Application of RS and GIS in disaster managment

Course Outline (1)

AT09.98

Applied GIS and Remote Sensing
for Disaster Mitigation

1. Introduction
1.1 Overview of Natural Hazards
1.2 Applications of GIS and RS to Disaster Mitigation

#1 Introduction

2. Hazard Analysis
2.1 Seismic and Tsunami Hazard
2.2 Volcanic Hazard
2.3 Flood Hazard

4 September, 2002

Fumio YAMAZAKI

3. GIS Data and Inventory Development
3.1 GIS Data and Digital Maps
3.2 Data Acquisition for Built Environment


/>SEC/SCE and STAR/SAT, AIT.

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Course Outline (2)

Class Schedule
1)
2)
3)
4)
5)
6)

4 September Lecture
Introduction
11 September Lecture + Lab Seismic Hazard
18 September Lecture + Lab Tsunami and Volcanic Hazard
25 September Lecture + Lab
2 October Lecture + Lab
9 October Lecture + Lab
16 October Midterm Exam
7) 30 October Lecture + Lab Lecture on Flood by Dr. Dutta
8) 6 November Lecture + Lab
9) 13 November Lecture + Lab
10) 20 November Lecture + Lab
27 November Final Exam

4. Damage Assessment
4.1 Damage Assessment Methodologies
4.2 Early Damage Assessment
4.3 Examples of Damage Assessment Tools on GIS

5. Damage Detection and Disaster Monitoring
5.1 Satellite Remote Sensing for Damage Detection
5.2 Airborne Remote Sensing for Damage Detection
5.3 GPS and Real-time Monitoring

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References

Grading System

Lecture Note (PPT files) on the Web
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The Final grade will be computed according to the
following weight distribution:
Mid-Term Exam 35%
Final Exam 35%
Laboratory 30%

Related reference books and materials
– P.A. Longley, et al.: Geographical Information Systems and Science,
John Wiley & Sons, Inc., 2001.
– T. M. Lillesand and R. W. Kiefer: Remote Sensing and Image
Interpretation, Fourth Edition, John Wiley & Sons, 2000.
–

United Nations Initiative towards Earthquake Safe Cities: Risk

Assessment Tool for Diagnosis of Urban Areas against Seismic
Disasters, CD-ROM, .

–

Canada Centre for Remote Sensing: Fundamentals of Remote
Sensing: />6

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Hazard, Risk and Disaster
Hazard: Circumstance of the
occurrence of an event. Probabilistic

Risk

Hazard

Event: A specific natural phenomenon
(e.g., earthquake, flood), an accident or an
incident (e.g., traffic accident, terror )
Deterministic

Event
System to
be affected
Loss (effect)

Vulnerability; Probabilistic
Loss/effect due to an event

Deterministic/Probabilistic

Risk: Probability of occurring loss to a system Probabilistic
Disaster: An event which causes significant losses. Deterministic7

Probabilistic Modeling of Load and Resistance
Probability Density Function

Closed-book examinations are given both in the midterm and finals.

Load: L
(hazard)

Resistance: R
(vulnerability)
Probability of Failure
Pf = P(L>R)
l : a specific value of L

l
pR(l) : the probability such that R< l

L
R
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Major natural catastrophes in the 20th century

1. Introduction

Munich Re Group:World of Natural Hazards, CD-ROM.

1.1 Overview of Natural Hazards
Earthquakes, Tsunamis

Geological Hazards

Volcanic Eruptions
Tropical / Winter Storms
Floods, Droughts

Hydro-Meteorological
Hazards

Thunder Storms, Tornados

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Natural Disasters in the World (Type, Period)
Source: Center for Research on the Epidemiology of Disasters, Louvain Catholic University
(CRED)

Disaster: more than 10 people killed or more than 100 people affected
WC-21 <1975-1999>
Number of Disasters(Period/Type)-World Total
1,400

1,200
Wind storm

Number of Disasters

1,000

Costly Natural Catastrophes in the

20th

Wild fire
Wave/surge
Volcano

800

Slide
Insect infes-tation
600

Flood
Extreme temp
Earthquake

400

Century

Drought

200

0
1975-79

1980-84

1985-89

1990-94

1995-99

P er iod

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Amount of Damage in the World (Type,
Period)

Breakdown
in continent

WC-24 <1975-1999>
Amount of Damage(US $)(Period/Type)-World Total

W C -2 6 < 1 9 7 5 -1 9 9 9 >
Nu mb er of P eople Killed-W orld T ota l
Europe
3%

Total=1,552,985

Oceania
0%

Africa
37%

x US $ 1,000
450,000
400,000
Wind storm

D a m a g e ( M illio n U S $ )

350,000

Asia
51%

Wild fire

Americas
9%

Wave/surge

300,000

Volcano
250,000

Slide
Insect infes-tation

200,000

Flood
150,000

People killed

Africa

Americas

Asia

Europe

Oceania

W C -27 < 1975-1999>
T otal Nu mber of A ffected P eople-W orld T otal

Extreme temp
Earthquake

100,000

Total=3,772,452,863

Europe

Oceania

Africa

1%

1%

6%

Americas
4%

Drought

50,000
0
1975-79

1980-84

1985-89

1990-94

1995-99

Perio d

Losses due to natural disasters are increasing…

Asia

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88%

People affected
Africa

Total= 781,673

A C -2 < 1 9 7 5 -1 9 9 9 >
Nu mb er of P eople Killed-A sia T ota l
0%

Earthquake

Wind storm

48%

32%

Earthquake
Extreme temp
Flood
Insect infestation
Slide

0%

Oceania

Wave/surge

Wave/surge

Volcano

Europe

Volcano

Wild fire

1%

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Asia

Fault Rupture in
the 1999 Chi-Chi,
Taiwan EQ

Drought

Drought

Americas

Flood
Slide

Wild fire

Extreme temp

15%

2%

2%

Wind storm

Insect infes-tation

0%

0%

A C -4 < 1 9 7 5 -1 9 9 9 >
A mou n t of Da ma g e(US $ )-A sia T ota l
Wave/surge
0%

