15arspc submission 52

8/8/2019 15arspc Submission 52

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3.2 Resolution

The 250m resolution MODIS Rapid Response satellite imagery was suitable forSES usage during the north-west flood operation. The whole area of operationtotalled more than 100,000 square kilometres or 10 million hectares (Figure 5)which makes it unfeasible to monitor using airborne remote sensing. Areassurrounding towns identified by SES were however flown using the LPMAADS40 to record specific flood impacts at high resolution.

3.3 Latency

Emergency decision-makers can accept a longer lead time for imagery deliveryat an inland flood event compared to coastal floods. In the recent event north ofLightning Ridge, flood waters were observed to progress 2-5km per day. Underthese conditions a daily update is acceptable for operational mapping

requirements. Weather conditions in particular cloud cover can vary deliverytimes for optical sensors.

Delivery options of large image files by external hard drive, FTP or web servicesneed to be considered in the latency requirements. In the case of remote townssuch as Goodooga, connectivity infrastructure is a factor.

Figure 5 SES Area Of Operation (shown in blue) for the December 2009 May 2010

Flood Operations.


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4. Airborne Remote Sensing

As mentioned earlier, areas surrounding towns identified by SES were flownusing the LPMA ADS40 to record specific flood impacts at high resolution. In2007 Land and Property Information (LPI), replaced its film-based aerialphotography operations with digital imagery technology. The LPI DigitalImagery Acquisition System (DIAS) comprises of a Leica ADS40 Aerial DigitalSensor and additional imagery processing capabilities (Figure 6). By vastlyimproving the efficiency of aerial imagery processing, LPI can now provide TheNSW State Emergency Services with faster and more effective products andservices. Overall Imagery forms part of the Spatial Data Infrastructure (SDI)Program which comprises a suite of initiatives to ensure NSWs key spatialdatasets are current, comprehensive, accurate and readily available for thebenefit of government and other geospatial users.

LPI has refined its imagery workflow in order to respond to emergency eventssuch as floods and bushfires. The elapsed time for capture, processing anddistribution of imagery has been dramatically reduced from weeks to days.Depending on accuracy requirements, image data can also be processedwithout use of ground-control or reference stations.

The recent flood demonstrated the efficiency of the system with 22 individualimagery products were produced in 26 working days. Colour Infrared (CIR)images as well as true colour images were created and supplied to SES.Applications include orthophoto production, feature extraction (e.g. flood zones)and remote sensing as shown in Figure 7. Further details of such analysis canbe found in Woodbury et al (2010).


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Figure 6 Second Generation ADS40 Sensor and Multi-spectral data acquisition systemconfiguration (Leica Geosystems 2007).


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Figure 7 Paroo Overflow Flood area. Left: False Colour (CIR). Middle: True Colour(RGB). Right: Water extent extracted from ADS40 image and converted to vectorpolygon.


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5. Satellite Remote Sensing

Requests were sent to several overseas space agencies in order to use theItalian COSMO-SkyMed, German TerraSAR-X, Chinese HY, Japanese ALOS,European Envisat and Canadian Radarsat-2 satellites to monitor the flood fromspace as a research activity. While it is only possible to briefly discuss hereresults from the COSMO-SkyMed radar satellite constellation (ASI 2010), fulldetails of the study will be published in a separate paper.

5.1 The COSMO-SkyMed radar satellite constellation

The COSMO-SkyMed constellation consists of 4 medium-size satellites (threealready in orbit and the 4th to be launched by the end of 2010), each oneequipped with an identical microwave high-resolution synthetic aperture radar(SAR) operating in X-band, having ~600 km single side access ground area,orbiting in a sun-synchronous orbit at ~620 km height over the Earth surface,with the capability to change attitude in order to acquire images at both rightand left side of the satellite ground track (nominal acquisition is right lookingmode). The SAR sensors can also be configure to image at a wide range ofresolutions from sub-metre, 1 m, 3 m, 15 m, 30 m, and 100 m as shown inFigure 8. Because of the left and right looking flexibility as well as theconfigurable imaging modes, the full CSK constellation is accessible to respondto emergency events 24/7 as indicated in Figure 9.

