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Papers/Articles
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Radarsat Data for Operational Rice Monitoring and its Potential for Yield Estimation
Yun Shao1 Hao Liu1 Xiangtao Fan1,2 Jianhua Xiao1
Qing Dong1 Xingyuan Wang1,2
S. Ross3 B. Brisco3 R. Brown4 G. Staples5
1.Institute of Remote Sensing Applications,
Chinese Academy of Sciences,
P.O. Box 9718, Datun Road, Beijing 100101, China
Tel: 86-10-64876313, Fax: 86-10-64889786
E-Mail:yunshao@public.bta.net.cn
2. Department of Earth Sciences, Nanjing University, Nanjing, China
3. Noetix Research Inc., Ottawa, Ontario, Canada.
4. Canada Centre for Remote Sensing, Ottawa, Ontario, Canada
5. RADARSAT International, Vancouver, British Columbia, Canada
Abstract 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. Radar remote sensing is appropriate for monitoring rice, as cultivated areas are most often cloudy and rainy. For this reason, SAR is anticipated to be the dominant data source in tropic and sub-tropical regions and also provide re-visit schedules suitable for agricultural monitoring. This paper presents the results of a study examining the backscatter behavior of rice using multi-temporal RADARSAT dataset acquired in 1996 and 1997. A rice-type distribution map was produced, showing 4 types of rice with different life spans ranging from 80 days, to 120-125 days. The life span of a rice crop has significant impact on yield, as well as the taste and quality of the rice. The yield of three counties and two administrative regions, totaling 5000 square kilometers, are estimated in this study. The accuracy was found to be 91%, providing confidence that multi-temporal RADARSAT data is capable of rice monitoring and yield estimation. Based on the studies carried out in the Zhaoqing test site, it is suggested that rice yield estimations require three radar data acquisitions taken at 3 stages of crop growth circle. That is 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. In 1999, we started a pilot experiment on operational rice monitoring and potential yield estimation using multi-temporal RADARSAT data. Finally, this paper proposes a pilot scenario for operational rice monitoring and yield estimation.
1. 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 interests (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.
The use of microwave remote sensing technology to study ecological systems is becoming more and more popular among the world's scientific community (Dobson, 1992; Kasischke and Christensen, 1990). Scientists have carried out extensive field measurements (Ulaby et al 1986), airborne flight mission (Zebker et al, 1991),
Data Source
Parameters |
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 |
In 1996:
June 17,
Aug. 4,
Sept.21,
Oct. 15
Nov. 8,
Dec. 2 |
In 1996:
Mar. 26, Apr. 25,
June 10, Aug. 23,
Aug. 28,
Sept. 16
Nov. 27
In 1997:
Apr. 25, May 19,
June4,June 12,
June 28, July 6,
July 22
In 1999:
Apr. 17, Apr. 22,
Apr. 24,May 11,
May 16, May 18, |
Table 1. System Parameters of SAR Data
(Campbell et al, 1995, Guo et al, 1995, 1997, Shao et al, 1995 a, b), spaceborne mission (Stofen et al, 1995). Many microwave backscatter models were developed to study the backscatter behavior of vegetation (Chauhan, et al, 1994; Karam and Fung, 1988; Matzler, 1994; Ulaby, et al, 1990). There are certainly much more literatures available on researches on forest applications, rather than agriculture (Engheta and Elachi, 1982; Freeman et al, 1992; Ulaby, et al, 1990, Brisco et al, 1997). However there are many successful examples in radar remote sensing for agricultural applications (Shao et al, 1994, 1996; Le Toan et al, 1989; Ulaby et al, 1982; Soares et al, 1987, 1997; Schotten et al, 1995; Anys and He, 1995), and a few papers specifically on rice monitoring (Shao, et al, 1997 a, b, c, d; Liu et al, 1997; Kurosu et al, 1995, 1997; Le Toan et al, 1997; Aschbacher et al, 1995 ). The results on rice monitoring using SAR technology were very promising.
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. The life span of a rice crop has significant impact on yield, as well as the taste and quality of the rice. The yield of three counties and two administrative regions, totaling 5000 square kilometers, are estimated in this study. The accuracy was found to be 91%, providing confidence that multi-temporal RADARSAT data is capable of rice monitoring and yield estimation. Based on previous studies in the Zhaoqing test site, it is suggested that rice yield estimations require three radar data acquisitionstaken 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. Finally, this paper proposes a pilot scenario for operational rice monitoring and yield estimation.
2. 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. Airborne SAR firstly imaged the test site 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. For Zhaoqing test site, there was a three years continues RADARSAT data acquisition for rice monitoring. The first two years data acquisition focus on studying the backscatter behavior of rice and the potential of RADARSAT for rice yield estimation. The third year's data acquisition is for operational rice monitoring and yield estimation.
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