Landslide Hazard Zonation using Remote Sensing and GIS: a case study of Dikrong river basin, Arunachal Pradesh, India

被引:53
作者
Pandey, Ashish [1 ]
Dabral, P. P. [2 ]
Chowdary, V. M. [3 ]
Yadav, N. K. [2 ]
机构
[1] Indian Inst Technol, Water Resources Dev & Management Dept, Roorkee 247667, Uttar Pradesh, India
[2] NERIST, Dept Agr Engn, Arunachal Pradesh 791109, India
[3] Kyoto Univ, CSEAS, Kyoto, Japan
来源
ENVIRONMENTAL GEOLOGY | 2008年 / 54卷 / 07期
关键词
GIS; landslide; relief; remote sensing; slope;
D O I
10.1007/s00254-007-0933-1
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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.
引用
收藏
页码:1517 / 1529
页数:13
相关论文
共 33 条
[11]   The geology of Dunedin, New Zealand, and the management of geological hazards [J].
Glassey, P ;
Barrell, D ;
Forsyth, J ;
Macleod, R .
QUATERNARY INTERNATIONAL, 2003, 103 :23-40
[12]   Monitoring landslides from optical remotely sensed imagery:: the case history of Tessina landslide, Italy [J].
Hervás, J ;
Barredo, JI ;
Rosin, PL ;
Pasuto, A ;
Mantovani, F ;
Silvano, S .
GEOMORPHOLOGY, 2003, 54 (1-2) :63-75
[13]  
Kienzle SW, 1996, IAHS-AISH P, P183
[14]   Major risk from rapid, large-volume landslides in Europe (EU Project RUNOUT) [J].
Kilburn, CRJ ;
Pasuto, A .
GEOMORPHOLOGY, 2003, 54 (1-2) :3-9
[15]  
Kumar KV, 1993, ASIA PAC REMOTE SENS, V6, P63
[16]  
KUNTE SV, 1983, ARUNACHAL PRADESH MI, V43, P125
[17]   Embedding a geographic information system in a decision support system for landslide hazard monitoring [J].
Lazzari, M ;
Salvaneschi, P .
NATURAL HAZARDS, 1999, 20 (2-3) :185-195
[18]   Probabilistic landslide hazard mapping using GIS and remote sensing data at Boun, Korea [J].
Lee, S ;
Choi, J ;
Min, K .
INTERNATIONAL JOURNAL OF REMOTE SENSING, 2004, 25 (11) :2037-2052
[19]   Determination and application of the weights for landslide susceptibility mapping using an artificial neural network [J].
Lee, S ;
Ryu, JH ;
Won, JS ;
Park, HJ .
ENGINEERING GEOLOGY, 2004, 71 (3-4) :289-302
[20]   Regional landslide risk to the Cairns community [J].
Michael-Leiba, M ;
Baynes, F ;
Scott, G ;
Granger, K .
NATURAL HAZARDS, 2003, 30 (02) :233-249