In the Philippines, rice is cultivated on 2.76 million ha, much of which is cropped

twice a year. However, production is not enough to meet increasing domestic

demand. In support of the country's rice self-sufficiency plan, IRRI and PhilRice

formed an integrated project funded by the Department of Agriculture. Part of this

project is the mapping and assessment of rice areas in the country. In partnership

with sarmap, a Swiss company, we are developing a dedicated processing chain

that enables the mapping of rice areas, detection of emergence, and monitoring of

growth for the whole season. This poster presents the processing chain and the

first rice mapping results from this public/private research partnership.

• We are using multitemporal remote sensing images acquired by different SAR

sensors to adequately capture flooding, planting, and emergence dates in major

rice-producing provinces of the Philippines (Table 1, Fig. 1).

Mapping and monitoring of rice

areas

Table 1. Description of SAR data used.

Sensor Ban

d

Wavelengt

h (cm)

Spatial

resolution (m)

Revisit

period (d)

Polarizationa

Cosmo SkyMed (CSK)

ENVISAT ASAR

ALOS-PALSAR

X

C

L

3.0

5.6

23.6

3 to 15

15 to 25

8 to 15

4

35

46

HH

HH

HH-HH/HV

Conclusions and further work

• Multitemporal and multisensor acquisitions are required to properly capture, at the

country level, the critical stages, such as flooding and planting dates, that vary

widely in time and space.Fig. 2. General procedure for rice mapping in RICEscape®.

• We are working to further improve the rice mapping methodology. Rice ecologies

vary across the Philippines and the methodology must accommodate this

variation.

aHH = radar signal is emitted and received in the horizontal plane, HV = radar signal is emitted in

the horizontal plane and received in the vertical plane.

• When completed, this project will provide the first SAR-based high-spatial-

resolution map of rice areas covering the major rice-producing provinces in the

Philippines.

• With the launch of Sentinel-1A and 1B (ESA C-band missions) planned for 2012-

13, the temporal acquisition frequency (revisiting cycle, 7 days) will enable

continuous rice growth monitoring at the country level. C-band data from Sentinel

will also be provided free of charge.

DEM

Multilooking + filtering

Geometric calibration

Radiometric calibration

Radiometric normalization

Filtering

SAR-derived rice map

Preprocessing

Classification

• sarmap has developed a dedicated rice mapping software, RICEscape®, to

automate SAR data preprocessing while still allowing operators to fine-tune the

mapping process based on their location-specific knowledge of rice ecologies

(Fig. 2).

• Planting dates vary widely across the Philippines, highlighting the importance of

acquiring multitemporal images for monitoring rice areas.

• Flooding, planting, and crop emergence (Fig. 3) can be detected using multi-

temporal SAR images and used to map rice areas (Fig. 4).

Preliminary findings

Fig. 4. Preliminary rice map derived from multitemporal CSK and

PALSAR images over Nueva Ecija.

Information that will be generated from this project is crucial in rice importation

decisions and in prioritizing research and extension activities such as the

dissemination of location-specific technologies.

Fig. 1. The top 20 rice-growing provinces (yellow) and monitoring sites (red dots) (A), and

coverage of acquired SAR images (B, C, D) for the 2011 dry season.

PALSAR

D A

ASAR

C

Rice map

generation

Mask

generation

Preprocessed SAR image

Validation using ground

truth data

Fig. 6. Comparison of BSWM 1980 (A), SAR-derived 2011 dry season only (B), and MODIS-

derived 2009 (C) rice maps highlighting the changes in rice areas (A vs. B, C) and difference in

resolution (B vs. C).

• Planting dates can be mapped using SAR temporal signatures (Fig. 5).

15 Dec. 2010

31 Jan. 2011

23 March

2011

Standard format original

SAR products

(Digital elevation model)

Fig. 3. Actual condition

during field visits.

1International Rice Research Institute, Los Baños, Laguna, Philippines, 2Philippine Rice Research Institute, Science City of Muñoz, Nueva Ecija, Philippines, 3sarmap, Cascine di Barico, CH 6989 Purasca, Switzerland

Jeny Raviz,1 Eduardo Jimmy Quilang,2 Massimo Barbieri,3 Elmer Alosnos,2 Sonia Asilo,1 Gina Balleras,2 Airene Claire Baradas,2 Artemio Corpuz,2 Jovino de Dios,2 Rona Dollentas,2

Eddie Dupitas,2 Noel Ganotisi,2 Francesco Holecz,3 Alice Laborte,1 Mary Rose Mabalay,2 Juanito Maloom,2 Aileen Maunahan,1 Jean Rochelle Mirandilla,2 Andrew Nelson,1 Arnel

Rala,1 Gilbert Romarez,2 Albert Christian Suñer,2 Belen Tabudlong,2 Frenciso Varquez,2 and Joana Rose Vergara2

0

20

40

60

80

100

1 Dec 2010 28 Dec 2010 18 Jan 2011 31 Jan 2011 1 Mar 2011 23 Mar 2011

Plant height (cm)

–15

–14

–13

–12

–11

–10

–9

–8

Backscatter (dB)Planting

Tillering

Milking

Harvest

Plant height, cm

Backscatter,

dB

Fig. 5. Temporal signature of rice derived from multitemporal images and rice growth stage based

on actual field observations in Nueva Ecija.

• The rice area detected with RICEscape® compares favorably with the rice area

depicted in the Bureau of Soils and Water Management (BSWM) and Moderate

Resolution Imaging Spectroradiometer (MODIS) rice maps (Fig. 6).

Area (000 ha) 46.0 38.1 59.3

A B C

CSK

B

4 Jan. 2011

Mapping and monitoring rice areas using multisensor Mapping and monitoring rice areas using multisensor Mapping and monitoring rice areas using multisensor Mapping and monitoring rice areas using multisensor

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