センシシード

%
%
ALFAE
in%
%
%
Obihiro,%Japan%%%28%June%2014
HONDA%Kiyoshi,%Chubu%University%
Akihiro%YUI,%IHI%Corp.%
Amor%Ines,%Columbia%University%
Apichon%Witayangkurn,%Univ.%of%Tokyo%
Kumpee%Teeravech,%RBRU,%Thailand%
R.%Chinnachodteeranun,%Geomove%Co.,%Ltd.%
• 
• 
• 
• 
• 
%
(GeoinformaTcs)
%
%
%
%
– 
%
–  Tomorrow’s%Wheat%
%
Modeling on Big Data for Scenario Simulation
%–%
• 
UAV
%
Satellite RS
• 
%
• 
Model
Calibration
Crop Model
%
Cluster, GRID)
%
• 
• 
• 
• 
Scenario Simulation
%
Real Time Update
%
%
%
• 
• 
• 
UI%
• 
• 
%
Field%Touch
Decision
Making
IHI
IHI
! 
! 
! 
! 
! 
! 
SNS
/
%
Web Service
Field%Sensor%
Network
Observa
tories
Satellite
s
Aircrafts
UAV
FieldServer
s
LAI_sat
4
HPC (GPGPU,
•  SOS,%WMS,%WCS,%WFS%
• 
Comparison of Satellite LAI and Simulated LAI
5
LAI
Weather
–%
Web%Service
Interoperability%
Agri.
Machines,
Applicatio
n records
Cloud & Data Integration
Yield, Soil,
etc.
%
• 
Sensor
Network
LAI_sim
3
2
1
0
0
30
60
90
120 150 180 210 240 270 300 330 360
DOY
Ubiquitous%GeoinformaTcs%
%
Web
%
%
LBS
Satellite
Remote
Terra
SAR-X
Sensing
1m
Radar
%
Global Monitoring
City Modeling
Disaster Management
UAV
Navigation
Sensor Network
LBS
%
• 
– 
%
•  Interoperability
•  OGC%(%Open%GeospaTal%ConsorTum%)
%
• 
Web%Service
%
%
–  SOS%(%Sensor%ObservaTon%Service%)%
–  WMS%(%Web%Map%Service%),%WCS%(%Web%Coverage%Service%)%
–  WFS%(%Web%Feature%Service%)%
–  WPS%(%Web%Processing%Service%)%
• 
%
%
Plug&Play
Web Service
cloud
Sense
The project is organized by
University of Tokyo,
University COOP in Japan
and Fujitsu Design Co., Ltd.
AIT,
Sensor Back-
Field Sensor end Cloud Application
Service
OGC’s&Standard&Web&Service:&Sensor&
Observa5on&Service(SOS)&enables&
Rapid,&Low&Cost&and&Flexible&
Applica5on&Dlevelopment
-
Asia&Pacific&ICT&Alliance&
Award&2010&
Winner!
Tools and
Infrastructure"
Applications
Category
( Data Assimilation ) -
RS
GA
LAI
LAI
GA
Eavpotranspiration LAI
Fitting
RS
Spinach Promotion from
Thailand to Japan.
Application on the cloud
Service
Model
Day Of Year
Honda K ( Chubu U ) et.al
%
Reducing)uncertainty)with)updated)informa4on)
• 
• 
Data assimilation
%
• 
• 
%
%
%
%
• 
model uncertainty
climate uncertainty
Climate forecasts
planting
anthesis
Time
harvest
◄——— PREDICTION ———
SIMULATION
Weather%
Generator
Uncertainty
• 
CROP MODEL
• 
Hansen et al. (2006) Clim. Res.
%_%EnKF%
• 
• 
• 
• 
Integrated%data%(%RS,%UAV,%Field%Sensor/Obs.%)%for%AssimilaTon%
Reducing%uncertainty%as%Tme%passes%through%by%weather%and%data%
assimilaTon%
Up_to_date%predicTon%as%probability%distribuTon and%filtering%
Standard%Web%Services%and%Web%Interface%for%informaTon%service
DSSAT%–%Crop%Model%
Decision%Support%System%for%Agrotechnology%Transfer
•  SimulaTng%
water%
environment%
•  PracTcal%
FuncTonality%
•  Popular%
•  Strong%support%
•  Various%plant%
modules%
•  Going%to%be%
Open%source%
•  Nitrogen%
Satellite&
B,&G,&R,&RE,&NIR&
AircraM&
Hyper&Spectral&/&NIR&Camera
UAV&
RGB/NIRGB&Camera
Swinglet CAM
RapidEye%
3,500km2%
6.5m%resoluTon%
2%–%3%image/month%
distribuTon%
Copyright©© 2013
2013 IHI
All All
Rights
Reserved.
