Remote sensing –Beyond images Mexico 14-15 December 2013 The workshop was organized by CIMMYT Global Conservation Agriculture Program (GCAP) and funded by the Bill & Melinda Gates Foundation (BMGF), the Mexican Secretariat of Agriculture, Livestock, Rural Development, Fisheries and Food (SAGARPA), the International Maize and Wheat Improvement Center (CIMMYT), CGIAR Research Program on Maize, the Cereal System Initiative for South Asia (CSISA) and the Sustainable Modernization of the Traditional Agriculture (MasAgro)

1. Remote sensing technology for crop insurance –
Applications and limitations
CIMMYT Workshop: Remote Sensing - Beyond Images
December 14-15, 2013, Texcoco, Mexico
Dr. Joachim Herbold
Slide 1

2. Welcome address
Topic:
Remote sensing technology for crop insurance –
Applications and limitations
Dr. Joachim Herbold
Agricultural Division
Munich Reinsurance Company
Contact: jherbold@munichre.com
RS technology for crop insurance
Dr. Joachim Herbold
Slide 2

3. Agenda
1. Crop insurance - status and outlook
2. Remote sensing for crop insurance
3. Need for further research
4. Summary
RS technology for crop insurance
Dr. Joachim Herbold
Slide 3

4. Crop insurance
Slide 4

5. Crop insurance
Drought in the USA in 2012
Slide 5

6. Crop insurance
Drought in the USA in 2012 - Financial consequences
• Total crop losses: around 20 billion US$
• Indemnifications to farmers: 17 billion US$
→ Biggest insurance loss in the history of crop
insurance in the USA and worldwide.
RS technology for crop insurance
Dr. Joachim Herbold
Slide 6

7. Crop insurance
Why do crops fail?
Losses per peril in MPCI programs
USA
Ontario, Canada
(1981–2005)
(1966–2009)
Disease
3%
Winterkill
3%
Other *
17%
Other
13%
Plant Disease
2%
Drought
39%
Heat
4%
Drought
42%
Hail
6%
Frost
9%
Hail
9%
Freeze
4%
Excess Moisture
24%
Source: RAIN&HAIL, 2011
Excessive Rainfall
25%
Source: AGRICORP, 2011
Estimate for developing countries:
70-80% of losses attributable to either a lack or excess of rain (incl. flood)
RS technology for crop insurance
Dr. Joachim Herbold
Slide 7

8. World Map of Agricultural Insurance
© Joachim Herbold, 2013
RS technology for crop insurance
Dr. Joachim Herbold
Slide 8

9. Remote sensing technology
Slide 9

10. Initial situation – Dominance of NDVI
 Most agriculture-related RS applications are focused on monitoring the
vegetation status using the NDVI (Normalized Difference Vegetation
Index)
 Advantage of NDVI: daily recording by different sensors and time-series
of up to 30 years.
 Disadvantages of NDVI: inaccuracies as a consequence of such factors
as background reflectance and the three-dimensional structure of the
canopy,
→ alternative indices are currently being developed: FAPAR (Fraction of
Absorbed Photosynthetically Active Radiation), VHI (Vegetation Health
Index) and LAI (Leaf Area Index).
For more information, see Meroni et. al., 2013 and Rojas et. al., 2013.
RS technology for crop insurance
Dr. Joachim Herbold
Slide 10

11. Challenges applying RS technology to crop insurance
1. Insured area relatively small: 1 ha – approx. 100 ha:
→ relatively high spatial resolution required.
2. Vegetation period: 4 to 9 months
→ medium temporal resolution required, cloud cover in vegetation
period can be a critical success factor for optical sensors.
→ high temporal resolution required if RS is to be used after a
specific loss event
3. Biomass ≠ yield
4. Ground truth data essential for calibration and validation → reliable yield
data
RS technology for crop insurance
Dr. Joachim Herbold
Slide 11

12. Radar sensors – a solution for the future?
 Advantage: data can be obtained even when there is a cloud cover
 Area of application in agriculture restricted at present
 Applications at present:
 Information on cultivated area
 Soil moisture analysis,
 Flood monitoring
→ often in combination with optical sensors
 With availability of new bands and more research, advances may be expected in
future
RS technology for crop insurance
Dr. Joachim Herbold
Slide 12

