Application of RS and GIS in disaster managment

Course Outline (1) AT09.98 Applied GIS and Remote Sensing for Disaster Mitigation Introduction 1.1 Overview of Natural Hazards 1.2 Applications of GIS and RS to Disaster Mitigation #1 Introduction Hazard Analysis 2.1 Seismic and Tsunami Hazard 2.2 Volcanic Hazard 2.3 Flood Hazard September, 2002 Fumio YAMAZAKI GIS Data and Inventory Development 3.1 GIS Data and Digital Maps 3.2 Data Acquisition for Built Environment yamazaki@ait.ac.th http://www.star.ait.ac.th/~yamazaki/ SEC/SCE and STAR/SAT, AIT Course Outline (2) Class Schedule 1) 2) 3) 4) 5) 6) September Lecture Introduction 11 September Lecture + Lab Seismic Hazard 18 September Lecture + Lab Tsunami and Volcanic Hazard 25 September Lecture + Lab October Lecture + Lab October Lecture + Lab 16 October Midterm Exam 7) 30 October Lecture + Lab Lecture on Flood by Dr Dutta 8) November Lecture + Lab 9) 13 November Lecture + Lab 10) 20 November Lecture + Lab 27 November Final Exam Damage Assessment 4.1 Damage Assessment Methodologies 4.2 Early Damage Assessment 4.3 Examples of Damage Assessment Tools on GIS 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 References Grading System Lecture Note (PPT files) on the Web http://www.star.ait.ac.th/~yamazaki/ 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, http://www.unisdr.org – Canada Centre for Remote Sensing: Fundamentals of Remote Sensing: http://www.ccrs.nrcan.gc.ca/ccrs/eduref/tutorial/tutore.html 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 Major natural catastrophes in the 20th century 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 10 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 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 1975-79 1980-84 1985-89 1990-94 1995-99 P er iod 11 http://www.adrc.or.jp/databook/Index_eng.htm 12 Amount of Damage in the World (Type, Period) Breakdown in continent WC-24 Amount of Damage(US $)(Period/Type)-World Total W C -2 < -1 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 1975-79 1980-84 1985-89 1990-94 1995-99 Perio d Losses due to natural disasters are increasing… Asia 13 88% People affected Africa Total= 781,673 A C -2 < -1 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% 14 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 > 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 15 16 The Gujarat, India EQ on January 26, 2001 Urban Area Rural Housing Plate Tectonics and Earthquakes 17 18 Tsunami Earthquake Hazard 19 20 Eruption of Mt Usu, Japan, March 2000 Tsunami Hazard 21 22 Japan Hit by Typhoon Pabuk, August 21, 2001 Active Volcanoes http://news.bbc.co.uk/hi/english/world/asia-pacific/newsid_1503000/1503880.stm 23 24 Tropical and Winter Storms Tropical Storm 25 26 Thai flood death toll rises to 164 August 15, 2001 http://news.bbc.co.uk/hi/english/world/asiapacific/newsid_1487000/1487394.stm 27 Major Floods 28 Map of torrential rain and seasonal focus Tornado 29 Tornado and Lightning Hazard 30 Lightning Exposure to Natural Hazards (1) Thailand vs Indonesia Thailand 31 Indonesia 32 Exposure to Natural Hazards (3) China vs India Exposure to Natural Hazards (2) Japan vs USA China USA Japan India 33 34 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) 35 Soft Tech Preparedness Response GIS and RS 36 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 37 Few Days Large Coarse 38 Landsat-7 ETM+ image after the Kocaeli, Turkey earthquake on 17th August, 1999 RGB= bands 7, 5, Image acquired on 18th August, 1999 39 40 http://www.globexplorer.com/disasterimages/index.html IKONOS Image of Bhuj, India on Feb 2, 2001 IKONOS Image Lower Manhattan, Post Attack 9.15.2001 Resolution: 1m (Panchromatic), 4m (Multi-Spectral) 41 42 http://www.spaceimaging.com/carterra/applications/disaster/bhuj.htm 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% 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 43 Damage Estimated Peak Ground Velocity 44 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 45 Landsat image of Mt Fugen, Japan, before and after the eruption 46 NOAA/AVHRR Images of Flood in Changjiang (Yangtze) River, China http://spaceboy.nasda.go.jp/lib/index_e.html 1.1 km resolution R, B: Visible band G: Near-infrared band http://aqua.cr.chiba-u.ac.jp/gdes/sid/ china98flood/yangtze/yangtze.html April 15, 1988 September 17, 1992 47 48 Hurricane Loss Estimation Model on GIS Area of stricken by forest fire, Mongolia JERS-1 OPS, RGB=231 http://www.nibs.org/hazus4b.htm http://spaceboy.nasda.go.jp/lib/index_e.html Wind Hazard Wind Effects Wind loading effects Building/facility response models Structure/Physical Damage HAZUS (hazard US) Risk Assessment and Loss Analysis 49 Oil outflow to Tokyo Bay on July 2, 1997 SPOT-2 (HX) image 50 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 http://www.eoc.nasda.go.jp/homepage.html Hazard Identification Risk Evaluation & Engineering Assessment Hazard data, RS, GIS After Oil Outflow July 3, 1997 Mitigation 51 52 [...]... Assessment ◆Building ◆BuildingInventory Inventory ◆Estimated ◆EstimatedDamage Damage ◆Information ◆Informationon on Family Family ◆Preparedness ◆Preparedness 45 Landsat image of Mt Fugen, Japan, before and after the eruption 46 NOAA/AVHRR Images of Flood in Changjiang (Yangtze) River, China http://spaceboy.nasda.go.jp/lib/index_e.html 1.1 km resolution R, B: Visible band G: Near-infrared band http://aqua.cr.chiba-u.ac.jp/gdes/sid/... Tokyo Bay on July 2, 1997 SPOT-2 (HX) image 50 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 http://www.eoc.nasda.go.jp/homepage.html Hazard Identification Risk Evaluation & Engineering Assessment Hazard data, RS, GIS After Oil Outflow July 3, 1997 Mitigation 51 52... http://aqua.cr.chiba-u.ac.jp/gdes/sid/ china98flood/yangtze/yangtze.html April 15, 1988 September 17, 1992 47 48 Hurricane Loss Estimation Model on GIS Area of stricken by forest fire, Mongolia JERS-1 OPS, RGB=231 http://www.nibs.org/hazus4b.htm http://spaceboy.nasda.go.jp/lib/index_e.html Wind Hazard Wind Effects Wind loading effects Building/facility response models Structure/Physical Damage HAZUS (hazard US) Risk Assessment and Loss...http://www.globexplorer.com/disasterimages/index.html IKONOS Image of Bhuj, India on Feb 2, 2001 IKONOS Image Lower Manhattan, Post Attack 9.15.2001 Resolution: 1m (Panchromatic), 4m (Multi-Spectral) 41 42 http://www.spaceimaging.com/carterra/applications /disaster/ bhuj.htm Damage Assessment using GIS Heavy Damage Classification 100% W ■ 80% Damage Ratio Building Inventory 90% RC ● 70% S ○ 60% LS ▲... 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 43 Damage Estimated Peak Ground Velocity 44 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 ... Hazards (3) China vs India Exposure to Natural Hazards (2) Japan vs USA China USA Japan India 33 34 Introduction GIS and RS in Disaster Management 1.2 Applications of GIS and RS to Disaster Mitigation... Storms Man-made Disasters (e.g., oil spills, terrors) 35 Soft Tech Preparedness Response GIS and RS 36 Remote Sensing Satellite Optical Sensor/SAR 700-900km Platforms and Sensors for RS Space Shuttle... 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