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Workshop on the Application of Remote Sensing Technologies to Disaster Response

Rapid Damage Mapping for Post-Earthquake Building Damage Assessment

Keiko Saito, Robin Spence The Martin Centre for Architectural and Urban Studies

University of Cambridge

Workshop on the Application of Remote Sensing Technologies to Disaster ResponseSeptember 12 2003


12 September 2003 Rapid Damage Mapping for post-Earthquake Building Damage Assessment 2

Objective

Develop methodologies to create a post-earthquake rapid building damage map using high-resolution optical satellite images by

combining

• Visual Interpretation• Automatic remote sensing techniques



• Pilot project Using remote sensing for post disaster damage assessment”, funded by EPSRC, UK.

• Case study carried out in Gujarat, India



Questions

• Main focus on post earthquake building damage assessment• According to a study, “70-80% success rate using semi-automatic

techniques”• Can visual interpretation do better? • Can a method that combines both achieve better results? • What kind of semi-automatic methods can be used to assess

damages to buildings?• What kind of damage maps will be useful for search and rescue or

during the reconstruction phase?



Satellite images acquired for pilot project

1m B&W

1m B&W

Image type

IKONOS2

IKONOS2

Satellite

OXBhuj

OOAhmedabad

PostPrePlace name



Sample IKONOS image

(left) Full view of IKONOS 1m panchromatic satellite image of west Ahmedabad, Gujarat, India, taken on 27 January 2001, a day after the earthquake. Covers121km2.

Zoom in of the image



Which is better?

Panchromatic image(from Reuters web page)Multispectral image



Three visual interpretation experiments using the satellite images

Experiment 1 - Comparison study using ground photos and post-earthquake IKONOS satellite image of Bhuj

Experiment 2 - Comparison study using pre- and post-earthquake images of Ahmedabad

Experiment 3 - Area based damage assessment study



Experiment 1 Comparison study using ground photos and post earthquake satellite image of Bhuj

Methodology

Compare ground photos of a damaged building and satellite image showing the same building, to see what type and level of damage can be identified in an IKONOS image



Image interpretation

Chris Going (Cambridge Architectural Research)

Michael Markus (University of Karlsruhe)

Keiko Saito (The Martin centre, University of Cambridge)



Location of buildings recorded using handheld GPS single measurement (red dots).

Ground photos of 24 buildings taken approximately a week after the earthquake by Michael Markus.

IKONOS 1m panchromatic Date & Time: 2/2/2001, 6:05am Processing Level: Geometrically CorrectedPositional accuracy: 50m Map Projection: UTM 42 NDatum: WGS84Pixel Size: resampled to 1mSun angle: 45o

Area size: 100km2

Supplied by Space Imaging Middle East.

Data sources



Evaluating building damage using ground photos

Parapet and wall have fallen off

Middle part has collapsed

Cracksin the wall

Balcony walls have fallen off

Roof collapse

Water tank has fallen off

Heap of rubble



Comparison with satellite image

Observations•Balcony walls fallen off•Roof collapse•Partial collapse•Big pile of rubble•Roof and wall fallen off•Cracks in the wall•Damage to water tank

Building no.43Visible•Displacement of thewater tank

Not Visible•Shadow is hiding the rubble•Partial collapse in the middle section not clear•Damage to walls not visible



Create Database



ResultsTypes of visible damages

1. Totally collapsed buildings.



However, if the building is located in a built up area, it is difficult to identify

even if the building had totally collapsed.



2. Tilted buildings



3. Displacement of Building Appendages



4. Split in the middle of a high-rise building



5. Overturned buildings



6. Debris



Effect of shadows

Shadows can hide information



Shadows could be used to estimate building height



Non-visible damage

Lower Storey collapse



Damages on low rise buildings

Low rise buildings tend to have small area size



Damages on buildings located in built up areas

Possible, but difficult without the help of ground photos.



