The Utilization of GIS for the The Utilization of GIS for the Measure against Slope Failure Measure against Slope Failure

Disaster in Urban Area Disaster in Urban Area

Akiyuki KAWASAKI, and Satoru SADOHARAAkiyuki KAWASAKI, and Satoru SADOHARAYokohama National University, Yokohama, JapanYokohama National University, Yokohama, Japan

BackgroundBackground

⇒ It’s difficult for a municipality to afford it.

・ Many people and much budget are required to accomplish this kind of project (so far).

⇒ Municipality needs a measure against slope failure disaster

・ Many slope failure disasters happen in Yokohama

(the ultimate goal)

・ To createcreate a “Real-time evaluation system against slope failure disasters” by by existing data and documentsexisting data and documents in municipal government..

⇒ 　 It will reduce the damage of slope failure disasters wiwith a small budget and people.th a small budget and people.

ObjectiveObjective

AA．． SpecifyingSpecifying the “steep slope” and “the predicted damage a the “steep slope” and “the predicted damage area” automatically rea” automatically by DEM and LandUse data using GIS using GIS raster raster & vector analysis& vector analysis..

B. B. Predicting the dangerous area for slope failure the dangerous area for slope failure by by rainfall data at the timerainfall data at the time using GIS spatial analysis. using GIS spatial analysis.

For that objective, three For that objective, three methodologies were carrying forward methodologies were carrying forward in this study.in this study.

(Presented last year)

(Presented last year)

C. Evaluate the possibility of slope failure disaster, using Inspection Record and Multivariate Analysis.

((Presented this yearthis year))

被被被災災災危危危険険険区区区域域域ののの抽抽抽出出出 崖崖崖区区区域域域ののの抽抽抽出出出

i.最大値

j.最小値

h. GRID

d.TIN e.TIN ポリゴン

p.被災 危険区域

k.高さを算出

f.急傾斜地 ポリゴン

l.高さ GRID

m.崖ポリゴン

（属性：区域・高さ）

（属性：斜面方向・高さ）

a.土地利用

元元元デデデーーータタタ c.自然的土地 利用ポリゴン

b.ＤＥＭ

g.崖区域 ポリゴン

e.斜面方向 ポリゴン ‘

m. 崖ポイント ‘ o.斜面方向の ライン作成

n.バッファ の発生

Steep Slope Predicted-damaged area

Software: ArcInfo Workstation & ArcView

LandUseLandUse

DEMDEM

Steep Steep slopeslope

PredictedPredicted

damaged damaged areaarea

AA．．Methodology of Methodology of specifyingspecifying the “steep the “steep slope” and “the predicted damage area” slope” and “the predicted damage area” automatically.automatically.

(Review)

This is helpful to predict which building and house would be damaged by collapse. Only two data is required.

AA．．Methodology of Methodology of specifyingspecifying the “steep the “steep slope” and “the predicted damage area” slope” and “the predicted damage area” automaticallyautomatically..

(Review)

These are the specified dangerous steep slopes⇒We verified that it covers more than 90% of (existing)

“ Municipality’s dangerous areas”

AA．．Methodology of Methodology of specifyingspecifying the “steep the “steep slope” and “the predicted damage area” slope” and “the predicted damage area” automaticallyautomatically..

(Review)

Predicted damage area is calculated by the height of the slope. It means that higher steep slope has longer damaged area.

AA．．Methodology of Methodology of specifyingspecifying the “steep the “steep slope” and “the predicted damage area” slope” and “the predicted damage area” automaticallyautomatically..

(Review)

Predicted damage area is calculated by the height of the slope. It means that higher steep slope has longer damaged area.

B. Methodology of pB. Methodology of predicting the dangerous the dangerous area for slope failure by area for slope failure by rainfall data at the rainfall data at the timetime. .

(Review)

Dangerous Area at the time by Rainfall data （ August/22th/2001 ）

2.00 am 6.00 am 10.00 am 2.00 pm

1 hour rainfall (mm)

Y = ‐0.174X + 28.4

(“Raster Calculation” )

AA．． Dangerous steep slope and predicted Dangerous steep slope and predicted damage area are specified.damage area are specified.

B. Relationship between collapse and rainfall are analyzed.

C. C. Relationship between collapse and the Relationship between collapse and the slope’s factorsslope’s factors..

⇒⇒　　 Provoking causeProvoking cause 《《 Triggered factorTriggered factor》》 for collapsefor collapse

⇒⇒　　 Primary causePrimary cause 《《 Basic factorBasic factor》》 for collapsefor collapse

For the objective, three methodologies For the objective, three methodologies were carrying forward in this study.were carrying forward in this study.

⇒　 Automatic specification.

