31:319–342
Ohlmacher GC, Davis JC (2003) Using multiple logistic regression and GIS technology to predict landslide hazard in northeast Kansas, USA. Eng Geol 69:331–343
Pieraccini M, Casagli N, Luzi G, Tarchi D, Mecatti D, Noferini L, Atzeni C (2003) Landslide monitoring by ground-based radar interferometry: a field test in Valdarno (Italy). Int J Remote Sens 24(6):1385–1391
Saha AK, Gupta RP, Arora MK (2002) GIS-based landslide hazard zonation in the Bhagirathi (Ganga) Valley, Himalayas. Int J Remote Sens 23(2):357–369
Sakellariou MG, Ferentinou MD (2001) GIS-based estimation of slope stability. Nat Hazards Rev 2(1):12–21
Van Westen CJ (1994) GIS in landslide hazard zonation: a review, with examples from the Andes of Colombia. In: Price M, Heywood I (eds) Mountain environments and geographic information system. Taylor and Francis, London pp 135–165
Van Westen CJ, Seijmonsbergen AC, Mantovani F (1999) Comparing landslide hazard maps. Nat Hazards 20:137–158
Van Westen CJ, Rengers N, Soeters R (2003) Use of geomorphological information in indirect landslide susceptibility assessment. Nat Hazards 30:399–419
Westen CJV, Getahun FL (2003) Analyzing the evolution of the Tessina landslide using aerial photographs and digital elevation models. Geomorphology 54:77–89
Yamaguchi Y, Tanaka S, Odajima T, Kamai T, Tsuchida S (2003) Detection of a landslide movement as geometric misregistration in image matching of SPOT HRV data of two different dates. Int J Remote Sens 24(18):3523–3534
Acknowledgments
The authors gratefully acknowledge the technical help provided by scientists, Regional Remote Sensing Service Center, Kharagpur in carrying out this study. First author of the paper is extremely thankful to Ministry of Human Resources Development, Government of India, New Delhi for sponsoring this research work. The authors would also like to thank the anonymous referees for useful suggestions, which led to a substantially improved manuscript.
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Pandey, A., Dabral, P.P., Chowdary, V.M. et al. Landslide Hazard Zonation using Remote Sensing and GIS: a case study of Dikrong river basin, Arunachal Pradesh, India. Environ Geol 54, 1517–1529 (2008). https://doi.org/10.1007/s00254-007-0933-1
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DOI: https://doi.org/10.1007/s00254-007-0933-1