Characterization of Croatian Minefields SPRINT - … image processing 4. Data fusion –first level...

Characterization of Croatian Minefields using Satellite Radar Image Time Series Analysis.

SPRINT project results

N. Milisavljevic – D. Closson

V. Lacroix (presenter)

Royal Military Academy, Belgium

5th Mine Action Technology Workshop, Pretoria; June 20, 2014

Outline

1. SPRINT project

2. AOI & image database

3. Radar image processing

4. Data fusion – first level

5. Data fusion – second level

6. Examples

7. Validation

8. Conclusions


SPRINT project

AcronymSPaceborne Radar INterferometric Techniques for Humanitarian Demining Land Release

SPRINT aims at differentiating human-induced effects/activities affecting the Earth surface from the natural ones by exploiting combinations of amplitude and phase changes of space-borne radar signals

The goal: to provide a new layer of information towards determining whether mine suspected areas are hazardous indeed or not


AOI & image database

Source: M. Bajić, Operations with Advanced Intelligence Decision Support System for Suspected Area Asessmentin Croatia and Bosnia and Herzegovina, Workshop “Merging Mine Action Technology and Methodology”,GICHD, Geneva; 6-8.09.2010


AOI

Source: M. Bajić, Operations with Advanced Intelligence Decision Support System for Suspected Area Asessmentin Croatia and Bosnia and Herzegovina, Workshop “Merging Mine Action Technology and Methodology”,GICHD, Geneva; 6-8.09.2010


AOI

Suspected hazardous and confirmed hazardous areas shown in hatched and crosshatched red polygons (data from 2009) - 4km x 4km grid.


Radar image database

GOSPIC


Radar image processing

Source: Sarmap, SBAS tutorial, 2013.


42 ERS + 40 Envisat (1992‐2010)

Source: ESA


Amplitude & coherence

Monday 03 Jun 13

Amplitude T0Phase T0

Amplitude T1Phase T1

Coherence T0-T1

Black = surface changes

Minefield Buffer





Data fusion – first level

• Four data sources: ERS coherence data stack, ERS amplitude data stack, Envisat coherence data stack and Envisat amplitude data stack

• Firstly, data within each of these stacks are combined and classified using multi‐temporal signature analysis, where pixels with similar signatures are grouped together

• Thus, at the output of this level, we have unsupervised classification result for each of the data sources:

– ERS coherence

– ERS amplitude

– Envisat coherence

– Envisat amplitude

• These classification results are inputs for the second level


All vs. selected data

Acquisition dates for all ERS data, selected ERS, all Envisat data and selected Envisat data


Data fusion – second level

Combination strategies

ERS intensityERS coherence Envisat intensityEnvisat coherence

coherence combination intensity combination

coherence and intensity combination

Envisat combinationERS combination

ERS coherence Envisat coherenceERS intensity Envisat intensity

ERS and Envisat combination

all data used:

1

2

selected data used:

3

4


Example

• Visual observation:

– Suspected minefield contains mainly grass, crops and urban part

– Buffer around it contains trees, grass, crops and an urban part


ERS coherence unsupervised classification results

• If all coherence data are used: • If only selected coherence data are used:


ERS intensity unsupervised classification results

• If all intensity data are used: • If only selected intensity data are used:


Envisat coherence unsupervised classification results

• If all coherence data are used: • If only selected coherence data are used:


Envisat intensity unsupervised classification results

• If all intensity data are used: • If only selected intensity data are used:


Recall of level 2 fusion

Combination strategies

ERS intensityERS coherence Envisat intensityEnvisat coherence

coherence combination intensity combination

coherence and intensity combination

Envisat combinationERS combination

ERS coherence Envisat coherenceERS intensity Envisat intensity

ERS and Envisat combination

all data used:

1

2

selected data used:

3

4


ERS coherence classification

IntensityCoherence

Low High

Low

High

ERS intensity classification

Envisat intensity classification

Envisat coherence classification

An example of the summary: Combination coherence and intensity strategy

(using all data)

1


ERS intensity classification

Envisat intensity classification

ERS coherence classification

Envisat coherence classification

ERSEnvisat

L ML MH H

L

ML

MH

H

IntensityCoherence

Low High

Low L ML

High MH H

the tables show the color codes used for intermediate results (upper table)and for the final output (lower table)

Combination ERS and Envisat strategy (using selected data)

4


Validation (1/4)

Example of the fortification objects, remnants of war marked with arrows, triangles or circles visible on the aerialimage that was acquired in April 2009 at the MSA community of Gospić (© Milan Bajić)


Validation (2/4)


orientation point of the mine recordreconstructed position of the minefieldbunker linecover for infantry and artilleryabandoned roaddestroyed house

trenchpassage under the railwaynatural objects arranged for fiery actiondrywallbridges and gangwaysheliportshallow draftsabandoned surfaces

safe roadsurface in use

house in useroad in usetruck with bees

Validation (3/4)


Brown= reconstructed minefield positionGreen = surface usedPurple = pathway usedRed = various levels of danger (dark is the highest)

ERS using all data

Monday 03 Jun 13

Validation (4/4)

ERS using selected data

Monday 03 Jun 13

Envisat using all data

Monday 03 Jun 13

Envisat using selected data

Monday 03 Jun 13

Conclusions

SPRINT showed the technical feasibility of processing stacks ofradar images to produce useful information to the MSA reduction issue.

The example chosen - Gospic region - is relevant because CROMACanalyzed this area in great detail in 2008-2010. It was thereforechallenging to provide new and relevant information to them.

The validation of the work carried out by Prof Milan Bajic allows us tobuild up future projects towards an operational tool for SGR (Sentinel-1data collection).

In the near future, Sentinel-1 SAR (C-band) images will be provided forfree by the EU-ESA owing to the Copernicus project. The resolution willbe better than ERS and Envisat (5 m vs 20m); the revisit time 11 days(and then 6 days when 2 satellites) vs 35 days.

Free software such as POLSARPRO already allow the users toprocess such type of data.


Characterization of Croatian Minefields SPRINT - … image processing 4. Data fusion –first level...

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