introduc on to asia rice technical demonstra on sites ii
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Introduc)on*to*Asia/RiCE* Technical*Demonstra)on*Sites*II.** - PowerPoint PPT Presentation

Introduc)on*to*Asia/RiCE* Technical*Demonstra)on*Sites*II.** Japan,*Indonesia,*Vietnam* Kei$Oyoshi 1 ,$Nobuhiro$Tomiyama 2 ,$Toshio$Okumura 2 ,$Shinichi$Sobue 1,2 ,$ Wahyu$Supriatna 3 ,$Rizatus$Shofiya? 3 ,$Lam$Dao$Nguyen 4


  1. 
 
 Introduc)on*to*Asia/RiCE* 
 Technical*Demonstra)on*Sites*II.** Japan,*Indonesia,*Vietnam* Kei$Oyoshi 1 ,$Nobuhiro$Tomiyama 2 ,$Toshio$Okumura 2 ,$Shinichi$Sobue 1,2 ,$ 
 Wahyu$Supriatna 3 ,$Rizatus$Shofiya? 3 ,$Lam$Dao$Nguyen 4 $and$Thuy$Le$Toan 5 * ! 1$ Japan$Aerospace$Explora?on$Agency$(JAXA) 
 2$ Remote$Sensing$Technology$Center$(RESTEC) 
 2$ Indonesian$Center$for$Agricultural$Land$Resources$Research$and$Development$(ICALRD) 
 4$ Vietnam$Southern$Satellite$Technology$Applica?on$Center$(VAST/STAC) 
 5 Centre$d'Etudes$Spa?ales$de$la$BIOsphère$(CESBIO) 
 7th$GEOSSYAP$Symposium@Tokyo,$Japan 
 27$May$2014

  2. AsiaYRiCE$:$Aims$of$TDS$Ac?vi?es ! Each$technical$demonstra?on$site$covers$approximately$100$ square$kilometers$or$a$single$province$and$represents$one$of$the$ key$components$of$AsiaYRiCE.$ ! $They$seek$to$develop,$exercise$and$refine$the$process$–$from$ stakeholder$engagement,$through$resource$marshalling$and$ deployment,$and$on$to$trial$implementa?on$and$product$ genera?on$using$SAR$and$other$Earth$observa?on$data$for$rice$ crop$monitoring.$ [AsiaYRiCE$GEOGLAM$Phase$1$Space$Data$ Requirements$Technical$Demonstrator$Site$ Characteriza?on,$2013]$ 2

  3. Target$Products$for$AsiaYRiCE Enhance$our$rice$monitoring$ability$through$the$use$of$blending$ various$earth$observa?on$data,$especially$the$u?liza?on$of$SAR$data$ ID Product Descrip)on @Cul?vated$area$(every$year)$ 
 P1 Rice*Crop*Area*Map @Inventory$of$agricultural$facili?es @Timing$of$sowing,$plan?ng,$growing$and$ P2 Crop*Calendars harves?ng/growing$status 
 @Iden?fica?on$of$growth$stages$and$ @Detec?on$of$flooding$and$other$disaster$ P3 Crop*Damage*Assessment impacted$area 
 @Detec?on$of$drought$area 
 @Nowcast$and$anomaly$of$radia?on,$land$ P4 Agro/met*informa)on surface$temperature,$precipita?on,$soil$ moisture$and$so$on. @EmpiricalYsta?s?cal$model$es?mate$ Rice*Produc)on*Es)ma)on*and* P5 Forecas)ng with$satellite$derived$agroYmet$ 
 [AsiaYRiCE$Team,$2012,$$hdp://www.asiaYrice.org/files/workplan.pdf] 3

  4. Japan Technical*Demonstra)on*Sites China Taiwan India Laos Vietnam*(North) Philippines Thailand Vietnam*(South) Malaysia Phase*1A:*Jun*2013*/ Phase*1B:*Apr*2014*/ Indonesia 4 4

  5. World$Rice$Produc?on$(2011) ! Asian$countries$produce$and$consume$90%$of$global$rice.$ Top*20*Rice*Produc)on*Countries*in*2011 China India Indonesia Bangladesh Vietnam Thailand Myanmar Philippines Brazil Cambodia Japan [FAOSTAT,$2012] 5

