Abstract
Rice is the staple grain in southeastern Asia. Its monitoring and yield estimation has special
significance to this region. Radar remote sensing is appropriate for monitoring rice, as cultivated
areas are most often cloudy and rainy. For this reason, Synthetic Aperture Radar (SAR) is
anticipated to be the dominant data source in tropic and sub-tropical regions. SAR satellites can
also provide frequent re-visit schedules suitable for agricultural moni-toring. Firstly, this paper
presents the results of a study examining the backscatter behavior of rice using multi-temporal
RADARSAT dataset. A rice-type distribu-tion map was produced, showing 4 types of rice with
different life spans. The accuracy of rice classification was found to be 91%, providing confidence
that multi-temporal RADARSAT data is capable of rice monitoring and has potential for yield
estimation. Based on the studies in the Zhaoqing test site, it is suggested that rice yield
estimations require three radar data acquisitions taken at 3 stages of crop growth: at the end of the
seedling development period, in the ear differentiation period, and at the beginning of the harvest
period. Alternatively, if multi-parameter radar data is available, only two data acquisitions are
required: at the end of the seedling period, and at the beginning of the harvest period. Secondly,
this paper presents the potential of polarimetric SAR technology for rice and tropic vegetation
monitoring. A suggestion on optimum SAR system parameter selection for this type of application
was made for future system design consideration.
Introduction
Rice is a heat and water favorite crop. Most paddy rice in the world grows in warm, humid
environment with heavy cloud cover and rainfall. It is hard to acquire optical remote sensing data
in rice growing regions. Synthetic Aperture Radar (SAR), with all weather, independent of
illumination imaging capability and frequent revisit schedule, is anticipated to be the dominant
data source for agriculture monitoring in tropic and sub-tropic regions.
Rice monitoring and yield estimation has special significance to China, as rice is the staple grain
and accounts for 42% of the crop yield for this country. The estimation of crop yield is a topic of
global interest (McDonald and Hall, 1980), and the efficient management of agricultural land
resources is strongly related to social and economic sustainable development, especially in China.
It is well known that China is the largest country in population. However, as the population
increases, and economy and industry develop, the quantity and quality of cultivated land is
decreasing rapidly. The food supply to the current 1.2 billion people is a serious concern facing
China, and will intensify as the population continues to grow. Therefore, it is important to find an
efficient way to face this dilemma. Remote sensing technology will provide the needed
information on crop distribution, acreage and potential yield.
This paper presents the results of a study examining the backscatter behavior of rice using multi-temporal
RADARSAT dataset. A rice-type distribution map was produced, showing 4 types of rice
with different life spans ranging from 80 days, to 120-125 days. Based on previous studies in the
Zhaoqing test site, it is suggested that rice yield estimations require three radar data acquisitions.
Alternatively, if multi-parameter radar data is available, only two data acquisitions are required.
Test Site and Data Source
The Zhaoqing test site is located in Guangdong Province, south of China center at latitude 22.30,
longitude 112.30. It is sited at the northwestern end of Pearl River Delta. The test site was firstly
imaged by airborne SAR in 1993 under the GlobeSAR program (Shao, 1995, 1996; Guo 1997).
The Shuttle Imaging Radar C-band (SIR-C) and X-band SAR (X-SAR) also flew over the area on
April 18, 1994. In addition, there were multiple RADARSAT images acquired from March to
December in1996, and from April to July in 1997. The system parameters, imaging modes, and
acquisition dates of images used in this study are listed in table 1.
Table 1. System Parameters of SAR Data
| Parameters |
Data Source
| GlobeSAR
| SIR-C/X-SAR
| RADARSAT (Fine)
| RADARSAT (Standard)
|
| Frequency (GHz) |
C X
5.30
9.25 |
L C X
1.24 5.3 9.6
| C
5.3 |
C
5.3 |
| Polarization |
HH, HV
HH
VV, VH
VV |
HH HH VV
HV HV |
HH |
HH |
| Incidence Angle (°) |
14-45 |
34.1 |
43-46(f4) |
36-42(S5),
41.46(S6) |
| Nominal Resolution (m) |
6*6 |
25*25 12.5*12.5 |
10*10 |
30*30 |
| Pixel Spacing (m) |
6*6 |
25*25 |
6.25*6.25 |
12.5*12.5 |
| Swath Width (km) |
18 |
37.8 |
50 |
100 |
| Imaging Date |
Nov.20,21,93 |
April 18,94 |
Multi-temporal |
Multi-temporal |
Rice Calendar
In the Zhaoqing test site, there are two crops per year; early season rice and late season rice. There
are five major growth periods in the life cycle of rice. 1) Transplanting period: rice plant seedlings
are transplanted from the seedbed to the paddy field. The transplanting date depends on the
weather, especially temperature; 2) Seedling developing period: the seedling splits up and begins
to develop a root system; 3) Ear differentiation period; 4) Heading period: headings begin to form;
5) Mature period: the rice plants mature and are ready to be harvested. Temporally, these five
periods for early season rice are March 25-April 5, April 15-25, May 10-30, June 10-25, July 5-31.
For late season rice, the growth stages occur as follows: July 20-August 5, August 10-20,
September 1-30, October 1-20, November 1-25 respectively.
With progress in agricultural technology, it is known that the longer the rice lifetime, the higher the
yield will be. For this reason, the transplanting date of rice is getting earlier. Plant maturity
rates and lifetimes are species dependent.