Evaluate the primary cause (basic factor), using Inspection Report and Multivariate Analysis; Quantification Theory TypeⅡ.

Easy to collapse

Difficult to collapse

C. C. Relationship between collapse Relationship between collapse and the slope’s factors and the slope’s factors . .

(Provided by City of Yokohama, Bureau of Building)

Inspection Report for a Steep Slope

- Height

- Slope

- Overhang

- Surface thickness

-Leaking water

- Vegetation

- Looseness, relaxation

- Surface water

- Drainage on the top

10 items are quantified quantified

by report’s category.

Collapse Collapse

recordrecord

Multivariate Analysis; Quantification Theory TypeⅡ

This model clarify qualityquality “explanatory variable “explanatory variable (item)”(item)” affecting qualityquality “objective variable”“objective variable” ,as a quantityquantity weighted coefficient.

““explanatory variable (item)”explanatory variable (item)” : 10 items on inspection report

““objective variable”objective variable” : Collapse record (collapsed or not)

Example of analysis result

0.0

0.5

1.0

1.5

Heig

ht

Slo

pe

Su

rface

Leakin

gw

ate

r

Loose

ness

rela

xati

on

Vag

itati

on

Su

rface W

ate

r(a

bove)

Su

rface W

ate

r(s

lop

e)

Dra

inag

e o

n t

op

Over

Han

g

Pattern 1 Pattern 2 Pattern 4Range

Factor’s effectiveness for collapse

パターン１

Surface

Roam

Pattern 1

slump

パターン１

Surface

Roam

Pattern 1パターン１

Surface

Roam

Pattern 1

slump

パターン２

Surface

Roam

Pattern 2

Plat form Plat form layerlayer

slide

パターン２

Surface

Roam

Pattern 2パターン２パターン２

Surface

Roam

Pattern 2

Plat form Plat form layerlayer

slide

パターン４

Surface

Pattern 4

Plat form Plat form layerlayer

slide

パターン４

Surface

Pattern 4

Plat form Plat form layerlayer

パターン４

Surface

Pattern 4パターン４

Surface

Pattern 4

Plat form Plat form layerlayer

slide

Slope Failure Pattern in Yokohama

(Categorized by “Yokohama city slope failure committee”)(Categorized by “Yokohama city slope failure committee”)

Item CategoryNum. ofsample

Weightdcoefficient

Rangepartial

correlationcoefficient

10m - 24 - 0.3785m - 10m 38 0.086

- 5m 12 0.48560° - 23 0.272

40° - 60° 44 - 0.107- 40° 7 - 0.21950cm - 8 0.644- 50cm 66 - 0.078Exist 4 1.296No 70 - 0.074

Exist 8 1.207No 66 - 0.146

Bare ground 17 - 0.346tree 5 0.151

grass/ field 11 0.278tree grass/ field＋ 41 0.050

Exist 35 0.190No 39 - 0.171

Exist 42 0.160No 32 - 0.209

Bad/ Uncompleted 54 0.013Good 20 - 0.036Exist 7 0.018No 67 - 0.002

0.224

0.125

0.005

0.171

0.255

0.311

0.159

0.134

0.863

0.491

0.020

0.049

0.369

0.361

0.624

0.722

1.353

1.370

Height of Slope(Hm)

Slope(degree)

Over Hang

Thicknessof Surface

Leaking Water

LoosenessRelaxation

Vegitation

Surface Water(above)

Surface Water(slope)

Drainage on top

0.158

0.018

Results of Quantification Theory TypeⅡ

0.0

0.1

0.2

0.3

0.4

崩壊あり 崩壊なし

-2.0 - 1.5 - 1.0 - 0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0

Sample score

Rela

tive f

requency

Frequency distribution of distinction result

Actual

collapsed

No collapse

Discriminate Value – 0.06

(Accuracy 85.1%)

Pattern 1

Surface

Roam

Surface

Roam

Sample score : Total of weighted coefficient of a slope

0.086+(-0.107)+(-0.078)+1.296+……=0.677

パターン１

Surface

Roam

Pattern 1

slump

パターン１

Surface

Roam

Pattern 1パターン１

Surface

Roam

Pattern 1

slump

パターン２

Surface

Roam

Pattern 2

Plat form Plat form layerlayer

slide

パターン２

Surface

Roam

Pattern 2パターン２パターン２

Surface

Roam

Pattern 2

Plat form Plat form layerlayer

slide

パターン４

Surface

Pattern 4

Plat form Plat form layerlayer

slide

パターン４

Surface

Pattern 4

Plat form Plat form layerlayer

パターン４

Surface

Pattern 4パターン４

Surface

Pattern 4

Plat form Plat form layerlayer

slide

Slope Failure Pattern in Yokohama

(Categorized by “Yokohama city slope failure committee”)(Categorized by “Yokohama city slope failure committee”)