Wild fire
7%

Wind storm
16%

Drought

Earthquake

1%

44%

V olcano

Earthquake
Extreme temp

0%

Flood

Slide

0%

Insect infes-tation
0%

Drought

Insect infestation
Slide
V olcano
Flood

Extreme temp

31%

1%

Total= 447 x 109 US$

Wave/surge
Wild fire
Wind storm

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The Gujarat, India EQ on January 26, 2001

Urban Area

Rural Housing

Plate Tectonics and Earthquakes

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Tsunami

Earthquake Hazard

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Eruption of
Mt. Usu, Japan,
March 2000

Tsunami Hazard

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Japan Hit by Typhoon Pabuk, August 21, 2001

Active Volcanoes

/>
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Tropical and Winter Storms
Tropical Storm

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Thai flood death toll rises to 164
August 15, 2001

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Major
Floods

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Map of torrential rain and seasonal focus

Tornado

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Tornado and Lightning Hazard

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Lightning

Exposure to Natural Hazards
(1) Thailand vs Indonesia
Thailand

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Indonesia

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Exposure to Natural Hazards
(3) China vs India

Exposure to Natural Hazards
(2) Japan vs USA

China

USA

Japan

India

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1. Introduction

GIS and RS in Disaster Management

1.2 Applications of GIS and RS to Disaster Mitigation

Cycle of Disasters

Earthquakes, Tsunamis

Pre-Event Æ Event Æ Post-Event
★

Volcanic Eruptions
Floods

Hard Tech.

Tropical Storms

Mitigation

Restoration/Reconstruction

Disaster Information Systems

Tornados, Thunder Storms
Man-made Disasters (e.g., oil spills, terrors)
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Soft Tech.

Preparedness Response

GIS and RS
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Remote Sensing
Satellite
Optical Sensor/SAR
700-900km

Platforms and Sensors for RS

Space Shuttle
Airborne SAR
185-575km

Aerial Photography

Objectives: Land cover, Urban modeling, Damage detection
Data Type: Spatial Information (2D, 3D) Æ GIS
Weather and Day Light: Optical Sensor, SAR

Action
Prompt

Area
Resolution
Small
High

10-12km

・Aerial Television
・Aerial Photography
・Airborne SAR, LIDAR

1.2-3.5km

Aerial Television

・Satellite SAR, Opt. Sensor

0.3km

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Few Days

Large

Coarse

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Landsat-7 ETM+ image after the Kocaeli, Turkey
earthquake on 17th August, 1999
RGB= bands 7, 5, 2

Image acquired on
18th August, 1999

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/>
IKONOS Image of Bhuj, India on Feb. 2, 2001

IKONOS Image
Lower Manhattan,
Post Attack
9.15.2001

Resolution: 1m (Panchromatic), 4m (Multi-Spectral)
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/>
Damage Assessment using GIS
Heavy

Damage Classification

100%
W ■

80%

Damage Ratio

Building
Inventory

90%

RC ●

70%

S ○

60%

LS ▲

50%

40%
30%

Shake Map Development for
the 1995 Kobe EQ based on
Building Damage Data

20%
10%
0%
0

20

40

60

80

100

120

140

160

180

PGV (cm/s)

Geological
Data

Seismic Hazard

Vulnerability
PGV (cm/s)
150 120 - 150
90 - 120
60 - 90
30 - 60
- 30
No Building

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Damage

Estimated Peak
Ground Velocity

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Development of building inventory on GIS is
most costly in seismic risk assessment.
Remote sensing is expected to serve this task…

Microscopic GIS Database for Risk Assessment

◆Building
◆BuildingInventory
Inventory
◆Estimated
◆EstimatedDamage
Damage
◆Information
◆Informationon
on Family
Family
◆Preparedness
◆Preparedness

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Landsat image of Mt. Fugen, Japan,
before and after the eruption

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NOAA/AVHRR
Images of Flood
in Changjiang
(Yangtze) River,
China

/>
1.1 km resolution
R, B: Visible band

G: Near-infrared band
/>china98flood/yangtze/yangtze.html

April 15, 1988

September 17, 1992

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Hurricane Loss Estimation Model on GIS

Area of stricken by forest fire, Mongolia
JERS-1 OPS, RGB=231

/>
/>
Wind Hazard
Wind Effects
Wind loading effects
Building/facility response models

Structure/Physical
Damage
HAZUS (hazard US)

Risk Assessment
and Loss Analysis

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Oil outflow to Tokyo
Bay on July 2, 1997
SPOT-2 (HX) image

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Steps in assessing and mitigating losses
due to natural disasters
Inventory
Collection
Field Survey,
RS, GIS

Before Oil Outflow
August 21, 1996

Natural Hazards
Impact Assessment
GIS

/>
Hazard
Identification

Risk Evaluation &
Engineering Assessment

Hazard data,

RS, GIS

After Oil Outflow
July 3, 1997

Mitigation
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