Mapping rice areas with radar remote sensing – a case study for Leyte, Philippines”

Mapping rice areas with radar remote sensing – a case study for Leyte,

Philippines

IRRI SSD seminar

Roman Skorzus, GIZ PH / IRRI

1Los Banos – November 14th 2012

REMOTE SENSING-BASED INFORMATION AND INSURANCE FOR CROPS IN EMERGING ECONOMIES

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1 RIICE project introduction2 Rice Mapping with Radar Remote Sensing

1 Methods2 Validation

3 Interview Survey in Leyte4 Recommendations for RIICE

Outline


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Rice is the most important staple food of the world

Project introdution

70% of the poor people live in Asia Rice covers up to ¾ of the daily calories Consumption up to 200 kg/capita/year rice Growing population vs economic growth Small scale rice farmers (<1 ha) High enviromental risks

Source: MACLEAN 2002, RIBBES; LE TOAN 1998


Farmers‘ risks 4


Yield prediction, food security

Social security Water/irrigation

management Greenhouse gas

emissions Risk management

Why rice monitoring? 5


REMOTE SENSING-BASED INFORMATION AND INSURANCE

FOR CROPS IN EMERGING ECONOMIES

Duration: 2012-2015

Funding by the SDC Research and Development by

IRRI and sarmapManagement by GIZ and Allianz Re

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Project partner 7

Sentinel based data and maps

LAI and yield modelling (ORYZA2K)

(re)Insurance developement, distribution

and implementation

Key donor and knowledge management


Developing microinsurances for 5 Mio. rice farmers in: India, Bangladesh, Vietnam, Cambodia, Thailand,

Indonesia, Philippines Yield information based on remote sensing and

modelling (Sentinel 1 a/b, bridged by ENVISAT, PALSAR, CSK)

Faster reaction for insurance related events and pay out, prevent poverty due to loss of yield

Project goals 8


9New insurance scheme


Based on the Area Based Yield Insurance (ARBY)

How the insurance (will) work?

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80 % trigger Average yield of a 20

years time series Based on national

irrigation system (NIS)

Lost: 10 %NO PAYOUTLost: 25 %

PAYOUT for 5 %Lost: 40 %

PAYOUT for 20 %


Rice Mapping with Radar Remote Sensing

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Mapping rice areas in Leyte (study site) Deriving farming dates from satellite data Validating the map and check the accuracy

The Goal 12


Rice season 13

Soaking & transplanting

tillering flowering

2 rice seasons:Dry: November - AprilWet: May - October


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Own photograph on June 16th 2012


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Own photograph on August 1st 2012


Remote sensing devices (satellites or airplanes) are measuring the reflectance of electromagnetic energyFrom the sunFrom radar

With remote sensing you can see the surface of the earth (e.g. vegetation, soil, water)

What is remote sensing? 19


Optical remote sensing 20


Optical remote sensing 21


Radar remote sensing 22


How is radar remote sensing working?

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What the satellite is „seeing“.


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time

Ra

dar

ba

cks

cat

ter



June 12 July 12 Sept 12 Oct 12

Before land preparation Fields soaked with water Vegetative stage Harvested

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Accuracy: 81.7 % Other land cover: herbacious (38), forest

(33), coconut (27), village (21), grassland (12), street (12), …

Results 41

Ground Truth Rice Not Rice Classification Rice 161 34 195

Not Rice 29 121 150 190 155 345


Interview Survey for Rice Farmers in Leyte

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Collecting information about the 2011 ARBY farmers LocationFarming practices

Dates Seeds, chemicals, fertilizer

Personal information Age, income, farming experience

The Goal 43


GPS tagging of the location Questionaire for the interviews

Translator for Visayan, Tagalog and Cebuano Support by the municipality agriculture

officers (MAO) and land govermental units (LGU)

35 farmers have been interviewed

Methods 44


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Age 49

Municipality Number of farmers

Avg age in years Avg years of farming experience

Barugo 4 50,25 25,75Hindang 11 58,82 22,27Ormoc 19 57,37 36,53San Miguel 1 39,00 1,00Total 35 56,49 29,80


Yield (ws 2011)April - November

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Avg yield in cavan/ha

Avg kg/cavan Avg yield in kg

Barugo 4 67.50 43.50 2,930Hindang 11 73.00 45.00 3,304Ormoc 19 67.68 48.05 3,203San Miguel 1 40.00 49.00 1,960Total 35 68.54 46.60 3,168


Yield (ds 2011)November - March

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Avg yield in cavan/ha

Avg kg/cavan Avg yield in kg

Barugo 4 72.50 43.50 3,155Hindang 11 79.09 45.05 3,615Ormoc 19 79.03 47.16 3,691San Miguel 1 40.00 44.00 1,760Total 35 77.19 45.99 3,550


Seeds, irrigation and chemicals

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used irrigation

used insecticide

used fungicide

used herbicide

used pesticide

yes 33 24 18 21 16

No 1 2 6 6 11

as needed 7 9 7 7

Total 34 33 33 34 34

rice variety Counthybrid 10inbred 32Total 42


All farmers are experiencing pest and diseaseStem borerLeaf borerRats, snails, bugs, beetlesVirus infections

Pest and disease 53


54Stem borer


55Rice bugs and beetles


(ARBY) farmers are well embedded within the barangays

No concerted farming, use of seeds, chemicals, fertilizer

No recording of important informations (e.g. yield, income, inputs/outputs)

Very heterogenious Other income sources (e.g. barangay or pigery) Still interested in insurances

Observations 56


Increasing the number or insured farmersWord-of-mouth-propagandaAdvertising „in the field“In general new marketing forms (flyer, manuals,

etc.) Building a database of farmers Management of farmers in barangay level

Recommendations for RIICE

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Salamat sa inyong pakikinig!Thank you for listening!

Danke fürs Zuhören!

Documents

Mapping rice areas with radar remote sensing – a case study for Leyte, Philippines”