f. c. dai and c. f. lee a spatiotemporal probabilistic modelling of storm-induced shallow landslide...
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F. C. DAI AND C. F. LEE
A Spatiotemporal Probabilistic Modelling of Storm-Induced Shallow Landslide Using Aerial Photographs and Logistic
Regression
報告者:蔡雨澄指導教授:李錫堤報告日期: 2010/12/30
Varnes (1984) defined natural hazard as the probability of occurrence of a potentially damaging phenomenon
within a specified period of time and within a given area.
Mapping or delineating areas prone to landsliding is essential for land-use activities and management decision making in hilly or mountainous regions.
Study Area
Study Area
Mean annual rainfall for the study area over the period 1961–91 is in the range of 2000 to 2400 mm (Lam and Leung,1994).
Linear Model
i i iy x e +
Logistic regression
1 1 2 2 3 3
1( 1| )
11
( 1| ) 11 0
1( 1| ) 0
1
ii i i i i i
i i i
i i i
P y x x x xe
P y x
P y x
…
Logistic regression
1 1 2 2
1 1 2 2
1 1 2 2
1( 1| )
1 1
1( 0 | ) 1 ( 1| )
1
( 1| )Odds( 1)
( 0 | ) 1
ln Odds( 1) ln1
logit( )
i
i i
i
i
i i i i i
i i i i
i ii
i i
i i i i
i i
eP y x x x
e e
P y x P y xe
P y x Py e
P y x P
Py x x
P
Y x x
…
…
…
1 11 2 21
1 12 2 22
1 13 2 23
1 ( ....)
2 ( ....)
3 ( ....)
11
11
01
10
1
x x
x x
x x
Pe
Pe
Pe
Data
aerial photographs
The date taken on
spatial scales Landslide occurred
1st 1991/12/30 1:8000
2nd 1992/11/11 1:16000 103
3rd 1993/12/03 1:10000 132
cumulative maximum in any 24 h period
Data1992/7/18 1993/11/4~5
Data
DEM (2m×2m)Slope gradient ( <15,15-20,25-30… 50 ) (degree)
Slope aspect ( 8+1(flat) )
Elevation ( <50,50-100,100-150… 500 ) (m)
Slope shape ( LL, LX, LV, XL, XX, XV, VL, VX, VV )
Data
Lithology
1:5000 geological maps
Data
Land cover
(a) developed land
(b) grassed land
(c) shrub–grassed land
(d) forest–shrubbed land
(e) forested land
Data
Rainfall data 1992/7/18
1993/11/4~5
+
1990/9/11
1992/6/13~14
1990/9/11
1992/6/13~14
Data
number Value of ln(P/(1-P) )
Landslide grid cells 11955 1
Stable grid cells 12000 0
3000+3000+3000+3000
Modelling result
Statistical Package of Social Sciences (SPSS)
Modelling result
Error matrix
Observed data
occurred
Not occurre
d
Predicted result
occurred
10704 1813
Not occurre
d1251 10187
Accuracy 89.5% 84.9 %
Model Application
10-year 20-year
50-year 100-year
DISCUSSION AND CONCLUSIONS
For each landslide cell, the maximum rolling 24 h rainfall was designated as the dynamic variable.
The rainfall return periods conventionally used were assessed using data from only one site and should be applied only to that site.
The antecedent rainfall may have some influence on the
occurrence of landslides, but this effect is not accounted for in the predictive model as stated.
DISCUSSION AND CONCLUSIONS
Land-use planners may differ in the level of risk they can afford or accept. This model allows them to choose their own level of increased risk.
This model has been useful in identifying areas likely to have landsliding in a way that has not been possible previously.
End
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