Discriminate Value – 0.06 (Accuracy 85.1%)

Discriminate Value – 0.01

(Accuracy 84.2%)

Discriminate Value 0.01

(Accuracy 82.1%)

Sample score

Rel

ativ

e fr

eque

ncy

Actual collapsed

No collapse

0.0

0.1

0.2

0.3

0.4 崩 壊 有 り 崩 壊 な し

- 2.0 - 1.5 - 1.0 - 0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5

Sample score

Rel

ativ

e fr

eque

ncy

Actual collapsed

No collapse

0.0

0.1

0.2

0.3

0.4 崩 壊 有 り 崩 壊 な し

- 2.0 - 1.5 - 1.0 - 0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5

Frequency distribution of distinction result

0

0.1

0.2

0.3

0.4

0.5 崩 壊 有 り 崩 壊 なし

- 2.0 - 1.5 - 1.0 - 0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5

Sample score

Rel

ativ

e fr

eque

ncy

Actual collapsed

0

0.1

0.2

0.3

0.4

0.5 崩 壊 有 り 崩 壊 なし

- 2.0 - 1.5 - 1.0 - 0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5

Sample score

Rel

ativ

e fr

eque

ncy

Actual collapsed

Sample score

Rel

ativ

e fr

eque

ncy

Actual collapsed

No collapse

0.0

0.1

0.2

0.3

0.4 崩 壊 有 り 崩 壊 な し

- 2.0 - 1.5 - 1.0 - 0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5

Sample score

Rel

ativ

e fr

eque

ncy

Actual collapsed

No collapse

0.0

0.1

0.2

0.3

0.4 崩 壊 有 り 崩 壊 な し

- 2.0 - 1.5 - 1.0 - 0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5

- Factors and the category’s effectiveness for collapse were clarified quantitatively.

- Accuracy of distinction for collapse by sample score was over 80%

⇒⇒ 　　 Municipality’s Inspection report woks adequMunicipality’s Inspection report woks adequately to evaluate the possibility of collapse.ately to evaluate the possibility of collapse.

C. C. Relationship between collapse Relationship between collapse and the slope’s factors and the slope’s factors . .

Conclusion 1.Conclusion 1.

⇒ ⇒ By combining these three, a “Real-time evaluation systeBy combining these three, a “Real-time evaluation system against slope failure disasters” would be completed m against slope failure disasters” would be completed

AA．． Dangerous steep slope and predicted Dangerous steep slope and predicted damage area are specified.damage area are specified.

B. Relationship between collapse and rainfall are analyzed.

C. Relationship between collapse and the slope’s factors.

⇒⇒　　 Provoking causeProvoking cause 《《 Triggered factorTriggered factor》》 for collapsefor collapse

⇒⇒　　 Primary causePrimary cause 《《 Basic factorBasic factor》》 for collapsefor collapse

⇒　 Automatic specification.

Specify dangeroushouse

Rain Fall

InspectionResults

Records ofSlope Failure

Specify thedangerous area

１． Specifying the Dangerous Area by Rain Fall Data

Possibility ofSlope Failure

InspectionResults

２． Possibility of Slope Failure

InspectionResults

Records ofSlope Failure

PredictedDamage Area

３． Specifying the Predicted Damage Area

Future worksFuture works

Conclusion 2.Conclusion 2.

All the methodology in this study was from the All the methodology in this study was from the existing data and document in municipal existing data and document in municipal government.government.⇒⇒　　 Original data and document are existed separately in eaOriginal data and document are existed separately in each bureau and section. In this study, all the data was digitized ch bureau and section. In this study, all the data was digitized and connected.and connected.

““e-government” and “e-municipal government” are declared ie-government” and “e-municipal government” are declared in Japan.n Japan.

⇒⇒　　 This is an example to show the efficiency of digitizing aThis is an example to show the efficiency of digitizing and utilizing the existing data and document in municipal govend utilizing the existing data and document in municipal government. rnment.

Akiyuki KAWASAKI, and Satoru SADOHARAAkiyuki KAWASAKI, and Satoru SADOHARAYokohama National University, Yokohama National University,

Yokohama, JapanYokohama, JapanE-mail: akiyuki@arc.ynu.ac.jpE-mail: akiyuki@arc.ynu.ac.jp

sato610@arc.ynu.ac.jpsato610@arc.ynu.ac.jp

AcknowledgementAcknowledgement

- Risk management office & Building Bureau, City of Yokohama

- Prof. Midorikawa & Prof. Okimura, Yokohama city slope failure committee