Es+ma+on	
  of	
  Forest	
  Biomass	
  Change	
  from	
  Fusion	
  
                    of	
  Radar	
  and	
  Lidar	
  Mea...
ECOSYSTEM	
  STRUCTURE	
  Baseline	
  Requirements	
  

                      	
  The	
  DESDynI	
  Mission	
  shall	
  ma...
DESDynl	
  Mission	
  ObjecMves	
  


              Aboveground	
  Biomass	
  from	
  Fusion	
  
              Of	
  Lidar...
Changes	
  of	
  Forest	
  Biomass	
  
              Depending on antecedent history, a forest with the biomass level
    ...
Scale	
  of	
  Forest	
  Biomass	
  

               Large and Small Scale
              Dynamics are Different
          ...
Forest	
  Disturbance	
  
                     2005	
  Katrina	
  Hurricane	
  Forest	
  impact	
  was	
  equivalent	
  to...
Forest	
  Recovery	
  Process	
  




                                       Lucas	
  et	
  al.	
  2002	
  
DESDynI	
  
Statement	
  of	
  Problem	
  

              1.  DESDynl	
  Es+ma+on	
  of	
  Annual	
  Deforesta+on	
  (Radar)	
  

    ...
Old	
  Growth	
  Height	
  1997	
  




DESDynI	
  
Old	
  Growth	
  Height	
  2006	
  




DESDynI	
  
Changes	
  in	
  Forest	
  Height	
  



              Height	
  difference:	
  h(2006)-­‐h(1997)	
  




                 ...
Secondary	
  Forest	
  Height	
  1997	
  




DESDynI	
  
Secondary	
  Forest	
  Height	
  2006	
  




                                              Mean:4.84	
  m	
  
           ...
Growth	
  Dynamics	
  From	
  Lidar	
  
              •    Sampling	
  lidar	
  can	
  be	
  used	
  to	
  observe	
  dyna...
La	
  Selva	
  Forest	
  Dynamics	
  (2005-­‐1998)	
  




              Biomass	
  Change	
  [Mg/ha]	
  
               0...
SAR	
  Measurement	
  of	
  Disturbance	
  

                  •  Annual forest disturbance, deforestation, degradation, f...
Requirement	
  for	
  PolarizaMon	
  
                                         (Disturbance)	
  

                        ...
Global	
  Biomass	
  Change	
  Requirements	
  


                                 Hardwoods




                         ...
SAR	
  Measurement	
  of	
  Bioamss	
  Recovery	
  

                                                                     ...
Radar	
  Forest	
  DegradaMon	
  Index	
  



           ALOS	
  
          La	
  Selva	
  
         Costa	
  Rica	
  



...
RFDI	
  to	
  map	
  disturbance,	
  DeforestaMon,	
  Intensive	
  Logging	
  



              LHH	
  
              LHV	...
RFDI	
  over	
  Slopes	
  
              ALOS	
  PALSAR	
  Peru	
  




                                              Fore...
RFDI	
  &	
  Changes	
  in	
  Biomass	
  

              ALOS	
  PALSAR	
  Mosaic	
  (Borneo)	
            UAVSAR	
  	
  
...
Radar	
  Forest	
  DegradaMon	
  Index	
  
                                   For	
  Forest	
  Recovery	
  EsMmates	
  
  ...
RFDI	
  Base	
  Forest	
  Recovery	
  
                ALOS	
  June	
  2007	
  




              ALOS	
  June	
  2010	
  ...
RFDI	
  Base	
  Forest	
  Recovery	
  
                ALOS	
  June	
  2007	
               RFDI10-­‐	
  RFDI07	
  




  ...
For	
  N	
  lidar	
  samples	
  
                                           We	
  have	
  (N-­‐1)!	
  Δσ	
  samples	
  


...
L-­‐band	
  Measurement	
  of	
  Recovery	
  

                                              Radar & Lidar Fusion of Recov...
SUMMARY	
  


              •    Quad-­‐Pol	
  data	
  is	
  required	
  to	
  measure	
  disturbance	
  and	
  recovery	
...
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WE1.L09.5 - ESTIMATION OF FOREST BIOMASS CHANGE FROM FUSION OF RADAR AND LIDAR MEASUREMENTS

