OTTAWA FLOODING 2019 APRIL/MAY PROCESSING OF SENTINEL-1 IMAGERY WITH PCI

GEOMATICA FOR HYDRAULIC RISK MANAGEMENTVera Costantini

▪ Sysdeco Italia can boast a twenty-years experience in GIS and Remote

Sensing fields.

▪ Sysdeco Italia represents the main companies that produce GIS & Remote

Sensing softwares and applications to optimize and manage human resources

as ; Airbus, ESRI, Extensis, PCI Geomatics, SII Imaging Services and Trimble

▪ FIELDS OF WORK

▪ Territory planning

▪ Environmental monitoring

▪ Landcover maps generation

▪ Urban plans

▪ Cadaster’s maps management

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Geomatica

The flooding

■ Heavy rains hit eastern Canada from mid-April to early May,

causing Ottawa River to overflow many times. The first

flooding occurred on April 26th.

■ More than 6 thousand people were urgently evacuated in the

single night between Saturday 27 April and Sunday 28 April in

Sainte-Marthe-sur-le-Lac, west of Montreal, after a dam

suddenly broke

The flooding

■ The most affected areas go from Ottawa to Montréal, along

the Ottawa river which represents the natural border between

the provinces of Québec and Ontario.

■ The devastating flooding destroyed and damaged several

homes along a huge stretch of the Ottawa River

Input Data

■ Sentinel-1 multitemporal images acquired in the following

dates

– September 4, 2018 (dry period)

– Aprile 26, 2019 (first flood)

– May 2, 2019

– May 14, 2019

■ All images were acquired in INTERFEROMETRIC WIDE SWATH

mode, spatial resolution= 10 meters

Input Data

September 4, 2018 (dry period)

Input Data

April 26, 2019

Input Data

May 2, 2019

Input Data

May 14, 2019

Input Data

First processing and emergency response

■ One of the PCI Geomatics company's headquarters is in

Ottawa, so our partners from PCI rushed to generate a map of

the first flood and made it public online to help with the

emergency response, using 3 Sentinel-1 images with a simple

analysis

Video

http://www.pcigeomatics.com/Ottawa_Floods_2019/

First processing and emergency response

■ One of the PCI Geomatics company's headquarters is in

Ottawa, so our partners from PCI rushed to generate a map of

the first flood and made it public online to help with the

emergency response, using 3 Sentinel-1 images with a simple

analysis

Video

http://www.pcigeomatics.com/Ottawa_Floods_2019/

Data processing: Orthorectification

■ In Geomatica OrthoEngine

Sentinel 1 images in

manifest.safe were imported

and converted to .pix

■ Images were orthorectified

using RPC Math Model

▪ Rational Functions math model is a simple math model that builds acorrelation between the pixels and their ground locations.

▪ RPC is more suitable than Toutin rigorous model in case GCPs are notwell distributed over the area and are in low number, as in this case.

▪ With RPC Model in Geomatica we can achieve a good accuracy withouttoo many GCPs and we can extract a high resolution high detailed DSM

Data processing: Orthorectification

Data merge and display

■ Data merge of the dry season dataset with April 26

and May 2 imagery

■ In RGB the flooded areas appear in BLUE

Intensity Change DetectionWorkflow

■ CCDINTEN measures the change in total radar backscattering

between a test image and a reference image by comparing

the sum of the intensities of the input channels.

■ Given two registered detected or single-look complex SAR

images, CCDINTEN determines the overlap area, normalizes

the intensity values based on the total span of intensity

values, and calculates the change (represented as a

percentile).

Intensity Change DetectionWorkflow

■ The output file will consist of the overlap area, and four channels

that describe:

1. the intensity value (or sum of intensities) of the input test

data

2. the intensity value (or sum of intensities) of the reference

data

3. the absolute value of the intensity ratio (written in decibels)

between the test and reference average intensity

4. the change, as percentiles, ranked from 0% (no change) to

100% (maximum change)

Intensity Change DetectionWorkflow

■ The change detection was applied between the after flooding images and the dry

season image

■ the Ranked change metric in percentile layer was further analyzed

Intensity Change DetectionWorkflow

■ Only changes above 95

percentile were exported in

polygon shapefiles with

algorithm EXPOLRAS

■ This algorithm converts a

raster layer into a vector layer

and allows to choose only

specific values

Intensity Change DetectionWorkflow

OB Classification and GIS Analysis

CLASSIFICATION

-River in the dry season image

-Water in the 3 floodedimages

GIS ANALYSIS (1)

-ERASE on the 3 changespolygon shapefiles with River layer

- CLIP of resulting shapefileswith water polygons for eachimnages

- Select polygons bigger than10 ha

GIS ANALYSIS (2)

•Changes shapefilesobtained are overalyedto evaluate the flloodingevolution

OB Classification and GIS Analysis

■ The RIVER has beenclassified with the tool Object Analyst in the dry season image in order to use it as a mask

■ In the after floodingimages all water areasare also classified to take into account onlychanges related to flooding (low backscattering)

Petrie Island

Change Aprile 26 - September

Results: Flooding Evolution

Petrie Island

Change May 2 - September

Results: Flooding Evolution

Petrie Island

Change May 14 – September

Results: Flooding Evolution

Cumberland

Change Aprile 26 - September

Results: Flooding Evolution

Cumberland

Change May 2- September

Results: Flooding Evolution

Petrie Island

Change 14 maggio -

September

Results: Flooding Evolution

Cumberland

Change May 14- September

Rigaud

Change April 26 - September

Results: Flooding Evolution

Results: Flooding Evolution

Rigaud

Change May 2 - September

Results: Flooding Evolution

Rigaud

Change May 14 - September

Results and Conclusions

■ the peak of the flood seems to have occurred on May 2nd

– Aprile 26th ~ 2500 ha flooded areas

– May 2nd ~ 4800 ha flooded areas

– May 14th ~ 2000 ha flooded areas

■ Unfortunately there are no images between May 2 and 14

■ The analysis allowed to evaluate extension and evolution of

flooding

■ Automation is partially implemented (Modeler) but all workflow

could be automatized through Python scripts

Thank you for your attention!