Copyright
IHICorporation
Corporation
Rights
Reserved.
Cessna%
9.9km2(4720m×2115m)%
10 50km2%%/%flight%
1 5m%
Various%type%of%sensors%
Sensefly%SwingletCam/%eBee%
1 10km2%/%flight%
5 10cm%resoluTon%
Super%high%reso,%easy%
depoloyment%
RapidEye
• 
• 
• 
• 
• 
• 
UAV%(%Unmanned%Aerial%Vehicle%)%became%realisTc%sensor%plaform%
for%agriculture
movie
UAV
UAV : Obihiro : 2013-08-02
UAV
UAV : Obihiro : 2013-08-02
NIR (8cm) 38 images
VIR (8cm) 39 images
UAV
27
SOS
Web Service
• 
cloudSense
Web Service
Poteka Meisei
Elec.
AMeDAS - NIAES
Memuro, Obihiro
FieldServer & Field
Point – elab
Experience Inc.
Weather Bucket Obihiro City Hall
& Agri Weather
• 
• 
•  AMeDAS - NIAES
Web Service
1
GetCapabilities
Simulation
System
OGC API
List of authorized
SOS stations with
its sensors
2
GetObservation
User Interface for
Famers
Sensor Data with
Timestamp
Ground Measurement
Weekly measurement of
Spectroradiometer
LAI meter
Phenotypes ( Height, width… )
Sakurai-Wheat-3 : 2013-07-09
RapidEye Satellite Images to LAI Development
• 
• 
• 
• 
• 
Vernalizing%Wheat%ObservaTon
LAI%simulated%shows%becomes%0%
Wheat%keeps%leaves%while%vernalizaTon%
Sampling%on%25%Feb%2014%
Sakurai%Farm%(%snow%depth%60cm)%
Ikemori%Farm%(%snow%depth%0cm)%
LAI%Measurement
•  Scan%_>%Cut%edges%manually(%noisy%part%)%_>%Binary%
image(thresholding%%by%Sum(R,G,B)%<%500%%)%_>%LAI%%
Sakurai Farm Samples
Snow%Cover%Effect
•  Soil%Temp%under%
snow%does%not%go%
below%0%because%of%
heat%insulaTon%
effect%of%snow%
•  1%Dec%–%31%Mar%
•  Limit%min%of%Tmin,%
Tmax%to%_0.1,%+0.1%
•  Solar%Rad%reducTon%
0.95%%
17 Dec
24 Mar
9 Apr
Ikemori Farm 1 Nov 2012 – 30 Apr 2013
( No Camera image from 25 Mar-8 Apr )
Reference
•  Tokachi%Agricultural%Experiment%StaTon%(
%
•  Growth%measurement%in%their%field%(%not%the%averages%
of%Tokachi%area%)%Hokushin%–%1997_2012(14yrs)%
•  Kitahonami%–%2009_2013(5yrs)%
–  Sowing,%Emergence,%Flowering,%Maturity%
–  N%Leaves,%Height%and%Tllers%(%20%Oct,%May,%Jun,%Jul,%
(%oct%is%fro%2005)%
–  Maturity%(H%of%Tiller,%L,%Density%Nseed%of%Spike)%
–  Yield,%Weight%of%Seed,%Quality%
–  FerTlizer%(%base%and%addiTonal%)%
GeneTc%coefficients%of%DSSAT_CSM_Wheat%Model
&"
$"
!#,-'./'0.1"2)'
SimulaTon%Service%for%Decision%Making%
How sowing date impacts expected yield
#!(("
0123456,/"
#!(!"
!"
)*+,-.,/"
345678'
(9:456;<'()*+,'
#!!'"
#"
#!!&"
•  All%parameters%are%
unknown%in%the%
calibraTon
!"#$%&'()*+,'
%"
%
• 
Dynamic%Filtering%
– 
%Plaform%
• 
– 
%
– 
API%_>%Web%Service%
–  Big%Picture%<_%ALFAE%
%
• 
– 
User%I/F %
• 
Acknowledgement
Farmers%in%Obihiro%
Ms.%Y.%Matsubara%(%Univ.%of%Tokyo),%%
Prof.%M.%Hirafuji(NARO)%%%
Dr.%T.%Kuwagata(NIAES)%
Obihiro%City%Hall%
and%to%all%who%provided%
wisdom,%knowledge%and%
materials.
%
Materials
http://tesla2.isc.chubu.ac.jp/
www.hondalab.net
www.researchgate.net