Remote Sensing Technology for Earthquake Damage Detection

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1 Workshop on Application of Remote Sensing to Disaster Response September 12, 2003, Irvine, CA, USA Remote Sensing Technology for Earthquake Damage Detection Fumio Yamazaki 1,2, Ken-ichi Kouchi 1, Masayuki Kohiyama 1, Miguel Estrada 1 and Masashi Matsuoka 2 1. Institute of Industrial Science, The University of Tokyo, Japan 2. Earthquake Disaster Mitigation Research Center, NIED, Japan 1

2 GIS and RS in Disaster Management Cycle of Disasters Pre-Event Event Post-Event Hard Tech. Mitigation Restoration/Reconstruction Soft Tech. Disaster Information Systems Preparedness Response using GIS and RS Urban Inventory Damage Map 2

3 Remote Sensing Satellite Optical Sensor/SAR km km Space Shuttle Airborne SAR Aerial Photography Aerial Television km 10-12km 0.3km 3

4 Contents Moderate to Low Resolution Satellites Landsat SAR Tools for Field Survey Airborne Remote Sensing High-Resolution Satellites IKONOS for the 2001 Gujarat Earthquake QuickBird for the 2003 Algeria Earthquake 4

90 mm 30 m 30 m Near IR 5 1.55-1.75 mm 30 m 30 m Mid IR 6 10.4-12.5 mm 60 m 120 m Far IR 7 2.08-2.

5 Lansat-7 ETM+ (launched April, 1999) Landsat-7 ETM+ Landsat-5 TM Band Wavelength Spatial resolution Spatial resolution mm 30 m 30 m Blue mm 30 m 30 m Green mm 30 m 30 m Red mm 30 m 30 m Near IR mm 30 m 30 m Mid IR mm 60 m 120 m Far IR mm 30 m 30 m Mid IF 8 (panchr omatic) mm 15 m - Altitude 705 km Repeat cycle 16 days Swath width 185km ETM+ : Enhanced Thematic Mapper Plus 5

6 Landsat TM Images of Kobe Area Aug. 17, 1994 (Before EQ) Jan. 24, 1995 (After EQ) 6

7 Spectral Characteristics in Damaged Areas 80% Typical Spectral Reflectance Curves Water (clear) Vegetation (green) 70% Dry bare soil (gray-brown) 60% BlueGreenRedNear IR Mid IR Mid IR Reflectance Reflectance 50% 40% 30% TM band 20% 10% 0% (µm) Wavelength (m m) Wave length of satellite optical bands and spectral reflectance of various surfaces Liquefied Area High [Visible~Mid-infrared] by Sand Soil Burned Area Low [Visible] by embers/ashes Damaged Area High [Visible~Mid-infrared] by Soil under Roof and/or Walls 7

8 Damage Distribution Estimated from Landsat Images Liquefied Area Burned Area Heavy Damage Slight Damage No Damage Pre-event: 08/17/94 Post-event: 01/24/95 Actual damage 8 data

9 SAR: Synthetic Aperture Radar Active Microwave Sensor Emitting microwave signals, then receiving their reflection from objects on earth s surface All Weather, Day and Nighttime ERS/SAR Wave Length: 5.7cm (C-band VV) Resolution: 30m Recurrent Period: 35 days 9

Estimation of Damage Areas due to 1995 Kobe EQ using ERS/SAR Phase Front B Sat-1 Sat-2 Coherence High Low High Phase Front z 1 z 2 weak weak Coherence High Low High strong strong 1 0.

10 Estimation of Damage Areas due to 1995 Kobe EQ using ERS/SAR Phase Front B Sat-1 Sat-2 Coherence High Low High Phase Front z 1 z 2 weak weak Coherence High Low High strong strong Severe damage area Very severe damage area Filtering Window: 21 x 21 Calculation Window: 13 x 13 95/05-94/10 95/05-94/06 95/05-93/08 95/05-92/11 Correlation Coefficient of Intensity Images Difference of Backscattering Coefficient [db] ERS (1995/5/ /6/3) Red: Very severe damage area Yellow: Severe damage area 10

11 Use of GPS and RS Data for Field Survey Joint Survey by MCEER/EDM after the 1999 Kocaeli, Turkey EQ Landsat image as a map GPS and mobile PC 11

