f. c. dai and c. f. lee

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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