Application of remote sensing technologies for mapping of ...
Transcript of Application of remote sensing technologies for mapping of ...
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Application of remote sensing technologies for
mapping of cropping pattern and area
estimations for major summer and winter crops
across spatial and temporal scales: Lessons
learnt in Australia
A Potgieter
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Climate variability
11 year running mean high variability at
temporal & spatial
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Area (MHa) Production (Mtons)
Impact (Economic, Natural, Social)
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Operating within a Variable Climate
• Australian producers are excellent risk
managers. Successful businesses within the
world’s most variable climate and without
subsidies
• Climate risk and change is already built into
the system
• Integration of climate forecasts with targeted
decision making tools – improved decision
making
• Developed world-leading crop production
systems frameworks & decision-support tools
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Utility
Utility of crop predictions is a function of timing and accuracy
Early-Low
Late
-Hig
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1 Jun 19?? to 31 Dec 20??
1 October 2003 to 31 May 2004
1 Jun 19?? to 31 Dec 19??
Start of
fallowForecast
distribution
based on
climate
forecast
Generating Yield Forecast Data Plumes –
Climate Forecast Set (e.g. at 1 June 2004)
Run model using weather data
to date for current season
Run model projections on subset of
historical analogues from climate
forecast to complete season
Regional crop prediction framework
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Yie
ld (
t/h
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Forecast Worst10% Forecast-median Forecast Best10%
Forecast Climatol Lt-median
Hindcast Qld 1994SOI phases
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Median
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Potgieter et. al. 2003, 2005, 2006
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Spatial & temporal forecast
© QAAFI 2010 Created 9/08/2010 [Slide 7]
Predicted percentile
median yield
relative to all years
1st July 2015
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Temporal scale
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SWQ Wheat
SWQ Barley
SWQ Chickpea
CQ Wheat
CQ Chickpea
SEQ Wheat
SEQ Barley
(b)
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- Traditional approach:
Single date approach e.g.
DOY 225 does not capture
all possibilities of peak crop
canopy across regions
- Proposed approach:
Multi-temporal capturing all
available crop growth
information
- Ability to accurately
discriminate between
crops
Discriminating Crops: “MISSING LINK”
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Curve Fitting Procedures
Time
Gre
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alu
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. EV
I)
peak
Reconstructing of crop growth profile
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HANTS (Verhoef et al 1996)
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Day of Year (DOY)
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Day of Year (DOY)
(Verhoef et al 1996; Potgieter et al.
2007, 2010, 2011 )
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Discriminating between crops
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Actual
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Harmonic analysis of time series
Barley from satellite
Wheat from satellite
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Validation & Training – ground truth data http://www.paddockwatch.com.au
Paddock Watch
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Example of Winter cropping: Waggamba & Moree 2015
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Ground truth & Accuracies: Waggamba 2015
EVI multi-temporal canopy profiles Accuracy of area estimates during
25 May 26 Jun 28 Jul 29 Aug 30 Sep 17 Nov
Jan May Nov
AVG: 87%
Wheat-78%; Chickpea-
98%
Barley-96%
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Crop Area Estimates
Waggamba Moree
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Other outputs: Land Use: Aug 2013 to Jul 2014
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Cropping trajectories over time
AVG: 602k Ha
QLD: Increasing trend in Summer cropping of 36k Ha per year
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Regional scale commodity forecasting framework
Potgieter et. al. 2003, 2005, 2006
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Summer
2014/15 Winter
2014
Specific & Total Crop Area & Production
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Land use patterns Bangladesh (source: Perry Poulton CSIRO)
Southern Bangladesh 16th Jan 2007 Lat:22.89ºN Long:91.40ºE(7173 km2)
Original image
Classified image
Land use class Area (%) Area (ha)
1. Fallow 13.7 217.8
2. Trees 18.3 291.8
3. Ponds 3.2 51.3
4. Cropping (*other) 64.8 1031.2
Total 100 1592.1
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What lessons have we learnt?
• Utility of any prediction is based on accuracy and
timing
• Framework high efficacy in predicting crop area
estimates: at crop type level
• Successfully integrated to determine crop
production estimates at regional scale
• What spatial scale is needed? - horses for courses;
depending on what the issue is.
• Temporal resolution of outputs are sometimes more
useful than accuracy: TRENDS
• Ground truthing fields are critical in crop
discrimination
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(source: NASA)
Which Satellite platform? Vegetation type:
• 75 current and planned
sensors from 2015 to 203
• Temporal & spatial
resolution
•Accessibility of data:
• 1 m to 1 km resolution
• once every 10 minutes
to ~once every month
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The right answer
to the wrong
question
therefore…
Asking the right questions before designing any framework
KEEP IT SIMPLE !!!
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Thankyou