  6. Overview$of$Progress$in$TDS$Ac?vi?es ! Japan*(Yamagata*Pref.) 
 Y$Field$survey$and$installing$AWS$system$with$camera 
 Y$Acquisi?on$of$SAR$data$(RadarsatY2)$ 
 Y$Development$of$paddy$field$mapping$sojware 
 ! Indonesia*(West*Java,*South*Kalimantan) 
 Y$Field$Survey 
 Y$Acquisi?on$of$SAR$data$(RadarsatY2) 
 Y$Airborne$SAR$observa?on$and$phenology$classifica?on 
 Y$Preparing$SAR$data$processing$for$paddy$field$mapping$ ! ! Vietnam/South*(An*Giang*Prov.) 
 Y$Field$Survey 
 Y$Acquisi?on$of$SAR$data$(CSK,$RadarsatY2) 
 Y$Paddy$field$mapping$by$SAR$(CSK)$and$valida?on 
 Y$Yield$es?ma?on$by$SAR$(CSK)$and$valida?on 6

  7. Japan: Yamagata Pref.

  8. Loca?on$of$Technical$Demonstra?on$Site Top*10 
 90x150km Rice*Produc)on*Prefecture*(t)* 2012 700,000"" 600,000"" 500,000"" 400,000"" 300,000"" 200,000"" 100,000"" 0"" Nigata" Hokkaido" Akita" Ibaraki" Yamagata" Miyagi" Fukushima" Tochigi" Chiba" Iwate" Tokyo" Rice*Crop*Calendar*in*Yamagata*Prefecture* Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Plan?ng Harves?ng Calendar Transplan?ng,$Irrigated$cropping,$Yield$=$approx$6.0$t/ha 8

  9. Rice$Cul?vated$Area$Mapping$Sojware ! INAHOR$:$INterna?onal$Asian$Harvest$mOnitoring$system$for$Rice 1.$Main$Window 2.$Select$SAR$data$for$Processing 3.$Rice$Cul?vated$Area$Mapping$ 4.$Calculate$Mapping$Area This*so]ware*enable*us*to*easily*map*rice*cul)vated*area*from*)me/series*SAR*data. 9

  10. Paddy$Field$Mapping$by$ALOS$PALSAR$over$Yamagata Google$Eearth Tsuruoaka*City

  11. Paddy$Field$Mapping$by$ALOS$PALSAR$over$Yamagata ALOS$PALSAR$FBS$ ( 2009 ) :$Planting$Season$(Min) Tsuruoaka*City

  12. Paddy$Field$Mapping$by$ALOS$PALSAR$over$Yamagata ALOS$PALSAR$FBS$ ( 2009 ) :$Vegetative$Season$(Max) Tsuruoaka*City

  13. Paddy$Field$Mapping$by$ALOS$PALSAR$over$Yamagata ALOS$PALSAR$FBS$ ( 2009 ) :$Range$(Max$Y$Min) Tsuruoaka*City

  14. Paddy$Field$Mapping$by$ALOS$PALSAR$over$Yamagata ALOS$PALSAR$FBS$ ( 2009 ) Tsuruoaka*City

  15. Field$Survey$for$Valida?on ! Landcover$PreYsurvey$(Apr$2014)$ ‣ Paddy$field,$soybeans,$agricultural$land$abandonment$etc. Landcover*survey*will*be*conducted*in*the* beginning *of*Jun. 15

  16. Field$Router$(Automa?c$Weather$Sta?on) ! Characteris?cs � Y$Automa?c$data$collec?on � Y$Wireless$communica?on$(daily) � Y$Powered$by$solar$panel 
 ! Meteorological$ sensor � Y$Air$Temperature � Y$Precipita?on$(rain$gauge) � Y$Radia?on 
 Y$Wind$direc?on$and$velocity 
 ! Image$sensor � Y$CMOS$camera$(120$M) [Developed$by 
 Prof.$Mizoguchi,$U.Tokyo] 16

  17. Near$realY?me$inYsitu$and$Satellite$Monitoring$System ! Tsuruoka$City$in$Yamagata$Prefecture$ • NDVI$(Vegeta?on)$ • NDWI$(Water)$ • NDSI$(Snow) Near*real/)me*photo*and*satellite*monitoring*system AWS*with*Camera 17

  18. NDVI$(MOD13A1$500m)$vs$FR$Photo N38˚ 41’ 47” ! E139˚ 49’ 16” DOY = 348 ! (Snowing) DOY = 296 ! (tiller) DOY = 162 ! DOY = 195 ! DOY = 264 ! DOY = 244 ! (installing syatem) (Max NDVI) (Harvest) SAR*observa)on*data*(ALOS/2*etc.)*will*be*included*in*this*comparison*in*2014. 18