Summary

Not visible

Damages in built up areas, even totally collapsed (difficult without pre-damage image or ground photo)Damages hidden in the shadowsDamages on walls (cracks etc)Damages on low rise buildingsStorey collapse

Visible

Totally collapsed single buildingsHeavily tilted buildingsWater tank displacementSplit in the middle of a high risebuildingTurned over buildingsDebris Shadows (shape and height)

High rise buildings Low rise buildings, built up areas



Experiment 2 – Comparison study using pre and post earthquake IKONOS images

Methodology

Comparison between the pre- and post- image

Grid-by-grid damage assessment of West-Ahmedabad

Pre-EQ image Post-EQ image



Possible to find collapsed and severely damaged buildings



Collapsed buildings



Out of the 12 collapsed buildings found,10 had collapsed, 2 had not collapsed. Took 15 hours to complete assessment



Experiment 3 – Area based damage assessment study

Methodology

Carry out a grid by grid damage assessment only using the post-earthquake image

Assign a damage level toeach grid based on a pre-defined classification

Result of area-based damage assessment



Damage classification methodology

Transparent0No buildings/ water/

outside study area

Dark Brown475-100%

Pink350-75%

Gray225-50%

Yellow10-25%

Fill colourAssigned damage level

Percentage of collapsed buildings (D4 or D5 EMS

scale) within a grid



Result of visual damage interpretation



Comparison with ground survey result

EPC ground survey resultVisual interpretation

“General damage pattern agrees with the ground survey”



Discrepancy

153126Total

3425212401-1

Number of gridsDiscrepancy

General tendency to underestimate – need for training



Analysis of the discrepancy

Resampling method to be blamed?

Original EPC damage map Resampled EPC damage map



North part of Walled city has many low-rise buildings in a densely built-up area

Grids with 3 (yellow) and 2 (light blue) levels of discrepancy. The map is the original EPC damage survey



Better results in the south, where there are many modern middle to high rise buildings Grids that match EPC survey results



Implications

Resolution of IKONOS images are good enough to be used for visualinterpretation

-Develop an easy-to-use visual damage assessment manual- How can the accuracy of the assessment be improved?

Limitations include;-shadows-built up areas, small buildings -weather (cloud cover)-availability of pre-event imagery



Next Phase

• Concentrate on the use of post-event images only.

• Visual interpretation – continue to accumulate experience using other data sets, modify area-based assessment classification method

• Experiment on semi-automatic remote sensing techniques – stereo viewing using pre- and post-event imagery, extraction of building footprints using edge detection techniques, unsupervised classification, supervised classification, texture analysis and rectification in the horizontal and vertical planes.



Elements in the process of creating a rapid damage map

1. Obtaining information on the building stock e.g. footprints, function of the building, height, area size, material of building.

2. Assessment of the damage to each building, e.g. total collapse, tilted, lower storey collapse.

3. Creating the damage map, e.g. area-based damage mapping, building-by-building damage mapping, mapping of the roads.



Quick Bird images of Bourmerdes23rd May 03 18th June 03

Collapsed buildingsTilted buildings

Area-based damage assessment carried out on the images from two different dates. The two images look quite different due to the debris been cleared.



Observed change between the May and June images

23rd May 18th June

Additional damage was observed on the image from June. Note the difference in the look angle as well.



Comparison with the IKONOS images of Gujarat cities

Ahmedabad, 29th January 01 Walled city-Bhuj, 2nd February 01 Bourmerdes, 18th June 03

•Different morphology of the three cites •Difference in building density – less obstruction by the shadows in Bourmerdes image•Façade visible in Ahmedabad image – look angle is 61 degrees – ideal for visual interpretation, not ideal for change detection



Multispectral images

•Spatial resolution not good enough to be used as it is for visual interpretation of damage to buildings•The colours can help understand the nature of the object – in this case, tents. •Other use – NDVI (to exclude vegetation), material of buildings



GPSUsing high-resolution satellite images as a map

• “Satellite image map” created using standard GIS software.• Used to reach sites with collapsed buildings.• Especially useful in areas where readily made maps are not available.

Location of sites with

potential collapsed buildings

Upload/ Download positional data with your GPS

Coordinates of the

building sites can be displayed. (in this case, UTM)

Major Road names



Other potentially useful tool

Stereo imagery

• No case studies yet (using satellite imagery).

• Expensive



Obstacles of using optical satellite images?

• Cloud cover, Smoke, Shadows, Tall buildings, Built up areas • In such case, other means of detecting damage should be considered.

• However, the majority of the major earthquakes in the last few years were, or could have been, covered by cloud free satellite images, e.g. Kobe, Northridge, Kocaeli, Seattle, Gujarat, Miyagi and Bourmerdes.

high probability of cloud free coverage?



Conclusion

• The use of high-resolution optical satellite images for damage mapping is feasible. Should be further pursued.

• Research collaboration for rapid acquisition of satellite imageswould be useful.

• Acquisition of ground truth data is time consuming. Negotiations can be delicate. Could be assisted by international associations such as EERI. Agreements offering reciprocal benefits to the provider of

ground truth information likely to be needed.

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