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WE1.L09.5 - ESTIMATION OF FOREST BIOMASS CHANGE FROM FUSION OF RADAR AND LIDAR MEASUREMENTS

  1. 1. Es+ma+on  of  Forest  Biomass  Change  from  Fusion   of  Radar  and  Lidar  Measurements     Sassan  Saatchi  (Jet  Propulsion  Laboratory/UCLA)   Ralph  Dubayah  (University  of  Maryland)   David  Clark  (University  of  Missouri  )   Robin  Chazdon    (University  of  ConnecCcut)   David  Hollinger  (USDA  Forest  Service)   Other  contributors:   Hank  Shugart  (University  of  Virginia)   Michael  Lefsky  (Colorado  State  University)   ScoJ  Hensley  (JPL)   Maxim  Neumann  (JPL)   DESDynI   TIME  
  2. 2. ECOSYSTEM  STRUCTURE  Baseline  Requirements    The  DESDynI  Mission  shall  map  aboveground  woody  biomass  within  the   greater  of  20  Mg/ha  or  20%  (errors  not  to  exceed  50  Mg/ha),  at  a  spaMal   resoluMon  of  250  m  globally  and  100  m  for  areas  of  low  biomass  annually  (  <  100   Mg/ha).    The  DESDynI  Mission  shall  map  global  areas  of  disturbance  at  100  resoluMon   annually  and  measure  subsequent  regrowth  to  an  accuracy  of  4  Mg/ha/yr*  at  100   (1-­‐ha)  resoluMon.   Measurement  requirements  for  SAR  and  Lidar  Fusion  are:   Lidar:  5  beams  on  sun-­‐synchronous  orbit  with  at  least  50  shots  within  a  600  m        grid   at  the  equator  at  the  end  of  5  years.   Radar:  Polarimetric  (linear  polarizaMons)  L-­‐band  SAR        25-­‐35  degrees  incidence  angle  with  100m  resoluMon  (>100  looks)          Two  seasons  of  polarimetric  coverage  for  annual  biomass  maps        Monthly  global  imaging  capability  at  dual-­‐pol  (linear  polarizaMon)  for          mapping  disturbance  and  biomass  change     Mission  Life+me:  5  years   DESDynI              
  3. 3. DESDynl  Mission  ObjecMves   Aboveground  Biomass  from  Fusion   Of  Lidar  and  Radar   Inventory   Mapping  Deforesta+on  and  Disturbance   DeforestaMon   Disturbance   Mapping  Degrada+on  (logging,  infesta+on)   Logging   Forest  Recovery   Recovery   DESDynI  
  4. 4. Changes  of  Forest  Biomass   Depending on antecedent history, a forest with the biomass level associated with a mature forest, could be storing carbon, losing carbon or staying the same. This means that a single biomass “snapshot” does not completely reveal forest carbon dynamics. DESDynI  
  5. 5. Scale  of  Forest  Biomass   Large and Small Scale Dynamics are Different and Influenced by Structure Small-Scale Dynamics ≠ Large-Scale Dynamics DESDynI  
  6. 6. Forest  Disturbance   2005  Katrina  Hurricane  Forest  impact  was  equivalent  to  25%  of    annual  forest  Sequestra+on  (chambers  et  al.,  2007)   +mber  losses  from  Hurricane  Katrina  alone   amount  to  roughly  4.2  billion  cubic  feet  of   +mber  (15-­‐19  billion  board  feet),     spread  over  5  million  acres  of  light  to   heavily  damaged  forest  land  in  Mississippi,   Alabama,  and  Louisiana.   2005  Storm  in  Amazon   Killed  ½  Million  Trees   (Negron-­‐Juarez  et  al.,    2010)   2005  storm  killed  between  300,000  and  500,000   trees  in  the  area  of  Manaus  which  is  equivalent  to   30  percent  of  the  annual  deforesta+on  in  that  same   year  for  the  Manaus  region,  which  experiences   rela+vely  low  rates  of  deforesta+on. DESDynI  
