lp 2013 diversity -...

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Ute Gangkofner 1 *, Carsten Brockmann 2 , Marc Paganini 3 , Gregor Ratzmann 4,1 , Florence Stoeger 1 , Olaf Danne 1 , Per Wramner 5 , José Brito 6 , Rasmus Fensholt 4 , Kurt Günther 7 1 GeoVille Information Systems GmbH, Sparkassenplatz 2, A-6020 Innsbruck, Austria; 2 Brockmann Consult, Max-Planck-Str. 2, D-21502 Geesthacht, Germany; 3 European Space Agency (ESA), ESRIN, Via Galileo Galilei, Casella Postale 64, I-00044 Frascati, Italy; 4 Department of Geography and Geology, University of Copenhagen, Øster Voldgade 10, DK-1350 Copenhagen, Denmark; 5 Brockmann Geomatics Sweden AB, Torshamnsgatan 39, S-164 40 Kista, Sweden; 6 Centro de Investigação em Biodiversidade e Recursos Genéticos da Universidade do Porto (CIBIO), Instituto de Ciências Agrárias de Vairão, R. Padre Armando Quintas, P-4485-661 Vairão, Portugal; 7 German Aerospace Center (DLR), German Remote Sensing Data Center (DFD), Münchener Straße 20, D-82234 Oberpfaffenhofen, Germany * Corresponding Author: Ute Gangkofner, [email protected] Tel: +43 512 562021-19 Envisat MERIS Data for Global Dryland Monitoring

Transcript of lp 2013 diversity -...

Ute Gangkofner1*, Carsten Brockmann2, Marc Paganini3, Gregor Ratzmann4,1, Florence Stoeger1, Olaf Danne1, Per Wramner5, José Brito6, Rasmus Fensholt4, Kurt Günther7�

 �1 GeoVille Information Systems GmbH, Sparkassenplatz 2, A-6020 Innsbruck, Austria; 2 Brockmann Consult, Max-Planck-Str. 2, D-21502 Geesthacht, Germany; 3 European Space Agency (ESA), ESRIN,  Via Galileo Galilei,

Casella Postale 64, I-00044 Frascati, Italy; 4 Department of Geography and Geology, University of Copenhagen, Øster Voldgade 10, DK-1350 Copenhagen, Denmark; 5 Brockmann Geomatics Sweden AB, Torshamnsgatan 39, S-164 40 Kista, Sweden; 6 Centro de Investigação em Biodiversidade e Recursos

Genéticos da Universidade do Porto (CIBIO), Instituto de Ciências Agrárias de Vairão, R. Padre Armando Quintas, P-4485-661 Vairão, Portugal; 7 German Aerospace Center (DLR), German Remote Sensing Data

Center (DFD), Münchener Straße 20, D-82234 Oberpfaffenhofen, Germany�* Corresponding Author: Ute Gangkofner, [email protected] Tel: +43 512 562021-19�

   

Envisat  MERIS  Data  for  Global    Dryland  Monitoring  

Overview  

•  Drylands  part  of  ESA  DUE  Diversity  II    

•  Exploi>ng  10  years  of  Envisat  MERIS  FR  data  

•  EO  based  contribu>on  to  the  Conven>on  on  Biological  Diversity  (CBD)  

Specific  Aim    

•  EO  based  framework  to  monitor  global  dryland  biodiversity  

•  Provide  poten>al  users  with  relevant  and  informa>ve  GIS  products  

Test  site  selec>on  by  aridity  index  threshold,  WWF  ecoregion,  protec>on  status  and  other  

Global  Dryland  Test  Sites  

Data  Base  •  Biophysical  data:  MERIS  JRC  fAPAR,  AVHRR  GIMMS  NDVI3g  

•  Ancillary  data:  TRMM  3B42/3B43  v7  precipita>on  es>mates,  GPCP  v2.2  precipita>on  es>mates,  CCI  SoilMoisture    es>mates  

•  Addi>onal  biodiversity  relevant  informa>on:  protec>on  status,  GlobCover  land  cover  maps  and  other  

•  In-­‐situ  data  for  EO  data  valida>on  

Example:  Test  Site  12,  Southern  Africa  

Example:  Test  Site  12,  Southern  Africa  MERIS  fAPAR  >me  series  for  different  GlobCover  land  cover  classes  

Project  Output  Products  •  Status,  change  and  trends  of  vegeta>on  phenology  based  NPP  proxies  

•  Status,  change  and  trends  of  ancillary  clima>c  factors  (rainfall,  soil  moisture)  

•  Status,  change  and  trends  of  rain  use  efficiency  and  soil  moisture  use  efficiency  

•  All  products  with  a  spa>al  reference  to  administra>ve  borders,  land  cover  and  protec>on  status  

Product  Processing  Chain  

Extrac>on  of  Vegeta>on  Phenology  

Extrac>on  of  Vegeta>on  Phenology  

•  NPP  proxies  derived  from  important  phenological  descriptors,  such  as  start  of  season,  vegeta>on  year,  cyclic  frac>on,  length  of  growing  season,  avarage  dry  season  fAPAR  and  other  

•  Analogous  extrac>on  of  clima>c  factors  •  Results  are  annual  NPP  proxies  and  ancillary  datasets  

Efficiency  Indices  

Normaliza>on  of  NPP  proxies  for  clima>c  constraints  such  as  rainfall  and  soil  moisture:  

   Rain  use  efficiency  :  

   RUE  =  NPP  proxy  /  precipita>on  Soil  moisture  use  efficiency  :  

   SMUE  =  NPP  proxy  /  soil  mositure  

Status  and  Change  

•  Status:  annual  NPP  proxies,  ancillary  data  and  efficiency  parameters  

•  Change:  Integra>on  of  3  consecu>ve  years  by  averaging,  consequent  comparison  of  change  between  different    3  year  periods  

Product  Example:  Vegeta>on  Status  in  Southern  Africa  

Calcula>on  of  Trends  

•  Linear  median  slope  trends:  Non-­‐parametric  trend  operator  acer  Theil  (1950)  and  Sen  (1968)  

•  Consequent  test  on  trend  significance  acer  Mann  (1945)  and  Kendall  (1975)  

Product  Example:  Vegeta>on  Trends  in  Southern  Africa  

Product  Example:  Vegeta>on  Trends  in  Southern  Africa  

Relevance  for  Biodiversity  

•  EO  status/change/trend  phenomena  related  to  biodiversity  and/or  land  degrada>on:  biodiversity  indicators  

•  Example:  Land  degrada>on  and  loss  of  biodiversity  caused  by  woody  plant  encroachment  in  Namibian  grass  lands  detectable  in  NPP  proxy  trends  

Aggregated  Products    

Final  products  are  aggregated  by:      

»   administra>ve  borders,  »   land  cover  classes    »   protec>on  status    »   degree  of  change/trend  

Valida>on  

Valida>on  of  MERIS  JRC  fAPAR  using  in-­‐situ  fAPAR,  example    from  a  Senegal  field  sta>on:  

Valida>on  of  biodiversity  indicators  and  NPP  proxies:  comparison  of  status/change/trends  to  results  from  in-­‐situ  studies