This document summarizes research using satellite data to monitor rice crops and forecast production in Cambodia. MODIS satellite imagery was analyzed for three provinces from 2011-2012. Rice acreage, crop intensity, phenology and production were estimated and found to correlate well with ground statistics. Time-series NDVI was used to map rice areas for wet and dry seasons, identify planting and maturity dates, and develop production forecasting models with R2 values up to 0.97. The methods demonstrated the capability of satellite data to generate rice crop information and forecasts across Cambodia.

1. Geoinformatics Center
Asian Institute of Technology
Department of Planning and Statistics
Ministry of Agriculture, Fisheries and Forestry
CAMBODIA
Rice Crop Monitoring and Production
Forecasting with Satellite Data

2. Introduction
Total Land Area: 181.035 Sq.km
Population: Over 14.9 Million
(2012)
 23 Provinces + 1 Phnom Penh
City
80% of population is living in
rural area with 75% engaged in
agriculture.
Crop producing households 2.4
million
Agriculture sector contribution in
GDP 27.5% in 2012

3. Objectives
 Create rice statistical information using satellite data.
 Rice Crop Area
 Crop Intensity
 Rice Phenology
 Predict rice crop production using satellite data.

4. Study Area
 Three (03) Major rice cultivation Province are selected as
study provinces.
 Kampong Chhnang
 Kampong Speu
 Takeo

5. Data Used – Satellite Data
 MODIS (Moderate Resolution Imaging Spectroradiometer)
data from Terra and Aqua satellites vegetation indices
product.
Product Name MOD13Q1 and MYD13Q1
Spatial Resolution 250 meter
Temporal Resolution 16 days
Spatial Coverage Cambodia, Vietnam (Tile No h27v07)
No of Images 54 images from May 2011 to June 2012
Product Type NDVI

6. Data Used – Satellite Data
 NDVI layer
 16 bit signed integer and range – 2000 to 10000
 VI Quality Assurance layer
 16 bit unsigned integer with Bits unit
 Composite Day of Year Layer
 Julian day of year of each pixel

7. Data Used – Statistics Data
 Agriculture Statistics data for 3 provinces from Department
of Statistics and Planning, MAFF, Cambodia from 2002 to
2012.
 Area of cultivation
 Area of harvest
 Yield
 Production
 Crop Calendar

8. Time Series NDVI
 Rice Area

9. Temporal Changes in Paddy Field
 Greenness of field
increase with time
 At maturity stage it looks
dark green
 After that it becomes
yellowish

10. Paddy Crop Information from NDVI TS

11. Methodology – Acreage and Phenology
Mapping

12. Methodology - Smoothing
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
5/ 1/ 2013 6/ 1/ 2013 7/ 1/ 2013 8/ 1/ 2013 9/ 1/ 2013 10/ 1/ 2013 11/ 1/ 2013 12/ 1/ 2013
NDVI(X10000)
DATE
Raw NDVI TS Smoothed NDVI TS

13. Methodology – Crop Intensity

14. Methodology – Start of Season (SOS)
SOS – number
of days
before max
NDVI.

15. Methodology – Production Forecasting

16. Results – Rice Acreage
Area Study
Rice Cultivated Area in Wet
Season (ha)
Rice Cultivated Area in Dry
Season (ha)
Land Use (ha)
Statistics Remote Sensing Statistics Remote Sensing
Kampong Chhnang 111,477 104,549 36,036 43,749 125,360
Kampong Speu 114,239 217,054 794 6,197 177,533
Takeo 194,955 192,982 94,858 56,852 233,611

17. Results – Rice Acreage (KC)
 Wet Season  Dry Season

18. Results – Rice Acreage (KS)
 Wet Season  Dry Season

19. Results – Rice Acreage (TK)
 Wet Season  Dry Season

20. Results – SOS (KC)
 Wet Season  Dry Season

21. Results – Rice Acreage (TK)
 Wet Season  Dry Season

22. Results – Field Verification (KC)

23. Results – Field Verification (KS)

24. Results – Field Verification (TK)

25. Results – Production Forecasting
 Production forecasting model results
Province R2 Correlation
Coefficient
Takeo (Wet)
0.9469 0.97311
Takeo (Dry) 0.606 0.7784
Kampong Chhnang (Wet) 0.458 0.67716

26. Results – Production Forecasting (KC)

27. Results – Production Forecasting (TK-Wet)

28. Results – Production Forecasting (TK-Dry)

29. Season
NDVI Mean
2013
A (Coeff)
B
(Intercept)
Predict Production
(Ton)
TK - Wet 1988.51 1325 -2035202 599575.5251
KC - Wet 1017.86 2569 -2261146 353723.9246
Prediction for 2013 Wet Season