  7. 7. Forest  Recovery  Process   Lucas  et  al.  2002   DESDynI  
  8. 8. Statement  of  Problem   1.  DESDynl  Es+ma+on  of  Annual  Deforesta+on  (Radar)   2.  DESDynl    Es+ma+on  of  disturbance  (Fire,  Storms,  etc.)  (Radar)   3.  DESDynl  Es+ma+on  of  Forest  Degrada+on  (Radar)   4.  DESDynl  Es+ma+on  of  Forest  biomass  loss  (Radar/Lidar)   5.  DESDynl  Es+ma+on  of  Forest  biomass  recovery  (Radar/Lidar)   (  accuracy/precision,  resolu1on,  temporal  coverage)   DESDynI  
  9. 9. Old  Growth  Height  1997   DESDynI  
  10. 10. Old  Growth  Height  2006   DESDynI  
  11. 11. Changes  in  Forest  Height   Height  difference:  h(2006)-­‐h(1997)   Mean:  1.18  m   Stdev:  8.1  m   DESDynI  
  12. 12. Secondary  Forest  Height  1997   DESDynI  
  13. 13. Secondary  Forest  Height  2006   Mean:4.84  m   Stdev:  6.2  m   DESDynI  
  14. 14. Growth  Dynamics  From  Lidar   •  Sampling  lidar  can  be  used  to  observe  dynamics   –  Not  efficient  for  forest  loss  mapping  (compared  to  radar  or  TM)   –  Can  directly  measure  growth/loss  in  canopy  at  footprint  or  grid  scale   •  Orbital  cross-­‐overs  could  provide  millions  of  direct  observaMons   ElevaMon   2005 1998 Amplitude   DESDynI  
  15. 15. La  Selva  Forest  Dynamics  (2005-­‐1998)   Biomass  Change  [Mg/ha]   0.5  ha  Old  Growth  Plots   r2  =  0.79   1:1  line   Field  Es+mate   DESDynI  
  16. 16. SAR  Measurement  of  Disturbance   •  Annual forest disturbance, deforestation, degradation, fragmentation are mapped at 100 m resolution a)  Disturbance:  -­‐  12.5  dB   b)  Disturbance:  -­‐  5  dB   Maximum  Likelihood  ClassificaMon   90%  classificaMon  accuracy   0 0 σ dist ≅ 0.78σ ref € c)  Disturbance:  -­‐  2.5  dB   d)  Disturbance:  -­‐  1.0  dB   N log(µ) Gamma[N − ] −1+ µ class[N, µ] = 0.9 = 1− Gamma(N) µ = 0.78 : -1.04 dB € At  100  m  resolu+on  (~100  looks)   forest  degrada+on  of  1.0  dB  change   can  be  classified  at  90%  accuracy  by     DESDynI   LHV  channel  only.   16  
  17. 17. Requirement  for  PolarizaMon   (Disturbance)   ResoluMon:  100  m   Radar  BW:  40  MHz   1.  Single  pol  (HH)  data  will  map   disturbance    with  ~50%   accuracy   2.  Dual-­‐pol  data  will  be  the     Minimum  requirement  to  map   Disturbance  with  ~80%   accuracy)   3.  Quad-­‐pol  data  will  provide   HH,  HV,  VV   map  Disturbance  with  >  90%   HH   accuracy    17   DESDynI   VV   HV  
  18. 18. Global  Biomass  Change  Requirements   Hardwoods Softwoods Temperate  &  Boreal  Forests   Tropical  Forests   Average Production: ~5 Mg/ha/yr 2.5-3% of counties had wood Average Biomass Production of forests after production > 10 Mg/ha/yr disturbance: ~4 Mg/ha/yr DESDynI   Brown & Schroeder 1999
  19. 19. SAR  Measurement  of  Bioamss  Recovery   Assump+ons  for  mapping     forest  recovery:   Recovery  Phase   •       Rate  of  RegeneraMon:  4  Mg/ha/yr   Disturbance  Even            Biomass  EsMmaMon  Accuracy:  20  Mg/ha          ResoluMon:  100  m  (>  100  looks)          Aker  5  year  SAR  will  measure          4Mg/ha/yr  biomass  change  at  100  m            ResoluMon   •       in  US  temperate  forests  about  50%          of  forests  produce  >  4  Mg/ha/yr.   •       AssumpMon:  radar  looks  achieved          from  azimuth  and  range  averaging   •   Aker  3  years,  SAR  will  not  meet  the  requirement  of  biomass  change   •         3  year  mission  will  only  cover  forests  with  >  7  Mg/ha/yr  recovery.  Over              US  forests,  this  is  about  15%  of  forests.     DESDynI  
