1  National Institute for Agro-Environmental  Sciences, Tsukuba, Japan 2  Aomori-ITC, Kuroishi, Japan Estimating Biophysic...
Yield Rice yield in Japan 2009 2008 2007 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1996 1995 1994 1993
1. Multi-frequency Ka ---  35.25 GHz Ku ---  15.95 GHz X  ---  9.60 GHz C  ---  5.75 GH L  ---  1.26 GHz 2. Full-Polarizat...
Objective To investigate the capability of high-resolution satellite-SAR imagery in C- and X-bands for assessment of rice ...
CASI-Hyper Tsugaru site 5 km C-band  @ 1 m HH  25º  VH 21 º  [Radarsat-2 spotlight] Year: 2009,2010 X-band  @ 1 m VV 54 º ...
Inoue et al. (RSE 2002) Ka Ku X C L
Inoue et al. (RSE 2002) Ka Ku X C L
Datasets Ground-based measurements
1. Canopy height 2. Hill density 3. Stem density 4. Leaf Area Index 5. fAPAR 6. Chlorophyll index 7. Leaf FW, DW, W% 8. St...
<ul><li>14 dB larger in rice than water in HH.  </li></ul><ul><li>11 dB larger in rice than water in VH. </li></ul><ul><li...
Relations of plant variables with  C-HH and VH  σ 0  at panicle initiation stage <ul><li>No plant variables had close corr...
C-VH  signatures at two separate stages  in 2009 and 2010 <ul><li>Variability of VH σ0 for rice at two different stages wa...
S=0.69dB/1LAI S=13.2dB/1kg S=1.2dB/1kg S=2.8dB/1fAPAR S=3.8dB/1m S=-0.03dB/1% Relations of  C-VH  σ 0  with major plant va...
<ul><li>Some positive relationships for mass-related variables such as LAI, fAPAR, leaf density, and biomass </li></ul><ul...
X-VV  signatures at maturity stage in 2009 and 2010 <ul><li>Variability of σ0  </li></ul><ul><li>for rice 0.19 dB  </li></...
S=-0.06dB/1LAI S= 1.9dB/1fAPAR S= 1dB/1kg X-VV σ 0   (dB) LAI Leaf-DW  (g m-2) fAPAR Relations of  X-VV  σ 0  with major p...
Increase with grain growth Seasonal change of X-VV σ 0  at 55º  over a rice canopy    Inoue et al. (RSE 2002) 15 dB 15 dB ...
S= 1.7dB/1kg S= 2.4dB/1k S= 0.67dB/dm X-VV σ 0   (dB) Leaf-length (m) Stem-DW  (g m-2) Stem density  (m-2) Relations of  X...
Relations of  X-VV  σ 0  with major plant variables X-VV σ 0   (dB) X-VV σ 0   (dB) Total-DW  (g m-2) Head-DW  (g m-2) <ul...
r = 0.5 Summary of correlations between  X-VV  σ 0  and plant variables
<ul><li>C & X backscattering signatures (σ 0 ) of rice canopies and water were stable and consistent at 2 stages over 2 ye...
<ul><li>The sensitivity of the present C-band SAR may not be high enough to detect plant biophysical variability. </li></u...
5. The X-band signature was found to be best correlated with head biomass indicating a good capability for direct assessme...
 
Upcoming SlideShare
Loading in...5
×

IGARSS2011_TH2.T06.5.ppt

183

Published on

Published in: Technology, Education
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total Views
183
On Slideshare
0
From Embeds
0
Number of Embeds
0
Actions
Shares
0
Downloads
6
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide
  • 20100201 課題評価会議:農業空間情報 RP
  • IGARSS2011_TH2.T06.5.ppt