12 Automated damage detection of airborne video images using edge and color information Edge Intensity Kobe EQ, 1995 Turkey EQ, 1999 Color 12

13 Multi Level Slice method Selection of training data MLC method Selection of training data C-3 N-3 C-1 G-1 N-1 N-2 C-2 Hue, Saturation, Brightness, Edge intensity & its variance Percentage (%) Building C-1 C-2 C-3 N-1 N-2 N-3 Maximum Setting threshold values Principal component analysis likelihood classifier Hue (0-360 degree) Automated extraction 13

14 Automated damage detection from aerial Photo Red: collapsed Yellow: damaged Red: Extracted Field survey and visual inspection Automated Detection 14 (Revised criteria in spatial filtering )

(Resolution: 1.0m) Everyday (Resolution: 2.

15 High-Resolution Satellite: IKONOS Resolution: 1m (Panchromatic), 4m (Multi-Spectral) Recurrence Time: 11days Retake Time: 3days (Resolution: 1.0m) Everyday (Resolution: 2.1m) Launched on September 25, 1999 Cost: $70 / km 2 IKONOS Image of Bhuj, India on Feb. 2,

IKONOS Image and Field Survey of Bhuj after the

Stones fell down from the parapet of the palace

16 IKONOS Image and Field Survey of Bhuj after the 2001 Gujarat, India Earthquake A part of IKONOS satellite image of Bhuj city after the Gujarat earthquake. Stones fell down from the parapet of the palace building and they are seen in the IKONOS image as well as 16in the ground photographs.

17 Boumerdes 17

18 Damages 2,276 people killed 11,000 people injured

QuickBird QuickBird launched on October 18, 2001.

The system will collect 61cm class panchromatic and 2.

19 QuickBird QuickBird launched on October 18, The highest resolution commercial satellite in operation. The system will collect 61cm class panchromatic and 2.5m multispectral stereoscopic data. 19

20 Specification of QuickBird Products Spatial and Spectral Resolution Panchromatic Multispectral Product Type Pixel Resolution Black & White 450 to 900-nm Blue 450 to 520-nm Green 520 to 600-nm Red 630 to 690- nm Near IR 760 to 900- nm Panchromatic 60-cm (2-ft) or 70-cm (2.3-ft) Multispectral 2.4-m (8-ft) or 2.8-m (9.2-ft) Natural Color 60-cm (2-ft) or 70-cm (2.3-ft) Color Infrared 60-cm (2-ft) or 70-cm (2.3-ft) Pan sharpened (4-band) 60-cm (2-ft) or 70-cm (2.3-ft) 20

21 QuickBird True Color Image (1) ~5 km Pre-event image 2002/04/ days before the earthquake ~5 km 21

22 QuickBird True Color Image (2) ~5 km Post-event days after the earthquake ~5 km 22

23 QuickBird True Color Image (3) ~5 km Post-event days after the earthquake ~5 km 23

24 Acquisition Parameters of QuickBird Images for Boumerdes, Algeria Pre-event Post-event 1 Post-event-2 Date 2002/04/ /05/ /06/18 (from 21 May, 2003 Earthquake) 394 days before 2 days after 28 days after Time 10:38:03 10:36:03 10:25:18 Sun azimuth ( o ) Sun elevation ( o ) Satellite azimuth ( o ) Satellite elevation ( o ) In track view angle ( o ) Cross track view angle ( o ) Off nadir view angle ( o ) Mean collected GSD (Multi/Pan) (m) 2.529/ / /

25 Image Enhancement (Pan-sharpening) R G B Encode BLUE I H S I R H G S B Manipulate Decode IHS/RGB encoding and decoding CYAN Display and analysis Panchromatic band is used for Intensity for resolution improvement. Mutispectrum bands for H and S. GREEN Intensity: total brightness of a color Hue: dominant wavelength of light contributing a color Saturation: the purity of color relative to gray I YELLOW MAGENTA BLACK WHITE GREEN CYAN BLUE WHITE RED MAGENTA RED YELLOW BLACK H S RGB based color cube IHS based color hexcone 25

26 Pansharpened Image True color image ~ 2.4m Panchromatic Bands 3, 2 and 1 (RGB) image ~ 0.6m True color pansharpened image ~ 0.6m 26

