Analysis  of  Landslides  in  Morretes・Brazil  2011  

Tokyo-­‐Japan,  August  7th  2012    

Brazil  –  Eng.  Fábio  Sato  -­‐  SIMEPAR  

Case  Study:  Morretes  2011-­‐03-­‐11  Small  tourisNc  and  rural  city  in  Paraná  state,  Brazil.  

Has   recently   suffered   flooding   and   several  landslides  in  March  11th  2011,  caused  by  3  days  of  conNnuous  rainfall.  

Civil  Defense  Sta.s.cs  Damaged  houses:  2.720  Homeless  people:  967  Removed  people:  8.453  

Deaths:  04  Affected  people:  23.828  Affected  ciNes:  7    

Case  Study:  Event  LocaNon  

Case  Study:  Pictures  of  the  Event  

Case  Study  Data

Before  Event  (Master  data)    

2  years  before    

ObservaNon  date:  2009/03/25  Processing  level:  1.1  

Scene  shi[:  -­‐4  Mode:  FBS  

Scene  id:  ALPSRP168626680  

A?er  Event  (Master  data)    

2  weeks  a[er  

ObservaNon  date:  2011/03/31  Processing  level:  1.1  

Scene  shi[:  -­‐4  Mode:  FBS  

Scene  id:  ALPSRP275986680  

Analysis  Methodology

1.  Amplitude  image  analysis  1.  Image  Difference  (HH  &  VV)  2.  NSDI  (HH  &  VV)  

2.  Polarimetric  Analysis:  1.  Pauli  Image  2.  Freeman  decomposiNon  3.  H/A/alpha  decomposiNon  

 

Interferometry  and  phase  coherence  analysis  could  not  be  conducted

Analysis  Flowchart  1/3 Master  Level  1.1  data

Slave  Level  1.1  data

Polsar  Pro

•  Geocode  T3  Matrix  ASF  MapReady

3x3  Complex  Coherency  T3  

files  

•  Extract  MulNlook  Image  (4x4  window)  

Geocoded  T3  files

Analysis:  Flowchart  2/3

Geocoded  T3  files

Polsar  Pro Freeman3  decomposiNon  H  /  A  /  Alpha  decomposiNon

Freeman  RGB  Composite

H/A/Alpha  RGB  

Composite

Analysis:  Flowchart  3/3

Master  Level  1.1  data

Slave  Level  1.1  data

ASF  MapReady

STRM  DEM

GeoTiff  files

ArcGIS

Difference  Image NDSI  Image

•  Geocode  •  Terrain  CorrecNon  with  DEM  

Results:　Backscafer  HH  Images

Before A?er

Results:　Composite  Images  (R:  B,  G:  A,  B:  A)

HH VV

Results:　Normalized  Diference  of  Sigma0  (NDSI)

HH VV

Results:　Difference  Images

HH VV

Results:　Pauli  Images

Before A?er

Results:　Freeman  DecomposiNon

Before A?er

Results:　H/A/Alpha  RGB  Composite

Before A?er

Results:　H/Alpha  ClassificaNon Before A?er

H

alpha

Surface  Scafering

Quasi  DeterminisNc

Bragg  Surface

Conclusions

•  Landslides  could  be  idenNfied  on  all  generated  images/products  

•  In  this  case,  befer  results  where  provided  by  Difference  and  NDSI  images  

•  The  analysis  of  polarimetric  products  are  more  difficult  to  interpret    

•  Although  it  was  possible  to  detect  landslides,  it  is  difficult  to  produce  a  final  

threshold  image  of  the  landslides  regions  from  SAR  data    

Future  Plans

•  Short   Term:   IntegraNon   of   SAR   data   into   meteorological   visualizaNon  

systems  at  SIMEPAR  

•  Medium   Term:   Develop   operaNonal   system   for   landslide   detecNon/

monitoring  with  satellite  opNcal  and  SAR  data  in  Parana  

•  Long  Term:  Pursue  research  on  landslide  forecasNng  

•  OpportuniNes:   Propose   projects   about   landslide   monitoring   in   Brazil   and  

LaNn  America  

Thank  You!  

Fábio  Sato  fabiosato@gmail.com