  19. Current$TDS$Tsuruoka$Site$:$20th$May$2014 NDVI Planting Stage NDWI NDSI 19 NDVI NDWI

  20. RADARSATY2$Acquisi?on$Plan$Over$Tsuruoka Date UTC Site Beam Pass 16YAprY2014 $08:36:08.331 Japan Wide$Fine$ Ascending 23YAprY2014 $20:46:23.634 Japan Wide$Fine$ Descending 10YMayY2014 $08:36:08.331 Japan Wide$Fine$ Ascending 17YMayY2014 $20:46:23.634 Japan Wide$Fine$ Descending 3YJunY2014 $08:36:08.331 Japan Wide$Fine$ Ascending 10YJunY2014 $20:46:23.633 Japan Wide$Fine$ Descending Wide Fine Mode ! 27YJunY2014 $08:36:08.331 Japan Wide$Fine$ Ascending - 5.2x7.7 m ! 4YJulY2014 $20:46:23.633 Japan Wide$Fine$ Descending - 170x150 km ! 21YJulY2014 $08:36:08.331 Japan Wide$Fine$ Ascending - Inc. 20-40 deg ! 28YJulY2014 $20:46:23.633 Japan Wide$Fine$ Descending - VV+VH 14YAugY2014 $08:36:08.331 Japan Wide$Fine$ Ascending 21YAugY2014 $20:46:23.633 Japan Wide$Fine$ Descending 7YSepY2014 $08:36:08.331 Japan Wide$Fine$ Ascending 14YSepY2014 $20:46:23.633 Japan Wide$Fine$ Descending 1YOctY2014 $08:36:08.331 Japan Wide$Fine$ Ascending 8YOctY2014 $20:46:23.633 Japan Wide$Fine$ Descending 25YOctY2014 $08:36:08.331 Japan Wide$Fine$ Ascending 1YNovY2014 $20:46:23.633 Japan Wide$Fine$ Descending 18YNovY2014 $08:36:08.331 Japan Wide$Fine$ Ascending 25YNovY2014 $20:46:23.633 Japan Wide$Fine$ Descending 20

  21. Indonesia: West Java

  22. Loca?on$of$Technical$Demonstra?on$Site West$Java$ 
 (Subang,$Karawang,$Indramayu) 22

  23. Airborne$SAR$Observa?on$Campaign$(PiYSARYL2) Azimuth 4*August*2012 Range 20*km 90*km 23

  24. Rice Phenological Mapping by Airborne SAR Airborne SAR (Pi-SAR-L2) data analysis 
 - Pi-SAR-L2 carries similar SAR sensor as ALOS-2 


  25. Phenological Stages Each sampling area was classified into 6 phenological stages based on the visual interpretation of photos. Planting Vegetated1 Vegetated2 Harvesting Harvested Drought 25

  26. SAR Images of Phenological Stages VV • R:G:B = HH:HV:VV HH HV Planting Vegetated1 Vegetated2 Harvesting Harvested Drought 26

  27. 27

  28. Rice Phenology Mapping by Airborne SAR 28 Planting Vegetated$1 Vegetated$2 RIpening 18

  29. Classification Result in Batola, South Kalimantan Courtesy:$Wahyu$Supriatna$ and$$Rizatus$Shofiya?$ Class$distribution$for$selected$area No Class Percent 1 rice150days_kb3 8.818 2 rice105days_kb5 23.071 3 rice140days_kb2 8.127 4 water 1.024 5 mixedtreecrops 16.864 6 others 17.120 7 nodata 24.976 Total 100.000 Overall$Class$Performance$:$ (13953$/$16954$)$=$$82.3%$ Kappa$Statistic$(X100)$=$$73.4% 29

  30. Dry$Biomass$vs$Backscadering$Coef. HH HV r=0.85 r=0.62 n$=$37 VV Dry*Biomass Backsca`ering*Coef.*(dB) r=0.74 HH*showed*highest*correla)on*coefficient. 
 ALOS/2*ScanSAR*mode*has*HH*mode. 30

  31. SAR Data Collection : Radarsat-2 RADARSAT-2 Data (Ascending) RADARSAT-2 Data (Descending) Obs.*date Orbit Mode Beam Obs.*date Orbit Mode Beam 23#Aug#2013 Des Fine W2 01#Dec#2013 Asc Fine W2 03#Nov#2013 Des Fine W2 15#Dec#2013 Asc Fine W2 27#Nov#2013 Des Fine W2 18#Jan#2014 Asc Fine W2 21#Dec#2013 Des Fine W2 11#Feb#2014 Asc Fine W2 14#Jan#2014 Des Fine W2 07#Feb#2014 Des Fine W2 Prelim inary result Processed by I NAHOR Rice cultivated area mapping 31

  32. Vietnam: An Giang Prov.

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