  20. 20. Radar  Forest  DegradaMon  Index   ALOS   La  Selva   Costa  Rica   RFDI   HV   HH − HV HH   RFDI = HH + HV HH:  Dominated  by  volume  &  volume-­‐surface     Scajering   € HV:  Dominated  by  volume  scajering   RFDI  Sensi+vity  to  calibra+on  is  small   DESDynI   RFDI  Sensi+vity  to  topography  and  slope  is  small  
  21. 21. RFDI  to  map  disturbance,  DeforestaMon,  Intensive  Logging   LHH   LHV   LHV  Texture   DESDynI  
  22. 22. RFDI  over  Slopes   ALOS  PALSAR  Peru   Forest   Savanna   ALOS  PALSAR  Peru   DESDynI  
  23. 23. RFDI  &  Changes  in  Biomass   ALOS  PALSAR  Mosaic  (Borneo)   UAVSAR     Howland  Forest   100  m  ResoluMon   80  MHz  Bandwidth   DESDynI  
  24. 24. Radar  Forest  DegradaMon  Index   For  Forest  Recovery  EsMmates   I N N I N −1 ⎧ NI ⎫ p( 0 )= 0 ⎪ exp⎨− 0 ⎪⎬ < I > < I >N (N −1)! ⎪ < I > ⎪ 0 0 ⎩ 0 ⎭ where < I > is the mean intensity of a homogeneous region at time t 0 0 N is equivalent number of looks For two independent measurements I = HH and I = HV , the difference and ratios will follow 0 1 the integration of the joint probability over I 0 d = I −I 0 1 ⎧ NI ⎫ N N exp⎪− ⎨ 0 ⎪ ⎬ ⎪ < I > ⎪ j = N −1 (N −1+ j) p( d ,< I >) = ⎩ 0 ⎭ × ∑ <I > 1 (< I > + < I >)N (N −1)! j = 0 j!(N −1− j)! 0 0 1 r = I /I 1 0 N N −1 p( r ,< I >) = (2N −1)!r r <I > 1 (r + r )2N (N −1)!N 0 where r =< I > / < I > 1 0 I −I RFDI = 0 1 I +I 0 1 Change Detection will be performed between the ratio of RFDI for two dates. I −I RFDI = 0 1 DESDynI   I +I 0 1 Delta  (RFDI)*20   €
  25. 25. RFDI  Base  Forest  Recovery   ALOS  June  2007   ALOS  June  2010   DESDynI  
  26. 26. RFDI  Base  Forest  Recovery   ALOS  June  2007   RFDI10-­‐  RFDI07   ALOS  June  2010   DESDynI  
  27. 27. For  N  lidar  samples   We  have  (N-­‐1)!  Δσ  samples   25  m   100  m   DESDynI  
  28. 28. L-­‐band  Measurement  of  Recovery   Radar & Lidar Fusion of Recovery Baysian MLE Method 20%  error   N : Number of looks in  biomass  change   Prob. of Error : is  detectable  at     100-­‐250  m  resolu+on   PE = 1/2 − f (x) + f (1/ x) € Lombardo  and  Oliver,  2001   28   DESDynI   Rignot  &  vanZyl  1995  
  29. 29. SUMMARY   •  Quad-­‐Pol  data  is  required  to  measure  disturbance  and  recovery  from  L-­‐band  SAR   data   •  Increasing  cross-­‐points  in  Lidar  will  provide  es+mates  of  biomass  changes  at  the   stand  and  ecosystem  levels   •  RFDI  based  on  dual-­‐pol  data  will  provide  the  most  consistent  index  to  classify      deforesta+on,  degrada+on  and  recovery.    However,  more  research  is  needed  to    assess  its  quan+ta+ve  capability  for  measuring  biomass  loss  and  gain.   •  Fusion  of  L-­‐band  polarimetry  and  Lidar  has  the  poten+al  of  quan+fying  stand   scale  patch  scale  changes  in  biomass.   •  Use  of  repeat  pass  interferometry  along  with  RFDI  has  the  poten+al  of  mapping   forest  regrowth.   DESDynI  

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