13. Potential applications
Plot identification
Relevant topics:
• Agricultural use?
• Boundaries of plot
• Size of plot
© GAF AG, 2008, Relin et al. 2005, Relin 2013
RS technology for crop insurance
Dr. Joachim Herbold
Slide 13

14. Potential applications
Crop identification
Relevant topics:
• Which crop/crop type?
Auxiliary factors:
• Sowing/planting date
• Ripening date
• Harvest date
• Phyllotaxy
• Leaf area in relation
to soil area in different
growing stages
RS technology for crop insurance
Dr. Joachim Herbold
Slide 14

15. Potential applications
Monitoring of crop progress
Alternatively:
 Soil preparation
 Sowing
 Emergence
 Closing of rows
 Tasseling/Flowering
 Ripening
 Harvesting
RS technology for crop insurance
Dr. Joachim Herbold
Slide 15

16. Potential applications
Yield estimations
Approaches for yield forecasts:
1. Satellite information as primary source: NDVI as classic example
RS technology for crop insurance
Dr. Joachim Herbold
Slide 16

17. Potential applications
Yield estimations
Approaches for yield forecasts:
1. Satellite information as primary source: NDVI as classic example
2. Crop growth models as a tool, using satellite information on the biomass as input
factor, as well as other factors such as soil type, weather conditions (e.g.
precipitation, temperature) and management factors
RS technology for crop insurance
Dr. Joachim Herbold
Slide 17

18. Potential applications
Loss event monitoring
Applications
 Crop insurance
 Disaster management (state authorities)
→ Early loss estimations and categorizing the regions according to degree affected
Flood monitoring
 Radar sensors in addition to optical sensors very efficient.
 Crop loss assessment: duration and height of flood, crop types
RS technology for crop insurance
Dr. Joachim Herbold
Slide 18

19. Typhoon “Parma” in Northern Philippines on October 2 , 2009
Monitoring of flood
Max. monitoring
frequency: 6
images/day
Legend:
Reference water, (Oct
2)
Flooded
(Oct 4)
Flood draw-off
between Oct. 3 and 4
RS technology for crop insurance
Dr. Joachim Herbold
Slide 19

20. Potential applications
Loss event monitoring – use of unmanned aircraft
• Unmanned system
• Aerial photos
• Partial losses in big
plots
RS technology for crop insurance
Dr. Joachim Herbold
Slide 20

21. Potential applications
Risk assessment and underwriting
1. Digital elevation models
→ to assess flood and frost risk
2. Insurance products
 based on NDVI
→ grassland USA and Spain
 in future: area yield products?
RS technology for crop insurance
Dr. Joachim Herbold
Slide 21

22. Need for further research
Slide 22

23. Need for further research
1. Yield estimations: increase in accuracy
 In field:
o methodology for yield estimations (e.g. size of samples,
methods used)
o Automatic yield recording devices
 Satellite-based technology
o Integration of satellite data into crop growth models
o Validation of results using ground truth data
RS technology for crop insurance
Dr. Joachim Herbold
Slide 23

24. Need for further research
2. Yield modeling
 Yield variability in the case of extreme weather events (actual
yield models reproduce yields inaccurately for extreme weather
events)
 Yield models with few input parameters
 Variability between regional yields (from official statistics) and
farm specific yields.
→ may differ for different crops and growing conditions
RS technology for crop insurance
Dr. Joachim Herbold
Slide 24

25. Need for further research
3. Susceptibility of crops in different vegetation periods to adverse
climatic conditions
 Hail: good knowledge
 Frost: for some specialty crops in Mediterranean climate: good
knowledge; for others not.
 Drought, excessive rain and flooding: research required
RS technology for crop insurance
Dr. Joachim Herbold
Slide 25

26. Summary
Slide 26

27. Summary
1. Crop insurance currently in its infancy.
2. Potential to further develop and enhance crop insurance and
disaster response by state authorities.
3. Major constraints:
 heterogeneous structure in crop production
 limited temporal availability of optical methods because of
cloud cover.
4. Advances in the field of radar data may supplement optical data.
RS technology for crop insurance
Dr. Joachim Herbold
Slide 27

28. Thank you. For further information please see
Article: Herbold, J.: RS technology for crop insurance. Geospatial World, September 2013. Can be downloaded from:
http://www.drjoachimherbold.de/
Further information:
http://www.munichre.com/en/reinsurance/business/non-life/systemagro/services.aspx
Slide 28