The CSK constellation is the first of its kind and has the following uniquefeatures,

Cloud and haze penetration; High-resolution (1m for civilian applications); Large amount of daily acquired images; Satellites worldwide accessibility; All weather and Day/Night acquisition capabilities; Very short interval between the acceptance of the user request acquisition

and the release of the remote sensing product (System Response Time); High image quality (e.g. spatial and radiometric resolution);

Both intensity difference and interferometric coherence were used to produceflood extent maps from multi-temporal COSMO-SkyMed (CSK) radar images innear real-time.


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Figure 8 CSK imaging modes (e-GEOS 2010).

Figure 9 CSK constellation revisit time (e-GEOS 2010).

5.2 Intensity DifferenceThe intensity values in a radar intensity image are proportional to thebackscattering coefficient of the Earths surface. The backscattering coefficientis dependent on ground surface roughness, the moisture level or water contentof the area, and the incident angle and the wavelength of the radar signal.Water surfaces are generally smooth at radar wavelengths and can be regardedas specular reflectors which yield small backscatter. The surrounding terrain isassumed to be rough at radar wavelengths which exhibits diffuse scattering withmoderate backscatter. Hence, water is regarded as low intensity areas in SARimages, whereas the surrounding terrain corresponds to brighter intensities(Henderson 1995).


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Therefore, thresholding is the traditional method of detecting flooding in non-forested areas as in the north-west of NSW (Brivio et al 2002). Intensities belowthe threshold are regarded as flood or open water, whereas pixels withintensities above the threshold are regarded as dry land. The threshold will

depend on the contrast between the land and water classes, and generallyneeds to be set for each SAR scene. Furthermore, ripples on the water surfaceinduced by wind or waves will increase the backscattering from the floodedareas as shown in Figures 10 and 11. Hence, the contrast will decrease withincreasing wind speed.

In order to enhance thresholding based analysis and detect fresh flooding area,intensity difference was calculated between the two radar images taken on 20and 21 March 2010 for the area between New Angledool and Lightning Ridgeas shown in Figure 12. However, it is not straight forward to delineate the water-dry land boundary from intensity difference.

5.3 Coherence analysis

Coherence in radar interferometry measures the similarity or the complexcorrelation coefficient between the same imaged pixels in the two SAR imagesof the interferometric pair. Higher coherence values indicate more stable phaseproperties and vice versa. Before the coherence between the interferometricpair data can be calculated, the master and slave SAR images are coregisteredat sub-pixel accuracy.

It has been shown in earlier studies that flood detection can be enhanced in alltypes of terrain, included urban areas, by combining multitemporal intensityanalysis with interferometric coherence from ERS-1/2 tandem data (Dellepianeet al 2000; Stabel and Loffler 2003).

Taking full advantage of the CSK constellation and the one day difference of theoverpass time between satellites, interferometric coherence between 20 and 21March 2010 images was produced as shown in Figure 13 in near real-time by

UNSW to initiate research into this area. Flood extent has been clearly indicatedas dark/ low coherence area. Feature extraction was conducted on thecoherence image and the extracted flood extent was converted to vectorpolygon given in Figure 14 (in blue), overlaid on the radar image which in turnwas overlaid on a Landsat image.


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Figure 10 CSK image acquired on 20 March 2010.

Figure 11 CSK image acquired on 21 March 2010.


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Figure 12 SAR intensity difference between 20 and 21 March images.

Figure 13 Interferometric coherence between 20 and 21 March images.


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products, using both recent and historical products, within few hours(approximately 3 h) from the most recent acquisition.

Table 1 Statistics of CSK near real-time analysis.