27 Boumerdes on May 23,

28 Building Collapse C B A D Pre-event 2002/04/22 Post-event 2003/05/23 28

29 South Campus, Boumerdes University C B A D Photo by Dr. K. Meguro on 22 July, 2003 C 29

30 Level of damages detected by QuickBird E F H G Pre-event 2002/04/22 Post-event 2003/05/23 30

31 Level of damages observed in field survey F E Damage to short columns Collapse of First Story Photo by Dr. K. Meguro on 22 July,

32 Level of damages observed in field survey H G Fall off infill blocks Collapse of the first story. This damage is difficult to identify from the vertical image Photo by Dr. K. Meguro on 22 July,

33 Building Damage and Cleaning Works (1) 2002/04/ /05/ /06/

34 Building Damage and Cleaning Works (2) 2002/04/ /05/ /06/ This building does not look so severely damaged, but it was demolished. 34

35 Classification of damage to buildings of reinforced concrete used in the European Macroseismic Scale (EMS) Grade 1: Negligible to slight damage (no structural damage, slight non-structural damage) Fine cracks in plaster over frame members or in walls at the base. Fine cracks in partitions and infills. Grade 2: Moderate damage (slight structural damage, moderate non-structural damage) Cracks in columns and beams of frames and in structural walls. Cracks in partition and infill walls; fall of brittle cladding and plaster. Falling mortar from the joints of wall panels. Grade 3: Substantial to heavy damage (moderate structural damage, heavy non-structural damage) Cracks in columns and beam column joints of frames at the base and at joints of coupled walls. Spalling of concrete cover, buckling of reinforced rods. Large cracks in partition and infill walls, failure of individual infill panels. 35

36 Classification of damage to buildings of reinforced concrete used in the European Macroseismic Scale (EMS) Grade 4: Very heavy damage (heavy structural damage, very heavy non-structural damage) Large cracks in structural elements with compression failure of concrete and fracture of rebars; bond failure of beam reinforced bars; tilting of columns. Collapse of a few columns or of a single upper floor. Grade 5: Destruction (very heavy structural damage) Collapse of ground floor or parts (e. g. wings) of buildings. Grade 5 and Grade 4 (and in some case, Grade 3) can be detected from QuickBird Images. 36

37 Flow of the damage classification Judgment by using the 23May image Grade 5 Grade 4 Grade 3 Grade 2,1 Unclear Confirmed by using the pre-event image Judged by using the pre-event image Grade 5 Grade 4 Grade 3 Grade 2,1 37

38 Visual damage detection using Post-event 1 image Green: Grades 1 and 2 Yellow: Grades 3 Orange: Grades 4 Red: Grade 5 38

39 City blocks used for the calculation of damage ratio and determined damage grade for each buildings Buildings Total: 3,446 Grade 5: 71 Grade 4: 54 Grade 3:

40 Number of buildings classified as Grades 3, 4, and 時期で確認, 検証 Judged by using preand post-event images Judged by using preand post-event images <Difficult to judge only by post-image> 2 時期で判読 ( 不明分 ) 1 時期 Judged by using postevent image only 0 G rade5 G rade4 G rade3 40

41 Damage ratio for Grade 5 in each block 41

42 Damage ratio for Grades 3, 4 and 5 in each block 42

43 2002/04/22 Tents for Refugees 2003/05/ /06/ Photo by Dr. K. Meguro on 22 July,

44 Distribution of tents in each block 284 tents on May 23, ,150 tents on June 18,

45 Conclusions (1) Remote sensing is quite a promising tool for earthquake disaster management. - Moderate resolution satellites (optical & SAR) for capturing macroscopic damage distribution - Airborne images for quick reconnaissance - High resolution satellites for capturing damages of buildings and infrastructures 45

46 Conclusions (2) Visual damage detection was carried out using QuickBird images for the 2003 Algeria earthquake. - Building damages of Grades 4 and 5in EMS can be identified. - Minor damages may be difficult to identify from vertical images. - GIS maps for building damage and tents were produced from the QuickBird images. 46

Urban Classification of Metro Manila for Seismic Risk Assessment using Satellite Images

Urban Classification of Metro Manila for Seismic Risk Assessment using Satellite Images Fumio YAMAZAKI/ yamazaki@edm.bosai.go.jp Hajime MITOMI/ mitomi@edm.bosai.go.jp Yalkun YUSUF/ yalkun@edm.bosai.go.jp