    1. 1. 1 National Institute for Agro-Environmental Sciences, Tsukuba, Japan 2 Aomori-ITC, Kuroishi, Japan Estimating Biophysical Variables in Rice Canopies by High-Resolution X- and C-SAR Signatures Yoshio Inoue 1 , Eiji Sakaiya 2 , Naoki Ishitsuka 1
    2. 2. Yield Rice yield in Japan 2009 2008 2007 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1996 1995 1994 1993
    3. 3. 1. Multi-frequency Ka --- 35.25 GHz Ku --- 15.95 GHz X --- 9.60 GHz C --- 5.75 GH L --- 1.26 GHz 2. Full-Polarization HH, HV, VH, VV 3. Multi-angular Incident angle: 20 º ~ 60 º  25 º , 35 º , 45 º , 55 º Azimuth angle: -60 º ~ +60 º  -28º, -14º, 0º, 14º, 28º Inoue et al. (RSE 2002) Paddy field
    4. 4. Objective To investigate the capability of high-resolution satellite-SAR imagery in C- and X-bands for assessment of rice growth. ➢ Operational field scale ➢ Detailed plant data
    5. 5. CASI-Hyper Tsugaru site 5 km C-band @ 1 m HH 25º VH 21 º [Radarsat-2 spotlight] Year: 2009,2010 X-band @ 1 m VV 54 º VV 54 º [Skymed spotlight] Year: 2009, 2010 Sky conditions for SAR
    6. 6. Inoue et al. (RSE 2002) Ka Ku X C L
    7. 7. Inoue et al. (RSE 2002) Ka Ku X C L
    8. 8. Datasets Ground-based measurements
    9. 9. 1. Canopy height 2. Hill density 3. Stem density 4. Leaf Area Index 5. fAPAR 6. Chlorophyll index 7. Leaf FW, DW, W% 8. Stem FW, DW, W% 9. Head FW, DW, W% 10. Total FW, DW, W% 11. Leaf number/m 2 12. Leaf length 13. Leaf width 14. Leaf thickness 15. Leaf density/m 3 16. Head layer depth 17. Leaf layer depth 18. Stem layer depth 19. Stem diameter Major plant variables 1. Panicle initiation stage 2. Maturity stage
    10. 10. <ul><li>14 dB larger in rice than water in HH. </li></ul><ul><li>11 dB larger in rice than water in VH. </li></ul><ul><li>Large differences due to biomass, LAI, and geometrical structures. </li></ul>C-HH and C-VH signatures at panicle initiation stage (2010) C-VH σ 0 (dB) C-HH σ 0 (dB) VH = 0.81 HH - 11.5 <ul><li>Sensitivity to mass-related change: 24% higher in HH than VH </li></ul>
    11. 11. Relations of plant variables with C-HH and VH σ 0 at panicle initiation stage <ul><li>No plant variables had close correlations (r >0.5) with both HH and VH signatures. </li></ul>r = 0.5 r= - 0.5
    12. 12. C-VH signatures at two separate stages in 2009 and 2010 <ul><li>Variability of VH σ0 for rice at two different stages was small 0.8-1.4 dB </li></ul><ul><li>For water 0.7-1.1 dB </li></ul><ul><li>Difference between rice and water was 11 dB in two years. </li></ul>
    13. 13. S=0.69dB/1LAI S=13.2dB/1kg S=1.2dB/1kg S=2.8dB/1fAPAR S=3.8dB/1m S=-0.03dB/1% Relations of C-VH σ 0 with major plant variables fAPAR C-VH σ 0 (dB) C-VH σ 0 (dB) Leaf-W % Plant height (m) LAI Leaf-DW (g m-2) Total-DW (g m-2)
    14. 14. <ul><li>Some positive relationships for mass-related variables such as LAI, fAPAR, leaf density, and biomass </li></ul><ul><li>No significantly high correlations (r >0.5) between plant variables and VH signatures. </li></ul><ul><li>C-VH σ0 saturated with small amount of leaves and biomass. </li></ul>Relations of plant variables with C-VH σ 0 in 2 years r = 0.5 r= - 0.5
    15. 15. X-VV signatures at maturity stage in 2009 and 2010 <ul><li>Variability of σ0 </li></ul><ul><li>for rice 0.19 dB </li></ul><ul><li>for water 1.6 dB </li></ul><ul><li>Stable and consistent </li></ul><ul><li>Average of σ0 </li></ul><ul><li>for rice -9.62 dB </li></ul><ul><li>for water -17.65 dB </li></ul><ul><li>8 dB higher in rice compared to water </li></ul>X-VV σ 0 in 2009 (dB) X-VV σ 0 in 2010 (dB)
    16. 16. S=-0.06dB/1LAI S= 1.9dB/1fAPAR S= 1dB/1kg X-VV σ 0 (dB) LAI Leaf-DW (g m-2) fAPAR Relations of X-VV σ 0 with major plant variables <ul><li>No relation with LAI, leaf-biomass, and fAPAR. </li></ul><ul><li>Obvious difference from water surface </li></ul><ul><li>Saturated quite early with low density of scattering elements </li></ul>
    17. 17. Increase with grain growth Seasonal change of X-VV σ 0 at 55º over a rice canopy   Inoue et al. (RSE 2002) 15 dB 15 dB Jump with transplanting
    18. 18. S= 1.7dB/1kg S= 2.4dB/1k S= 0.67dB/dm X-VV σ 0 (dB) Leaf-length (m) Stem-DW (g m-2) Stem density (m-2) Relations of X-VV σ 0 with major plant variables <ul><li>Little sensitivity to stem biomass, stem density, and leaf morphological variables </li></ul>
    19. 19. Relations of X-VV σ 0 with major plant variables X-VV σ 0 (dB) X-VV σ 0 (dB) Total-DW (g m-2) Head-DW (g m-2) <ul><li>Significant sensitivity to head biomass and total biomass. </li></ul><ul><li>Sensitivity 5 times larger than leaf and twice larger than total biomass. </li></ul><ul><li>-13 bB may be assumed for the zero yield conditions. </li></ul>
    20. 20. r = 0.5 Summary of correlations between X-VV σ 0 and plant variables
    21. 21. <ul><li>C & X backscattering signatures (σ 0 ) of rice canopies and water were stable and consistent at 2 stages over 2 years. </li></ul>Conclusions   ( 1/3) 2. The σ 0 values in rice canopies were much higher than in water surfaces in both C and X bands; X:8dB; C: 11dB.
    22. 22. <ul><li>The sensitivity of the present C-band SAR may not be high enough to detect plant biophysical variability. </li></ul>Conclusions   (2 /3) <ul><li>C-band σ 0 were correlated weakly with canopy mass parameters such as leaf density, stem density, and biomass. </li></ul>
    23. 23. 5. The X-band signature was found to be best correlated with head biomass indicating a good capability for direct assessment of rice grain yield at regional scales. Conclusions   (3 /3) 6. Systematic approaches would be useful to improve the accuracy; modeling/ optical sensors.
    1. A particular slide catching your eye?

      Clipping is a handy way to collect important slides you want to go back to later.

    ×