5.5 Validation of satellite remote sensing result with aerial and SES maps

In order to assess the quality of flood map derived from satellite imagery (givenin Figure 15 (a)), it has been compared with the ADS40 colour infrared image(Figure 15 (b)) and the SES map (Figure 15 (c)). Figure 15 (a) is a zoom-in ofFigure 14 around New Angledool in order to match the ADS40 coverage. Figure15 (c) is the flood boundary mapped by the SES helicopter equipped with aGPS receiver. It can be seen that the three agree well with each other whilemore details are available from the aerial and satellite results.

(a)


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Figure 15 Validation of satellite remote sensing result with aerial and SES map.


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6. Concluding remarks

There is value in freely available public domain imagery. The well documented

and consistent supply schedule of MODIS made it suitable for mapping inlandfloods.

The ADS40 aerial photography imagery flown by LPMA was used for capturingdetail and complemented the broad coverage satellite imagery. Thecommunication channels between the SES State Operations Centre MappingUnit and the LPMA Air Services Unit was refined and flight plans were taskedby the SES Planning cell specifically for flood peaks and areas of interest suchas the Bourke levee.

The comparison of satellite derived flood map with aerial image and SES mapdemonstrated the three products agree well with each other while more detailsare available from the aerial and satellite results. Radar sensors and SARsourced during the event would be better suited to coastal flood events wherethe capabilities can be tested in environments of greater cloud cover.

Clear governance and coordinated tasking of satellites is essential foremergency services which are often responding to concurrent incidents.Engagement with the newly formed Imagery Working Group of the NSW Spatial

Council would be recommended.

Acknowledgements

Several members of the Geodesy and Earth Observation Systems Group,UNSW, participated in the near real-time mapping of the flood events. We thankMr Kubic Zhang and Dr Michael Chang for radar and GIS analyses of CSKsatellite data respectively.

The SES map showing the New Angledool flood area was obtained by SESmember and air observer James Able during helicopter reconnaissance.

COSMO-SkyMed TM Product ASI [2010] processed under license from ASI Agenzia Spaziale Italiana. e-GEOS and Thales Australia are gratefullyacknowledged for supporting the near real-time flood mapping.


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References

ASI, 2010, https://cosmo-skymed-ao.asi.it/, accessed on 12 August 2010.

BOM 2010, The Australian Bureau of Meteorology New South Wales in summer2009-10: Ex-tropical cyclones bring rain to NSW Monday, 1 March 2010 -Seasonal Climate Summary for New South Wales - Product codeIDCKGC25R0.

Brivio, P. A., Colombo, R., Maggi, M., and Tomasoni, R., 2002, Integration ofremote sensing data and GIS for accurate mapping of flooded areas. Int. J.Remote Sensing, 23(3):429-441.

Cossu, R., Schoepfer, E., Bally, P., Fusco, L., 2009, Near real-time SAR-basedprocessing to support flood monitoring, J Real-Time Image Proc (2009) 4:205 218, DOI 10.1007/s11554-009-0114-4.

Dellepiane, S., Bo, G., Monni, S., and Buck, C., 2000, Improvements in floodmonitoring by means of interferometric coherence. In Posa, F. and Guerriero,L., editors, SAR image analysis, modeling and techniques III, volume 4173 ofProceedings of SPIE, pages 219-229.

e-GEOS, 2010, www.e-geos.it , accessed on 12 August 2010.

Henderson, F. M., 1995, Environmental factors and the detection of opensurface water areas with X-band radar imagery. Int. J. Remote Sensing,16(13):2423-2437.

Leica Geosystems, 2007, ADS40 Documentation, Volume 2, TechnicalReference Manual. Version 2.12-86, (Heerbrugg: Leica Geosystems AG).

Stabel, E. and Lffler, E., 2003, Optimised mapping of flood extent andfloodplain structures by radar EO-methods. In Proceedings of FRINGE 2003,Frascati, Italy.

Woodbury, P., Hosken, J., and Herrick, D., 2010, NSW Land and PropertyManagement Authority: Rapid Response Imagery, the 15th AustralasianRemote Sensing and Photogrammetry Conference, Alice Springs, Australia, 13-17 September.

15arspc submission 52

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